determination-of-oil-and-gas-reserves
TRANSCRIPT
Determination of Oil and Gas Reserves
Petroleum Society Monograph No.1
THE PETROLEUM SOCIETYOF THE CANADIAN INSTITUTE OF MINING, METALLURGY AND PETROLEUM
Determination of
Oil and Gas Reserves
Petroleum Society Monograph No.1
© 1994 by The Petroleum Society of the Canadian Institute of Mining, Metallurgy andPetroleum, Calgary Section.
All rights reserved. First edition published 1994.
Printed in Canada.
10 9 8 7 6 5 4 3 2
Permission is granted for individuals to make single copies for their personal use inresearch, study, or teaching and to use figures, tables and short quotes from thismonograph for republication in scientific books and journals. There is no charge forany of these uses. The publisher requests that the source be cited appropriately.
Canadian Cataloguing in Publication Data
Main entry under title:
Determination of oil and gas reserves.
(Petroleum Society monograph; no. I)Includes bibliographical references and index.ISBN 0-9697990-0-4
I. Petroleum reserves. I. Petroleum Society of CIM. II. Series.
TN871.D47 1994 622'.1828 C94-910092-7
Edited by Virginia MacKay.
Cover design by Guy Parsons.
Typesetting and graphic design by lA. (Sandy) Irvine, By Design Services.
Printed and bound in Canada by D.W. Friesen Ltd., Altona, ME.
CONTENTS
Figures xiv
Tables xvii
Foreword xix
Preface xxi
Acknowledgements xxiii
Authors .' xxiv
PART ONE: DEFINITIONS AND GUIDELINESFOR CLASSIFICATION OF OIL AND GAS RESERVES
1. OVERVIEW OF PART ONE 3
2. DEFINITIONS 4
2.1 Introduction 42.2 Resources 4
2.2.1 Discovered Resources or Initial Volumes in Place 52.2.2 Undiscovered Resources or Future Initial Volumes in Place 5
2.3 Remaining Reserves 52.3.1 Remaining Proved Reserves 52.3.2 Probable Reserves 52.3.3 Possible Reserves 52.3.4 Development and Production Status 6
2.4 Cumulative Production 72.4.1 Sales 72.4.2 Inventory 7
2.5 Reserves Ownership 72.6 Specified Economic Conditions 82.7 Reporting of Reserves Estimates 8
2.7.1 Risk-Weighting of Reserves Estimates 82.7.2 Aggregation of Reserves Estimates 82.7.3 Barrels of Oil Equivalent 9
3. GUIDELINES FOR ESTIMATION OF OIL AND GAS RESERVES 10
3.1 Introduction 103.2 Methods ofCaiculating Reserves 10
3.2.1 Deterministic Procedure 103.2.2 Probabilistic Procedure II
3.3 Guidelines for Specific Methods 123.3.1 Volumetric Method 123.3.2 Material Balance Method 173.3.3 Decline Curve Analysis 183.3.4 Reservoir Simulation Method 223.3.5 Reserves from Improved Recovery Projects 223.3.6 Related Products 22
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PART TWO: DETERMINATION OF IN-PLACE RESOURCES
4. OVERVIEWOF PART TWO 27
4.1 Introduction 274.2 ResourceEstimates 27
4.2.1 Volumetric Estimates 274.2.2 Material BalanceEstimates 30
4.3 Procedures for EstimatingIn-Place Resources 304.4 Sources and Reliabilityof Data 314.5 Interrelationship of Parameters 314.6 Uses of ResourceEstimates 314.7 Backgroundand Experience of Evaluators 34
5. ESTIMATION OF VOLUMES OF HYDROCARBONS IN PLACE 35
5.1 ReservoirArea and Volume 355.1.1 Introduction 355.1.2 Acquisitionof Data 355.1.3 Data Analysis 365.1.4 Mapping 385.1.5 Refinementof Volumetric Estimates 43
5.2 Thickness 445.2.1 Introduction 445.2.2 Defining Net Pay 455.2.3 Data Acquisition Programs 465.2.4 Data Interpretation 485.2.5 Factors AffectingData Quality 49
5.3 Permeability 535.3.1 Introduction 535.3.2 Permeabilityfrom Core 535.3.3 Relative Permeability Measurement 54
5.4 Porosity 555.4.1 Introduction 555.4.2 Sources and Acquisition of Data 555.4.3 Analysis of Data 585.4.4 Factors AffectingData Quality 63
5.5 Hydrocarbon Saturation 655.5.1 Introduction 655.5.2 SaturationDetermination From Core 655.5.3 SaturationDetermination From Logs 695.5.4 Flow Test Procedures for Gas and Oil Saturation 705.5.5 Factors AffectingData Quality 72
5.6 Testing and Sampling 755.6.1 Introduction 755.6.2 DrillstemTests 755.6.3 ProductionTests 755.6.4 Sampling 77
5.7 ReservoirTemperature 815.7.1 Introduction 815.7.2 Data Sources 815.7.3 Data Analysis 825.7.4 Data Analysison a Regional Basis 82
5.7.5 Data Quality 855.8 Reservoir Pressure 86
5.8.1 Introduction 865.8.2 Data Sources 865.8.3 Data Analysis 86
5.9 Gas Formation Volume Factor 915.9.1 Introduction 915.9.2 Ideal Gas Law 915.9.3 Gas Compressibility Factor 915.9.4 Sour Gas 925.9.5 Derivation of Gas FormationVolumeFactor 94
5.10 Oil Formation VolumeFactor 965.10.1 Introduction '" 965.10.2 Data Sources 965.10.3 Data Acquisition 965.10.4 Data Analysis 965.10.5 Data Adjustment 985.10.6 Summary '" 100
5.11 Quality and Reliabilityof Data and Results 1015.11.1 Introduction 1015.11.2 Permeabilityfrom Cores 1015.11.3 Porosity from Cores 1015.11.4 Saturations from Cores 1025.11.5 Effective PorousZone and Net Pay from Cores 1025.11.6 Porosity from Well Logs 1035.11.7 Water Saturations from Well Logs '" 1035.11.8 EffectivePorous Zone and Net Pay from Well Logs 1035.11.9 DrillstemTests 1045.11.10 ProductionTests 1045.11.11 Reservoir Fluid Samples 1045.11.12 Reservoir Temperature 1045.11.13 ReservoirPressure 1045.11.14 GasCompressibilityFactor 1055.11.15 FormationVolume Factor 1055.11.16 Material Balance 1055.11.17 Interrelationships 105
6. PROBABILITYANALYSIS FOR ESTIMATES OF HYDROCARBONS IN PLACE 106
6.1 Introduction 1066.2 Warren Method Theory 1076.3 Application 1086.4 Typical Situation: Conventional Gas 110
7. MATERIALBALANCE DETERMINATION OF HYDROCARBONS IN PLACE 120
7.1 Introduction 1207.2 Underlying Assumptions 1207.3 Explanation of Terms 1217.4 General Material BalanceEquation .......................•.............. 1227.5 Special Cases of the MaterialBalance Equation 122
7.5.1 Undersaturated Oil Reservoirs 1227.5.2 SaturatedOil Reservoirs 1237.5.3 Gas Reservoirs 123
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7.6 Limitations of Material Balance Methods 1237.7 SupplementalCalculations 124
7.7.1 Gas Caps and Aquifers 1247.7.2 Water Influx Measurements 1247.7.3 Analytical Water Influx Models 124
7.8 Multiple UnknownMaterial Balance Situations 1257.9 Computer Solutions 127
PART THREE: ESTIMATION OF RECOVERY FACTORS ANDFORECASTING OF RECOVERABLE HYDROCARBONS
8. OVERVIEW OF PART THREE 131
8.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 1318.2 Purpose of Depletion Strategy 1318.3 Techniques for Reserves and Production Forecasting 132
9. NATURAL DEPLETIONMECHANISMS FOR OIL RESERVOIRS 133
9.1 Introduction 1339.1.1 Fluid Expansion 1339.1.2 Solution Gas Drive 1339.1.3 WaterDrive 1349.1.4 Gas Cap Drive , 1349.1.5 CompactionDrive 1349.1.6 CombinationDrive 135
9.2 Forecasting of RecoverableOil 1359.2.1 Solution Gas Drive 1379.2.2 Water Drive 1379.2.3 Gas Cap Drive 1409.2.4 CombinationDrive 140
9.3 Factors Affecting Oil Recovery 1409.3.1 ProductionRate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1409.3.2 Oil Quality 1419.3.3 Reservoir Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 1419.3.4 Reservoir Geometry 1419.3.5 Effects ofEconomic Limit 142
10. DEPLETION MECHANISMS FOR NATURALGAS RESERVOIRS 145
10.1 Introduction 14510.2 Characteristicsof Natural Gas 14510.3 Definition of Reservoir Types from Phase Diagrams 14610.4 Gas Recovery 14710.5 Gas Reserves 148
10.5.1 Nonassociated Gas Reserves Determination .. , 14810.5.2 Solution Gas Reserves Determination 15010.5.3 Associated Gas Reserves Determination 150
10.6 Pipeline Gas Reserves 15010.7 Reserves of Related Products 151
10.7.1 Natural Gas Liquids 15110.7.2 Sulphur 151
10.8 Gas DeliverabilityForecasting 15110.9 Well Spacing 15210.10 Cycling of Gas Condensate Reservoirswith Dry Gas 152
10.11 Secondary Recovery of Gas 15310.12 EnhancedGasRecovery 153
II. ENHANCED RECOVERY BY WATERFLOODING 154
11.1 Introduction 15411.2 Displacement Process 154
11.2.1 Mobility Ratio 15411.2.2 Interfacial Tension 15411.2.3 Fractional Flow 155
11.3 Types of Waterfloods 15611.4 Analysis Methods and When to Apply Them 156
11.4.1 Pool Discovery 15711.4.2 Delineated Pool: Immature Depletion 15711.4.3 Post-Injection Startup 15811.4.4 Post-Watertlood Response 15811.4.5 Mature Watertlood 158
U.s Volumetric Analysis 15811.5.1 Overview of Method 15811.5.2 Parameters and Factors Affecting Analysis 15811.5.3 Reliability of Results 162
11.6 Decline Performance Analysis 16211.6.1 Overview of Method 16211.6.2 Factors Affecting Analysis 16211.6.3 Reliability of Results 163
11.7 Comparison to Analogous Pools 16311.7.1 Overview of Method 16311.7.2 Procedure and Factors Affecting Analysis 16311.7.3 Reliability of Results 164
11.8 Analytical Performance Prediction 16411.8.1 Overview ofMethods 16411.8.2 Reliability of Results 164
11.9 Numerical Simulation 16611.9.1 Overview of Method 16611.9.2 Parameters and Factors Affecting Analysis 16611.9.3 Reliability of Results 166
11.10 Waterflooding Variations 16711.10.1 Naturally Fractured Reservoirs 16711.10.2 Polymer Flooding 16811.10.3 Micellar Flooding 168
11.11 Statistical Watertlood Analysis Survey 16811.11.1 Overview of Database 16811.11.2 Discussion of Results 168
12. ENHANCED RECOVERY BY HYDROCARBON MISCIBLE FLOODING 171
12.1 Introduction 17112.2 Types of Hydrocarbon Miscible Floods 171
12.2.1 Vertical Miscible Floods 17112.2.2 Horizontal Miscible Floods 172
12.3 Methods of Achieving Miscibility 17212.3.1 First-Contact Miscible Process 17212.3.2 MUltiple-Contact Miscible Process 17212.3.3 Vapourizing Multiple-Contact Miscibility 173
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12.4 Experimental Methods to Determine Miscibility 17312.4.1 P-X Diagram 17312.4.2 Multi-Contact Ternary Diagram 17412.4,3 Slim Tube Test 17412.4.4 Rising Bubble Apparatus 174
12.5 Screening and Feasibility Studies 17412.5.1 Volumetric Method 17512.5.2 Break-Through Ratio Method 17712.5.3 Geological Model 17712.5.4 Simulation Studies 17712.5.5 Estimation of Uncertainties 17812.5.6 Determination of Solvent and Chase Gas Slug Size 17812.5.7 Field Performance of Miscible Floods 179
12.6 Classification of Miscible HydrocarbonReserves 17912.6.1 Possible Reserves 17912.6.2 Probable Reserves 18012.6,3 Proved Reserves 180
13. ENHANCED RECOVERY BY IMMISCIBLE GAS INJECTION 183
13.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 18313.2 Types of Floods 18313,3 Performance Prediction 184
13.3.1 External Injection Schemes 18513,3.2 Dispersed Gas Injection Schemes 185
14. ENHANCED RECOVERY BY THERMAL STIMULATION 187
14.1 Introduction 18714.2 Cyclic Steam Stimulation 187
14.2.1 Process Variation 18714.2.2 Field Examples 18814.2.3 Recovery Mechanisms 18814.2.4 Design Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 188
14.3 Steam Flooding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 18914.3.1 Process Variation 18914,3.2 Design Considerations 189
14.4 Causes of Failure for Cyclic Steam Stimulationand Steam Flood Processes 19014.5 Forecasting Models 191
14.5.1 Marx and Langenheim Model 19114.5.2 Myhill and Stegeimeier Model 19314.5,3. Vogel Model 19414.5.4 ButierModel 194
14.6 In Situ Combustion Processes 19414.6.1 Recovery Mechanisms 19514.6.2 Process Variations 19514.6.3 Design Considerations 19514.6.4 Causes of Failure , , 196
14.7 Electromagnetic Heating 196
15. ENHANCED RECOVERY BY CARBON DIOXIDE FLOODING 200
15.1 Introduction , 20015.2 Process Review , 20015.3 Recovery Mechanisms 201
15.4 Design Considerations 20115.4.1 Phase Behaviour 20115.4.2 Displacement Efficiency 20115.4.3 Volumetric Sweep Efficiency 20215.4.4 Slug Sizing 202
15.5 Reserve Evaluation 20215.6 Field Applications 203
16. RESERVES ESTIMATION FOR HORIZONTAL WELLS 205
16.1 Introduction 20516.2 Reserves Determination Techniques 206
16.2.1 Performance Projection 20616.2.2 Volumetric Method 20916.2.3 Role ofHeterogeneities ; 20916.2.4 Importance of Channelling in Reserves Performance 20916.2.5 Recovery Factors 210
16.3 Determination of Reserves 21116.3.1 Determination of Reserves Parameters 21116.3.2 Key Elements 21116.3.3 Steps Involved in Reserves Determinations 211
17. NUMERICAL SIMULATION 214
17.1 Introduction 21417.2 Types of Reservoir Simulators 21417.3 Mathematical Formulation 21517.4 Anatomy ofReservoir Simulation 21617.5 Data Requirements 216
17.5.1 ReservoirGeometry 21617.5.2 Rock and Fluid Properties 21617.5.3 ProductionandWellData 216
17.6 Reservoir Model Grid Design 21717.7 Reservoir Model Initialization 21817.8 Model Sensitivity Analysis 21817.9 History Matching 21917.10 Forecasting Reservoir Performance 21917.11 Use and Misuse of Reservoir Simulation 22017.12 Summary 220
18. DECLINE CURVE METHODS 222
18.1 Introduction 22218.2 Source and Accuracy of Production Data 22218.3 Terminology 22318.4 Single-Well vs. Aggregated-WellMethods 22318.5 Decline Curve Methods for a Single Well 224
18.5.1 Exponential Decline 22518.5.2 Hyperbolic Decline 22618.5.3 Harmonic Decline 22918.5.4 Dimensionless Solutions and Type-Curve Matching 230
18.6 Decline Curve Methods for a Group of Wells 23118.6.1 Statistical Method 23118.6.2 Theoretical Methods 234
18.7 Summary 235
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19. RECOVERY FACTOR STATISTICS , 237
19.1 Introduction 23719.2 Data Source and Reliability 23719.3 Conventional Crude Oil 238
19.3.1 Natural or Primary Drive Mechanisms 23819.3.2 Oil Recovery Factor Distributions 23919.3.3 Average Recovery Factors 24019.3.4 Pool Size 24019.3.5 Fluid Type: Light and Medium vs. Heavy 24119.3.6 Lithology: Clastics vs. Carbonates " 24219.3.7 Geological Period 24319.3.8 Geological Play '" . 24319.3.9 Recovery vs, Common Reservoir Parameters 247
19.4 Conventional Gas 24719.5 Using Recovery Factor Statistics 249
PART FOUR: PRICES, ECONOMICS, AND MARKETS
20. OVERVIEW OF PART FOUR 253
21. CASH FLOW ANALySIS 254
21.1 Introduction 25421.2 Mineral Rights Ownership 25421.3 Principal Sources and Uses of Cash 25521.4 Royalties and Mineral Tax 25721.5 Federal Corporate Income Tax 26121.6 Financial Statements 26321.7 Finance and Economic Considerations 264
22. UNCERTAINTY AND RISK IN RESERVES EVALUATION 266
22.1 Introduction 26622.2 Concepts 266
22.2.1 Definition of Risk and Uncertainty 26622.2.2 Describing Uncertainty 26622.2.3 Areas of Uncertainty 26622.2.4 Causes of Uncertainty 26822.2.5 Magnitude ofUncertainty 27122.2.6 Use of Uncertainty 271
22.3 Estimation of Uncertainty 27322.3.1· Parameters to be Estimated 27322.3.2 Empirical Classification 27322.3.3 Quantifying Subjective Estimates 27422.3.4 Quantitative Estimation 274
22.4 Methods ofAnalysis 27522.4.1 Carrying Out a Stochastic Evaluation 27522.4.2 Decision Matrices 27622.4.3 Decision Trees 27722.4.4 Probabilistic Simulation 277
22.5 Evaluation of Undeveloped Lands 278
23. THE REGULATORY ENVIRONMENT 281
23.1 Introduction 28123.2 Resource Assessments 28123.3 Mineral Ownership 28223.4 Economic Development Policies 28223.5 Conservation Controls 283
23.5.1 Field Development and Production Conservation 28323.5.2 Consumer Demand Conservation 283
23.6 Development, Operating, and Environmental Regulations 28323.7 Domestic Supply Assurance 28423.8 Fiscal Policies 28523.9 Business Regulations 28523.10 International Policies 285
24. CRUDE OIL MARKETS 287
24.1 Introduction 28724.2 Transportation Network 28824.3 Major Markets 29024.4 North American Pricing 29124.5 Price Risk Management 294
24.5.1 Futures 29424.5.2 Options 29524.5.3 Swaps 295
24.6 Outlook and Challenges 295
25. NATURAL GAS MARKETS 297
25.1 Introduction 29725.2 The Market Environment 297
25.2.1 Review ofPre-DeregulationEra 29725.2.2 Review of Current Era 29825.2.3 Preview ofFuture Era 300
25.3 Market Mechanisms and Market Forces 30025.3.1 Market Types and Market Mechanisms 30025.3.2 Market Demand Forces 30225.3.3 Production Forecasting 304
25.4 The Role of Reserves 30425.5 Conclusions 305
26. USES OF RESERVES EVALUATIONS 306
26.1 Introduction 30626.2 Users of Reserves Volumes and Production Forecasts 306
26.2.1 Producers 30626.2.2 Transporters 30626.2.3 Governments 30626.2.4 Gas Marketers 30726.2.5 Other Users 307
26.3 Developing Values from Reserves Estimates 30726.3.1 Profitability Indices 30726.3.2 Incremental Economics 31026.3.3 Acceleration Projects 310
26.4 Uses of the Values Derived from Reserves Estimates 31126.4.1 Valuing Oil and Gas Companies 311
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26.4.226.4.326.4.426.4.526.4.626.4.726.4.826.4.926.4.10
Sale of ResourceProperties 312Evaluation of UnexploredLands and ExplorationWells 313Lending and Borrowing 314Auditing Evaluations 314SecuritiesReporting 315Accounting Requirements 316EstablishingFindingand Replacement Costs 317Estimating Barrelsof Oil Equivalent 318EstimatingNet-BackCalculations 320
Biographies ofAuthors 32i
Acronyms 329
Glossary 333
Bibliography 345
Author index 349
Subject index 353
FIGURES
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2.1-12.1-22.5-13.3-13.3-23.3-3
3.3-4
3.3-5
3.3-63.3-73.3-83.3-93.3-103.3-115.1-15.1-25.1-3
5.1-45.2-15.2-25.2-35.2-45.2-55.4-15.4-25.4-3
Resources 4Reserves 6Reserves Ownership 7Single Well Oil Pool with Good Geological Control 13Conventional Gas Pool, Zero Limit of Net Pay Map 14Conventional Gas Pool, Zero Limit of Net Pay Mapwith Individual Well Assignments 15Conventional Gas Pool, Zero Limit of Net Pay Mapwith Area of ProvedReserves . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 15Conventional Gas Pool, Zero Limit of Net Pay Mapwith Area of ProvedPlus ProbableReserves 16Material Balance(Gas Reservoir) 18Material Balance (Scattered Data) 19Material Balance(ReservoirDrive and DepletionMechanism) 19Decline Curve, ProvedReserves ., 20Decline Curve, Cumulative Gas Production 21Decline Curve, Cumulative Oil Production 21Pressure-Depth Plot for Free Water Level Determination 38Cross Contouring 40Series of RelatedMaps (zero edge from seismic,computer-contoured) (ZYCORSoftware) 41Examples of Mechanical and Interpretive Mapping 42Reservoir IntervalTerminology 44Air Permeabilityvs. Porosity 46Flow Chart for a Core AnalysisProgram 47Hydrocarbon Fluid ContactIdentification from Pressure Gradients 49Sand Unit ShapeDiagram 51Porosity of Cubic-Packed Spheres 55Typical Core Analysis Report 59Porosity vs. Horizontal Permeability 60
5.4-45.4-55.4-65.4-75.4-85.4-95.5-15.5-25.5-35.5-45.5-55.5-65.6-15.6-25.7-1
5.7-25.7-35.7-4
5.8-15.8-25.8-35.8-45.9-15.10-1
6.3-16.4-16.4-26.4-36.4-46.4-57.7-17.7-29.1-19.1-29.1-39.2-19.3-19.3-29.3-39.3-410.2-110.2-210.3-110.3-210.5-110.5-210.8-110.8-2
Core Analysis Report: Analytical Summary Sheet 60PorosityfromFormation Density Log 61Porosityfrom Sonic Log 61NeutronPorosityEquivalence Curves 62Porosityand Lithology Determination from Neutron-Density Log 62Impactof Clay on Log and CoreMeasurements 64Porosityvs. Formation Factor 67Formation Resistivity Index 68Air Brine Capillary Pressure Test 70Log Interpretation FlowChart 71Dual Water Model 72Shaly Sand Interpretation Process 73DrillstemTest Tool (UnsetPosition) 76DrillstemTest Tool (Set Position) : ; 76Representative HomerPlots from Wellsin the Utah-WyomingThrust Belt 83Relief Map for Southern Alberta 83ContourPlot of Spreadfor BHTValues in Southern Alberta 83Examples of Temperature vs. DepthPlotsfromTwo Areas in Southern Alberta 84StaticGradient 87Pressure vs. Time 87Homer Plot 88PorosityVolume Map 89Compressibility Factors for Natural Gases 93Comparison of Formation Volume Factorby Differential and Flash Liberation 96Estimation of Reef Volume 110Typical Situation: Gas Pool Map IIIConversion of BaseArea to Average Pool Area 113Typical Situation: Gas-in-Place Distribution 116Typical Situation: Reserve Distribution 118Typical Situation: Discounted Net ProfitBefore Investment 119StraightLine Plot for Oil Zone and Gas Cap Case 126StraightLine Plot for Oil Zoneand Water InfluxCase 127SolutionGas DriveReservoir 133Comparison of Solution Gas Driveand WaterDriveReservoirs 134Gas Cap DriveReservoir 135Recommended Methods for the Stagesof Exploitation 135Relationship Between Production Rate and Reserves 141Relationship Between Well Spacing and Abandonment Pressure 143Optimum Well Spacing 143Effectsof FacilityConstraints on Economic Limit 143Classification of Gas Basedon Source in Reservoir 145Occurrence of Oil and Gas 146Pressure-Temperature PhaseDiagram of a Reservoir Fluid 147Phase Diagram of a Cap Gas and Oil Zone Fluid 147Plot ofP/Z vs. Cumulative Gas Production 150Effect of WaterDriveon Pressure Decline 150Back Pressure Plot 152Gas Deliverability Plot 152
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11.2-1
11.2-2
11.3-111.3-211.3-311.5-112.3-112.3-212.3-312.5-113.2-114.5-114.5-2
16.2-117.2-117.3-117.6-117.6-217.6-317.6-418.3-118.3-218.5-118.5-218.5-3
18.5-418.5-518.5-618.6-118.6-218.6-318.6-418.6-519.3-119.3-219.3-319.3-419.3-519.3-619.3-719.3-819.3-919.3-1019.3-1119.3-1219.3-1319.3-14
Effect of Oil Viscosity on Fractional Flow Curve,Strongly Water-Wet Rock 155Effect of Oil Viscosity on Fractional Flow Curve,Strongly Oil-Wet Rock 155Cross Section for Vertical Waterflood 156Plan View for Horizontal Waterflood 156Flood Patterns for Horizontal Flood Schemes 157Effect ofMobility Ratio on Oil Production for the Five-Spot Pattern 159Pseudo-Ternary Diagram Indicating First-Contact Miscibility 172Development of Multiple-Contact Miscibility Condensing Process . . . . . . 173Development of Multiple-Contact Miscibility Vapourizing Process 173Reserves Distribution 178Gas Injection 184Types ofAnalytical Gravity Drainage Models 192Thermal Efficiency of Steam Zone as a Functionof the Dimensionless Time Parameter 193Schematic of Horizontal and Vertical Well Drainage Areas 208Schematic Diagram ofMatrix-Fracture Connectivity 215Mass Balance on Reservoir Element 2152D Areal Model 2172D Vertical Model 2172D Radial Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2173D Model 218Reservoir Performance Chart 224Production Performance Chart 224Exponential Decline Chart 226Decline Curve Analysis Chart Relating Production Rate to Time 227Decline Curve Analysis Chart Relating Production Rateto Cumulative Production 227Hyperbolic Curve Overlay 228Production Performance Graphs 229Composite of Analytical and Empirical Type Curves 230Production Performance Graph 232Rate-Cumulative Production Graph 232Distribution of Well Rates, Pembina Cardium Pool 233Rate-Ratio-Cumulative Graph, Pembina Cardium POOl 234Production Performance Graphs, Pembina Cardium Pool 234Oil Pools 239Distribution of Primary Oil Recovery Factors 240Large Mature Oil Pools 241Light and Medium Oil Pools 241Heavy Oil Pools 242Clastic Oil Pools 242Carbonate Oil Pools 242Upper Cretaceous Oil Pools 243Lower Cretaceous Oil Pools 243Jurassic Oil Pools 244Triassic Oil Pools 244Permian Oil Pools 244Mississippian Oil Pools 244Upper Devonian Oil Pools 245
7
19.3-1519.3-16(a)19.3-16(b)19.3-17(a)19.3-17(b)19.3-18(a)19.3-18(b)19.3-1919.3-2022.2-122.2-2
22.2-322.2-422.2-5
24.2-124.2-224.4-124.4-225.3-125.3-225.3-3
4.2-14.4-15.4-15.5-15.10-15.10-25.10-36.1-16.4-16.4-26.4-36.4-4
6.4-56.4-6
7.2-17.2-29.2-19.2-210.7-111.8-111.11-1
Middle Devonian Oil Pools 245Oil Recovery vs. Porosity 247Porosity Distribution 247Oil Recovery vs. Net Pay 248Net Pay Distribution 248Oil Recovery vs. Water Saturation 248Water Saturation Distribution 248Gas Pools (Producing) 249Large Gas Pools (Producing) 249Risk and Uncertainty 267Level of Uncertainty in Reserves Estimatesduring the Life of a Producing Property 269The Effect ofError and Bias on a Reserve Estimate 270Expectation Curves: Comparison of Results 271Expectation Curve: Reconciliation ofDifferent Viewsof Hydrocarbon Volumes and Values 272Major Alberta Pipeline Systems 288Major Crude Oil Pipelines and Refining Areas 289NYMEX WTI Prices at Cushing 293Alberta Crude Oil Pricing, Chicago Market (July 1992) 293Commercial and Regulatory Mechanisms for Ex-Alberta Markets 301Gas Marketing Options 302Reserves Connection to Markets 303
TABLES
In-Place Volumes of Related Products 30Sources of Data 32Comparison ofTechniques of Determining Porosity 56Wettability and Interfacial Tension 69Pressure Volume Relations 98Separator Tests of Reservoir Fluid Sample 99Differential Vapourization 99In-Place Volumetric Estimation Techniques 107Gas-in-Place Distribution for Most Likely Area of384 Hectares 114Gas-in-Place Distribution for Most Likely Area of 576 Hectares 115Gas-in-Place Distribution for Most Likely Area of 704 Hectares 115Gas-in-Place Distribution for Most Likely Area of 576 Hectares,Variable Temperature and Gas Deviation Factor 117Reserve Distribution for Most Likely Area of 576 Hectares 118Discounted Net Profit Before Investment Distributionfor Most Likely Area of 576 Hectares 119ReservoirVoidage Terms 121Reservoir Expansion Terms 122Recommended Reserves Forecasting Methods 136Decline Analysis Plots Used after Water Break-through 139Recoveries of Related Products 151Classification of 33 Waterflood Prediction Methods 165Summary of Recovery Factors: A Samplingof Western Canadian Waterfloods 169
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XV1l1
11.11-213.3-118.5-118.6-119.2-119.3-119.3-219.3-319.3-421.4-121.4-221.4-321.5-124.3-126.4-1
ReserveAnalysis Technique Distribution . . . . . . . . . . . . . . . . . . . . . . . . .. 169Recommended Performance Prediction Methods 185DeclineCurve Equations 225Statistical Parameters for Pembina Cardium Pool 233Public Data Available for Reserve Studies 237PrimaryOil Recovery by DriveMechanism 238AverageOil Recoveries 241Recovery Factorsfor UpperDevonian Zones 245Recovery Factorsfor Geological Plays in WesternCanada 246Summaryof AlbertaNatural Gas RoyaltyChanges 258Summaryof Equations for BasicRoyalty 259Summaryof AlbertaCrude Oil RoyaltyRate Changes 259Cash Flow and Income Tax Summary 262Importers of Canadian HeavyCrude 292Conversion Rates 318
7
FOREWORD
The estimating and reporting of reserves of oil and gas and related substances are of fundamentalimportance to the oil and gas industry. Reserves estimates form the basis for most development andoperational decisions and are ofcritical importance in financing and other commercial arrangementsthat allow oil and gas developments to proceed in an orderly and efficient manner. Reservesestimates also playa key part in relevant planning and policy decisions by governments and others.
The role of reserves estimates in operational, financial and policy decisions emphasizes the need forthe estimates to be as accurate and current as possible.The use ofconsistent terminology and estimation procedures is also essential. This monograph,Determination ofOil and GasReserves, has beendeveloped to assist in achieving the objectives of accuracy and consistency in estimating reserves.
The idea ofdeveloping such a monographwas conceivedby Dr. Roberto Aguilera who, as Chairmanof the Reserves Monograph Advisory Committee,has co-ordinatedthe preparation of the document.The project was sponsored by the CalgarySectionof the Petroleum Society ofthe Canadian InstituteofMining, Metallurgy and Petroleum.
The first organizational meeting of the committee took place in the spring of 1990. Since that time,members of the committee, on their own and with the support of their employers, have contributedsubstantial time and expertise to the project and enlisted the help of many industry experts in thepreparation and critique of specific chapters.The objective was to develop a reference that would beof substantial value to geologists, engineers and other technical persons involved in estimating reserves, as well as to others whouse such estimatesfor particularpurposes. With the publication ofthemonograph in the spring of 1994, the committeewill have achieved that objective.
A total of over fifty people have been involved in the planning, the writing and review of thechapters, the drafting of figures, and the editing and preparation of the final copy for the printing ofthe monograph. All those involved in estimatingoil and gas reserves, or who use such estimates, owethem a vote of thanks. I am confident that the monograph will become a standard reference for allpractitioners of the science ofestimating oil and gas reserves. It will also serve as an excellent training tool for persons who have only a basic understanding of reserves estimation methods and whowish to advance their knowledge of the subject.
G. 1. DeSorcy, P.Eng.Calgary, January 1994
xix
z
PREFACE
The estimation of reserves of oil, gas, and related substances has been a hot topic since the verybeginning of the oil industry. Over the ensuing years, the concept of reserves has meant differentthings to different people within this industry, with each evaluator, oil and gas company, financialagency, securities commission, and government department using its own version of the definitions.The monograph represents our effort to find definitions and guidelines for the classification ofreserves that will be acceptable to all ofthese users.
When the concept of this monograph was first discussed, we wrestled with the question: "Should weask one or two professionals to prepare the whole monograph or should we ask a variety ofspecialiststo contribute to it?" In the end we concluded that we would not find one or two people with expertisein all the topics concerned with oil and gas reserves, so we should use a number of knowledgeableauthors. We ended up with forty contributing authors and a group of reviewers who helped to polishthe thirty-seven topics covered in the twenty-six chapters ofthe monograph.
The topics have fallen into four major divisions that we have called "parts" in the monograph. PartOne presents the definitions and guidelines for the classification of oil and gas reserves. These havebeen prepared by the Standing Committee on Reserves Definitions of the Petroleum Society of theCanadian Institute of Mining, Metallurgy and Petroleum.
Part Two discusses the volumetric and material balance methods for estimating volumes of oil andgas in place, various sources of data, and the interpretation of the data. Part Two also deals withprobabilistic methods for estimating the volumes of oil and gas contained in reservoirs, in addition tothe more common deterministic methods.
Part Three considers the estimation of recovery factors for oil and gas reservoirs, with particularemphasis on volumes recoverable by enhanced recovery methods. Secondary and tertiary recoverymethods are discussed, as well as primary methods and the use of horizontal wells. Part Three alsoaddresses decline curve analysis and reservoir modelling by numerical simulation.
Part Four covers the other factors that must be considered in estimating reserves: cash flow analysis,the assessment of uncertainty, the role of markets, and potential regulatory impacts that must berecognized by evaluators. Part Four ends with a discussion of the uses that are made of reservesestimates. This part proved to be very challenging to write as the diverse nature of the applicationsof recovery estimates in economic evaluations led to some animated discussions between theengineering and financial groups. But in the end, I think we put together some information that willbe useful to all the professionals who deal with economic evaluations.
(cont'd)
xxi
xxii
For simplicity, the nomenclature and units ofmeasurement are defined following each equation. Wehave used the metric system (SI), with Imperial units shown as well in some cases.
Following the text, we have included brief biographies of the authors and several lists for theconvenience of readers: Acronyms, Glossary, Bibliography, Author Index, and Subject Index.
It is our sincere hope that this monograph, Determination of Oil and Gas Reserves, will help tosimplify and standardize the science and art ofestimating oil and gas reserves throughout the world.
Roberto Aguilera, P. Eng.Calgary, January 1994
ACKNOWLEDGEMENTS
Associated with the publication of the monograph was the time-consuming and challenging task ofco-ordinating the material produced by forty authors with forty different backgrounds and forty different writing styles. The Reserves Monograph Advisory Committee did a superb job ofco-ordinatingthe four parts of the monograph. As Chairman, I wish to thank the members of the committee for themany hours they devoted to planning the work, meeting with the authors, and reviewing the drafts.The following are the members of the committee with their company affiliations. We are grateful tothe employers for supporting the members in this endeavour.
N. Guy BerndtssonKeith D. BrownCAS. (Charlie) BulmerR.V. (Bob) EtcheverryJohn HewittR. V. (Bob) LangW.V. (Bill) MandolidisMichael E. McCormackr. Glenn RobinsonRoberto Aguilera, Chairman
Energy Resources Conservation BoardRoyal Bank of CanadaSproule Associates LimitedCN Exploration Inc.Martin Petroleum and AssociatesEnergy ConsultantSaskatchewan Oil and Gas Corp.Fractical Solutions Inc.Sproule Associates LimitedServipetrol Ltd.
7
The work on the monograph involved authors and reviewers with backgrounds in governmentregulations, banks, stock brokers, securities commissions, consultants, the University of Calgary,and major, mid- and small-sized exploration and production companies. On the following pages arelisted the names and company affiliations of the authors of the various chapters and sections of themonograph. These are the people who supplied the "meat" of the document through many volunteerhours of labour-writing, revising, and consulting with others-on the material they wereresponsible for.
In addition, we would like to thank the Petroleum Society ofCIM, Canadian Well Logging Society,Society of Petroleum Engineers, Society of Professional Well Log Analysts, American Associationof Petroleum Geologists, and Alberta Energy Resources Conservation Board, as well as WesternAtlas International Inc., Schlumberger, GulfPublishing Co., PanCanadian Petroleum Ltd., ChevronCanada Resources, and PennWell Publishing Co. for permission to use material from theirpublications.
We also express our gratitude to all of the various authors and organizations that have publishedmaterial on reserves estimation and thereby added to the body of knowledge on this subject.
Virginia MacKay, P.Eng., the professional editor for this monograph, undertook the daunting task ofediting the material written by the forty different authors and assembling it all into one coherentdocument. She was assisted very conscientiously by lA. (Sandy) Irvine, P.Geol., who entered thetext and figures on the computer. Together they prepared the camera-ready copy for the printer. MikeMcCormack checked the nomenclature throughout the monograph and also contributed to the compilation ofthe Subject Index. Our sincere thanks to Virginia, Sandy, Mike, and all the authors, reviewersand co-ordinators for their dedication to the quality of the monograph.
Roberto Aguilera, P. Eng.Calgary, January 1994
XXlll
AUTHORS
Part One
Standing Committee on Reserves Definitions
GJ. (Gerry) DeSorcyEnergy Consultant
George A. WarneEnergy Consultant
R. V. (Bob) LangEnergy Consultant
J. Glenn RobinsonSproule Associates Limited
Barry R. AshtonAshton Jenkins and Associates Ltd.
Graham R. CampbellNational Energy Board
David R. CollyerShell Canada Limited
John DruryConsultant (Ontario Securities Commission)
W.O. (Bill) RobertsonPrice Waterhouse
David W. TuttBank of Montreal
Chairman
Secretary
Co-ordinator
Co-ordinator
xxiv
Note: All committee members contributed to the writing of Part One.
AUTHORS (cant'd)
Part Two
R
N. Guy BerndtssonEnergy Resources Conservation Board
CAS. (Charlie) BulmerSproule Associates Limited
Brent AustinPanCanadian Petroleum Limited
Robin G. BertramTalisman Energy Inc.
Mike J. BrussetBrusset Consultants Ltd.
Merlin B. (Mel) FieldConsultant
J.D. (Joe) GiegerichChevron Canada Resources
DJ. (Dave) HemphillShell Canada Limited
Craig F. LambLonach Consulting Ltd.
Raymond A. MireaultGulf Canada Resources Limited
Co-ordinator
Co-ordinator
Co-Author of Sections 5.2,5.3,5.4,5.5
Co-Author of Section 5.6 andAuthor of Sections 5.8, 5.9
Co-Author of Section 5.6 andAuthor of Section 5.11
Author of Chapter 7
Author of Sections 5.7, 5.10
Author of Section 5.1
Co-Author of Sections 5.2,5.3, 5.4, 5.5
Author of Chapter 6
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AUTHORS (cont'd)
Part Three
XXVI
R.V. (Bob) EtcheverryCN Exploration Inc.
John M. HewittMartin Petroleum & Associates
Soheil AsgarpourGulf Canada Resources Limited
Anthony D. AuServipetrol Ltd.
Keith M. BraatenColes Gilbert Associates Ltd.
RonM. FishImperial Oil Limited, Resources Division
Mam Chand GuptaGM International Oil and Gas Consulting Corp
William E. KerrJoss Energy
Gobi KularAdvanced Petroleum Technologies
Dana B. LaustsenColes Gilbert Associates Ltd.
Margaret NielsenPetro-Canada
David C. PoonConsultant, D.C. Poon Consulting Inc.
Ross A. PurvisEnergy Resources Conservation Board
Darlene A. SheldonPetro-Canada
Phillip M. SigmundBRTR Petroleum Consultants Ltd.
Ashok K. SinghalPetroleum Recovery Institute
Andy WarrenEnergy Resources Conservation Board
Co-ordinator andAuthor of Sections 8.1, 8.2
Co-ordinator andAuthor of Section 8.3
Author of Chapter 12
Author of Chapter 17
Co-Author of Chapter II
Author of Chapter 13
Author of Chapter 10
Co-Author of Chapter 15
Co-Author of Chapter 14
Co-Author of Chapter II
Co-Author of Chapter 9
Co-Author of Chapter 14
Author of Chapter 18
Co-Author of Chapter 9
Co-Author of Chapter 15
Author of Chapter 16
Author of Chapter 19
AUTHORS (cont'd)
Part Four
KeithD. BrownRoyal Bank of Canada
JanuszBieleckiNationalEnergy Board
Noel A. ClelandSproule Associates Limited
DavidC. ElliottGeosgil Consulting
HaroldR. KeushnigEnergyResources Conservation Board
Tim J. ReimerPan-Alberta Gas Ltd.
Co-ordinator andAuthorof Chapters20, 21
Authorof Chapter24
Authorof Chapter26
Authorof Chapter 22
Authorof Chapter23
Authorof Chapter25
xxvii
7
PART ONE
DEFINITIONS AND GUIDELINES
FOR CLASSIFICATION
OF OIL AND GAS RESERVES
Chapter 1
OVERVIEW OF PART ONE
?
There are almost as many definitions for reserves of oiland gas and related substances as there are evaluators,oil and gas companies, financial agencies, securitiescommissions, and government departments. Eachuses its own version of the definitions for its ownpurposes. In addition, because of today's unstableeconomic conditions in the oil and gas industry, thelower quality of the reservoirs being discovered, andthe new recovery methods being developed, it is becoming increasingly difficult to estimate the reservesthat will be produced. All ofthese factors have made itimperative to develop a universal set of definitions forreserves that will meet the needs of all users.
Part One of the monograph contains the definitions ofkey terms, the system of reserves classification, andguidelines to illustrate the application ofthe definitionsand the classification system.
The task of writing the definitions was undertaken bythe Standing Committee on Reserves Definitions ofthePetroleum Society of the Canadian Institute ofMining,Metallurgy and Petroleum, and Part One of the monograph has been published as a separate documentcomprising the committee's 1993 report. The committee includes representatives of oil and gas companies,geological and petroleum engineering consulting firms,Canadian industry associations, financial and accounting organizations, regulatory agencies, and government.
The definitions ofkey terms and reserves classificationspresented in Chapter 2 are similar to those currently inuse by the oil and gas industry, particularly in NorthAmerica. They have been reviewed by users in the industry and representatives from regulatory agencies,government departments, industry associations, andtechnical and professional organizations.
Chapter 3 presents the guidelines that illustrate theapplication of the definitions and the classificationsystem. These are intended to complement the detailed guidelines on reserves estimation methods andprocedures that follow in subsequent chapters of themonograph.
The StandingCommittee believes that the recommendeddefinitions and guidelines are suitable for use with respect to all types of oil and gas and related substances,including offshore reserves and oil sands. Althoughthose segments of the industry have used somewhatdifferent terms and definitions, the principles reflectedin the definitions recommended here are applicable. Thefundamental principle is that those quantities that areknown to exist and to be economically recoverable arereserves. The total quantities, whether or not they havebeen discovered, are resources. Reserves and resourcesare further categorized depending on the level ofcertainty that they will be recovered.
It is the view of the Standing Committee that currentreserves estimation methods and categories, in general,match the recommended definitions and guidelines.The committee, therefore, does not expect that majorchanges to reserves estimates would result from adoption of the definitions, although it recognizes that forsome specific reserves estimates (generally for smallpools) changes could be significant. The committeehopes that, over time, reserves evaluators will increasingly conform to the recommendations presented in thismonograph and thus contribute to the overall qualityand consistency of reserves estimates.
The StandingCommittee received assistance from manyindividuals and organizations in the form ofcommentsas it formulated the definitions and guidelines. Thecommittee will continue to communicate with interested parties to ensure that its intent with respect to therecommended definitions is fully understood. Thecommitteewelcomes comments on its recommendationsas well as any other aspects of reserves definitions andtheir application. Since comments are being sought fromthose that use the recommendations, it is reasonable toexpect that the definitions may change with time. If theydo, the revisions will be available from the PetroleumSociety.
3
Chapter 2
DEFINITIONS
2.1 INTRODUCTIONThe terminology recommended for the classification ofestimated quantities ofoil and gas and related substances,at a particular time, is presented in Figures 2.1-1 and2.1-2. Each term is defined in this chapter. Figure 2.1-1and its related definitions set the framework for Figure2.1-2 and its related definitions.
The major classifications identified in this chapter areresources, remaining reserves, and cumulative production, each of which can be further divided into
sub-classifications. Reserves ownership is also discussedin this chapter.
2.2 RESOURCESResources are the total quantities of oil and gas andrelated substances that are estimated, at a particular time,to be contained in, or that have been produced from,known accumulations, plus those estimated quantitiesin accumulations yet to be discovered.
Figure 2.1-1 Resources
4
7
DEFINITIONS
2.2.1 Discovered Resources or InitialVolumes in Place
Discovered resources, which may also be referred to asinitial volumes in place (Figure 2.1-1), are those quantities of oil and gas and related substances that areestimated, at a particular time, to be initially containedin known accumulations that have been penetrated by awellbore. They comprise those quantities that are recoverable from known accumulations and those that willremain in known accumulations, based on known technology under specified economic conditions that aregenerally accepted as being a reasonable outlook forthe future.
Initial Reserves
Initial reserves are those quantities of oil and gas andrelated substances that are estimated, at a particular time,to be recoverable from known accumulations. They include cumulative production plus those quantities thatare estimated to be recoverable in the future by knowntechnology under specified economic conditions that aregenerally accepted as being a reasonable outlook forthe future. (Figure 2.1-2 shows how initial reserves areclassified.)
Unrecoverable Volumes
Unrecoverable volumes (Figure 2.1-1) are thosequantities of oil and gas and related substances that areestimated, at a particular time, to remain in known accumulations because they are not recoverable by knowntechnology under specified economic conditions that aregenerally accepted as being a reasonable outlook forthe future.
Unrecoverable volumes may be further dividedinto currently uneconomic volumes, which are thosequantities that are currently estimated to be technicallyrecoverable, but that are not economically recoverableunder the specified economic conditions, and residualunrecoverable volumes, which are those quantities thatare unrecoverable by known technologies.
2.2.2 Undiscovered Resources or FutureInitial Volumes in Place
Undiscovered resources, which may also be referredto as future initial volumes in place (Figure 2.1-1), arethose in-place quantities ofoil and gas and related substances that are estimated, at a particular time, to existin accumulations yet to be discovered.
Future Initial Reserves
Future initial reserves are those quantities of oil andgas and related substances that are estimated, at a particular time, to be recoverable from accumulations yetto be discovered by known technology under specifiedeconomic conditions that are generally accepted asbeing a reasonable outlook for the future.
Future Unrecoverable Volumes
Future unrecoverable volumes are those quantities ofoil and gas and related substances that are estimated, ata particular time, to remain in accumulations yet to bediscovered because they are not recoverable by knowntechnology under specified economic conditions that aregenerally accepted as being a reasonable outlook forthe future.
2.3 REMAINING RESERVESRemaining reserves (Figure 2.1-2) are estimatedquantities of oil and natural gas and related substancesanticipated to be recoverable from known accumulations, from a given date forward, by known technologyunder specified economic conditions that are generallyaccepted as being a reasonable outlook for the future.
2.3.1 Remaining Proved ReservesRemainingproved reserves are those remaining reservesthat can be estimated with a high degree of certainty,which for purposes ofreserves classification means thatthere is generally an 80 percent or greater probabilitythat at least the estimated quantity will be recovered.These reserves may be divided into proved developedand proved undeveloped to identify the status ofdevelopment. The proved developed may be further dividedinto producing and nonproducing categories.
2.3.2 Probable ReservesProbable reserves are those remaining reserves that areless certain to be recovered than proved reserves, whichfor purposes of reserves classification means that generally there is a 40 to 80 percent probability that theestimated quantity will be recovered. Both the estimatedquantity and the risk-weighted portion reflecting therespective probability should be reported. These reservescan be divided into probable developed and probableundeveloped to identify the status of development.
2.3.3 Possible ReservesPossible reserves are those remaining reserves that areless certain to be recovered than probable reserves, whichfor purposes of reserves classification means that
5
-I
generally there is a 10 to 40 percent probability thatthe estimated quantity will be recovered. Both the estimated quantity and the risk-weighted portion reflectingthe probability should be reported. These reserves canbe divided into possible developed and possibleundeveloped to identify the status of development.
2.3.4 Development and ProductionStatus
Each of the three reserves classifications, remainingproved, probable and possible, may be divided into developed and undeveloped categories (Figure 2.1-2). Thedeveloped category for proved reserves is often dividedinto producing and nonproducing.
Developed Reserves
Developedreserves are those reserves that are expectedto be recovered from existing wells and installed facilities or, if facilities have not been installed, that wouldinvolve a low expenditure to put the reserves on production (i.e., when compared to the cost of drilling awell).
Developed Producing Reserves
Developed producing reserves are those reserves thatare expected to be recovered from completion intervals
DETERMINATION OFOILAND GAS RESERVES
open at the time of the estimate. These reserves may becurrently producing or, if shut in, they must havepreviously been on production, and the date ofresumption of production must be known with reasonablecertainty.
Developed Nonproducing Reserves
Developed nonproducing reserves are those reserves thateither have not been on production, or have previouslybeen on production, but are shut in, and the date ofresumption ofproduction is unknown.
Undeveloped Reserves
Undeveloped reserves are those reserves expected to berecovered from known accumulations where a significant expenditure (i.e., when compared to the cost ofdrilling a well) is required to render them capable ofproduction.
In multi-well pools, it may be appropriate to allocatethe total reserves for the pool between the developedand undeveloped categories or to subdivide the developed reserves for the pool between developed producingand developed nonproducing. This allocation should bebased on the evaluator's assessment as to the reservesthat will be recovered from specific wells, the facilities
Figure 2.1-2 Reserves
6
DEFINITIONS
and completion intervals in the pool, and theirrespective development and production status.
2.4 CUMULATIVE PRODUCTIONCumulative production (Figure 2.1-2) comprises thosemarketable quantities of oil and gas and related substances that have been recovered to date from knownaccumulations.
2.4.1 SalesSales are produced quantities ofoil and gas and relatedsubstances that have been sold to date.
2.4.2 InventoryInventory consists of quantities of oil and gas andrelated substances that have been produced and areavailable for future use.
2.5 RESERVES OWNERSHIPThe terminology that is recommended for reporting theownership of quantities of oil and gas and related substances is presented in Figure 2.5-1. The terms aredefined as follows:
Gross remaining reserves are the total remainingreserves associated with the property in which an ownerhas an interest.
Company* gross remaining reserves are the company'slessor royalty, overriding royalty and working interestshare ofthe gross remaining reserves, before deductionof any Crown, freehold, and overriding royaltiespayable to others.
Company* net remaining reserves are the company'slessor royalty, overriding royalty, and working interest
Other OwnerInterest Reserves
•Lessor Royalty Interests
PayableOverriding Royalty Interests
Payable
7
Figure 2.5-1 Reserves Ownership
* The word"Company"may be replaced by moresuitable adjectives to betterdepictthe ownership of reserves, e.g., ABC Oiland Gas, 9367 LimitedPartnership, John Doe, etc.
7
share of the gross remaining reserves, less all Crown,freehold, and overriding royalties payable to others.
2.6 SPECIFIED ECONOMICCONDITIONS
In order for oil and gas and related substances to beclassified as reserves, they must be economic to recoverat specified economic conditions. The estimator shoulduse, as the specified economic conditions, a price forecast and other economic parameters that are generallyaccepted as being a reasonable outlook for the future.The revenue, appropriately discounted, must be sufficient to cover the future capital and operating costs thatwould be required to produce, process, and transportthe products to the marketplace. A more detailed discussion of discounting future cash flow is presentedin Chapter 21, Cash FlowAnalysis, and in Chapter 26,Uses ofReservesEvaluations.
Ifrequired by securities commissions or other agencies,current prices and costs may also be used. In either case,the economic conditions used in the evaluations shouldbe clearly stated. Occasionally, the estimator also maywish to determine the impact of higher or lower priceforecasts on estimates of reserves as compared to themost reasonable forecast. These cases (current, higheror lower prices) should not be reported as the most reasonable reserves estimates, but should be identified assensitivity cases with the assumptions clearly stated.They illustrate the impact of different specifiedeconomic conditions on estimates of reserves.
2.7 REPORTING OF RESERVESESTIMATES
2.7.1 Risk-Weighting of ReservesEstimates
Remaining proved reserves, as defined in Section 2.3.1,are those reserves for which there is an 80 percent orgreater probability that at least the estimated quantitywill be recovered. In instances where additional reservesare estimated in the probable and possible categories,both the estimated quantity and the adjusted (riskweighted) portion should be reported, particularly whenthe estimates are being aggregated.
Proper statistical procedures may be used to derive theexpected or risk-weighted reserves from the data. In thedeterministic procedure, the best estimate of eachparameter is used in the calculation of reserves. Theprobabilistic procedure quantifies the uncertainty in theresource estimate by using the evaluator's opinion todescribe the range of values that could possibly occur
8
DETERMINATION OFOILAND GASRESERVES
for each variable.' Ifa deterministic procedure is beingused and a probabilistic determination is not available,the following equality is recommended to approximatethe expected reserves:
expected = (proved ) + (p x probable) + (p x Possible)reserves reserves b reserves S reserves
where Pb = probability of recovering theprobable reserves (80-40%)
P, = probability of recovering thepossible reserves (40- I0%)
For individual pools, the amount for the expected orrisk-weighted reserves provides the evaluator's bestjudgement as to the quantity that will be recovered fromthe pool. The probability used to adjust the estimatedquantity for a specific pool should be that consideredby the evaluator to be appropriate for the particular circumstance, taking into account the available geological,geophysical and engineering data. It is likely, however,that the quantity actually recovered from a specific poolwill be more or less than the risk-weighted estimate. Ifthe number ofpools for which estimates ofreserves arebeing prepared is sufficiently large, then the sum of theexpected reserves should be the evaluator's best judgement as to the total quantity that will be recovered fromall the pools. According to the ranges specified in thesedefinitions, the risk-weighting should result in an average risk-weighting of 60 percent for probable reserves(the mid-point ofthe 80 to 40 percent probability range)and 25 percent for possible reserves (the mid-point ofthe 40 to 10 percent probability range).
When the value of the risk-weighted reserves is beingdetermined, the unrisked reserves must be used in theeconomic analysis. Risk for both the reserves and values should only be applied after the economic forecastshave been completed using total costs to develop theunrisked reserves.
2.7.2 Aggregation of ReservesEstimates
Traditionally, when deterministic approaches are beingused, the aggregation of a series of reserves estimateswill have been made using the arithmetic method. However, with the increase in the use of statistical methodsin reserves determination, the arithmetic method ofaggregation may not always be appropriate. Although
• Theseprocedures are described in more detailinSection 4.3.
DEFINITIONS
use of a statistical method of aggregation may be betterfor reserves estimates, the method of aggregation maybe dictated by regulators, auditors or management. Thus,when aggregating a series of reserves estimates, theevaluator should state whether the method of aggregation is arithmetic or statistical. Ifa statistical method isused, the evaluator should state how it is done.
If the proved reserves, which represent an 80 percentconfidence level, are summed arithmetically, the totalreserves will represent a confidence level that is muchhigher than would be achieved if the proved reserveswere totalled using a probabilistic approach of all theentities and an 80 percent confidence level. Conversely, .the proved plus probable reserves and the proved plusprobable plus possible reserves will be overstated whensummed arithmetically using a deterministic as compared to a probabilistic procedure.
On the other hand, the sum of the expected reserves, asdefined in the preceding sections, should be the same asthe deterministic (using arithmetic methods) and theprobabilistic procedures. This relationship is extremelyimportant in summing reserves, and therefore it is recommended that risk-weighted reserves be used in theaggregation of reserves. In any event, the evaluatorshould state whether the method of aggregation isarithmetic or probabilistic.
2.7.3 Barrels of Oil EquivalentFrom time to time, it may be desirable to report reservesofoil, gas and related substances in common units. This
is generally done by converting reserves that are not oilto barrels of oil equivalent (BOE). The conversion canbe made using either an energy equivalence or a relative value procedure, depending upon the purpose ofthe conversion.
The energy equivalence is only relevant at the burnertip and, since the value in the marketplace is differentfor various types of reserves and the costs to move thevarious types from wellhead to the end-user vary considerably, the value of the reserves at the wellhead (orin the ground) is only somewhat indirectly related toenergy content. Consequently, for making value-basedcomparisons, the conversion should be based on the relative values of the gas and related substances comparedto the values of oil reserves at the field level. The conversions to BOE are usually made to barrels of "light"oil equivalent. Since medium and heavy oil have valuesmuch lower than light oil, it may be desirable that themedium and heavy oil reserves be converted to BOEof light oil as well as converting the gas and relatedproduct reserves, to better indicate their real value.
Some companies may prefer to convert their reservesusing gas as the common unit. The procedure would besimilar, except that the converted reserves would bequoted as thousand cubic feet ofgas equivalent.
It is important, when reserves are reported in BOEor gas equivalent, that the method used and the respective conversion rates be disclosed. A more detaileddescription ofthe procedure is presented in Chapter 26,Uses ofReserves Evaluations.
9
Chapter 3
GUIDELINES FOR ESTIMATIONOF OIL AND GAS RESERVES
3.1 INTRODUCTIONThe quantification and classification of estimates ofreserves are, by nature, rather subjective processes.Estimates of reserves are developed under conditionsof uncertainty, and their reliability and classification aredirectly related to the quality of the data available, aswell as to the competence and integrity of the individualresponsible for preparing the estimates. The purposeof this chapter is to elaborate on the classification ofestimates ofreserves derived using the two primary reserves determination procedures: deterministic andprobabilistic.
The categories of proved, probable, and possible havefor some time provided a basis for differentiating estimates of reserves to reflect the probability of recoveryconsidered appropriate by the estimator. Stated in another way, the assignment ofthe estimate ofreserves tothe three categories has provided a qualitative measureof the probability that a particular estimate of reserveswill, in fact, be realized. However, for some time therehas been discussion as to whether a more rigorous approach should be adopted to describe the degree ofprobability associated with the specific reserves categories. Some observers view the use ofterms such as "highdegree of certainty" to describe reserves classificationcategories as too subjective, and believe a definitive statistical probability of recovery would give users moreconfidence in utilizing- the estimates of reserves provided for each of the categories. For this reason,consideration has been given to a means to further quantify the degree of probability associated with each ofthe categories.
The probability ranges adopted by the StandingCommittee on Reserves Definitions for the definitionsofproved, probable, and possible reserves are intendedto more explicitly quantify the probability of recoveryassociated with each of the reserves categories, both onan absolute and on a relative basis. The ranges providean assessment that is more quantitative in nature thansome prior definitions.
10
The use of probabilities to assist in the categorizationofreserves does not eliminate subjectivity from the process. It remains incumbent on the evaluator to ensurethat the basis for the estimate of reserves and the category to which the estimate is assigned are clearlyreported. The guidelines and examples given areintended to assist in this regard. The reserves classifications and associated probability ranges are applicableto estimates of reserves derived using either deterministic or probabilistic (stochastic) calculation procedures.
3.2 METHODS OF CALCULATINGRESERVES
3.2.1 Deterministic ProcedureThe deterministic procedure is the most commonly usedmethod ofreserves estimation in Canada. Ifthe true values of all parameters used in any calculation wereknown, a true or deterministic value could be calculated.However, due to the uncertainties in the geological,engineering and economic data, for the purposes of reserves estimation using the deterministic procedure, the"best estimate" ofeach parameter is used in the calculation of reserves for each specific case. As a result, theprobability distribution of the input parameters is generally not formally considered in the classification ofreserves calculated using this method.
Estimates ofreserves calculated using the deterministicprocedure should be assigned to the proved, probable,and possible categories based on the probabilities inherent in the estimates. The assignment ofthe estimatesof reserves to the respective classification categoriesshould be consistent with the prescribed ranges ofprobability, taking into account factors such as the stage inthe producing life ofthe reservoir, the amount and quality of geological and engineering data available, theavailability of suitable analogous reservoirs and,perhaps most importantly, the evaluator'sjudgement asto the uncertainty inherent in the estimate.
,
GUIDELINES FOR ESTIMATIONOFOILAND GAS RESERVES
The assignment of reserves estimates to the respectivecategories using the deterministic procedure normallyuses one of two approaches.
In the first, the evaluator develops a "best estimate" ofreserves for each of the categories, using consistentparameters. Using this methodology, the evaluatoreffectively establishes a range of estimates of reserves,with the proved estimate based on parameters for whicha high probability can be attributed, and additionalestimates of probable and possible reserves based onparameters for which there is a lesser probability ofoccurrence. The effect of this is to progressively increasethe estimated quantity as it is moved from the proved toprobable to possible categories, with the overall rangeofestimates dependent upon the uncertainty inherent inthe specific parameters upon which the estimates arebased.
In the second approach, a single estimate of reserves isderived for the pool and then allocated to the respectivereserve categories based on an assessment of the portions of the estimate that would satisfy the probabilityranges for each of the reserves categories. In makingthis determination, the evaluator must make a subjectivejudgement as to the uncertainty inherent in the singleestimate and, therefore, the extent to which it can beallocated to the proved rather than the probable orpossible category.
As already noted, where probable or possible reserveshave been estimated in addition to proved reserves, theyshould be adjusted (risk-weighted) and added to theproved reserves to result in the expected reserves.
In summary, using the deterministic procedure, estimatesof reserves are calculated and assigned to the proved,probable, and possible categories using primarily subjective criteria, the overall basis being that the assignedquantities satisfy the probabilities established for eachof the categories. It is incumbent on the evaluators toprovide the supporting rationale for the categorizationof the reserves estimates.
3.2.2 Probabilistic ProcedureThe probabilistic or stochastic procedure is lesscommonly used in Canada. It is more suitable forcircumstances where the uncertainty is high, such as forreservoirs in the early stages of development, frontierareas, or areas where new technology is being applied.As the level of uncertainty increases, it is generallyagreed that the probabilistic procedure becomes morerelevant and the deterministic less reliable. Rapidlyexpanding computer applications also facilitate the useof the probabilistic procedure.
This method uses the statistical analysis of data.Relative frequency curves established for each variabledescribe the range of possible values for each, as wellas the probabilities that these values will occur. Afterfrequency distribution curves have been established foreach variable to be used in a reserves classification, theMonte Carlo (described in Section 22.4.4) or a similarmethod is used to estimate a value for reserves. A singlesample of each variable is taken randomly from eachprobability distribution and used to calculate a singlevalue of the dependent variable. This procedure isrepeated a large number of times to ultimately create afrequency distribution curve that describes the range ofestimates of reserves and the probabilities of achievingparticular estimates.
Once the measures of central tendency (the meanor arithmetic average, the mode or "most likely" value,and the median or "middle" value) and the dispersion(range, standard deviation, and percentiles), have beendetermined using this technique, estimates of reservesmay be assigned to each of the proved, probable, andpossible categories.
The assignment of the estimates of reserves to therespective categories should be consistent with theprobabilities outlined in the reserves definitions, provedreserves being those with an 80 percent or greater probability, and probable and possible reserves having lowerprobabilities. The relative cumulative frequency distribution curves may be used as the basis for the assignmentof estimated quantities to the reserves categories. Again,the evaluator must clearly describe the supportingrationale for the categorization ofestimates ofreserves.
Like the estimates derived using the deterministicprocedure, the probable and possible reserves shouldbe adjusted (risk-weighted). Since the probabilities havebeen established through the probabilistic process, theyshould be used to adjust the respective estimates.
It should be noted that the probability associated withthe estimate of reserves for a pool should increase asthe pool is developed and produced over a period oftime. As the overall probability of recovery increases,the estimate of the proportion of reserves considered tobe proved is likely to increase, with a diminishing proportion in the probable and possible categories. Theobjective of the evaluator should be to minimize theextent to which it is necessary to reduce estimates ofproved reserves over the life ofa pool for reasons otherthan production, although there may be circumstances(i.e., a significant price decline) where such reductionsare necessary.
11
3.3 GUIDELINES FOR SPECIFICMETHODS
The guidelines and examples that follow are designedto provide guidance for evaluators on the calculation ofproved, probable and possible reserves, using thefollowing methods for determining reserves:
• Volumetric
• Material balance
• Decline curve analysis
• Reservoir simulation
This section also deals with the calculation of reservesof natural gas liquids (NGLs) and sulphur.
It must be emphasized that the guidelines touch on somekey factors related to reserves estimation, but are notall-inclusive. In the final analysis, the calculation andcategorization of reserves depend upon the judgementofthe evaluator as to the probability of recovery of thereserves of oil and gas.
It is intended that the guidelines will lead to moreuniform practices of reserves calculation in each category, and thus to reserves estimates that will be morecomparable and consistent throughout the industry, thefinancial community, and the government agencies thatuse them.
3.3.1 Volumetric MethodThe volumetric method is the most commonly usedapproach to estimating reserves in the early stages ofproduction from an oil or gas field. As more databecome available, the estimate may be refined, sometimes through the use of other reserves estimationmethods. Often the volumetric estimates are useful forcomparison with other methods.
The volumetric method is used by employing thestandard reserves equation with the appropriate choiceof parameters. For various parameters in the equation,the guidelines provide suggestions for choosing the appropriate value, according to the category of reservesbeing calculated.
Pool Area
The parameter that often has the greatest variabilityin the reserves equation is the area chosen to representthe areal extent of the pool. Thus, the choice of thevalue for the area plays a particularly important role incomputing reserves in each category.
12
DETERMINATION OFOILANDGASRESERVES
Single-Well Pools
For single-well pools, the area must be consistentwith the reserves category, recognizing the geologicaland engineering information with respect to the singlewellbore and the geological and other informationavailable for single-well pools in similar formations.
In the case of an isolated gas well with little or nogeological control, it is a frequent practice to assign reserves to one section,* a frequently used regulatoryspacing for gas wells. However, one section should onlybe .assigned as proved reserves if a review of similarwells in the same or a similar formation has satisfiedthe evaluator that such an area can be assigned 'witha probability of 80 percent or more. If the review ofsimilar wells shows that a smaller area, such as one halfsection or even one eighth-section, can be expected tohave a high degree of probability, this reduced areashould be used for proved reserves. On the other hand,in situations such as a blanker sandstone, the review ofsimilar wells may justify the assignment of more thanone section if it can be demonstrated with high probability that the well will drain reserves associated withthe larger area.
In the event that an evaluator is reasonably confidentthat gas would be recovered from an area, say one section, but not with a high enough probability for thereserves to totally qualify as proved, then some lesserarea for which there is a high probability, say one halfsection, should be assigned as the proved area. Theremaining half-section ofthe normal spacing unit mightthen be assigned to the probable or possible category,depending on the degree ofprobability that such reserveswould be recovered.
For single oil wells, the area assigned would generallybe less than for gas wells because the flow characteristics for oil result in smaller drainage areas. A typicalpractice is to assign proved reserves to areas rangingfrom one quarter-section for light crude oils to onesixteenth-section or less for heavy crude oils.
Such assignments should be made only when a reviewof similar wells demonstrates that such reserves can beexpected with a probability of 80 percent or more. Theprocess used to assign areas to single oil wells shouldotherwise be similar to that for gas wells, with an assignment that reflects the probability that the areacan be drained at the level required for each reservesclassification.
*One section = 259 hectares, 640 acres,or 1 squaremile.
GUIDELINES FORESTIMATION OF OIL AND GAS RESERVES
In certain cases such as sheet sandstones, even thoughonly one well has penetrated gas or oil, information maybe available, as a result of knowledge about nearbyabandonments and the regional geology, that justifiesthe preparation of an isopach map. This situation isillustrated for an oil pool in Figure 3.3-1, which showsthe zero pay limit. If the probability of a one quartersection pool is very high, based on a study of similarpools in the area, then the one quarter-section containing the well could be assigned as proved reserves. Theremaining three quarter-section parcels offsetting thewell, and within the zero limits ofthe isopachmap, couldalso be assigned reserves as additional proved or probable or possible depending on the degree of probabilitythat the oil will be recovered. These reserves, however,should be in the undeveloped category.
The assigrunent of reserves for single gas wells withconsiderable geological control can be handled in amanner similar to that detailed for the oil well in Figure3.3-1, except that the estimated drainage area for gaswill usually be larger, depending on the availablegeological and other data. An area larger than theassigned area determined as described may be used
-<>- ",-<>-L--
I 0 0 \------------ -~---~-~-~--
•\
0
)-, --[7
t-...
-<>-
depending on information on pressure, drillstem testresults, and seismic data.
Multi-Well Pools
In multi-well pools, the area between wells shouldbe considered to contain proved reserves if the areasassigned on a single-well basis overlap or are separatedby a very small area, or ifmaterial balance calculationsor production data and pressure response clearly demonstrate that the wells are in the same pool. There will,however, be many situations where such conclusive information is not available and the evaluators must usetheir judgement, based on geological and other data,regarding the areal extent and the assignment ofadditional reserves to adjacent areas.
For wells that are in separate pools, the precedingmethodology for assigning reserves for single-wellpoolsshould be followed. If more than one well can be included in a pool, the type ofprocedure described in thefollowing example might be used.
Example
Figure 3.3-2 shows the zero pay limits for a multi-wellconventional gas pool. It is important to emphasize that
WELL LEGEND
o Location
-<>- Abandoned• 011* Gas
1 mi
1 km
z
Figure 3.3-1 Single Well Oil Pool with Good Geological Control
13
DETERMINATION OF OIL AND GASRESERVES
RANGE
36 31 V -. 36
~1/ \
/ ~0-J:en
/zs:
I 0f- WELL LEGEND
~ / 0 Location
1 6 / 1 -<r Abandoned
1/ • Oil
\36 31 36 ~ Gas
-?- 1\ ~ L-4~
<, D One Section
Figure 3.3-2 Conventional Gas Pool, Zero Limit of Net Pay Map
this example illustrates a procedure that is useful forconventional oil and gas pools. The areas assignedrelate to the particular natural gas reservoir and woulddiffer in other geological settings.
Knowledge respecting the geological formation is suchthat the evaluator is prepared to make a proved areaassignment offour sections for a single well. The mapis constructed using all pertinent data, such as the netpays encountered in the three gas wells, and information on dry holes that indicates the limits of the pool.Perhaps seismic information and pressure data, alongwith experience in the area, suggest that the two wellsin the west are in communication with the one in thenortheast
The first step is to block in a 2 by 2 section area aroundthe productive well and within the zero net pay isopachlimit, as shown in Figure 3.3-3. These areas would beassigned proved reserves. Proved reserves would alsobe assigned to corridors of one mile or less in widthbetween the proved areas around each well and anyintervening corridors between the proved areas (Figure3.3-4). After limits had been established for the provedreserves, a border one mile wide would be drawn around
14
the proved limits as an indication of the proved plusprobable limits (Figure 3.3-5). As with the provedreserves, any corridor less than one mile between theproved plus probable limits would also be assigned tothe probable category (Figure 3.3-5). The procedurewould be continued for possible reserves ifany area wereleft within the zero pay limits.
For oil, a similar approach for assigning areas in multiwell pools can be used, but the area assignments wouldusually be smaller.
Presence of Hydrocarbons
In order to estimate any reserves, the presence ofhydrocarbons must have been confirmed by production data or by a demonstrated ability to flow basedon the results of drillstem tests. If production and testdata are not available, reserves may be estimated basedon information from cores, or provided that the reservoir is analogous (from the standpoint ofgeological andpetrophysical characteristics) to producing or tested reservoirs in the same area. Reserves should be assignedonly to reservoirs that have been penetrated by awellbore; otherwise, quantities should be categorized asa resource.
?
GUIDELINES FOR ESTIMATION OFOILAND GASRESERVES
RANGE
36 31 V- r-. 36
7/' \
// /
/ V~~0-
J:en WELL LEGENDZ
/ v //-V/ :s:/ / 'r>. / 0 0 Locationl-
I ~~V / -?- Abandoned
// V • Oil.v 'V
~6 / 1 Gas
/6 31 V 36\ '/// IZZ2I Proved
~ \ ~~V-----~
/ /V vv D One Section
Figure 3,3-3 Conventional Gas Pool, Zero Limit of Net Pay Map with Individual Well Assignments
RANGE
36 31 V- r-, 36
;7V \// /
/ :/~~0-
J:en WELL LEGENDZ/ / V/- / / :s:
/ '/ //VV ~ 0 Location
~~~ / -?- Abandoned/ / • 011~/ //Vr/
/ 1 ~ Gas/. // / 6
/ // / V 36V //VV 6 31 IZZ2I Proved\
~ \ ~~~ --~/ 'V
'<VV / D One Section
Figure 3,3-4 Conventional Gas Pool, Zero Limit of Net Pay Map with Area of Proved Reserves
15
DETERMINAnON OF OIL ANDGASRESERVES
RANGE
36
a.:cen WELL LEGENDzs:0 0t- Location
-<?- Abandoned
• Oil
* Gas
36 IZZa Proved
Probable
D One Section
Figure 3.3-5 Conventional GasPool, Zero Limit of Net Pay Mapwith Area of Proved Plus Probable Reserves
Reservoir Parameters
Values ofpay thickness, porosity, and fluid saturations,when combined with area, permit a calculation of thevolume of oil or gas contained in a reservoir. Theseparameters are estimated from analyses of cores orpetrophysical well logs.
In many situations, core analysis is not available, andwell logs indicate the presence ofoil or gas, but do notallow reliable estimates ofporosity or fluid saturations.Where the geological formation is known to be productive in the region, a pay thickness based on the logs forthe well and the values ofporosity and fluid saturationstaken from nearby wells in similar formations (valuesthat may be expected to have a high probability), maybe used to calculate proved reserves. In such cases, wherethese parameters can only be estimated with a lowerprobability ofoccurrence, probable or possible reservesmight be calculated.
In the estimation of reserves, the values used forpay thickness, porosity and fluid saturations mustalways be consistent. This requires proper use ofcutoffvalues, well log calibration, and proper petrophysicalcalculation methods.
16
Averaging these parameters over multi-well pools is alsoimportant in estimating and categorizing reserves. Ifreliable estimates for many wellbores exist for any orall of the parameters, they should be applied over theintervening area between wells and the edge ofthe reservoir by contouring or other appropriate averagingmethods. The calculation of the average, particularly ifit is by contouring, should have regard for the geologyand for any other factors that might influence the shapeof the reservoir.
Where insufficient individual well data respecting anyof these parameters are available to allow for contouring, averaging should be done in a manner consistentwith the probability necessary to support the particularcategory of reserves being estimated.
Certain other reservoir parameters are needed toestimate reserves, particularly for purposes of converting the volumes of oil or gas contained in a reservoirto volumes that will be recovered and marketed. Theseinclude reservoir pressure and temperature andhydrocarbon fluid composition. The choice of suchparameters does not usually dictate the categorizingofreserves estimates as proved, probable, or possible.
GUIDELINES FOR ESTIMATION OFOILAND GASRESERVES
However, particularly for proved reserves, theparameters must be based on reliable data or bedetermined through valid comparison to similar reservoirs in a manner that reflects the appropriate level ofprobability.
Recovery Factor
Estimates of recovery factor are based on analysis ofproduction data from the pool in question, by analogywith producing pools in an analogous reservoir unit, orby engineering analysis, without analogy or productiondata. The estimator should keep in mind that recoveryfactors may be influenced by other factors, such aswell spacing, the anticipated compression, the drivemechanism, and reservoir and fluid properties.
For proved reserves, the recovery factor may be determined from a detailed reservoir study, or by comparisonwith detailed studies ofanalogous reservoirs where therecovery factor can be estimated with a high degree ofprobability.
For probable and possible reserves, the value used forthe recovery factor may be similar to that used for thecalculation ofproved reserves, the different categorization ofreserves being accounted for in other parameters.
However, a larger recovery factor may be justified onthe basis ofgeological data that indicates improved reservoir parameters such as porosity and permeability incertain portions of the field. Where a range of recoveryfactors is known from analogous reservoirs with similar characteristics, values corresponding to the middleto upper end of the range may be used for probable andpossible reserves estimates.
In some cases the recovery factor for proved reserveshas been estimated on the basis of an 80 percent orgreater probability, and yet the characteristics of theformation indicate that better recovery might occur. Inother cases the recovery factor for proved reserves hasbeen estimated lower due to an anticipated recoveryproblem (i.e., water influx in a gas reservoir), but thereis only a chance that the problem will occur. In thesesituations the evaluator might use a higher recoveryfactor and assign the incremental reserves to the probable or possible categories, depending upon the degreeofprobability of their recovery.
3.3.2 Material Balance MethodThe material balance method is employed to estimatethe volume ofhydrocarbons in place in a reservoir whenappropriate geologic, production and laboratory data
are available. When economic producibility limitsare coupled with the material balance, reserves aredetermined. In its simplest form, the material balanceequation may be written as
initial volume = volume remaining + volumeremoved
Since oil, gas and water are present in petroleumreservoirs, the material balance equation may be written for the total fluids or for anyone ofthe fluids present.For gas reservoirs, the frequently used plot ofreservoirpressure, adjusted for the gas compressibility (P/Z), vs.cumulative production is a material balance method.
Four groups ofdata are required for a material balance:
• Fluid production
• Reservoir pressure and temperature
• Fluid analysis
• Core analysis and petrophysical logs
In addition to these data, it is highly desirable to knowthe type of reservoir mechanism that is operative inorder to expedite estimation ofthe volume of the initialhydrocarbons in the reservoir. As with other methods,the better the quality of the data, the higher the degreeof confidence in the results.
The evaluator, in categorizing reserves, must considerthe probability that the reserves in question will be recovered. The volume in place estimated by the materialbalance method might have a high enough probabilityto be considered as proved in the following situations:
- Where significant data are available, particularlyfluid production and reservoir pressure data, and thereservoir drive is known
- Where production and reservoir data are limited,but the reservoir is analogous to reservoirs in theimmediate vicinity and same geologic horizon
- Where such data are of sufficient quantity andquality to have established the reservoir drivemechanism
- Where production and reservoir data are limited, butthe estimate is supported by a calculation of thehydrocarbons in place by the volumetric method
For gas reservoirs, where there is a strong linearrelationship between P/Z and cumulative production(Figure 3.3-6), the probability ofrecovery is likely highenough to assign the quantity indicated as provedreserves. However, no additional reserves should be assigned beyond the proved reserves, since no significantlydifferent interpretation ofthe data would be reasonable.
17
h _
DETERMINATION OFOILANDGASRESERVES
Average I:::Oat. Pressure Z PIZ Cum. Prod.
ii~(kPa) (kPa) (108m')
72102 21540 0.875 24621 0.0 I:i
r-. 86107 20078 0.871 23063 96.0 I::87/08 18705 0.869 21532 209.086107 14623 0.874 16740 582.0 Iii
" 89/02 13258 0.879 15086 724.0 IX<, 89/09 10742 0.894 12018 920.0
f~~
90/0B 7357 0.922 79n 1 210.0
i."i i'·i.r-,<,r-.
I- - - -E=r~.'!'~C-r~!.--1-----1----- -----~ --~
PROVED8 ,
OGIP=1800x 10 m
ReserveS=1600xl06m3
30000
20000
PIZ(kPa)
10000
oo 250 500 750 1 000 1 250 1 500
8 aCumulative Production (10m)
1750 2000
Figure 3.3-6 Material Balance (Gas Reservoir)
There are a number of other situations where reservesestimates from material balance or some portion of theestimate might have an associated probability level thatresults in their being considered probable or possiblereserves:
- Where significant production data are available, butthe reservoir drive mechanism is uncertain or themagnitude of the reservoir drive is uncertain
- Where production and reservoir data are limited andthere are no analogous reservoirs in the immediatevicinity
- Where production and reservoir data are limitedand the estimate is not supported by volumetricdeterminations
For a gas reservoir, where the P/Z data do not givea definitive linear correlation, asin Figures 3.3-7 and3.3-8, the resulting reserves that should be classified asproved are those that represent the quantity that can beestimated to be recoverable with an 80 percentprobability. Proved plus probable reserves might reflecta larger volume than the data indicate may be recovered. In Figure 3.3-7, the scatter of points shouldencourage the evaluator to analyze the quality of the
18
data in terms of the type of pressure measurement(bottom-hole, drillstem test), and the type of recorder(mechanical or electronic). With respect to Figure3.3-8, the evaluator should develop an understandingofthe reservoir drive and depletion mechanism in orderto accurately classify proved and probable or possiblereserves. The apparent bending of the material balanceplot may be interpreted as gas migration from edge ortight areas of the reservoir, or pressure support from anunderlying aquifer. Use ofa reservoir simulation modelmight assist in this analysis.
3.3.3 Decline Curve AnalysisThe analysis of a production decline curve providesestimates of three important items of information:
• Remaining oil and gas reserves to be recovered
• Future expected production rate
• Remaining productive life of the well or reservoir
In addition, an explanation of any anomalies thatappear on the graph is useful. The analysis is only validprovided the well will not be altered (i.e., fractured oracidized) and the reservoir drainage is constant.
GUIDELINES FOR ESTIMATION OFOIL AND GASRESERVES
350300250
AverageDate Pressure Z P/Z Cum.Prod.
(kPa) (kPa) (10'm')
INIT. 30991 0.987 31391 0.076/06 31109 0.988 31479 13.481/06 21380 0.922 23182 72.784/09 20277 0.919 22075 103.486/09 16602 0.913 18179 122.986/09 19001 0.915 20762 122.987/05 18519 0.915 20237 128.689/07 18471 0.913 18036 144,8
20015010050o+---+---+----I----I-__~.L......:::>.I-..J--"'-I
o
a
Economic Limit
40000 -,----,----,----.---rI
10000 +----+---+----j----"'f.,;;:-=:O""d----l-----l
P/z(kPa)
Cumulative Production (10'm')PROVED
OGIP=300xl06m3
Reserves = 270 x 106m3
PROVED + PROBABLE
OGIP=350xl06m3
Reserves = 315 x 106m3
Figure 3.3-7 Material Balance (Scattered Datal
AveragePIZ Cum.Prod.Date Pressure Z
(kPa) (kPa) (lo'm')
85/11 21067 0.924 22800 0.075/08 16858 0.899 18761 102.976/10 14844 0.902 16451 138.476/11 15306 0.901 16989 138.477/08 13631 0.906 15044 162.3
.... 78/09 12604 0.910 13852 190.5
~80/07 13411 0.920 14 SIT 237.1....86/05 8936 0.929 9618 340.687/08 8556 0.932 9184 358.4
~ 88/06 8494 0.932 9115 368.2...
'<,
~- ~CEClOli9!~.!!- ~---- ----- ----- :"'-..l ::::---
PIZ(kPa)
30000
20000
10000
oo 100 200 300 400 500 600 700
Cumulative Production (10'm') PROVED , ,OGIP=620xl0 m
Reserves=550x 106m3
PROVED + PROBABLE6 ,
OGIP=675xl0 m
Reserves = 590 x 106m3
Figure 3.3-8 Material Balance (Reservoir Drive and Depletion Mechanism)
19
As with all other methods, the categorizing of reservesby decline curve analysis is dependent upon the judgement ofthe estimator. Important considerations includethe amount and quality of data, the variability of theprofile, and an understanding of past and futureproduction policy and the depletion mechanism.
Because ofthe empirical extrapolation, a decline curvecan usually have a wide range of interpretations. Therange depends upon the production history of the property. For example, if there is limited prior productionhistory, a wider range of interpretations is possible thanfor a well or property in the stripper stage of production. It is valuable to understand the production recovery
. mechanism of the formation (or the same formations inthe area) and the various characteristics of the well (netpay, permeability, and zone ofcompletion). Also, eachspecific interpretation is a function of the experience,integrity and objectivity of the individual doing theevaluation.
Determining reserves from historical graphs ofproduction data that exhibit strong consistent declinecharacteristics should be straightforward. When a highdegree ofprobability exists, as in Figure 3.3-9, provedreserves only would be assigned.
DETERMINATION OFOil ANDGAS RESERVES
In a case where well-established trends are not evident,proved reserves should be restricted to the minimumquantity that the evaluator believes will be recoveredwith an 80 percent probability. Figure 3.3-10 showssuch an example. Proved reserves are estimated byprojecting the steepest portion ofthe production declinedata. In this case, the incremental volume of oil thatmay be recovered if the lower rate of productiondecline prevails might be classified by the evaluator asprobable or possible.
This situation could also apply when the type ofdeclinepattern is not obvious. Figure 3.3-11 illustrates a casewhere either an exponential or a harmonic decline couldbe used to extrapolate the data. In this example, reservesdetermined from the exponential curve might beassigned to the proved category, since there is a highprobability that at least this volume will be recovered.The harmonic curve reserves might be classified as probable or possible, depending on the probability ofrecovery, as judged by the evaluator. In this examplethere is a large difference between the estimates usingthe different interpretations, and this suggests considerable uncertainty. Thus portions ofthe quantity in excessof the proved reserves could be classified as probableand possible.
PROVEO
Reserves = 33 x 103m3
n..LA'Y~
.
~v\''\.."
~~----f----------- _ E'<.O!!~,,!!"-Ll"!!!.. _-----------
20
~ 15."~....E-..~coII:c 100;:U::J."2e,
(5 5
oo 10 20 30 40
Cumulative Oil Production (103
m3)
Figure 3.3-9 Decline Curve, Proved Reserves
20
GUIDELINES FOR ESTIMATION OFOILANDGAS RESERVES
20
15 -It----,-----+-I------H
PROVED
Reserves = 155 x 106m:3
MQ--*II:co:s::J'DeQ.
i5
10
5-++----+-1-----
Economic Limit
PROVED + PROBABLE + POSSIBLE
Reserves = 176 x 106m3
o+--------+------\--------f-l-"'"---..L.::::>...-Jo 50 100 150
Cumulative Oil Production (10· m3
)
200
Figure 3.3-10 Decline Curve, Cumulative Gas Production
PROVED
Reserves = 17 x 103m3
PROVED + PROBABLE + POSSIBLE
Reserves = 25 x 103m3
~ 1\-,.~..
"""- ~Harmonic
Exponential/f~~ECOnOm!C
tLimit .T -
16
~ 12:EM
§.Q)~
'"II:c
80.,U::J'D0~
Q.
i5 4
oo 5 10 15 20 25 30
Cumulative Oil Production (103
m3)
Figure 3.3-11 Decline Curve, Cumulative Oil Production
21
3.3.4 Reservoir Simulation MethodA reservoir simulator is a tool that is used to simulatethe processes that take place in producing a reservoir.Simulation is often done to optimize recovery by analyzing various reservoir development plans, methodsof production, and the complexity of the reservoiritself. Although reservoir simulation methods are complex, they include a combination of the physicalprinciples and analytical techniques of one or more ofthe other methods of reserves estimation.
The criteria for categorizing reserves would include theamount and quality ofproduction and pressure data, thevalidity of the model and its demonstrated reliabilitywith comparable reserves, and the ability to historymatch. To illustrate, if sufficient amounts of good geological and performance data are available to allow fora reasonable history match, and if the estimator is usingan appropriate simulation model that has been usedsuccessfully in reservoirs similar to the one being studied, projections ofrecovery under primary mechanismsand the specified economic conditions might be considered proved reserves. Ifthe situation being modelledis an improved recovery mechanism, these criteria andthe guidelines given in Section 3.3.5 for categorizingimproved recovery reserves generally apply. This meansthat for existing and operating improved recoveryprojects where an appropriate simulation model is being used, adequate data exist, and the response to thedata is consistent with the simulation results; or wherefuture projects can be expected with a high probabilityinreservoirs ofthe type where the model has been shownto give reliable results, the simulated recovery can beconsidered as proved reserves.
At least a portion of the simulated recovery should becategorized as probable or possible or not consideredas reserves, depending on the evaluator's views onthe probability that the additional oil or gas will berecovered in the following situations:
- Where the model hasnot been shown to give reliableresults for the same type ofimproved recoveryprojectin a similar reservoir
Where insufficient data are available to properlyuse the model
- Where the installation of an improved recoveryproject cannot be predicted with a high probability
3.3.5 Reserves from Improved RecoveryProjects
The calculating and categorizing of reserves fromimproved recovery projects should be based on the
22
DETERMINATION OF OIL AND GASRESERVES
judgement of the evaluator and on information such asobserved performance, the results ofpilot projects, theperformance of projects in analogous pools, and engineering studies. To illustrate, reserves attributable toimproved recovery projects may be considered as provedreserves provided certain conditions are met. Such situations occur when the production response from a projectcorresponds to the results predicted by engineeringanalysis or where the improved recovery project hasbeen in operation for a considerable period and the analysis of a decline curve can be used with confidence, orwhere a history-matched simulation is available. If theproduction response has fallen short oforiginal predictions, the observed production data should be used forcalculating and categorizing reserves. Proved reservesmay be attributed to other areas of the pool where animproved recovery project has not yet been applied,provided that it is highly probable that a project willproceed, and that the geological and other reservoir characteristics are equivalent or superior to those for areaswhere an improved recovery project is in operation.
If a successful scheme has been implemented in asimilar pool that has analogous reservoir characteristics, proved reserves due to improved recovery may beassigned, provided the evaluator is convinced that theanalogy is sound and that there is a high probability thata project will proceed and be successful.
Probable or possible reserves can be assigned in othercases where the improved recovery method has beenapplied successfully to analogous reservoirs, but wherethere is a lower probability that a project will go aheadand be successful. Proved, probable or possible reservesmay be attributable to a planned workover treatment,improvement to equipment, or other procedures, depending on the evaluator's judgement respecting theprobability of success.
3.3.6 Related ProductsNatural gas liquids (NGLs) are the liquid hydrocarboncomponents recovered from natural gas. If they are recoverable, they must be calculated and reported asreserves of either natural gas or natural gas liquids,but not both.
The first test of recoverability ofNGLs is whether theywill be produced as part of the stream of raw naturalgas. If the fluid properties and reservoir pressures aresuch that the composition ofthe produced raw gas streamwill significantly change with time due to retrograde orother phenomena, this must be reflected in the calculated reserves. Components of natural gas that wiil
>
GUIDELINES FOR ESTIMATION OFOILANDGAS RESERVES
liquefy in the reservoir and not be recoverable must notbe included in reserves of either NGLs or natural gas.
If cycling or other special means of producing thereservoir is planned in order to reduce the liquid lossesthat might otherwise occur, the NGLs that would be sorecovered can be categorized only as proved reserveswhere their recovery can be estimated with a high probability. This would require sufficient reservoir and fluiddata to make an accurate detailed projection ofproduction and, also, the special means of production wouldhave to be actually in operation or expected with a highdegree ofprobability.
Where the prevention of losses in the reservoir is lesscertain, such NGLs should be categorized as probableor possible or not considered a reserve, depending onthe probability of their recovery.
For most reservoirs, the composition of the producedgas will not significantly change with time. For thesereservoirs, the only test of recoverability of NGLs relates to whether they will be recovered as liquids orremain in the natural gas. This is also a second test forthose reservoirs previously mentioned where the NGLcontent of the produced gas will change with time.
The first criterion in terms of their classification asreserves is that NGLs can only be categorized as provedifthe raw gas from which they are to be removed will,after processing, result in marketable gas that is categorized as remaining proved reserves.
Some portions of some hydrocarbon components,particularly ethane and propane, may not have to be removed from raw gas to make the gas marketable. Sincethe technology for removal of essentially 100 percentofall NGLs is well-proven, the only test of their recoverability from a proved natural gas reserve relates towhether the liquids would be recoverable at the specified economic conditions under which the estimates ofproved reserves are being made.
Where the removal of NGLs from the raw gas isnecessary in order to make the gas marketable, the removal of the liquids must be economically feasible orthe natural gas would not be economically recoverableas marketable gas at the specified economic conditions,
and therefore neither the natural gas nor the NGLs couldbe categorized as remaining proved reserves.
Where the removal of NGLs from the raw gas isnot required but is being planned, the removal ofthe liquids must be economically feasible or else theNGLs cannot be categorized as proved reserves. If theremoval ofthe liquids is not economically feasible, theywould be included as part of remaining proved reservesofnatural gas.
If raw gas containing NGLs that will be marketablenatural gas after processing is categorized as eitherprobable or possible reserves, the NGLs must becategorized in the same manner.
With respect to sulphur reserves, essentially all of thehydrogen sulphide and other sulphur compounds mustbe removed from the raw natural gas and converted toelemental sulphur to meet environmental and other standards. The necessary technology exists, and the keyquestion is whether the recovery of the sulphur is economically feasible at the specified economic conditions.If it is not, the natural gas would not be economicallyrecoverable as marketable gas and thus could not becategorized as reserves.
If the sulphur in question is economically recoverablebut is contained in natural gas categorized as probableor possible reserves, the sulphur must be categorizedin the same manner.
In some reservoirs, usually where the gas has a veryhigh HzS content, the pressure, temperature and fluidproperties are such that some ofthe sulphur will liquefyor solidify in the reservoir and will not be produciblewithout special production measures. Where such conditions are known to exist or can be expected, the sulphurthat would liquefy and remain in the reservoir cannotbe categorized as proved reserves unless special production measures for dealing with the problem have beendemonstrated to work successfully. They would haveto be feasible at the specified economic conditions, andeither have been implemented or have a high probability ofbeing implemented. Where these criteria are notmet, at least a portion of the sulphur should be categorized as probable or possible or not considered as areserve, depending on the overall probability of itsrecovery.
23
r
PART TWO
DETERMINATION OF
IN-PLACE RESOURCES
!n _
- I
..
Chapter 4
OVERVIEW OF PART TWO
b
4.1 INTRODUCTIONPart Two deals with the estimation of hydrocarbons inplace, the economically recoverable portions of whichare classified as reserves.
The estimation of initial in-place resources involvescontributions from several disciplines, primarily geology, geophysics, petrophysics, and engineering, butcontributions in varying degrees may also be requiredfrom specialists in chemistry, physics, economics, andother geological-engineering disciplines.
It is important that the size, or at least the range in size,of a potential resource be determined using consistentapproaches and considering the interrelationships oftheparameters used to make the estimate. The size of theresource forms the basis for the determination of howmuch oil, gas, and related products may ultimately beproduced for society's use, and for the formulation ofoperation plans and the necessary business decisions.
Volumes ofthese discovered resources may be estimatedby either a volumetric or a material balance method ofcalculation. These methods are described in Section 4.2.Section 4.3 describes the deterministic and probabilistic procedures for estimating in-place resources. Sections4.4 through 4.7 briefly discuss sources and reliabilityof data, the interrelationship ofparameters, the ways inwhich resource estimates are used, and the backgroundand experience of evaluators.
4.2 RESOURCE ESTIMATES
4.2.1 Volumetric Estimates
Reservoir VolumeThe first step in a volumetric calculation ofhydrocarbonresources is an estimation of the volume of subsurfacerock that contains oil and gas. The volume is derivedfrom the thickness of the reservoir rock containing thehydrocarbons and the areal extent of the accumulation.The important geological considerations in establishing a realistic estimate of reservoir volume include
the depositional environment of the reservoir beds, thehistory of any structural deformation of those beds, thetrapping mechanism for hydrocarbon accumulation, andthe positions ofthe various fluid interfaces.
Mapping the extent and configuration of the hydrocarbon accumulation requires the evaluator to have anunderstanding ofthe geological concepts ofsedimentation and the structural attitudes ofthe reservoir rock thatcontrol the limits and define the geometry of the deposit. Well samples and cores, well logs, seismic andwell test data, and pressure information are all used tointerpret the extent of the oil or gas pool. Visualizationof the accumulation in three dimensions is necessary toportray a realistic mapped interpretation.
Rockand Fluid Properties
The properties of the reservoir rock and the particularhydrocarbon are also important factors in the volumetric estimate of the resource. Although the volumes ofhydrocarbons are calculated at subsurface depths, theyare converted to standard surface conditions oftemperature and pressure for measurement and recording.The standard surface conditions in a particular location become the "base" temperature and pressure.
The following properties are. important in volumetricprocedures:1. Porosity, $, which is the measure of the void space
(fraction of rock volume)
2. Permeability, k, which is the measure of the fluidtransmissivity in millidarcies (mD)
3. Fluid saturation, Sw'which is the portion ofthe porespace that is occupied by oil, So, gas, Sg, and interstitial water (fraction)
4. Capillary pressure, Pc' which is the force per unitarea resulting from the interaction ofthe fluids withthe medium in which they exist in kilopascals (kPa)or pounds per square inch (psia)
5. Electrical conductivity of fluid-saturated rocks
27
DETERMINATION OFOILANDGAS RESERVES
Oil
The calculation ofoil in place is based on the followingequation:
IN=VRx<p x -x(I-So) (I)
Bo
where N = oil in place (ml)VR = rock volume (m') = 104 x A x h
A = drainage area in hectaries (ha)(I ha = 104 m2)
h = average net pay thickness (m)<p = porosity (fraction of rock volume)
B = formation volume factoro(res. m3/stm3)
Sw = water saturation (fraction)
In Imperial units, the equation is as follows:
Natural Gas
The in-place volume of natural gas is adjusted fortemperature and pressure in order to measure volumesat standard surface conditions. The compressibility factor adjusts for the compressibility characteristics fordifferent mixtures ofnatural gas components in changing from reservoir to surface conditions to account forthe variance from the Ideal Gas Law.
Natural gas resources may be classified as follows:
• Solution gas
• Associated gas (gas cap)
• Nonassociated gas
Solution gas is the gas liberated from oil produced froma reservoir. The rate of production of solution gas depends on the rate of oil production, the relative flowcharacteristics of the reservoir fluids, and the state ofdepletion of the reservoir.
IN=VRx7758x<px -x(I-So) (2)
Bo
oil in place (bbl)(1 acre-foot = 7758 stb)rock volume (acre feet) = A x hdrainage area (acres)average net pay thickness (ft)porosity (fraction of rock volume)formation volume factor(res. bbl/stb)water saturation (fraction)
VR =
A =h =
<pB =o
S =w
N=where
6. Formation volume factor, Bo, which is used toconvert subsurface volumes of oil to surface conditions (the conversion is a consideration ofa phasechange resulting in the liberation of gas (solutiongas) from the oil and the compressibility ofreservoir oil)
7. Gas compressibility factor, Z, which adjusts for thecompressibility characteristics in mixes of naturalgas in the conversion of ideal gas volumes to actualvolumes
Cutoff Values
Reservoir rock and fluid properties are used to helpdetermine the thickness of the reservoir rock that contributes oil or gas production based on testing or actualproduction. Relationships between porosity, horizontalpermeability, and water saturation can be developedfrom core and capillary pressure data to determinecutoff values below which any known economic recovery method will be ineffective, based on presenttechnology.
The limiting factor in oil and gas production is thepermeability, a measure of the flow characteristics ofthe reservoir fluids through the rock pores. The permeability to each of the three fluids-oil, gas andwater-varies in relation to the content of each of theother fluids in the reservoir. The contribution to production is best measured by the relative permeability ofthe rock-a flow characteristic of a fluid in the presence ofanother fluid or fluids. For example, the relativepermeability of the reservoir rock to oil or gas may bealmost nil in the presence of a high saturation of interstitial water, which would render the hydrocarbonsimmobile. The magnitude of the in-place resource hasthis limitation from a thickness perspective, being limited to the reservoir rock from which it is possible torecover the hydrocarbons.
Hydrocarbons in Place
The volumetric calculation of hydrocarbons in placeconsists of the following steps:
I. Determine the volume of rock containing hydrocarbons from thickness and area considerations orfrom an isopach map of net pay.
2. Determine the average effective porosity.
3. Determine the volume percentage containinghydrocarbons (from fluid saturations).
4. Correct for the volume of hydrocarbons measuredat the surface.
28
r
OVERVIEW OFPARTTWO
For calculation of initial solution gas in place, Gs' thefolIowing equation is used:
T PG = VR x ljl x (l-Sw) x " x -'- (5)
P"xT, Z;
G, =N XR,i (3)
where G, = solution gas in place (m")
N = oil in place (m')R,i = gas in solution at Pi (m3/m3)
Pi = original reservoir pressure (kPa)
In Imperial units, the solution gas in place is as follows:
VR = rock volume (acre feet) = A x hA drainage area (acres)
(1 acre = 43,560 square feet)h = average net pay thickness (ft)ljl = porosity (fraction of pore volume)
Tso = standard base temperature (ORankine)(460 + OF)
Pso = standard base pressure (psia)Tf = formation temperature (ORankine)
(460 + OF)
Pi = original reservoir pressure (psia)Zi = gas compressibility factor at Pi and Tf
The base pressure used varies with the location of theresource, but is related to the pressure ofone atmosphereat some elevation above sea level (e.g., in Alberta, 14.65psia and in British Columbia, 15.25 psia). The basetemperature is normally 15.6°C (60°F).
The determination of the compressibility of the gasinvolves the use ofa gas analysis to provide a factor fora particular mix of natural gas.
The equations set out in this section give in-placevolumes of raw gas expressed at standard surfaceconditions. Before the gas is delivered to the point ofsale, there are losses at the surface due to processingshrinkage, fuel consumption, and metering errors. Theselosses must be deducted from the raw gas volumes toarrive at the pipeline gas resources.
In sweet, dry gas fields, the shrinkage is related only tofuel consumption and line losses. For wet or sour gases,the shrinkage may also be a result of recoveries of related products and an allowance for plant fuel. Theshrinkage may be estimated from a representative gasanalysis to obtain the content of the related products,and an estimate of the recoveries of each product.Actual shrinkage for a producing field may be obtainedfrom the ratio ofthe saleable pipeline gas to the raw gasdelivered to the plant.
Related ProductsNatural gas liquids may be calculated from the volumepercentage of the product based on a representative gasanalysis and the gas-in-place volume. The volumes inplace ofnatural gas products expressed in standard volumes per volume of raw gas are shown in Table 4.2-1.Sulphur, which may be calculated from the weightpercentage, is also shown in Table 4.2-1.
The recovery factor assigned to the in-place volumesdepends on the method and efficiency of recovery.Actual gas plant statistics are a source of recoveryfactors for related products from a producing gas field.
(6)
Psc =T f =
hljl
S =w
Tsc =
G=VR =
A
T PG = VR x 43,560 x ljl x (l-Sw) x " x-'-
P"xT, Z;
where G = raw gas in place (scf)
where raw gas in place (m')rock volume (rn') = 104 XA x hdrainage area (ha)(I ha = 104 m2)
average net pay thickness (m)porosity (fraction of pore volume)water saturationstandard base temperature (OK)(273 + 0c)standard base pressure (kPa)formation temperature (OK)(273 + 0c)
Pi = original reservoir pressure (kPa)Z, = gas compressibility factor at Pi and Tf
In Imperial units, the equation is as follows:
G, = NXR,i (4)
where G, = solution gas in place (scf)N = oil in place (stb)
R,i = gas in solution at Pi (scf/stb)Pi = original reservoir pressure (psia)
Associated gas is the gas associated with an oilreservoir as a gas cap. Most, if not all, of the energy inthe gas cap is required for maximum oil recovery, soassociated gas reserves usually remain shut in until mostof the oil reserves have been produced.
Nonassociated gas is gas that is not associated withan oil reservoir. Production is limited only by marketavailability and contract terms.
For the calculation ofnonassociated and gas cap in-placevolumes, the folIowing equation is used:
29
---------------------
Table 4.2-1 In-Place Volumes of Related Products
Liquid Volume per Volume of Raw Gas
Vol % ProductProduct multiplied by
SI' Imperial'(m31l06m3) (bbVI06 cf)
Propane 36.88 6.54n-Butane 42.22 7.48i-Butane 43.80 7.77n-Pentane 48.53 8.60i-Pentane 49.02 8.69n-Hexane 55.10 9.77n-Heptane 61.80 10.96n-Octane 68.59 12.16n-Nonane 75.42 13.38n-Decane 82.26 14.59
SUlphur Weight per Volume of Raw Gas
Vol % SUlphurProduct multiplied by
(tonnesIl06m3) (It/I06cf)
Sulphur 13.60 0.377
4.2.2 Material Balance EstimatesCalculation of in-place volumes of hydrocarbons bymaterial balance requires equating the incrementalexpansion ofthe reservoir fluids upon pressure drop tothe reservoir voidage caused by the withdrawal ofoil, gas and water, corrected for any fluid influx orinjection. The process requires an accurate history ofreservoir performance, includingvolumes ofoil, gas andwater produced or injected, and pressure changes. Fiveto ten percent ofthe oil or gas must have been producedbefore a reasonably accurate calculation can be made.
4.3 PROCEDURES FOR ESTIMATINGIN·PLACE RESOURCES
The calculation of an in-place resource volume ofhydrocarbons does not yield an exact answer. Theaccuracy of each parameter used in the calculationdepends on the validity ofits source and the accuracy ofits measurement. When all the individual factors in anestimate are combined, the degree of variance can leadto substantial differences in the answers obtained. The
• Standard conditions of pressureand temperature are101.325 kPa, 15.6°Cfor 81; 14.65 psia, 60°FforImperial units.
30
DETERMINATION OFOILANDGASRESERVES
uncertainty associated with any estimate of volumes ofhydrocarbons in place is handled differently in the twoprocedures used for the calculation: the deterministicand the probabilistic.
The deterministic procedure is the one most commonlyused. The best estimate ofeach parameter is used in thecalculation ofreserves. The accuracy ofthe estimates isonly as good as the quality and source of measurementof each parameter used in the calculation and will reflect the experience of the professionals in selecting thebest estimate for the parameters. After recovery factorshave been applied to the in-place estimates, the reservesare classified as "proved," "probable," and "possible"to reflect the degree of uncertainty, in the view of theevaluator, associated with each category. Degree ofuncertainty is discussed in detail in Part One.
The probabilistic procedure quantifies the uncertaintyin the resource estimate by using the evaluator's opinion to describe the range of values that could possiblyoccur for each variable, and producing relative frequencycurves to describe the probability of the values occurring within that range. A combined relative frequencycurve is then generated to describe the possible rangefor the in-place resources and the associated probabilityof occurrence ofeach of the volumes within that range.A variety of methods exist to generate the reservesvolumes, the most common being the Monte Carlo computer simulation, which uses a computer to iterativelycalculate enough in-place values from the variable parameter ranges to construct the in-place frequencydistribution.
With rapidly expanding computer applications, theprobabilistic procedure is gaining popularity in portraying the uncertainties associated with a range ofestimates.However, there are alternative procedures to generatethe in-place resource frequency distribution. The alternative presented in Chapter 6 is a "short-cut" that canbe performed on a hand-held calculator. It must bestressed that, as in the deterministic, the reliability ofthe results using any probabilistic procedure is dependent upon the quality of the data and the experience ofthe evaluator in selecting the range of values for eachvariable. If properly derived. the probabilistic estimatesof resources in place and recoverable reserves shouldcompare closely with the proved. probable, and possiblevolumes obtained using the deterministic procedure.
In order to understand the uncertainty associated withall reserves estimates, the evaluator must have a goodappreciation of probability theory and statisticalmethods. This knowledge is critical when applying
OVERVIEW OFPARTTWO
classifications such as proved, probable, and possibleto the values of resources or reserves. Uncertainty inreserve estimates is covered in more detail in Chapters3,6, and 22.
4.4 SOURCES AND RELIABILITYOF DATA
Reliability of data is covered in various sectionsof Chapter 5 in the discussions of the individualparameters used in the calculation of in-place volumes,and in detail in Section 5.11, Quality and Reliability ofData and Results. The source of data and the accuracyof measurement are the two key elements in selectingparameters with some confidence. There can be severaldifferent sources of data from which a given parametercan be selected. Evaluators are usually faced with someconflicting values from which they must select eithertheir best estimate or a realistic range ofvalues for eachparameter. The experience ofthe evaluator in assessingthe validity ofthe data derived from each source is critical in explaining the difference and establishing the bestvalue to be used in the calculations.
Table 4.4-1 summarizes the sources for each of thevariable parameters used directly in volumetric estimates. The source ofeach factor is shown, with a priorityofsource given for derivation ofthe specific parameter.The priority is valid only if the testing methods andmeasurements are considered to be adequate. Resourceestimates are valid only with the available data andat the time they were prepared. Constant revision isnecessary as other sources of data become available.
4.5 INTERRELATIONSHIP OFPARAMETERS
The various parameters used in the volume calculationare interrelated and, despite their sources, must becompatible to one another. For example--as mentionedin the discussion ofcutoffvalues-porosity, permeability, and water saturation are related through the geometryof the pore spaces in the reservoir rock. Pressure andtemperature are both dependent upon the depth ofburialofthe reservoir rock. The parameters selected must makesense when viewed together.
The subject of recovery of hydrocarbons is coveredin Part Three, which discusses the derivation of therecovery factor chosen to convert the in-place resourcesto reserves. Since the selection of recovery factor maybe affected by other reservoir parameters that are discussed in Part Two, a few comments are in order here.
Recovery factor may be dealt with independently whenadequate values for parameters such as drainage area,net pay thickness, and pore volume can be assessed.When the information available allows only an estimateof gross productive interval (gross pay), or when thearea assigned may represent spacing or total pool arearather than effective drainage area, the recovery factorcommonly incorporates the allowance for portions ofthe reservoir that may not contribute to the productionin a given well. Allowance for this undrained volumewould probably be better accounted for by adjusting theparameters of thickness and area.
Competitive operation is another consideration that mayaffect the recovery assigned to an individual well.Hydrocarbons in the subsurface do not recognize boundaries of area ownership. Where reservoir continuityallows the movement of hydrocarbons across ownership boundaries, factors such as the date that productioncommenced and the rate of production have a greaterinfluence on recoveries from individual wells than thein-place resource underlying the individual companyowned tract. In such circumstances, a share of poolreserves based on past production and current production rates provides an acceptable method ofestablishingrecovery for individual wells.
Extrapolation of well-established production declinecurves is the most accurate means ofcalculating reservesand establishing recovery factors to be used withvolumetric estimates ofin-place volumes. Decline curveestimates, which are dealt with in detail in Chapter 18,may also lead to re-evaluation of other volumetricparameters. Decline curve methods may be used onlywhen there is sufficient production data to define therate of decline, and when the capacity of a well to produce is actually declining. At times, apparent decline inproduction may be due to mechanical limitations.Extrapolation of past performance into the futureassumes that the forces acting in the reservoir in the pastwill continue to act in the same fashion in the future.
4.6 USES OF RESOURCE ESTIMATESResource-in-place estimates are the starting point forvolumetric estimates of reserves. Regular reserveestimates provide most exploration and productioncompanies with a yardstick of their performance. Whencurrent inventory is compared to production rates,an indication of the life ofthe current resource is available at any time. Companies also report their reserveinventories to conservation authorities, securitiescommissions, and shareholders.
31
m _
Government agencies require reserve reporting toprepare resource inventories of the province or countryfor the purpose of determining requirements for pipeline construction and establishing a rationale forapproving spacing changes, setting allowables, andapproving secondary recovery schemes.
Evaluations of reserves of oil and gas are used foracquisition and disposition of these assets, borrowingrequirements for banking purposes, and illustrating investment returns to investors and joint venture partners.Individual property evaluations (reserves analyses) are
Table 4.4-1 Sources of Data
DETERMINATION OFOILANDGASRESERVES
used for purposes such as land sale acquisitions, exploratory drilling operations, development prospects,participation in third-party ventures, and implementation of enhanced recovery schemes.
Uses ofestimates ofin-place resources and reserves andevaluations based on these estimates are many and varied; the amount ofdetail required is dependent upon theaccuracy required for the particular purpose.
The uses of resource estimates are covered in moredetail in Chapter 26.
Units
Parameter Symbol SI Imperial Order Source of Data Requirements
Area A hectares acres Isopach map net pay Sufficient well control, geophysicalcontrol, and identificationof depo-sitional pattern and type of trapping
2 Assigned area } Establishing relation to drainage
3 Spacing unitsand adequately applying averagethickness
Thickness h metres feet Core analyses Representativerecoverynet pay Applying proper cutoffs
2 Porosity log deter- Establishingproper core-logmination based on log relationshipcore relationship Correlation for hole conditions
3 Log combinations } Proper identificationof
4 Porosity loglithology or rock matrix
S Other wireline log } Assessment ofgross pay
6 Geologist's logonly may be possible
Porosity decimal fraction Core analyses } Assessing weighted average
2 Log analysis based onporosity ofnet pay
log core relationshipVaried with lithology or matrix
3 Log combination } Lithology identificationand
4 Single porosity loguse of empirical relationships
S Derived from another
}well in the same pool or Acceptable comparisonanother pool in thesame zone
(cont'd)
32
rOVERVIEW OFPARTTWO
Table 4.4-1 (cont'dl
Units
Parameter Symbol SI Imperial Order Source of Data Requirements
Water Sw decimal fraction Oil base core Noncontamination of samplesaturation
2 Capillary pressure test Representative samples for testing
3 Log analyses based on Adequacy ofdetermination ofcorecorrelation formation water resistivity, R", from
water sample or logs
4 Log analysis using Adequacy of determination of R"combination logs from water sample or logs
S Resistivity vs. Variation of porosity affectingestimated porosity resistivity
6 Cores and/or logs from Validity of comparisonsamepool orname zone
7 From correlation with Establishment of correlationporosity or permeability
Formation Bo m3/sm3 bbl/stb 1 Oil analysis Acceptability of samplevolume factor
2 Comparison to similar Similar reservoir conditionsgravity crude
3 Correlation curves Validity of correlation
Gas Z dimensionless Gas analysis reservoir Acceptability of datacompressibility and pressurefactor
2 Comparison to reservoir Validity of comparisonat similar depth withsimilar gas
Formation Pr kPa psia Bottom-hole pressure Adequate pressure builduppressure bomb gauge
2 From other wells in pool Representative of subject well
3 From other pools at same Acceptability of pressure-depthdepth relationship
4 Estimated from depth vs. Adequacy of correlationpressure correlations
Formation Tf °C OF Bottom-hole temperature Mechanical operation oftemperature measurement - bomb equipment
2 Logs Temperature of mud reflectingformation temperature
3 From other wells in pool Adequacy of data
4 Other pools at same depth Validity ofparticular depthcorrelation
S Depth vs. temp correlation Validity ofparticular depthcorrelation
33
4.7 BACKGROUND AND EXPERIENCEOF EVALUATORS
An evaluator, in estimating oil and gas resources, mustplay the role of a modem-day Sherlock Holmes. Theinvestigative process-sifting through conflictingevidence, checking the validity of data, selecting thebest parameters, putting together the conclusions interms of an answer, and testing the reasonableness
34
DETERMINATION OFOILANDGAS RESERVES
of that answer-is a test in deductive reasoning. Theprocess may be considered partly an art and partly ascience.
The depth of experience of the evaluators plays a largerole in the acceptability oftheir answers. Drawing frommany disciplines-geology, geophysics, engineering,petrophysics, and statistics--evaluators require the fullbackground of knowledge in order to arrive at the bestanswer possible given the available data.
rChapter 5
ESTIMATION OF VOLUMESOF HYDROCARBONS IN PLACE
5.1 RESERVOIR AREA AND VOLUME
5.1.1 IntroductionThe two methods for estimation of original in-placevolume of hydrocarbons are volumetric mapping andmaterial balance. During the initial delineation anddevelopment of a field, volumetric mapping is the keyto estimation, possibly aided in the very early stages byanalogous field data. As depletion proceeds and adequateproduction history becomes available, material balancemay represent a practical second method and mayeventually become the most accurate procedure. Reasonable confirmation between the two methods canprovide assurance that appropriate data and assumptionshave been used for each estimate.
Certain reservoir factors tend to reduce the applicability of material balance and reinforce the importance ofvolumetric mapping throughout the life of the field:
• Moderate to strong water drive
• Low average permeability
• Complex internal architecture and poor lateral orvertical continuity
Any of these factors may make it difficult to obtain arepresentative average pool pressure in response toproduction.
The capability of mapping the "container size" as thebasis for volumetric estimation is primarily determinedby the interrelationship of the geological complexitiesand the amount, quality, and type ofdata. Well control,and the spacing of wells compared with the size of theaccumulation are usually the most important considerations. Where applicable, the quality, amount, andpositioning ofseismic data may also be very important.
Information on the following is also important tovolumetric mapping:
• Formation tops from logs and sample data
• Cuttings samples
• Core for lithology, environmental analysis andmeasurement ofparameters
• Log response and evaluation
• Pressure and pressure transients
• Fluid composition
• Fluid contacts
• Test data and more extended production data
5.1.2 Acquisition of DataThe scope of reservoir study and data acquisitionstarting at field discovery and extending over the life ofthe pool must meet the technical objectives, but mustalso realistically reflect the cost and potential benefits.The information collected should meet both short- andlong-termrequirements. Ifimportant data is not collectedwhen it is available even though it is not yet needed,there are likely to be serious regrets later when the information is no longer available or can only be obtainedat prohibitive costs.
The very basic data items such as logs and samplesfor formation tops are acquired rather routinely. Someof the other items are discussed in the followingsubsections.
Seismic Data
Seismic can be a useful tool for mapping, dependingon the geological setting and reservoir objectives.Traditional seismic has been used to provide the transittime from reflection horizons to define depth and formof subsurface structures.
Seismic technology has advanced tremendously in thelast several decades. Digital recording leading to common depth point seismic and the growing computercapabilities for data processing, have been keys to thisadvance. However, in many instances the depth responseis still all that can be extracted from seismic. In a goodnumber of geological settings where seismic quality permits, "stratigraphic seismic" may also be important.With this method, the amplitude response ofthe recorded
35
signal may provide data relative to lithology, porosityand-when the seismic signalisparticularlyclear-fluidcontent of the reservoir horizons.
The "new kid" on the seismic block is 3-D seismic,which has quickly gained major importance in manygeological settings, particularly as a development toolwith great potential for assisting in reserves mapping.The basic response and data provided by 3-D seismicare no different than those obtained from conventionalseismic. The difference is in the configuration ofa 3-Dsurvey, which is set up to provide a closely spaced gridofdata points. This grid allows a more continuous threedimensional definition of structuraland other geologicalvariations.
If seismic data is applicable to a reservoir, it probablywill have been gathered early in the exploration phase.Ongoing interactive review incorporating new wellsmust continue well into the developmentprocess. It alsomay be appropriate to shoot additional seismic to helpresolve problem areas or incorporate new technical advances. The potential benefits from 3-D seismic, forinstance, should be carefully considered, usually thesooner the better. Another aspect to consider in incorporating seismic data is that processing capabilityis continual1y improving. When field reviews areundertaken, reprocessing may offer data improvementwithout the added cost and possible timing delays ofnew shooting.
Original Pressure Data
Undisturbed original pressure data can only be obtainedbefore significant production is taken. Unless the reservoir is very small, normal production testing will not bea problem in this regard. Good initial pressures in gas,oil and water columns allow construction of pressuredepth plots for fluid contact definition. A geographicspread of original water phase pressures will assist indetermining whether hydrodynamics are important inthe region.
Pressure Transient Analysis
In recent years high-resolution pressure recorders haveprovided another possible source of information relating to reservoir limits. This process relies on theinterpretation of very subtle pressure changes. Carefuldesign of the procedure in consultation with experts isnecessary, as well as care in the acquisition ofdata. Oneof the difficulties, as with any kind ofreservoir simulation, is that the results are not unique and must becorroborated with other information.
36
DETERMINATION OFOILANDGASRESERVES
Analogous Fields
Another aspect to be kept in mind is that others mayhave drilled or be drilling in analogous field settingsrelative to the field of specific interest. Utilizingthis data as it becomes available may help maximizeusefulness of limited data sets.
Extended Flow Tests
Horror stories are told of significant investment infacilities and equipment for a well that declined precipitously when put on production. If analogous fielddata indicates a significant risk, an extended flow testmight provide insurance against such an occurrence. Asthe size of the project increases, the risk exposure increases proportionally. The running of extended flowtests must be weighed against certain considerations:
• The level ofapparent risk
• The cost of the test
• Whether it is practical, given the properties of thereservoir, to run the test long enough to resolvepossible lower size limits
• Environmental and conservation concerns
Another option is to put a pool on production withminimum investment to allow extended production datato be gathered. If warranted, further developmentoptimization can then be undertaken at minimal risk.
5.1.3 Data Analysis
Data accumulates rapidly during the delineation andearly development phase of field development. Thevolume of data and pace of activity can often lead to atendency to handle one well at a time and lose someperspective on the big picture. Periodic field-wide reviews of all geological data and related engineeringmaterial provide the best chance for optimal solutions.Also, careful management of data accumulation andstudy scheduling will ensure that holes in data setsare minimized and that the cost-benefit ratio of dataacquisition is efficient.
Depositional Environments
The recognition of depositional environments and theirrelationship to reservoir development is basic to petroleum geology. The study of recent deposits as "a key tothe past" is a common theme ofsedimentary geologicaltraining. Outcrops and producing fields provide a recordofancient depositional environments and resulting reservoir patterns. The extensive literature available onthese subjects should be searched for analogous fielddata in any major field study.
-
s
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
Adequate core coverage is required to define environmental concepts in the subsurface. Proper core spacingand intervals depend on the complexity of the patternsof reservoir development. Data gathering must beappropriately resolved in the early stages of delineationand field development. Nearby analogous fields mayadd to tbe database.
Once depositional environments are resolved from core,it may be possible to expand the study into noncoredwells by calibration to log response. However, there isalways more risk of error when using logs rather thancore for environmental interpretation.
Primary Porosity and Diagenesis
Primary porosity is retained in sedimentary rocksthrough deposition, initial burial, and lithification. Thistype of porosity and the patterns of its occurrence areeasily related to depositional environment. Most sandstones and some carbonates are dominated by primaryporosity.
Subsequent to the formation of primary porosity,sedimentary rock is often subjected to increasingor varying temperature, pressure, depth ofburial, and groundwater regimes. As a result, minerals may be dissolvedor precipitated. Also, the reservoir rock may befractured. The processes creating tbese changes in therock fabric and properties are called diagenesis. The diagenetic overprint and the resulting porosity andpermeability changes mayor may not be closely relatedto original depositional features and patterns. Diageneticporosity development may, in fact, be controlled bysomething entirely different such as fault and fracturesets or erosional surfaces. Diagenesis and its controlsand results must be considered in reservoir mapping,particularly in carbonate rocks.
Type of Trap
Petroleum deposits may accumulate in three basic typesof traps:
Structural Traps, which are formed by rock layers thathave been folded or faulted
Stratigraphic Traps, which are formed by depositional,diagenetic or erosional processes
Hydrodynamic Traps, which are created by movingformation water, buoyancy, and density interaction witha hydrocarbon accumulation
These traps may occur alone or in combinations ofdiffering dominance. Mapping patterns and style dependvery much on the types oftrap. Petroleum geology texts,which usually contain extensive detailed material on
traps, may be used for reference. Analogous field datais also very important when considering trapping.
The exploration concepts that led to a discovery wouldhave included an interpretation of hydrocarbon sourceand trapping. This interpretation should be reviewed andrefined or revised, if necessary, at an early stage. Mostbasins or play areas tend to have a limited suite of traptypes of economic importance. Trapping should be understood within the limits of available data beforedetailed reserves mapping proceeds.
Reservoir Continuity
Larger scale structural and stratigraphic features are offirst-order importance in determining the limits ofa reservoir and the volume ofgas or oil in place. Limits maybe defined by faults, folds, facies changes, diageneticboundaries, or erosional surfaces.
It is often unclear in the early stages of exploration anddevelopment whether an accumulation of oil or gas isin a single pool ora series ofpools in close proximity.The keys to resolution ofthis question may be providedby pressure; pressure-depth plots; gas, oil and watercompositional data; and indications from fluid contacts.
The degree of internal continuity and homogeneitywithin a pool is an important geological feature relativeto recovery efficiency. Detailed cross sections or fencediagrams are usually necessary to resolve the details ofinternal reservoir architecture.
Fluid Interfaces
Fluid interfaces important in reserves determinationinclude the following:
• Gas-oil
• Oil-water
• Gas-water
Pressure-depth plots provide the best technical resolution oftbese interfaces when good quality pressure andfluid density (gradient) data is available above and below the contact. This method defines a contact even inundrilled or untested intervals (Figure 5.1-1).
In medium- and coarse-grained reservoirs of highporosity and permeability, the transition from hydrocarbons to water will be sharp and easily defined bywell logs. Flow testing will also be conclusive to definition of contacts in this type of reservoir if wells andtest intervals are properly located.
Capillary effects in the small-diameter pore systems infine-grained rocks result in long hydrocarbon-watertransition zones and considerable difficulty in
37
1700
~ t- Gas Gradie~t4.4 kPaim
1800
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\
~15.Qlc
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\(ree Water Level::>>::
2100
Water Gradient /
I~2200
10'18 kPaim
34 36 38 40
Pressure (mPa)
Figure 5.1-1 Pressure-Depth Plot for Free WaterLevel Determination
resolving the water level. For example, in the TurnerValley Formation gas reservoirs in the Alberta foothills,the change from fully water-saturated zones to irreducible water saturations may occur over an elevationexceeding 100 metres. In this extreme case, accuratelydefining water levels is difficult using only log or testdata.
Gas-oil contacts may also be difficult to resolve.Pressure-depth plots offer a technical solution whenquality data are available. Flow testing, includingwireline repeat formation tester (RFT) data, may behelpful. The neutron and density log combination canbe definitive where the contact is located within a drilledcontinuous porous section.
On rare occasions, reservoir character and seismicquality may be sufficient to define fluid contacts by "flatevents" on seismic sections.
Hydrodynamic trapping will result in tilted oil-watercontacts with a tilt proportional to oil-water fluid density differences and flow velocity. Tilted contacts maynot be evident where a very local area is under study,but they become evident on a larger scale. Accurateresolution of this type of contact may be extremelysignificant to reserves definition. Gas accumulationsmay also occur in hydrodynamic settings, but the density difference ofwater and gas is such that measurabletilts on gas-water contacts are unlikely.
38
DETERMINATION OF OIL AND GASRESERVES
5.1.4 MappingResolution ofthe "container size and shape" by a mapof the hydrocarbon-filled reservoir is the single mostimportant step in volumetric reserves estimation. Sincethe reservoir is a three-dimensional form, verticalillustrations such as cross sections, fence diagrams,or isometric drawings may also be required to understand pool geometry. Examples of forms requiringvertical diagrams include complex faulting, majorunconformities and salt dome intrusives. Once thevertical geometry is better displayed and understood,more accurate maps may be drawn.
Mapsfor Volumetric Estimation
The interplay of structure, fluid contacts, and porousreservoir variations requires at least the combination ofa structure map and an area or volume map. In manycases, construction of a series of maps prepared in alogical sequence may be the best technical approach.This could include some or all of the following:
Structure Maps, which may be:
• Top formation or top porosity, showing location offaults and fluid contacts
• Base formation or porosity with limits as above
• Fault plane structures
Ifboth top and base porosity structure maps are drawn,then a gross pay isopach map can be derived by crosscontouring.
Isopach Maps, which are maps of thickness variationsof gross or net pay showing reservoir limits controlledby structural form, fluid contacts, depositional features,diagenesis, erosional features, or combinations of thesecontrols. The isopachs of gross and net pay thicknessvariations are simple geometric depictions of the reservoir form that can be assessed for "geologicalreasonableness" with some confidence.
Porosity-Thickness (<I>h)* Maps, which may be drawndirectly or constructed by drawing maps on theindividual parameters and cross-contouring. Porositythickness mapping is particularly important whereporosity in the reservoir is variable and average porosity would not approximate the reservoir void space inall areas.
• Porosity is represented by thesymbol "1\>" inthismonographand in the petroleum industry generally. The thickness ofthe reservoir is represented by the symbol "h."
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
Hydrocarbon Pore Volume (HPV) Maps, which maybe drawn directly or by cross-contouring ljlh with I-Swvalues." HPV mapping is particularly important whenwater saturations are variable within the reservoir.
Where a series of maps is drawn showing interrelatedvalues, cross-contouring is required to ensure that themaps are compatible. Ifcross-contouring is being doneby hand, maps on two separate variables are overlaidand, at each point where contours ofthe two maps cross,a related variable is calculated by the appropriate arithmetic manipulation ofthe individual values. Figure 5.1-2shows the derivation of a porosity-thickness (ljlh) mapon porosity and net pay thickness. The manual processis tedious, but current computer mapping software canhandle it readily.
The use of cross-contouring to combine parameters in atechnically rigorous process is warranted when individual parameters have consistent patterns that can bedrawn with reasonable accuracy and with greater assurance than the combined value. For example, a ljlh mapcan be constructed by preparing a map of porosity variations and an isopach map ofnet pay, and then combiningthem by cross-contouring. The less rigorous alternativeis to calculate and plot ljlh values at each well locationand construct the map directly from the combined variable. If individual data such as ljl does have a definedtrend, it may tend to be lost in this methodology.
Reservoir Limits and Wedge Zones
Structure maps based on seismic depth data andavailablewell control are often the first maps constructedon an oil or gas pool. Limits defined by structure andknown fluid contacts may then be located. In dippingreservoirs, the area offluid interfaces, for example, theoil-water interface, produces a wedge area where thegeometry must be carefully handled. This wedge areais geographically defined when the structure is mappedon both the top and the base of porosity.
Dipping faults may also create wedge areas, and solution of this geometry may require drawing a structuremap on the fault plane. When faults are steep, the wedgearea may become very small and may be reasonablyrepresented by a median line.
In stratigraphic traps, reservoir limits may not bedefined by structure maps, evident gradational thinning,or other simple techniques. Seismic amplitude responsemight be helpful in some cases, but stratigraphic limits
·Water saturation is represented by the symbol "Sw"throughout the monograph.
can remain uncertain well into the field developmentphase. Closely spaced drilling may provide theonly method for resolution of reservoir limits in thiscircumstance.
The Choice of Map Types
The final map to choose as a basis for volumetriccalculation is a matter oftechnical judgement: a simpleproductive area map, an isopach map depicting rockvolume, a pore thickness (ljlh) map, or a hydrocarbonpore volume (HPV) map. The choice should be basedon careful appraisal of the degree of complexity thatcan be fairly represented with the da!a available. Simplemaps such as productive area or gross pay isopach mapsrepresent physical forms that can be readily assessedfor realism. Maps that combine parameters are not aseasy to relate in detail to physical forms even thoughthey often tend to be dominated by a single variablesuch as gross pay thickness.
Interpretive geological mapping offers the potential ofproviding the best representation of the reservoir ifadequate data is available and the practitioner is thorough.One general rule worth considering even with interpretive mapping is that the simplest interpretation that fitsthe data and the geological concepts is often the best.Even with a thorough and technically sound interpretation, if there is freedom to vary the reservoir sizesignificantly, interpretation can introduce the risk ofsignificant error. Careful assessment is required todefine when this leads from the booking of"proven" to"probable" reserves.
In summary, mapping concepts may be reduced to afew simple concepts to consider:
I. Assessing specific data available, analogous fields,and geological concepts in order to understand andvisualize the feature to be mapped
2. Separately mapping each significant data item thatshows a definable pattern of variation
3. Combining maps by cross-contouring where appropriate (Figure 5.1-3 illustrates a series of maps)
Mechanically Contoured Maps
Where a large amount of data is available at reasonablespacing, an alternative method of reserves mapping isto use evenly spaced (mechanical) contours. Thisamounts to linear interpolation between actual well datapoints. The method may require some interpretation toassign reservoir boundaries, but once this is done thefreedom to vary the result becomes limited. For thisreason it is often used in unit or joint venture projects
39
DETERMINATION OFOILAND GASRESERVES
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Figure 5.1-2 Cross Contouring
40
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
Gas-water contact(·2603) intersectsbase reservoir
I 1 mile I
(a) Structure on Base Porosity (rn ss)
0.8
3.0
Gas-water contact(·2603) intersectstop reservoir
I 1 mile I
(b) Structure on Top Porosity (m ss)
Note:Gross thickness map was developed bycomputer cross-contouring structure
maps.
I 1 mile I
n
(c) Gross PorousThickness (m)
Figure 5.1-3 Series of Related Maps (zero edge from seismic, computer-contoured) (ZYCORSoftware)
41
where variations in interpretations can lead to disagreement and impasse. The mechanical method ofcontouring minimizes extension ofhigh contour valuesinto undrilled areas and, in contrast to an interpretivemap, may provide conservative reserves volumes.
The strength of mechanical contouring is that if doneproperly it honors the available hard data with minimalinterpretation. Its weakness is that unless the patternsare very simple it does a very poor job of representingthe geological patterns and reservoir variations. It shouldbe recognized as only a simple approximation for jointventure and reserves assignment. It is not a geologicalmap. An example of an interpretive and mechanicallycontoured map of the same data is shown in Figure5.1-4.
Computer Mapping
Advanced software is available for computer mappingofreservoir parameters with a number ofcontouring options. The computer is very good at handling simplesurfaces such as structure maps, but may have problemswith complex surfaces and fault discontinuities. The
DETERMINATION OF OIL AND GAS RESERVES
capability to adequately represent complex formsdepends very much on the quantity and spacing of thedata being mapped. Since computer mapping usesmathematically defined best-fit surfaces, the resultis noninterpretive and tends to be somewhat mechanical. Combining computer mapping on individual values,editing for geological concepts, and cross-contouringthe map series can produce a map that is geologicallysound.
A major benefit of computer mapping is the ability touse cross-contouring techniques and to calculate volumes. Even where hand-drawn interpretive maps arerequired to capture the geological concepts, it may beappropriate to digitize maps into computer format touse these computational capabilities.
Another benefit (curse?) ofcomputer mapping is that itis possible to test a range of different assumptions andanalytical approaches. This can be very useful ifprobabilistic reserves estimates are being prepared. Preparinga range of map interpretations can be an onerous taskwithout computer technology.
/IYankee
~
1 mile 1 mile
(a) Offshore bar cut by meandering shale filled channel.Environmental concepts may be assisted by log, core,seismicdata, or nearbyanalogous fields.
Source: AfterWeinmelster, 1989.
(b) Samedata as used in (a) but contoured ignoringenvironmental concepts. Apparenttrap integrityandvolumes are quite different from (a).
Figure 5.1-4 Examples of Mechanical and Interpretive Mapping
42
R
ESTIMATION OF VOLUMES OF HYDROCARBONS IN PLACE
5.1.5 Refinement of VolumetricEstimates
With time and addition of data in any of the areasdiscussed, it is reasonable to expect that the uncertaintyof volumetric estimates can be narrowed. The bestanswers are obtained when the maturity ofthe field provides an extensive database, all reasonable sources areincorporated in the solutions and-where discrepanciesbetween sources arise-preconceptions are challengedand either confirmed or revised. On occasion, new technology such as 3-D seismic, wellbore image logs,or other similar advances may supply better answers.Using all of the data sources may require crossingtechnical discipline boundaries; thus working inmultidiscipline teams is a growing trend in manycompanies.
ReferencesWeinmeister, M. 1989. "Calculating Recoverable Gas
in Place from Volumetric Data." Shale Shaker,May-Jun. 1989.
43
DETERMiNATJONOF OIL AND GAS RESERVES
5.2 THICKNESS
5.2.1 IntroductionNext to the areal extent of the reservoir under study, thethickness value referred to in engineering terms as "netpay" is the most variable component of the oil-in-placeequation. It is frequently the most poorly defined andmisunderstood term in discussions of reserves.
The confusion stems mainly from the differences infocus of the two contributing disciplines: geology andreservoir engineering. The geologist is concerned firstwith mapping the discrete reservoir elements in question irrespective of any real or commercial segregationdictated by gas-oil or oil-water interfaces.
At this stage geoscientists will map "gross reservoir"and "net reservoir." Later, after the bulk reservoir elements have been adequately defined and mapped,economic considerations will come to the forefront asthe reservoir engineer asks the geologist to produce amap showing only the outlines of the hydrocarbonaccumulation.
The terms "gross pay" and "net pay" are used todescribe reservoir thickness. Gross pay, referring to thetotal hydrocarbon-bearing zone, frequently includesintervening nonproductive intervals that may be presentin the reservoir (Figure 5.2-1). Net pay refers to the sumof the productive sections of the reservoir and is determined by the application of cutoffs, which are thespecified lower limits of core or log data (porosity,
0.0
0.0
---•,- -
OPHI
\\
,,
\c;:"
\
, -e..-__
"""-CNL Porosity.-... FOe Porosity
,-.----ill:::-,..... ----
0.6000
CAL - caliper
CNL - compensated neutron log
CSU - cyberservice unit
DS - bitsize
DPHI - densityporosity
FDG- compensated formationdensity
GR - gamma ray (APi)
ILd- deepinduction resistivity
urn- medium induction resistivity
NPHI - neutron porosity
SFL - sphericallyfocusedlaterotoq
SP - spontaneous potential
Source: Schlumberger of Canada, 1985.
Figure 5.2-1 Reservoir Interval Terminology
44
ESTIMATIONOFVOLUMES OFHYDROCARBONS INPLACE
permeability, and fluid saturations) below which aformation will be unable to achieve or sustain economicproduction. Cutoffs are determined by using existingproduction information from the subject or similar formations, and by constructing correlations betweenproduction, porosity, permeability, and water saturationand the recoverable reserves requirements.
While porosity and water saturation calculations (whichare discussed in subsequent sections) are subject tocertain inherent errors, none are large enough to changethe results by several orders ofmagnitude. The same isnot true for net pay.
Net pay is also important in determining the total amountof hydrocarbons in a reservoir so that the total amountofenergy in that reservoir can be calculated. Net pay inthis context can be much higher than the value used inthe oil-in-place equation because here it can includeintervals located in transition zones and even below producing oil-water contacts.
Another major criterion in determining net pay is thepotential oil available for future secondary or tertiaryrecovery programs. In such programs displaceable netpay may not equate to net pay in a pressure depletionprocess, particularly in the case ofa very heterogeneousreservoir.
Net pay may also be used during the unitizationprocess either as a stand-alone figure in net pay maps oras a guide for development drilling programs. Clearly,the purposes for which net pay calculations will be usedwill dictate how they should be determined.
5.2.2 Defining Net Pay
Logs
Wireline logs of all types have been incorporated intothe process of defining net pay. Porosity tools, by theirvery nature, offer the most universally consistent netpay criteria. Where single porosity tools are utilized tocharacterize reservoir porosity, the analyst will typicallydetermine the tool reading corresponding to the appropriate lower limit of porosity and draw a vertical linedown the log. All reservoir exceeding this lower limitmay be integrated to arrive at a value for net pay.
Where multiple porosity tools have been run and a moresophisticated solution approach has been employed,cutoff values, typically in the 2 to 4 percent range formost carbonates and 7 to 10 percent for many sandstones, will be applied to the computed data. In this waylogs are employed as the primary filter for net pay
because they represent the first available evidence ofthe productive potential of a well.
Beyond the obvious quantitative porosity estimatesafforded by neutron, density, and sonic tools, there arethe spontaneouspotential (SP), caliper, gamma ray (GR),and microresistivity devices such as the microlog. Theseprovide further qualitative evidence that a zone iscapable of fluid production.
In heterogeneous reservoirs with thin beds of widelyvarying quality, some logs may not properly define netpay due to their tendency to average or smooth porosityover larger intervals. This problem is most acute inpreviously explored areas with a high number of olderlogs.
Core
Full-diameter or wireline-retrieved small-diameter coresoffer a further level of definition beyond that accordedby logs alone. Permeability measurements may bematched to porosity to confirm or enhance the selectionof the lower level of producibility. It is useful to notethat the absolute value ofpermeability for a given reservoir and reservoir fluid dictates what the equivalentporosity cutoffwill be, and not the reverse.
Porosity-Permeability Cutoffs
The empirical selection ofporosity cutoffs to determinenet hydrocarbon pay is best accomplished for normaloil and gas reservoirs by using core permeabilityporosity cross-plots. Using minimum air permeabilityvalues of 1.0 mD (for medium to high gravity oils),0.5 mD (for wet gas), and 0.1 mD (for dry gas) willyield approximate effective porosity cutoff levels forcommercial hydrocarbon production into wellbores.These cutoffs are empirical (i.e., based on testing andactual production) and are a function of many parameters such as fluid viscosity (mobility), rock grain sizeand pore size (pore geometry), rock cementation andinfill, wettability, and capillary pressure properties.Porosity cutoffs usually increase with decreasing poreand grain size as illustrated in Figure 5.2-2. This plotwas generated from a large database of actual core dataacquired from dozens ofclastic and carbonate reservoirsscattered across the western Canadian sedimentarybasin.
Exceptions to the cutoffs listed are gas accumulationsin the microdarcy range «0.1 mD) and heavy oil inunconsolidated sands. Although sophisticated, largefracture treatments have been employed on wells inthe microdarcy range; however, such low-rate gas
45
b-----------------------------
DETERMINATION OF OIL AND GASRESERVES
Figure 5.2-2 Air Permeability vs. Porosity
when applied to net pay computations, but it is oftenessential in the evaluation process to estimate even semiquantitatively the effective permeability of the reservoir.
The open-hole drill stem test option affords the bestoverall assessment of net pay criteria because, underideal circumstances, large volumes ofthe reservoir fluidcan be recovered and studied in addition to the extensive drawdown and buildup pressure data that isobtained.
5.2.3 Data Acquisition Programs
Logs
The earliest methods for using logs to select net payintervals involved the use ofSP or OR logs. Using curveinflection criteria for determining the top and the baseofeach reservoir unit remains a valid method ifthe stratigraphic unit is a simple clean sandstone-shale sequencewith very porous and permeable sandstones present.However, the blanket assumption that all porous andpermeable reservoir units are capable of production isdangerous. Bitumen can be present in different forms: atar mat or solid pyrobitumen. Disseminated shale, pyrite particles, bitumen, or other blocking or cementingmaterials can seriously impair the capacity of a reservoir to produce hydrocarbons and thereby disqualify itas net pay.
When conditions such as these are known to exist orwhere the reservoir approaches the lower limits of theproducing porosity-permeability regime, more sophisticated logging methods must be considered. Here, allthe porosity measuring devices may be employed depending on availability, cost constraints and holeconditions. In clastic sequences, the neutron-densitycaliper combination in conjunction with the micrologand a standard induction resistivity device will resolvemost net pay situations satisfactorily.
In mixed lithology carbonate reservoirs, where gasmay be present, additional care must be exercised, particularly in the choice of the proper resistivity device.Where matrix porosity is low and water saturation is ator near irreducible conditions, resistivities can easilyexceed 2000 ohm-metres. The choice ofa laterolog overan induction device may be advisable if resistivity is tobe used as a net pay discriminator.
An additional environmental consideration involvesthin bed resolution. Thin beds are defined not only asvertical variations in lithology, but also may includeany closely spaced changing petrophysical parameterthat makes evaluation difficult. Rapid fluctuations in
3020Core Porosity ('Yo)
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production is considered to be uneconomic at the presenttime. The porosity cutoff for commercial primary production of heavy oil from wellbores is estimated to beapproximately 27 percent. Air permeability cutoffsshould not be used for heavy oil sands because themeasurement of air permeability in disturbed and extracted heavy oil sand is quite meaningless. At thisporosity level, the sand is becoming poorly cementedand mobile, permitting the heavy viscous oil to movesufficiently for economic production. These oils havethe capacity to carry loose sand grains, as well as smallamounts of connate water or gas bubbles. This flowmechanism is far different from that ofconventional oiland gas reservoirs.
Flow Tests
The ultimate test of the ability of a reservoir to give upfluids is the actual flow test. During the drilling processand just prior to the decision to run casing in a well, anoperator has two options available:
I. Open-hole/closed-chamber drillstem test (DST)
2. Wireline formation test (WLT)
Judicious use of these tests can enhance the reservoiranalyst's ability to discriminate between pay and nonpay zones. Approximate values of in situ permeabilitycan be calculated from WLT data, the object being tosample a cross section of the elements of a reservoirunit and project the permeability data to cover the entire reservoir. WLT techniques are at best "quick-look"
46
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
porosity type, rock texture or pore type may combine topreclude proper evaluation with standard logging methods. Where thin hydrocarbon-bearing laminae arethought to be present, the addition of a mud-gas log tothe open-hole logging program is advisable.
Core
Core data are used to supplement and calibrate log datawhen net pay is being determined. In addition to porosity and permeability, other properties may be measuredin the laboratory to determine whether the interval ofinterest possesses the properties required for inclusionin net pay. These supporting properties include watersaturation, electrical properties, capillary pressure,
wetlability, relative permeability, and sensitivity tocompletion fluids and methods. In order to determinethe appropriate analyses required, the core retrieval andanalysis program must be designed so that all coringobjectives may be achieved.
A flow chart depicting the process of designing andimplementing a core analysis program in net pay determination is shown in Figure 5.2-3. Ofcritical importanceis identification of the reservoir properties that must bemeasured in the laboratory to aid in the determinationof net pay. Once the coring objectives have beendefined, the operator must design the retrieval and analysis programs in conjunction with the relevant service
I Establishment of Coring Objectives IIrDesign ofCore Retrieval Program II
Core Retrieval and Preservationj
I Core Gamma Ij
Core Description and SampiingFor Basic Core Analysis
IBasic Core Analysis
• Porosity• Permeability• Fluid saturation
j
I IISampling For Reservoir I Sampling ForSupplementary I
Quality Analysis Core Analysis
I IPetrologicaiStudies Sample Screening I
and Reservoir • x-ray methodsQuaiityAssessment I
Supplementary Tests• Electrical properties• Clayswelling• FInes mobilization• Wetlability• Capillary pressure• Relative permeability
Ij
IData Synthesis II
Net Pay Calculations I
Figure 5.2-3 Flow Chart for a Core Analysis Program
47
rtn-. _
companies. Factors such as core barrel type, drillingfluid and core preservation methods may be important.Once the core has been retrieved, it is shipped to thelaboratory for appropriate analyses.
Well Testing
A wide varietyoftesting services and equipment is available to accomplish the objectives of the reservoirengineer in a safe and efficient manner. If the limitations ofvarious systems are understood, factors such asexcessive downhole pressure and temperature, roughborehole conditions, and the presence of highly toxichydrogen sulphide can be dealt with in advance toarrive at an optimum testing strategy. Service companyexperience has shown that the presence of those threefactors in the Foothills region of western Canada seriously limits the application of open-hole testing. Suchlimits apply to a lesser degree to the remainder of thebasin except where the presence of H2S is suspected.
An effective program must start with a clear idea of thepriorities given to the following objectives:
1. Reserve definition for either primary or secondaryhorizons
2. Stimulation treatment design criteria for follow-upcompletion attempts
3. Gathering of reference data to allow drilling andcompletion engineers to plan future wells for maximum efficiency by reducing reservoir damagecreated by the drilling or completion process
5.2.4 Data InterpretationNet pay has been defined as reservoir rock that meetsvarious quantitative cutoffs such as porosity, effectivepermeability, and water saturation. The parameters usedto distinguish net pay are usually well-defined for theformation and pool or area from a history ofproductioncharacteristics for the area. For a specific well to be keptfor production, it normally must have a net pay thickness sufficient to contain enough hydrocarbon reservesto pay for the well completion plus an acceptable profit.Wells with less net pay than this should be abandonedifthey are not required for other purposes such as waterinjector or disposal wells.
Porosity
Porosity is the most popular reservoir quality indicator,and this is unfortunate because the same enviromnentaland depositional factors that influence porosityalso influence permeability. Although increases inpermeability are frequently associated with increasing
48
DETERMINATION OFOIL ANDGASRESERVES
porosity, post-depositional processes in sands such ascompaction and cementation can shift the porositypermeability trend line. For example, increasing porosity associated with constant permeability might indicatethe presence of more numerous and smaller pores.
The concept of mean hydraulic radius is gainingacceptance as a better method to distinguish reservoir orhydraulic units (Amaefule et al., 1988). Mean hydraulicradius distinguishes pore morphological changes thatporosity and permeability alone cannot characterize.
Water Saturation
Water saturation is the next most frequently employedparameter used by reservoir engineers to describe thequality ofthe reservoir unit being investigated. Clearly,lower water saturations are indicative of better hydrocarbon production potential. Water saturation, or anyfluid saturation for that matter, may be affected by amultitude of rock properties (composition, grain size orshape, packing, sorting and cementation); therefore, useofa single saturation cutoffcould have serious implications in rapidly changing rock types.
Fluid Contacts and Transition Zones
The identification of the various fluid contacts, thelocation of the transition zone, and the determinationof other petrophysical, geological, and productioncharacteristics are essential for accurate assessment ofwhat constitutes net pay in the wellbore. This datamay then be used to estimate reserves, hydrocarboncolumn heights, productivity, water cut, and productioneconomics.
Fluid contacts may be identified using core analysis(capillary pressure), logs, or pressure data. In a reservoir that is thick enough, a plot of formation pressurevs. elevation can yield both formation fluid type andinterface location. Several pressure readings in gas, oiland water zones are required. Plotting and connectingpoints of common slope identifies the fluid types.Extrapolation ofthe lines to points ofintersection yieldshydrocarbon-fluid contacts as illustrated in Figure5.2-4.
The analysis of these plots to determine verticalpressure continuity in a single well or horizontal continuity from well to well is not straightforward becausepermeability barriers can also be present.
Where determinable, the most useful values are the freewater level (the water level if no rock material werepresent), the 100 percent water level (the level to whichwater rises due to the presence of the rock material and
TESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
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•Oil
<; \Water \ \
- - - - - \- - - - - - -- - - - - - - -- - - - - - - - - -- - - - - - - - - -- - - - - - - - - - - - -- - - - - - - - - - - - - -- - - - -
- - »<> / / / -----.- - --:;/ / / / O~ / A--
/ / / / / .r-/ / /
PressureSource: Computalog Gearhart Ltd., 1990.
Figure 5.2-4 Hydrocarbon Fluid Contact Identification from Pressure Gradients
e
the resultant rock-water capillary forces), the bottom ofthe transition zone (the same as the lOa percent waterlevel), and the top of the transition zone. Across thetransition zone, water saturations will vary from 100percent at the bottom (lOa percent water level) to irreducible water saturation at the top ofthe transition zone.Due to the varying relative permeabilities across the transition zone as saturations change, the hydrocarbon andwater cuts will change from bottom to top, A "no flow"situation is also possible.
5.2.5 Factors Affecting Data Quality
Adverse Borehole Environments
The reliability ofthe various net pay parameters, watersaturation, porosity, and net pay, when calculated fromopen hole logs or measured in full diameter cores, isdirectly related to the knowledge and understandingof the borehole environment from which this datawas drawn. A number of factors can influence thisreliability level. The principal factor is the physical condition ofthe borehole at the time oflogging. Bottom-holetemperature and pressure can affect the functioning of
every logging tool. Except in extremely hostile (hot andcorrosive) environments (as encountered in deep sourgas reservoirs in the Alberta foothills), these two factors are normally manageable and ofminor importance.Other factors that can, and often do, contribute to critical errors are rugosity (roundness or smoothness) oftheborehole and the depth of invasion of the drilling orcoring fluids employed.
Most logging service companies employ sophisticatedalgorithms to correct their porosity tools for hole irregularities, and use electrical devices to minimize the effectsof drilling fluid contamination. However, the reservoiranalyst must use caution when these corrections havebeen employed near "the edge ofthe envelope." In casesofextreme borehole rugosity, for example, density logsbecome totally unreliable for porosity. Unless other toolsthat are less affected by rugosity (i.e., the neutron andsonic logs) are available, the use ofnearby well controldata might be moreadvisablethan porosity data thatseems "a bit high."
Similarly, a quick scan of the log header on the primaryresistivity device for evidence of either anomalously
49
high mud weights or fluid loss characteristics is alwaysa worthwhile precaution. Either ofthese conditions maylead to excessive overbalancing and consequent flushing of the reservoir which, in tum, can create thickmudcake buildup and lead to erroneous calculations ofwater saturation.
Determination of net pay thickness is usually notsusceptible to direct measurement errors except wheredirectional or slant drilling techniques have beenemployed.
Penetration ofany reservoir at anything less than a rightangle to bedding will give erroneously high thicknessindications. Routine examination of the geologicalframework for the area, coupled with due diligence inthe area ofborehole trajectory, should remove this as aconcern in most instances.
Core Representation
When core data is being used to assess the net payinterval, it is important to realize that the core may, infact, not represent the true reservoir interval. The reason for this is that often the entire zone is not cored orcore may be lost, and therefore, there may be pay thatmust also be considered above or below the retrievedinterval. Proper sampling is essential if the resultingbasic core analysis data is to be representative of thereservoir. Friable unconsolidated sandstones, fracturedreservoirs and reservoirs with alternating competent andincompetent layers often are not fully recovered duringcoring operations. Small (em scale) to large (m scale)intervals may be ground up or washed out, leaving onlythe competent zones and some rubble. Unfortunately, itis the competent zones that are often tight and, therefore, the core may represent only the poor part of thereservoir.
The sampling should be based upon the lithologicaldistribution, porosity and permeability variations withinthe lithological units and the distribution of hydrocarbons. The samples should be representative of theinterval from which they are chosen, with three to foursamples being selected per metre. Where possible, sampling intervals and sizes should be uniform in orderto minimize statistical errors. In certain intervals,plug samples may be taken rather than full diametersamples, but the latter type of sampling should be usedin heterogeneous reservoirs such as those that arefractured, conglomeratic, or vuggy.
Core gamma logs are used in the core analysislaboratory to aid in correlation of core depths with logdepths and to determine the precise location of missing
50
DETERMINATION OF OIL ANDGASRESERVES
core intervals. Occasionally they are also useful inhelping to reconstruct the correct depth sequences ofmisoriented core.
Normally a core gamma logger is operated as a "totalinstrument," measuring all radiation in a certain, widerange of wavelengths. However, spectral componentsdue primarily to potassium, uranium and thoriumemissions may also be measured. Methods for using thespectral components to determine clay types, cationexchange capacities, clay volumes, and even toevaluate source rock have been or are being developed.
To properly assess the problem of representation, it isfirst necessary to measure the core and determine theamount ofrecovery vs. the length ofthe interval drilled.Ifthere is missing core, the lost core interval is customarily placed at the bottom ofthe interval. Often this doesnot represent the true picture. The actual missing interval can be determined by a detailed comparison of thecore gamma log to the downhole gamma log.
Formation Heterogeneity
Most logging devices respond to particular propertiesof a formation that are related to the depositional andpost-depositional history of the rocks. The search for abetter understanding of porosity and permeability distributions in reservoir rocks has inevitably led to theconclusion that geological environments may be recognized from log shapes in correlatable zones. The firstclues to the presence ofnearby reservoir boundaries orheterogeneitiesmay be derived rapidly and cheaply evenwhen very little physical sample material (cuttings orcores) is available from wells. However, as the multitude of examples in Figure 5.2-5 illustrates, care mustbe exercised because log shapes are much more characteristic than diagnostic. Log shapes also tend to be morepredictable and reliable in clastics than in carbonates.
Various logs are useful to calibrate geologic data.Spontaneous potential logs have long been used toinfer not only the presence, but the depositional environment ofsand bodies and thereby provide an indirectestimate ofareal extent. The gamma ray log will in mostcases reflect lithology better than the spontaneouspotential log, particularly where high hydrocarbon saturation exists. Acoustic logs can give clues to the presenceof unconformities and faulting and may be an earlywaming that more than one reservoir unit is present.Resistivity logs are often helpful in qualitatively assessing vertical grain size variations. The recent introductionof formation imaging technology, which presentseither an acoustic or an electrical image of the rock
=
•
ESTIMATION OF VOLUMES OF HYDROCARBONS IN PLACE
GENETIC SAND UNITS
Transgressionon
Unconformity
~II~
Cut and Onlapi
DistributaryChannel Fill
Cut and Fill
Alluvial-DeltaicPoint Bar
AlluvialPoint Bar
Offlap Fill·lnI i
Delta-Marine BarrierFringe Bar
[ CC L[ ~ \Slightly Smooth Smooth Slightly Smooth Serrate SerrateSerrate Bell Cylinder Serrate Cylinder Funnel Funnel
Bell Bell
Thick 20-150ft. 10-150ft. 10 - 300ft. 10-100ft. 20-75ft.
Form Linear; m~ Linear Linear Blanket Linearbe very wi e
Trend Parallelto Parallel to Parallel to Paralleltodepositional depositional deroSitiona, slope, shorelineslope slope bu variable
AMPLIFIED SAND UNITS
Thinand
Resistive
5-20ft.
Blanket
Cut and Fill Offlap Fill-In Fill-Ini
Barrier BarBuildup
Point Bar BuildupAlluvial Plain or
Valley
(Delta-Marine
FringeBuildup
~ c:Submarine Canyon
BUildupBuildup of
Graded Beds
Smooth BellSlightly Serrate
Bell
Thick 5 M 1000 ft.
Form Linear toblanket
Trend Parallel todepositlonalslope
MultipleSerrateFunnel
50 - 300 ft.
Blanket
MultipleSmoothFunnel
50-tOOOft.
Linear, butmaybe verywide
Parallel toshoreline
Smooth CylinderSlightly Serrate
Cylinder
50 - 500 ft.
Fan
Normaltoshoreline; normalorparallel toaxisofbasin
Smooth CylinderSlightly Serrate
Cylinder
30 - 300 ft.
Linearto blanket
Parallelto axisofbasin
HYBRID SAND UNITSSystematic
IProgradation of Alluvial
Over Delta-Marine FringeSerrate Trahsgression
Over Della
Serrate FunnelWithThin
Resistive Streak
Blanket
Smooth BellOnSerrateFunnel
BlanketSource: After Shell Development Company, 1970.
Figure 5.2-5 Sand Unit Shape Diagram
51
3
surrounding the borehole, shows great promise inassisting both the geologist and the reservoir analyst.Image data is particularly helpful in defining the arealextent of the pay zone before pressure transient databecomes available. In summary, the patient analyst hasmany tools available in the search for clues to the character of reservoir heterogeneity. Every avenue must beexplored at this early stage to reduce the uncertaintyregarding the most critical parameter in the volumetricequation: drainage area.
Tool Resolution
Many types of logging tools are utilized in thedetermination of reservoir parameters and net pay. Thevertical resolution of each tool is dependent upon therequirements ofthe particular measurement. The deepermeasuring tools, designed to overcome or minimize theeffect of the flushed zone, are limited in their verticalresolution. Conversely, tools that are designed forshallow measurements often have superior vertical resolution. Knowledge of the limitations and differences
52
DETERMINATION OFOIL AND GAS RESERVES
between the various tools and how these differencesrelate to geological variations will result in the analystbeing better able to understand and evaluate thereservoir.
References
Amaefule, J.O., Kersey, D.G., Marschall, D.M.,Powell, J.D., Valencia, L.E., and Keelan, D.K.1988. "Reservoir Description: A PracticalSynergistic Engineering and GeologicalApproach Based on Analysis of Core Data."Paper presented at SPE, Houston, TX, Oct. 1988,SPE 18167.
Computalog Gearhart Ltd. 1990. "The SelectiveFormation Tester." Calgary, AB.
Schlumberger of Canada. 1985. Open Hole LogInterpretation. Course notes, Calgary, AB.
Shell Development Company. 1970. ReservoirGeology ofSand Bodies. Houston, TX.
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
5.3.2 Permeability from CoreAll laboratory methods for determining permeability relyon a measurement or an interpretation of a flow rate
5.3 PERMEABILITY
5.3.1 IntroductionPermeability does not appear in the volumetricequation, but it is difficult to have any meaningful discussion about the concept of volumetrics withoutaddressing this key attribute of all commercial hydrocarbon reservoirs. Permeability is a measure of howeasily a single fluid (gas or liquid) will flow through theconnected pore spaces when a pressure gradient is applied. The permeability, k, of a reservoir rock is relatedto the volumetric flow rate, Q, through the rock by meansof'D'Arcy's Law:
where Q = volumetric flow rate (mLls)k = air permeability (mO)11 = fluid viscosity (cp)A = cross-sectional area (cm-)t>P = pressure differential (atmospheres/em)t>L = unit length (em)
This permeability is more properly termed specific (orabsolute) permeability: the permeability of a reservoirto a fluid when the fluid fills 100 percent of the porespace.
Specific permeability is not usually directly applicableto petroleum reservoirs. Essentially all reservoirs,whether they produce oil or gas, contain at least twocomponents: hydrocarbon and water. Calculationsrelating to reservoir conditions require effective permeability: the permeability to the fluid of interest atthe conditions of interest. Effective permeability mayreplace specific permeability in Equation (I) when theconditions are specified under which the permeabilityapplies. The main "condition" in this regard is the fluidsaturation. For this reason, there is yet another permeability measure termed relative permeability: theeffective permeability at the fluid saturation of interestdivided by the specific permeability. Relative permeability is mainly a function of fluid saturation, but alsodepends to varying degrees on other parameters suchas saturation history, temperature, pore pressure,overburden pressure, and interfacial tension. Permeability is interpreted from well test data or logs, or is directlymeasured on core samples in the laboratory.
•
k LlPQ=-A-
11 LlL(I)
through, and a pressure drop across, a sample ofknownlength and cross-sectional area, for a fluid of knownviscosity. This data is then analyzed by means of0'Arcy's Law. In theory, the nature of the fluid shouldnot be important; however, in practice, the nature ofthefluid is very important if the rock and fluid interact.
The measurement methods for permeability (AmericanPetroleum Institute, 1952), which are currently underreview, may be divided into classes based on the sampletype (plug or full diameter core), the fluid used (gas orliquid), and the technique (steady or unsteady state conditions). The sample type controls the amount andquality of information that can be obtained. For a plug,only a unidirectional permeability can be measured,while for a full diameter sample, the vertical permeability plus the permeability in any horizontal direction canbe determined. Although gas permeabilities are thesimplest ones to obtain, they suffer from two majorlaboratory problems that are only occasionally encountered in the field: slippage flow (Klinkenberg effect)and inertial (Forcheimer) effects. These problems, although theoretically possible, are rarely observed whenliquid permeabilities are being measured. Steady andunsteady state techniques may be used for both types ofsamples and both types of fluids.
The gas permeability ofwhole core samples is typicallydetermined and reported in three directions: one vertical and two horizontal. The two horizontal directionsare at 90° to each other, but otherwise are not usuallyoriented in any particular direction. However, ifthe corewas oriented when it was originally cut, the horizontalpermeabilities can be related to actual directions in thereservoir.
Liquid permeability may be measured using theprinciples ofgas permeability, but the fluid used is brineor oil instead of gas. Except for possible fluid-rockinteractions, unsteady state liquid permeability measurements on plugs do not encounter any major problemsthat would affect reservoir applications.
Test procedures are available to evaluate fluid-rockinteractions. These tests involve measuring the permeability of a rock as a function of time (investigation ofclay swelling) or as a function of flow rate (investigation of"fines" migration). The degree to which the clays,(most commonly smectite) in a sample have adsorbedwater can significantly change the size of pore throats,and hence the value of permeability. Even when claysdo not swell, they may contribute to fines migration.Mineral debris may become detached from the porewalls and entrained in the moving fluids above a
53
certain critical velocity. These particles are then carriedalong with the flow until they come to pore throatsthrough which they cannot pass. The particles lodge inthe pore throats, accumulate, block the throats, andthereby decrease the permeability.
Fines migration and clay swelling behaviours areencountered during liquid permeability testing. In gaspermeability tests, neither phenomenon is normallyobserved. However, if clays have been dehydrated during the cleaning ofhydrocarbons from the pore system,significant changes in gas permeability may result asthe test progresses.
The advantages of the steady-state plug liquidpermeameter (the apparatus used for permeabilitymeasurement) are that the data interpretation is straightforward and liquid permeabilities are more applicableto reservoir calculations than gas permeabilities. However, the apparatus is complicated and relativelyexpensive and, consequently, the procedure is moredifficult than in the case of the gas permeameter.Measurements of liquid permeabilities on whole-coresamples are less common because of even higher costs.
5.3.3 Relative PermeabilityMeasurement
Although the concept of relative permeability is verysimple, the measurement and interpretation of relativepermeability vs. saturation curves are not. There is evidence that relative permeability is a function of manymore parameters than fluid saturation. Temperature,flow velocity, saturation history, wettability changes andthe mechanical and chemical behaviour of the matrixmaterial may play roles in changing the functional dependence ofrelative permeability on saturation. The bestdefined of these secondary dependencies is the variation of relative permeability with saturation history;relative permeability curves show hysteresis betweendrainage processes (wetting phase decreasing) andimbibition processes (wetting phase increasing).
54
DETERMINATION OFOILANDGAS RESERVES
There are currently no industry standard methods fordetermining relative permeability, and much researchis ongoing, but there are two basic methods of obtaining relative permeability data: steady state and unsteadystate. For the steady state method and a two-fluid system, the two phases are injected at a certain volumetricratio until both the pressure drop across the core and thecomposition of the effluent stabilize. The saturations ofthe two fluids in the core are then determined. If thisexperiment is conducted at various volumetric flow ratios, a relative permeability vs. saturation curve may bederived. This method of testing is generally too timeconsuming and expensive. to be practical for manycommercial reservoir engineering purposes.
The unsteady state method is based on interpreting animmiscible displacement process. For a two-phase system, a core either in the native state (preserved) orrestored to the saturation conditions that exist in the reservoir is flooded with one of the phases. Typically theflood phase is water or gas since in the reservoir one orthe other ofthese phases usually displaces oil. The floodprocess to obtain relative permeability data is interpretedby means of a theoretical model or else by computersimulation.
It is sometimes claimed that the steady state andunsteady state methods yield the same values of relative permeabilities. Although undoubtedly true undersome circumstances, this statement is not generally true.For most cases, relative permeability is known to be afunction of saturation history. Because the history ofthe core is completely different in the two cases, it isreasonable to expect a difference in the resultant relative permeabilities. The unsteady state test would seemto be the more physically realistic in the context of theusual reservoir processes, because all such processesinvolve one phase displacing another.
ReferencesAmerican Petroleum Institute. 1952. "Recommended
Practice for Determining Permeability of PorousMedia." API RP 27 (3rd ed.), Dallas, TX.
--
•
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
Figure 5.4-1 Porosity of Cubic-Packed Spheres
Even though porosity is independent of the size of thespheres, the porosity of a uniform sphere system canvary from over 25 percent to nearly 48 percent depending upon the packing geometry. Ifpart ofthe pore spaceof the model is filled with mineral particles of smallersize than the spheres, porosity is decreased. The porosity continues to decline as ever smaller particles are put
5.4 POROSITY
5.4.1 IntroductionPorosity is the fraction ofthe reservoir bulk volume thatis filled with fluid or nonmineral matter-in other words,the "storage capacity" of the rock.
While various methods for determining porosity by coreand log analysis are described in Section 5.2.2, an understanding ofthe many ways pores may be distributedin reservoir rocks is necessary to fully appreciate theconcept of porosity. Figure 5A-I illustrateswhat is called"cubic packing" of spheres and is one example of thepacking of spherical sand grains.
Porosity, .p =L' - (Lid)' (ltd'/6l 0.4764
L'(1)
into whatever places they will fit and as the constituentspheres become irregular or nonrounded. The porosityofrocks, therefore, decreases as the variation in particlesize and shape increases. The porosity of competentrocks is also reduced as the amount ofcementing material in the matrix increases, since the cementing materialtends to bridge the contacting surfaces of mineralparticles and line the pore surfaces.
In addition to "primary" porosity created by the intergranular spaces in most clastic rocks and some uniformlydeposited carbonates such as oolites, "secondary"porosity can result from vugs and fractures that are generally created after deposition. Vugs are those porespaces that are larger than would be expected from thenormal fitting together of the grains that compose therock framework. They may originate in many ways,and the type of vug implies some features of its geometry and interconnection. Vugs may vary from tubes orplanes that traverse the matrix to vesicles isolated fromeach other. Fractures and fracture porosity result fromearth movements that create joints and faults throughwhich fluids may move. Although fractures mayonly contribute up to I or 2 percent porosity to a reservoir, they will have a significant effect on reservoirpermeability.
Hydrocarbons have been produced commercially fromrocks with porosities as high as 50 percent. Fracturedcarbonates, such as those in the Foothills belt of western Canada, are prolific, although matrix porosity maybe as low as 1.5percent. Some nonproductive rocks alsohave high porosities. Clays and shales and certain chalkycarbonates may have fractional fluid volumes ormicroporosity greater than 40 percent; yet these rocksare seldom productive. Porosity, therefore, cannot beconsidered the sole criterion for the determination ofreservoir productivity.
5.4.2 Sources and Acquisition of Data
Core Analysis
Core analysis has been called the cornerstone uponwhich formation evaluation rests, as it provides the onlydirectly quantifiable measurement of fundamentalreservoir parameters. Measurements are made on fulldiameter and plug samples obtained from conventionalcoring devices, and on plug samples obtained by rotaryor conventional sidewall coring tools.
The appropriate procedures are described in theRecommended Practice for Core Analysis Procedure(American Petroleum Institute, 1960). An overview ofthe most commonly used methods follows.
55
m _
Porosity measurements are made after a sample has beenselected and cut to form a right cylinder, and the hydrocarbons have been removed. The method of cleaningand subsequent drying can have an effect on the measurements. Samples are normally cleaned in a vapourphase unit or in a Dean Stark apparatus using tolueneas a solvent. For tight, competent samples, a pressurecore cleaner may be used. The samples are then dried inan oven to remove the residual toluene. If the samplescontain significant amounts ofclays, the samples shouldbe humidity (45 percent) dried or dried in a low temperature oven to minimize dehydration. Excessivedehydration results in porosity values that are too high.
A group of properties, including pore volume,porosity, bulk volume, bulk density, grain volume, andgrain density, are generally determined in the laboratory by means of a single test procedure. Typically, thesteps in this procedure are as follows:
DETERMINATION OF OIL AND GASRESERVES
I. Clean liquids from the rock samples.
2. Measure the mass of each cleaned sample (drymass).
3. Determine the volume of each sample (bulkvolume).
4. Measure the volume of the open space in eachsample (pore volume) or the volume of the solid ineach sample (grain volume).
The remaining properties may be calculated from themeasured values of dry mass and any two of the threevolumes (bulk, pore or grain).
Methods for determining porosity are oftwo basic types:those that yield porosity directly, and those that yieldvalues for grain volume, pore volume or bulk volumeindependently. Several analytical methods may be employed in the laboratory, as shown in Table 5.4-1. Thefollowing are the most commonly recommended ofthesemethods:
Table 5.4-' Comparison of Techniques of Determining Porosity
Measured Method Calculated Accuracy Need for Need Sample Sensitivity SensitivityProperty Precision Measurement of for Size to Surface to
Noneffective Cleaning Vugs CalibrationPore Space
Porosity Summation Poor Fair No No Moderate No Highof Fluids ±O.69% ±1.0%
Direct Good Good - Yes Any - Low
Grain ±O.OI cc ±O.OI cc
Volume Gas Good Good - Yes Any - HighExpansion ±O.02 cc ±O.02 cc
Steeping Good Good No Yes Any Yes Low
Pore ±O.OI4 cc ±O.05 cc
Volume Gas Good Good No Yes Any No HighExpansion ±O.OI7 cc ±O.05 cc
Steeping Good Good - Yes Any Yes Low±O.014 cc ±O.05 cc
Mercury Good Good - Yes Any Yes LowBulk Archimedes ±O.OI4 cc ±O.05 ccVolume Bulk
Volume
Caliper Good Fair - No Any No Low±O.015 cc ±O.OI5 cc
Source: Geotechnical Resources Ltd., 1991.
56
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
Gas Expansion Method. This is used for determininggrain volume; it is also known as helium porosimetryand the Boyle's Law method.
Mercury Archimedes Method. This method, used todetermine bulk volumes, is based on the fact that anonwetting fluid will not spontaneously invade a sample.
Caliper Method. This method is used to determine bulkvolume by measuring the length and diameter of a rightcylinder sample.
Summation-of-Fluids Method. This method is usedfor quick determination of the porosity of uncleanedsa~ples.
Log Analysis
Porosity is also obtained from a variety of downholemeasuring devices where tool response is a function ofthe formation porosity, the fluid in the pore space, andthe matrix properties. When the fluid and matrix endpoints are known or can be determined accurately, toolresponse can often be reliably related to porosity.
All three logging devices (acoustic, density, neutron)respond to the characteristics of the reservoir immediately adjacent to the borehole. The depth ofinvestigationis shallow (only a few inches on average) and usuallycompletely within the flushed zone created by invasionof drilling mud filtrate from the wellbore.
At present, the density log is the primary porosity logfor most reservoir engineering applications. In operation, a radioactive source applied to the borehole wallemits medium energy gamma rays into the rock. As thesegamma rays collide with the electrons in the formation,they lose energy, but continue to travel and are countedas an indication of formation density. Density tool response depends on the electron density which, in tum,depends on the density of the rock matrix, the formation porosity and the density, of the fluids filling thepores. For a clean formation of known matrix density,formation bulk density, Ph' is given by Equation (2):
$
where Ph = formation bulk density (g/cm")Pr = fluid density (g/cm")<I> = porosity (fraction)Pma= matrix density (g/cm")
Porosity, <1>, is therefore given by Equation (3):
<I> = Pm, - PbPm, - P,
(2)
(3)
Except in the presence of gas, the difference betweenapparent density, Pa, read by the tool and true bulkdensity, Ph' is trivial.
Acoustic logging tools employ one or more transmittersthat emit a sound pulse and receivers that record thepulse as it passes them. The acoustic log represents arecording ofthe time required for a compressional waveto traverse one metre offormation. This interval transittime is the reciprocal of the velocity of the wave.Interval transit time, <it, is dependent on lithology andporosity, <1>, as illustrated by Equation (4):
(4)
where <it = interval transit time (us/m)<itma = transit time in the matrix (us/rn)<itr = transit time in the fluid (us/m)
Neutron logs respond primarily to the amount ofhydrogen in the formation. In clean formations withpores filled by water or oil, the neutron log indicatesthe amount of liquid-filled porosity present. Rock hasessentially negligible hydrogen content and thereforedoes not contribute to the porosity response.
In the operation of the neutron log, high-energy fastneutrons are emitted continuously from a radioactivesource in the sonde or tool. These neutrons collide withformation nuclei in a billiard ball fashion and at eachcollision lose some energy. Within a few microseconds,the neutrons have been slowed down from initial energies of several million electron volts (eV) to thermalvelocities around 2.5 eV and proceed to diffuse randomly until captured by the nuclei of atoms such aschlorine, hydrogen or silicon.
The capturing nucleus then becomes intensely excited,emitting a high energy gamma ray ofcapture. Depending on the type oftool, either the capture gamma rays orthe neutrons themselves are counted by a detector inthe sonde. The counting rate at the detector is inverselyproportional to the hydrogen concentration. Therefore,low count rates infer high porosity and vice versa, andthis relationship will generally hold true except wheregas is present in the region of investigation of the tool.
Industry Databases
Except in rank wildcat environments, the reservoiranalyst should be aware that an important source ofreliable data exists in those wells that have already beenlogged or cored in the vicinity ofthe study well or area.Many governments, as part of the management of
57
nonrenewable resources, require that data recoveredduring the drilling and completion of a well be submitted to the managing agency. In Alberta, for example, allactivity is reported to the Energy Resources Conservation Board (ERCB), which maintains a core and cuttingsstorage and examination facility as well as copies ofalldata derived from the wells (logs, core analyses, specialcore analyses, well tests, and production histories). TheERCB also maintains a comprehensive database composed of all key reserves criteria for the oil and gas poolsin the province.
5.4.3 Analysis of Data
Statistical Techniques for Core Data
Porosity values for each sampled interval, along withrelated permeability and fluid saturation data are tabulated in a core analysis report (Figure 5.4-2).
Typically, the reservoir analyst will group core datameasurements into beds or layers that closely approximate the stratification evident on the open-hole logs.The interpretation ofthis data is aided by cross-plots ofhorizontal permeability vs. porosity (Figure 5.4-3). Bycomparing core porosities to individual log response,the reservoir analyst can more accurately calibrate theopen hole logs over the uncored portion of the intervalof interest.
Great care must be exercised in the use of core porositydata because many factors can affect the representativeness of this data. In reviewing core analysis reports, thereservoir analyst should ensure that a summary sheetdescribing all core retrieval and analysis procedures isincluded (Figure 5.4-4). this information provides thebest basis for assessing the quality of core data.
Porosity from Logs
Anyone or, more frequently, a combination ofall threeconventional porosity devices are typically run when awell has reached total depth or when a protective intermediate casing string is to be set prior to drilling deeper.
The science and art of interpreting these logs forporosity and fluid saturation is embodied in the termpetrophysics. Petrophysics seeks to express the physical and chemical properties of rocks as they pertain tothe evaluation ofhydrocarbon-bearing layers. Each loghas its own unique application.
Figure 5.4-5 illustrates the method used for computingporosity from a density log for a clean formationof known matrix density, Pm.' containing a fluidofaverage density, Pr. The lithology dependence ofthistool is evident in the fact that a log reading of
58
DETERMINAnON OF OIL AND GASRESERVES
2.54 g/cm'' produces porosity values ranging from6.6 percent for sandstone to 17.5 percent for a dolomitematrix.
Because sound travels more slowly in a fluid-filled porethan in solid rock, for each rock type a unique relationship exists that relates the measured transit time toporosity. The industry has adopted the Wylie TimeAverage Equation as the standard for computing porosity from acoustic logs in clean consolidated formationswith uniformly distributed small pores. Figure 5.4-6demonstrates this porosity vs, transit time relationship.For example, a value of216.5 us/m (66 ils/ft) producesthree different values for porosity depending on thenature of the matrix mineral.
Neutron log porosity readings are computed andrecorded directly on the log. These logs record porosityin linear units for a particular lithology. An internal program automatically provides corrections for the varyingeffects of mud weight, salinity, temperature and holesize variations. Once the appropriate lithology has beendetermined, porosity can be read directly from theservice company chart as illustrated in Figure 5.4-7.
Cross-plotting techniques have evolved because use ofa single tool to determine porosity is valid only wherethe lithology is known to consist of a single mineralthat is clean and water-filled. In nature, very complexmineral assemblages are the norm. Here, even the nature ofthe pore structure itselfcan affect tool response.Under these circumstances, data from two or moreporosity devices is needed to resolve the response todiffering matrix minerals to the presence ofgas or lightoils, and to the pore geometry. By far the most universally accepted and utilized ofthese is the neutron-densitycross-plot.
Today it is almost standard practice to run the neutronand density logs in tandem or combination and presentporosity from both logs on a compatible porosity scale.This overlay presentation provides the experiencedpetrophysical analyst with an additional qualitative interpretation of the nature of the porosity and the hostlithology and can aid in the detection of gas-bearingzones in the wellbore.
In Figure 5.4-8, a reading of 21 percent limestoneporosity from the neutron log is cross-plotted against a15 percent limestone porosity from the density log, defining a point, P, lying between the limestone anddolomite curves. If the lithology is known to be a mixture ofthese two minerals, it is appropriate to proportionthe distance on a line connecting equal porosity valueson both curves and assume that it represents the
-
=
"TI m<0' CORE ANALYSIS REPORT
en--<<:~~
'" »'" Sample Depth Thick- Sample Sample Permeability Porosity Saturation Grain Remarks* --<:.,.
Number Depth Length kmax k". k"". Oil H,O Density 5, ness z'" (m) (m) (m) (m) (mD) (mD) (mD) (%) (%) (%) (kg/m' ) 0
"T1
--i <-c BELLY RIVER FORMAnON 0"C r-(j' CORE # I 1023.00 m - 1041.00 m RECOVERY/CUT: 17.85 m/ 18.00 m cs:Ol
1023.00-1025.41 2.41 sh menoI 1025.41-1025.60 0.19 1025.43 0.13 82.94 78.49 8.59 20.8 12.6 11.9 2683 FD 00 "T1
~
'" 2 1025.60-1025.80 0.20 1025.67 0.12 9.53 8.57 1.89 13.3 10.4 35.8 2668 FD :I:-<» 3 1025.80-1026.42 0.62 1026.14 0.13 5.12 4.82 3.16 18.0 14.2 35.4 2675 FD 0
=:J :0Ol 4 1026.42-1027.32 0.90 1026.60 0.14 0.12 0.11 <0.01 10.6 TR 68.4 2677 FD 0-< n»IJ) :0IJ) OJ
::3J 0
'"Z
"C en0 Z~ -e.... r-»
10 1029.38-1029.63 0.25 1029.52 0.13 57.52 56.57 45.97 19.7 11.6 31.4 2643 FD ()m
11 1029.63-1030.07 0.44 1029.71 0.14 88.48 84.96 64 .29 19.9 8.4 24.8 2640 FD12 1030.07-1030.47 0.40 1030.12 0.13 24.47 23.38 17.80 23.4 9.3 25.2 2646 FD13 1030.47-1030.75 0.28 1030.55 0.12 25.68 25.23 7.63 19.4 11.9 35.0 2647 FD14 1030.75-1031.18 0.43 1030.80 0.15 84.63 74.86 3.04 16.3 8.2 39.6 2650 FD
1031.18-1031.39 01031.39-1031. 7103 1.73~1032.001032.00-1032.28Hl32.28-1032.60
20 1032.60-1032.81 0.21 1032.67 0.12 12.50 12.16 3.78 19.6 13.9 33.0 2661 FD21 1032.81-1033.64 0.83 1033.21 0.14 0.38 0.32 0.Q3 18.1 TR 20.3 2682 FD22 1033.64-1034.66 1.02 1034.32 0.15 0.55 0.53 0.22 18.4 TR 30.9 2682 FD
1034.66-1035.61 0.95 calc ss23 1035.61-1035.80 0.19 1035. 66 0.09 3.44 3.38 1.30 20.2 TR 46.6 2668 FD
calc ssMISSING
v.-c
Source: PanCanadian Petroleum Ltd., PCP Ferrybank 6-23-43-28W4. Date: Nov. 17, 1987, File: 87-GC-422.* FD = full diameter, P = plugged sample, sh ~ shale, calc ss ~ calcareous sandstone.
** Plug permeability-sample not suitable for full diameter measurement.
DETERMINATION OF OIL ANDGASRESERVES
~/
//
/
I- ...+,.//
i= ......+~~ + /
I- +;1" +'"/ +
t / T
/ .../ ...I- / ...+I- /
/ ...~
//
~/
/
I- //
/ .../
~/
//
I- // , ,
Equation: log (kh) = -2.7496 + 0.2128 <il
Correlation Coefficient: 0.5998Formation: Belly RiverDepth: 1025.41 m to 1037.12 m
1000
100~c.§.>-
=:a 10.,'"E~
'"a.iii~c0N.;:0J: .1
.01o 6 12 18
Porosity (%j
Source: PanCanadian Petroleum Ltd., PCPFerrybank 6-23-43-28W4.
Figure 5.4-3 Porosity vs. Horizontal Permeability
24 30
Core Intervals Recovery/Cut Formation No. of Boxes1023.00-1041.00 m 17.85/18.00 m BellyRiver 16
Coringequipment DiamondCoringdiameter 101 mmCore fluid Water-base mud
CLEANINGSolvent TolueneExtraction equipment Vapour phaseExtraction time 22 daysDryingequipment Convection ovenDrying time 24 hoursDryingtemperature 150'C
ANALYSISPore volume measured by Boyle's Lawheliumporosimeter
Grainvolume measured by Boyle's LawheliumporosimeterBulk volume measured by Mercury/caliper
Fluid saturation measured by Retort
Source: PanCanadian Petroleum Ltd., PCPFerrybank 6-23-43-28W4.
Notes: Plugsare I inchdiameterunlessotherwise noted.
Figure 5.4-4 Core Analysis Report: Analytical Summary Sheet
60
1.92.1
3Pm. =2.65 g/cm
3P, =1.0g/cm
3Limestone Pma = 2.71 g/cm
Sandstone
2.5 2.3Bulk Density, Pb (g/cm3
)
2.7
17.5%
O+-L---'C-.L--'--,-- .- -,- --,2.9
$ = Pm.' P.Pm.' P,
10.0%10 ~-----------
40
30
~ Dolomite~-e-.i- 20'wee
Figure 5.4-5 Porosity from Formation Density Log
$=
Sandstone Alma = 182 us/rn
I>t, =161511s/m
15.4%~----------------------
Dolomite .6.tma= 143 }.ts/m ---,,r/
Limestone ./ltma = 156 jls/m
7.7%
~-------------------- -13.0%
50
40
10
rf 30.".
;6.~
~ 20
400200 300IntervalTransitTime, I>t (lls/m)
O.J----L~-..L-_,_~-----~------~100
Figure 5.4-6 Porosity from Sonic Log
61
*------------------------
DETERMINATION OF OIL AND GAS RESERVES
40
30
10
12.6%-----------------------10.0%
Sandstone
Dolomite
O+-----'~:::..---_+---_r---___,----
o 10 20 30
Neutron Index(Apparent Limestone Porosity)40
Figure 5.4-7 Neutron Porosity Equivalence Curves
-20+----,---,-----;r-----,---;o 10 20
<I> CNL (Limestone) (%)
CNL = compensated neutron log
Figure 5.4-8 Porosity and LithologyDetermination fromNeutron-Density Log
40
25
30
30
10
5 '" Dolomite
25Sandstone~
20
Limestone
f~AnhYdrite
o
-10
30
40
~ 20C
"<::o00 10Q)
E2-.... 0
volumetric proportion of the two minerals. Therefore,the interval represented at P would be composed of40percent dolomite and 60 percent limestone and have aporosity of 18 percent.
While knowledge of the matrix constituents is alwaysimportant, an error in choosing or assuming the matrixpair does not have a great impact on the porosity determined except in very low porosity carbonates. Thisfeature ofthe neutron-density cross-plot, combined withits inherent gas identification properties, makes it themost popular technique.
Correlation of Log and Core Porosity
Many reservoir analysts prefer to use core analyses inreservoir studies, particularly where equity determination is a key issue. While computer-processed suites oflog data may represent the only continuous source ofcomputed reservoir parameters, it has long been recognized that log-derived values are not absolute numbers.In core-log matching exercises, the objective is to standardize the output results in such a way that differencesin results from well to well represent relative changesin reservoir quality. Therefore, it is common practice to use the core data as the reference point andfit log analysis data to it. A paper by Hamilton andStewart (1983) outlines a step-by-step procedure forconducting this type of analysis.
62
r+
ESTIMATIONOFVOLUMES OFHYDROCARBONS INPLACE
5.4.4 Factors Affecting Data Quality
Preservation of In Situ Conditions
The quality ofthe results obtained from core analysis isdirectly related to the quality ofthe core when it reachesthe laboratory. Therefore, in cutting and retrieving thecore, precautions must be taken to preserve, as much aspossible, the conditions that exist downhole in the reservoir. The cutting and retrieval ofcore to surface resultsin the removal ofoverburden pressure, the introductionofdril1ingfines, and some modification ofthe clays, al1ofwhich can affect porosity measurements.
Shale Content
The most important problem that has eluded solutionsince it was recognized by early logging over 50 yearsago is that of shaly sands.
The presence of shale or clay minerals in the intersticesofsedimentary rocks affects log analysis by moving theresistivity of the porous and permeable zones towardthe normal shale resistivity on the log. Shales also impact porosity measuring devices. With densities between2.4 and 2.7 g/cm-, shales can show up on density logsas having nil to moderate porosity. On acoustic and neutron logs, shales may appear to have moderate to highporosity. In extreme cases the effects on resistivity andporosity logs can cancel out in the computation of water saturation. However, ifthey do not cancel, the analystmay misinterpret or overlook prospective pay zones. Theamount ofshale must therefore be determined to permitits contribution to be subtracted from the measuredparameters.
The impact of clays on the results of core analysis isequal1y difficult to resolve. The main obstacle encountered is in distinguishing pore water from nonliquid claymineral water. In addition to retaining the clay latticewater, the core analyst must be careful to preserve thelast few molecular layers of adsorbed water on the clayminerals.
Figure 5.4-9 illustrates the complexity that the presenceof clay minerals can introduce to the process ofporosity determination from either cores or logs.
Rock Compressibility
In the assessment of data quality and reliability, itmust be remembered that most laboratory porositydeterminations are based on information obtained at surface conditions. Rocks are elastic media and can becompressed and decompressed when subjected to thestress and release of overburden pressure. Mineralelasticity, grain movement and, final1y, grain failure al1
contribute to reductions of porosity with increasingdepth.
There is strong evidence of a continuous reduction inporosity with increasing pressure differential appliedbetween the interior and exterior of a sample. The analyst should be aware that in situ porosity will be lowerthan that measured under atmospheric conditions in thelaboratory. Pore volume compressibility tests may beconducted to determine the appropriate reductionfactor for the reservoir under study, and this type ofmeasurement is now virtual1y routine.
Reservoir Heterogeneity
The results of sampling with wireline logging tools orcore samples can be misrepresentative of the reservoir.The actual volume of reservoir sampled even with welllogs is insignificant in comparison to the unsampledreservoir volume and is never statistical1y random.Certain geologic environments such as marine sands canbe predictable over distances in the order ofkilometres,while carbonate reservoirs may vary significantly overdistances in the order ofcentimetres. The effects ofreservoir heterogeneity on the quality ofthe data being usedto characterize the reservoir can be minimized only bycareful geological investigation.
With respect to reservoir heterogeneity, three maincriteria should be considered: sample homogeneity, thepresence of fractures, and sample size. As a basic ruleof thumb, the larger the sample, the better it will represent the range of microscopic variations in the rock.Most reservoir rocks, even those that visually appear tobe homogeneous, exhibit variations in permeability overrelatively smal1 distances. In highly fractured reservoirs,there are real1y two permeabilities of interest: matrixand fracture permeability. To determine the matrix component in such reservoirs, plug samples are used becauseal1 fractures must be excluded from the samples. In thiscase, the general rule "the bigger the sample, the betterthe sample" does not apply. Fracture permeability shouldbe measured on whole core samples. To get representative values, however, the samples should be restressedto overburden conditions. The procedures utilizedfor fractured reservoirs are also applicable to vuggycarbonate reservoirs.
Measurement Precision and Tool Resolution
Anyone who has ever attempted to use wel1 logs andcore analysis data to accurately characterize a reservoirknows that even with the wide range of tools availableone rarely gets the same answer from each tool.
63
DETERMINATION OFOILANDGAS RESERVES
Petrophysical Qualities
(After Overburden Correction)
Log Measurements
---VC1ay 'I' <I> Effective
<I> Total •
I <I> Free Fluid•
ClayBound,
Free Water,Dry : Clay WaterClay : Water,,
~~<I>cor. •
f--- <I> NML
<I> Density
1----------- <t> Neutron
VClay = volumeofclayNML = nuclear magnetic log
Source: Schlumberger, 1988.
<t> Sonic
Figure 5.4-9 Impact of Clay on Log and Core Measurements
The sources of errors in logs and core analyses are bothrandom and systematic and are introduced by theimplicit limitations imposed on the measuring deviceby design considerations. Statistical variation in radioactivity measurements is an example ofa random error;improper or degrading calibration in a logging toolor pressure recorder is an example of a systematic orconstant error.
By far the most serious source oferror is introduced bythe unavoidable complexity ofthe reservoir rock. Whatis referred to here is any closely spaced variation in petrophysical parameters. When petroleum engineers areconfronted with thinly bedded strata, they must be evenmore aware of the vertical resolution limitations of themeasuring device.
64
ReferencesAmerican Petroleum Institute. 1960. "Recommended
Practice for Core Analysis Procedure." API RP40, Dallas, TX.
Geotechnical Resources Ltd. 1991. "Porosity." In TheScience and Technology of Core Analysis (2nded.). Course notes, Calgary, AB.
Hamilton, J.M., and Stewart, J.M. 1983. "Thin BedResolution and Other Problems in Matching Logand Core Data." SPWLA 24th Annual LoggingSymposium, Calgary, AB.
Schlumberger. 1988. "Measuring Porosity, Saturationand Permeability from Cores: An Appreciation ofthe Difficulties." The Technical Review," Vol. 36,No.4, Oct. 1988.
"Material from The Technical Review is printedwith thepermission of The Oilfield Review.
7
ESTIMATION OF VOLUMES OF HYDROCARBONS INPLACE
5.5 HYDROCARBON SATURATION
5.5.1 IntroductionThe saturation ofa given fluid is defined as the fractionof the pore volume occupied by that fluid. This definition, while simple, provides no insight as to how orwhere the fluids are held within the porous network ofthe rock; it merely states that some fraction of the porenetwork contains the given fluid.
5.5.2 Saturation Determination FromCore
The saturations of hydrocarbons (both liquid andgaseous) and water in petroleum reservoirs are two ofthe most important properties of interest to the reservoir analyst. However, because these fluids are generallymobile, they are not always recovered during conventional coring operations. Therefore, by the time the coreis analyzed in the laboratory, the fluid saturations donot necessarily represent those that exist in the reservoir. For this reason, fluid saturations measured by coreanalysis are generally treated as qualitative numbersrather than precise values. With proper precautions, suchas drilling with lease crude and using pressurized orsponge coring techniques, saturation measurements maybe made more accurately. However, these techniquesadd considerable expense to the core retrieval. It shouldbe noted that the inaccuracy ofthe measurements is notdue to the laboratory techniques, but to the difficulty inobtaining proper samples.
For accurate estimates ofsaturations in a reservoir, bothcore and geophysical well log data must be used; furthermore, the log data must be interpreted accurately.This means that calibration constants for electrical properties should be measured on core samples. When propercare is taken, reliable saturation values can be obtainedfrom logs.
More accurate saturation data may be obtained byusing sponge core or oil-base core techniques. With thesponge core technique, core is recovered by means ofan aluminum inner core barrel that has a sponge lining.Fluids escaping from the core are absorbed by thesponge. Samples are cut from the core and analyzed forfluid content using the Dean Stark technique. In thisprocess the sample is weighed and placed in the DeanStark apparatus, and the extraction solvent is boiled andcondensed repeatedly. The water-solvent vapour mixture rises and condenses, with the water collecting in agraduated collection tube. Solvent cleans oil out of thesample. The volume of water is measured directly and
the mass ofoil originally in the sample is calculated bydifference.
The sponge corresponding to each sample is similarlyanalyzed in order to obtain the total fluid content of thecore.
Oil-Base Coring for Connate Water Saturation
With oil-base core, the core is drilled with lease crudeor an appropriately designed fluid as a lubricant. Thecrude will only displace oil and, therefore, it is possibleto accurately determine connate water saturations. Therecovered core is kept immersed in this fluid until it isready for analysis in the laboratory.
The recovery of an oil-base core and the successfulmeasurement of an average connate water saturation,Swo' requires balancing the need for accurate water saturation data with the realities of conducting a potentiallyhazardous coring operation with minimal risk and reasonable expense. Careful consideration must be givento the selection of the proper coring fluid to preservethe native wettability in the core. (Wettability is definedin Section 5.5.5.)
To determine a reliable connate water saturation, theoptimum placement of the core location is, as far as isfeasible, above the local oil-water contact. Detailedknowledge ofreservoir pressure permits maximum overbalance reduction to minimize the stripping of connatewater during the coring process.
When all elements of the operation are carefullycontrolled, laboratory analysis (Dean Stark) on fulldiameter core samples for connate water saturation compares favourably with other methods such as single welltracer testing and open-hole log evaluation.
The economic attraction of such an operation is easilyappreciated, considering that reductions in recognizedwater saturation may approach or even exceed 50 percent and may result in increases ofas much as 20 percentin the perceived original oil in place. Changes of thismagnitude can impact not only estimated reserves, butalso field development plans and production throughincreased maximum rate limitations.
Saturation Measurement
Three general families of techniques are available forthe measurement ofsaturations in rocks: chemical, whichincludes retort and distillation methods; electrical, whichincludes both laboratory and geophysical log methods;and nonintrusive, which includes X-ray and nuclearmagnetic resonance. The chemical techniques are
65
b ....----------------------------
DETERMINATION OF Oil AND GASRESERVES
currently the universal choice for routine core analysisoperations, and electrical, for wellbore measurements.
The nonintrusive techniques are gaining acceptanceas on-line saturation methods for displacement andenhanced oil recovery studies, but are not generally usedto determine routine oil and water saturations and willnot be discussed further.
Chemical Methods
The procedure for determining fluid saturations by theretort method is based on taking two companion samples.One is weighed, thoroughly cleaned, and then itsporosity determined (porosity sample); the other iscrushed, placed in a retort oven, and heated for analysisof its oil and water contents. In the distillation method,the sample is placed in a Dean Stark apparatus with toluene. As the toluene is heated and condensed, fluids areremoved from the rock, and the water is captured andmeasured. Oil values are determined by calculation.
Generally, the sum ofthe water and oil saturations doesnot total one, but is a fraction of the porosity because agas saturation has developed with the depressuring ofthe core sample.
ljl = porosity (fraction)m = cementation exponentS; = water saturation (fraction)n = saturation exponent
As a consequence ofArchie's work, the exponents m=2and n=2, and the coefficient a= I are generally used information evaluation; "a" is a constant, also used inEquation (3). However actual values of "a," "rn,' and"n" can be determined in the laboratory for any specificreservoir,At this time, a recommended procedure does not existfor formation factor measurement. Although mostlaboratories use custom-built apparatus, all have thesame basic principles of operation.
The sample is capped with mandrels and placedinside a pressure containment cell fitted with electrically insulated end caps. The chamber is pressurizedand the sample is then saturated with brine.
Ifthe tests are to be performed at reservoir temperature,the pressure containment cell is placed in an oven. Theresistivity of the sample is measured and the formationfactor, F, is calculated using the following equation:
Electrical Methods
Because brine is electrically conducting, it seemsreasonable to expect the electrical conductivity, or itsinverse, the electrical resistivity, to vary with brine saturation. This expectation is the basis of the electricalmethod of saturation determination.
During the 1930s, a large number ofworkers performedtests to determine the relationship between the resistivity of rock samples and the brine content. In general, itwas found that correlations existed, but it was not untilthe comprehensive work ofArchie (1942) was publishedthat these correlations were placed in their modem context. Archie's work was based on GulfCoast sandstonesin the porosity range of 10 to 40 percent, saturated withbrines of salinity between 10 000 mg/L and lOa 000mg/L of NaCI. The work covered both fully saturatedand partially saturated samples, and presented theclassical empirical equation still employed today bypetrophysicists and formation evaluation experts:
The determination of the "n" exponent in the Archieequation (Equation I), is considerably more complicatedthan formation factor measurement because it necessitates measurement of not only a resistivity, but also asaturation at each data point. Samples are commonlydesaturated by one of two methods: centrifuging, orusing a porous diaphragm.
(3)
(2)
log F = log a - m log ljl
where R, = resistivity of water- saturated formation(ohm-m)
The ultimate objective offormation factor measurementis to determine the values of "a" and "m" that characterize a reservoir. For this reason, a suite of samplesshould be chosen having a range ofporosities that spansthe range found in the reservoir. A prerequisite toobtaining representative values of "a" and "m" is avery careful sample selection procedure.
Formation factors and porosities (preferably measuredunder stressed conditions) are determined for this suiteof samples. The values for all samples tested are thenplotted on log- log paper as illustrated in Figure 5.5·1and fitted with an equation of the form:
(I)aR"R, = ljlms:
R, = true formation resistivity (ohm-m)a = constantR,. = formation water resistivity (ohm-m)
where
66
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
10Source: Schlumberger, 1972.
~-. ,
'. <,", <,
'. , Hard. ,<, 1yF=-, $'
"
~<,
<,<,
'. ,". <,
-: ,.... :-:."-
SOf!(HUm/~ c..,(S"-'"". '" - 1 87 0.019
F = 0.62 . ~ m-. +$,.1. ".~ $
". <,
~'. ,
". <,/. ,F = 0.81 .... -,$' '.
<,<,
<,-,
<,<,
<,<,
<,<,
"
50
30
20
~
>!i.g....-e-~ 10Uleoa..
5
2
110'
Formation Factor, F103
Once a set of saturation-resistivity data has beenobtained, the saturation exponent is found by plottingthis data in log - log format as illustrated in Figure5.5-2 and fitting the data with an equation of the form:
where I = formation resistivity index
Capillary Pressure Studies
It is usually accepted that hydrocarbons displace waterin a reservoir rock during the normal process of accumulation. Because sedimentary rock is usually depositedin a water environment, the pore network must havebeen originally full of water. To gain a better understanding ofpresent fluid distributions, it is necessary tounderstand how hydrocarbons displace water to formthe hydrocarbon accumulation in the first place.
The pore geometry of sedimentary rocks is frequentlydescribed in terms of the "bundle-of-tubes" concept,
Figure 5.5-' Porosity vs. Formation Factor
log I = -n log Sw (4)
where the tubes represent pore throats interconnectingindividual pores. For a hydrocarbon accumulation tooccur, the pore spaces must be continuously interconnected and the capillary pressure of a water-filled poremust be exceeded by the pressure of the encroachinghydrocarbons. This threshold pressure, also referred toas the displacement pressure, determines whether or nothydrocarbons can accumulate in a pore on the microscopic scale or in a particular geologic structure on themacro scale. In the case of a cap rock or reservoir seal,it determines the maximum height a hydrocarboncolumn can reach before the seal is breached.
The density differences between the hydrocarbon andwater phases results in a force called buoyancy effect,which is the principal motive force causing oil or gas tomigrate upwards through water-saturated rocks in thesubsurface.
67
Company:Well:Location:
PanCanadian Petroleum Ltd.PCP Ferrybank 2-23-43-28LSD 2-23-43-28W4M
Formation:Field:Province:
DETERMINATION OFOIL ANDGASRESERVES
Basal Belly RiverFerrybankAlberta
10
I \I ! I
\
R, 1.00-=--Ro S~·68
1\
\\
\ -.\
\
\-\~
~
~,\.
~
~~
Source: PanCanadian Petroleum ltd.
Figure 5.5-2 Formation Resistivity Index
10"Brine Saturation (fraction)
1.0
Opposing this upward force, however, is the capillarypressure of the reservoir which depends on threefactors:
1. Radius of the pore throats of the rock
2. Interfacial tension of the two fluids
3. Wettability of the rock
Capillary pressure data is generally obtained from smallcore samples which represent a tiny fraction of the reservoir. In the laboratory, an air-mercury fluid system isoften used to represent the reservoir system. Air-brineand oil-brine systems are also used. It is essential for
68
the analyst to combine data from many samples to moreappropriately model the reservoir under study. Severalmethods are available to average capillary pressurecurves. A frequently used method is one developed byHeseldin (1973) in which he uses a displaced rectangular hyperbolic function to relate porosity to bulk volumehydrocarbon for varying levels ofpressure and, in tum,relates capillary pressure to water saturation for variouslevels ofporosity. This method has been used successfully in Alberta in the Waterton, Jumping Pound andVirginia Hills fields.
TESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
(cr cos 0)'/H.Pc,,". = 0.433h (SGw - SG,) (7)
(o cos 0),/w
where PColllg = air-mercury pressure (kPa)PCw10 = water-oil pressure (kPa)
3. Calculate PColllg for any height above the free waterlevel for the selected rock type.
4. From the air-mercury capillary pressure curves(Figure 5.5-3), read the percentage bulk volumeoccupied by Hg at that level for the selected rocktype and convert it to Sw' or read Sw (wetting phasesaturation) directly.
For reservoir systems with fluid characteristics similarto the laboratory systems, conversion factors arenot required. However, if the characteristics differ,adjustments similar to these steps must be taken.
5.5.3 Saturation Determination FromLogs
All water saturation calculations in theoretically shalefree formations assume a homogeneous intergranularpore system. These determinations are made from resistivity logs and are based on some form of Archie'swater saturation equation. As with the computation ofporosity from the various geophysical logging combinations, the determination of fluid saturation fromvarious resistivity and porosity logs has generated manyunique approaches.
Nearly all these techniques are derived from theclassical Archie equation, and the results are wholly dependent on the accuracy of the basic input parameters:R", F and R,. The analyst usually selects the deep resistivity reading from either the induction or the laterologdevice and after correcting it for environmental, borehole, bed thickness and invasion effects, adopts itas true resistivity, R,. Porosity derived from the sonic,the neutron-density, or some combination of logand core coverage will be matched with the appropriatelithologically dependent porosity-formation factorrelationship. Finally, R" will be determined either fromlog calculations, test recovery, or a sample ofproducedwater from a nearby water-bearing zone in the samegeological formation. In shale-contaminated reservoirsand in low porosity complex carbonate rocks, Sw canonly be accurately calculated by employing the most
(6)_ (cr cos 0)'/H.PCa/ Hg - PCw/0
(o cos 0)'/w
System 0 Cos 0 cr a Cos 0Air-water-solid 00 I 72 72Air-mercury-solid 1400 -0.766 480 -370Oil-water-solid 00 I 35 35
Pcw/, =0.433h (SGw - SG,) (5)
When all data has been assembled, the process forinterpreting water saturation in an oil-water system fromair-mercury capillary pressure curves is a four-stepprocess:
I. Determine the capillary pressure - height relationship in the reservoir.
Another method used is one developed by Leverett(1941). This method employs a correlating functioncommonly called the "J function," which was originallyproposed as a means to convert all capillary pressuredata to a universal curve. However, experience hasshown that significant differences in the correlationof the J function with water saturation occur fromformation to formation.
The prime use ofcapillary pressure curves is to confirmwater saturations in difficult evaluation environments.Other uses include determination of rock characteristics such as average pore throat size, pore throat sizedistribution and permeability; calculation of depth offree water level or oil-water contact; and determinationof the extent of the transition zone. The manipulationofcapillary pressure curves is fraught with many uncertainties, and only an experienced reservoir engineeror petrophysicist should attempt such an exercise.Accurate knowledge ofthe specific gravities ofthe reservoir fluids, interfacial tension between fluids and rock,and rock wettability is required for translating capillarypressure data into equivalent oil-water or gas-water data.Table 5.5-1 lists commonly used values for wettability,0, of a water-wet system and interfacial tension, o, indynes/em.
Table 5.5-1 Wettability and Interfacial Tension
where PCw10 = capillary pressure of the wateroil system (kPa)
h = height (m)SG = specific gravity, relative to water
2. Convert the reservoir water-oil pressure system intothe laboratory air-mercury pressure system usingthe appropriate rock-fluid values and fluid specificgravities.
69
it
-DETERMINATION OFOIL ANDGASRESERVES
Company:Well:Location:
PanCanadian Petroleum LimitedPCP Ferrybank 2-23-43-28LSD 2-23-43-28W4M
Formation:Field:Province:
Basal Belly RiverFerrybankAlberta
Air-Mercury CapillaryPressure Curve
\
I~r-...
\1 1~ 1~ 1~
BulkVolume Occupied Hg (volume fraction)
1
10
10'
105
<? 103
a.~
~:::J
'"~a, 10'
Air-Mercury CapillaryPressure Curve I-
\ r-;
2
12
14
10
<?o,
""x 8'"0:::::..~:::J 6'"'"OJ~
a.
4
oo .2 .4 .6 .8 1
Wetting Phase Saturation (fraction of pore volume)
Source: PanCanadian Petroleum Ltd.
Figure 5.5-3 Air Brine Capillary Pressure Test
advanced computational routines that in themselves relyheavily on data support from special core analysis studies. The casual analyst is well-advised to seek expertadvice in these areas because improper selection of input parameters could lead to solutions that grosslymisrepresent true reservoir conditions.
Figure 5.5-4 represents a flow diagram of a typicalpetrophysical evaluation based on saturations determined from electrical resistivity relationships.
The resultant water saturation is the fraction ofthe porevolume of the reservoir that is water-filled. That portion not filled with water is assumed to be filled withhydrocarbons.
5.5.4 Flow Test Procedures for Gas andOil Saturation
Well test analysis has always held great interest andattraction for drilling and reservoir engineers because itoffers the potential to assess not only the true saturationcondition ofthe formation, but also formation transmissibility. As advances were made in mathematicalmodelling theory, early field data that was frequentlyambiguous became more amenable to resolution. Withthe advent of very sophisticated electronic pressuregauges, high speed computers and advances in the fieldofmathematics, a new frontier has opened. Addition ofthe pressure-time derivative to log-log type curves nowpermits the identification of multiple reservoir boundaries and heterogeneities such as fractures and layeredformations.
70
,
It
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
Rock FormationType Fluid Tests
~-------------------------+
k
---------------------+ Permeability
Cores.1-0-- Sidewall Samples.
Drill Cuttings
---------~
III
Drilling I+--- ------------+1Time I Quantitative
IIIII ----- Quantitative Under
Natural I Special Circumstances----Radiation I
IIIII
InducedII
Radiation II--
<I>
Porosity -AcousticalVelocity -
Spontaneous---- PotentialI--
RwFormation -WaterResistivity R.
Produced Water-bearingWater Formation
Resistivity
Electrical------------------------+
Resistivity Rt
TrueFormation Sw
Resistivity r-- WaterSaturation
Source: After Shell Development Company, 1969,
Figure 5.5-4 Log Interpretation Flow Chart
71
where F* = formation resistivity factor for shalysand
B = equivalent conductance of clay exchange cations (sodium as a functionof C; at 25°C (mho ern- meq")
Q, = concentration of clay-exchangeablecations per unit pore volume (meqml,")
5.5.5 Factors Affecting Data Quality
Presence of Shale or Clay
Shale- or clay-free environments are rare occurrencesin nature. Shale is, in fact, one of the most commonconstituents of sedimentary rocks.
Aside from the negative effect on porosity and permeability, as previously discussed, the unique electricalproperties ofthese complex mineral assemblages greatlyinfluence the determination of fluid saturation.
Most analysts resort to one oftwo techniques to resolvewater saturation in a shaly sandstone environment. TheWaxman-Smits relationship (Smits and Waxman, 1968)attempted to relate the resistivity contribution ofthe shaleto the cation exchange capacity (CEC) of the shale:
In designing any test, reservoir engineers integrate asmuch open-hole logging and geological information aspossible. Some of the flow regimes that can be recognized during a pressure test include infinite acting,pseudo-steady state, and steady state. It is important thatthe test be designed to recognize and capture data fromall flow regimes. Critical formation properties like permeability and skin factor can be determined only fromthe infinite acting flow period. Reservoir size and shapecan be deduced from the pseudo-steady state phase, andthe steady state phase can give clues to that most-soughtafter parameter: drainage volume. Pressure transient testscan be conducted either in the open hole or in perfor
. ated casing. The open-hole drillstem test (DST) employsa valve, packer, and pressure gauge. A more sophisticated production logging tool string run in a cased holecan measure temperature, pressure, fluid density, andflow rate in addition to gamma ray activity and borehole diameter. In both cases, the goal is the same: toassess the fluid content and transmissibility of the reservoir as well as the extent of the producing formationaway from the wellbore.
. ,I s; BQ,Sw-=--+--R, F*Rw F*
(8)
DETERMINATION OFOILAND GAS RESERVES
In 1968, continuous measurements of rock CEC in situwere not possible and, for practical purposes, a DualWater Model was proposed as a solution.
In this approach, clay is modelled as consisting of twoparts: bound water and clay minerals, with the clay minerals assumed to be electrically inert. The Dual WaterModel as applied to shaly formations is illustrated inFigure 5.5-5.
Solids Fluids
Matrix Silt Dry Clay Bound Free Hydro-Water Water carbons
Matrix ShaieEffectivePorosity
Source: Schiumberger, 1987. Total Porosity
Figure 5.5-5 Dual Water Model
The analyst determines R. and R.b and inputs them toany ofa number ofgeneral computer interpretation programs for clastic sequences, such as the schematic of atypical process illustrated in Figure 5.5-6. To evaluate ashaly formation, four parameters must be determined:water conductivity, C; (or R.), conductivity of boundwater, Cwb (or R.b)' total porosity, li>, and bound Watersaturation, Swb' In practice, a cross-plot ofneutron anddensity logs generates acceptable values of li>,. Any ofavariety of shale-sensitive measurements, usually thegamma ray, can be the source of Swb'
Presence of Bitumen
Bitumen, in either the fluid or solid (pyrobitumen) phase,is observed in significant quantities in many reservoirsin western Canada, particularly in the Devonian carbonates that account for nearly 70 percent of all oil and 20percent ofall gas produced. When present, pyrobitumenis a major source of uncertainty because of its effectson porosity, permeability, wettability and chemicaladsorption, properties that can have a major impact onhydrocarbon recovery processes. On the other hand,bitumen in the liquid phase can be a reserve in itself, asfor example, the 50 x 10' m3 of resources assigned tothe Devonian Grosmont Formation ofnorthern Albertaand Saskatchewan.
When a reservoir engineer encounters a reservoir witheither bitumen or pyrobitumen, careful study and analysis are necessary to adequately gauge the impact that itspresence could have on production and production
72
ESTIMATION OF VOLUMES OF HYDROCARBONS INPLACE
j
I Correlate logs Ij
I Mark permeable beds (SP, ML) II
Breakbeds into zones SP
LaterolooML
InductionR'h/ <;P'h
Conductive" 2' I Zones" 2' Llt'hResistive " 5' I
Igr
I $N
In shale zones, determine average values for Ro•
R'h P,h Llt'h eneutron., ZI $.
Determine shalevolumeusingshale scalar RwChart 1 and Chart2 v;
IRt
I Start zone analysis
j
Readconductivity (or resistivity) and Igr for zone II
I I j
Density One of: density, Cross-plot
P'h = 2,65neutron, acoustic two logs
Yes NoCorrectfor shalinessLlt Chart 3
I P Chart4neutron Chart5
1$ from Chart 41j
Solve shaly sandequation to get R0.' Z
(need$., Rw' Vsh' R'h)
iSolve for Sw
(need Roo, a, Z)
ILast zone
Yes No
\The End
= spontaneous potential= microlog= resistivityshale= bulk density, shale= sonic travel time, shale= gamma ray index
= neutron porosity,shale= wet resistivityof undisturbed
zone= shaliness index= effectiveporosity= formation water resistivity= volume, shale= true resistivity
't
Data Required• Resistivity-induction, dual induction, laterolog• Gammaray• Porosity log(s) - densityneutron, acoustic• Water resistivity
Figure 5.5-6 Shaly Sand Interpretation Process
Charts Required1. Shalescalar2. Relationship for gamma ray vs. percentclay (V'h)3,4,5. Acoustic, density, neutron response
73
strategies. Reservoir rocks with organic-basedpyrobitumen frequently exhibit strong tendencies to oilwetness, resulting not only in abnormally low calculated connate water saturation, but also in high effectivewater permeability. And more important to those concerned with reserves and estimating ultimate recovery,these reservoirs frequently suffer "premature" waterbreak-through on waterflood recovery schemes.
Reservoir Heterogeneity
As noted in the discussion on the use of capillarypressure curves, each plug represents the characteristics of only the rock type present in that tiny sample. Itis imperative, therefore, that the reservoir engineer havesome appreciation ofthe variability that can be encountered within the total reservoir under study. Each discretelayer is itself susceptible to subtle changes, both vertically and horizontally, that may escape the eye ofeventhe most careful investigator or lie beyond the depth ofinvestigation of any borehole logging devices.
While logs and cores provide data that is useful incalculating water or hydrocarbon saturation, logsrepresent a moving observation point. This runningaverage, when compared to the stationary observationdata point derived from core data, can result in a lack ofconformity between samples of differing geometricalcharacter. It is important, therefore, that common sensebe employed when comparing saturation data derivedfrom differing measurements and differing rock volumes. Good correlation between widely diversemeasurements might indicate the presence of a homogeneous reservoir and permit the analyst to employ fairlylarge-scale approximations ofthe reservoir. Conversely,poor correlation could signal the presence of extremeheterogeneity in the larger reservoir sense.
74
DETERMINATION OF OIL AND GASRESERVES
Wettability
Wettability is defined as the tendency of one fluid tospread on or adhere to a solid surface in the presence ofother immiscible fluids. Wettability is a major factorcontrolling the location, flow and distribution of fluidsin the reservoir. The wettability oforiginally water-wetreservoir rock can be altered by the adsorption ofpolarcompounds or the deposition of organic material. Thewettability of the reservoir can affect the estimation ofin-place hydrocarbon volumes as well as estimates ofhydrocarbon recovery.
The estimation of hydrocarbons in place is affectedbecause the understanding of fluid saturations, resistivity measurements, capillary pressures, relativepermeability and residual saturations is changed whenthe system varies from being strongly water-wet tostrongly oil-wet.
Recovery estimates can also be significantly affectedbecause the initial and residual saturations, relativepermeability, primary, secondary and tertiary recoveryprocesses are different for the oil-wet and water-wetcases.
References
Archie, G.E. 1942. "The Electrical Resistivity Log asan Aid in Determining Some ReservoirCharacteristics." Trans., AIME, No. 146,pp.54-62.
Heseldin, G.M. 1973. "A Method of AveragingCapillary Pressure Curves." Canadian WellLogging Society, Vol. 6, No. I, Dec. 1973, pp.33-46.
Leverett, M.C. 1941. "Capillary Behaviour in PorousSolids." Trans., AIME, Vol. 2, T.P. 1223, pp.152169.
Schlumberger. 1972. Log Interpretation Charts.Houston, TX.
---. 1987. Log Interpretation Principles!Applications. Houston, TX.
Shell Development Company. 1969. PetrophysicalEngineering. Course notes, Houston, TX.
Smits, L.J.M., and Waxman, M.H. 1968. "ElectricalConductivities in Oil-Bearing Shaly Sands."Trans., AIME, Vol. 243, pp. 107-122.
-
b
ESTIMATIONOFVOLUMES OF HYDROCARBONS INPLACE
5.6 TESTING AND SAMPLING
5.6.1 IntroductionThe flow capability of a well is generally found bymeasurement of actual production. Two general typesof flow tests, the drillstem test and the production test,are often used to measure production rates and obtainflow pressures. In addition to collecting this data, flowtests provide good opportunities to gather samples ofproduced fluids for further analysis. This section willdiscuss flow tests, as well as the reasons and proceduresfor collecting fluid samples.
5.6.2 Drillstem TestsThe drillstem test (DST) is often the first opportunity toobserve the flow characteristics and record the pressureof a reservoir. A DST meets three objectives whenconducted properly:
1. To obtain a stabilized initial reservoir pressure
2. To obtain an indication of stabilized flow rates
3. To obtain samples of reservoir fluids
The majority of wells today are drilled using the rotarydrilling technique, which consists of rotating a bit thatis fastened to a drill string made up of pieces ofthreadedpipe called the drill stem, and drill collars. The drill collars are heavy pieces ofdrill stem and allow a downwardforce to be applied to the bit. The bit is rotated by thedrill string which, in turn, is rotated at the surface by thedrilling rig. Using this rotary drilling technique, the drillhole is deepened until the prospective zone is reached.
A DST is conducted by replacing the drill bit with adrillstem test tool, attaching it to the bottom ofthe drillstring and lowering it into the hole. The tool consists ofone or two sets of isolating packers, a valve for allowing reservoir fluid to flow, and locations where pressurerecorders may be placed. A packer is an expandablerubber element that is squeezed up against the hole.When the packers are expanded, or set, the zone of interest is isolated from the fluids trapped between thehole and the pipe (also known as the annulus). Figures5.6-1 and 5.6-2 illustrate a typical DST tool in unsetand set position. It is important to ensure that thepackers are set in a zone that will allow a tight seal.
Once the packers have been set at the proper depth, thevalve inside the tool is opened, allowing reservoir fluids to flow up the drill string to the surface. Producedliquids (oil, condensate, water) are sent to tanks, andgases are generally sent to a flare pit or flare stack.After a set period oftime, the downhole valve is closed,and the reservoir pressure is allowed to increase to
stabilized conditions. The valve in the tool may beopened and closed as often as required once the packershave been set. A typical DST would include a 5-minutepreflow, a 30-minute shut-in, a main flow of 60minutes, and a final shut-in of 90 minutes.
The flow rate during a DST is usually measured whenreservoir fluid appears at the surface. Gas and liquidrates are easily measured by the service company providing the DST equipment. Flow rates may be estimatedin cases where reservoir fluid does not reach the surfaceby observing the amount ofliquid recovered in the drillstring after the test is complete because any fluid thattravelled past the valve in the DST tool during the testwould be trapped in the drill stem after the valve wasclosed for the final buildup. Many experienced rig supervisors are able to accurately determine the amountof fluid recovered in the drill stem while retrieving theDST tool. Average flow rates are estimated by dividingthe flow times into the volume of liquid recovered.
Pressures are recorded by gauges inserted in the DSTtool. Drillstem test tools allow the placement ofgaugesin a variety of locations so pressures can be measuredabove the DST valve, outside the tool, and below thetool. The most important measurements are those recorded inside the tool itself. Analysis ofthese pressuresindicates the hydrostatic head of the mud column anddrawdown and buildup' pressures. Pressure gauges arediscussed in more detail in Section 5.8.
Closed-chamber DSTs are run in much the samemanner as regular DSTs, but the fluids are not allowed
to flow to the surface. A pressure gauge at the surfacerecords the increase in pressure as fluids enter the drillstring. A detailed analysis of the pressures obtained atsurface, the pressure measurements recorded downhole,and the liquid recoveries will yield production rates.
5.6.3 Production TestsProduction tests are performed on completed wells; thetests provide the engineer with insight into the production potential of the reservoir. Production tests may beconducted immediately after the well has been completed or after the well has produced for several years.This is an important consideration as reservoir characteristics do change through the life of the reservoir.Parameters such as pressure and flowpotential all changeas fluid is withdrawn from the pool.
The equipment necessary for a production test canvary from well to well. The basic requirements are pressure recorders to continuously measure flowing andbuildup pressures, and surface equipment that is able
75
Figure 5.6-1 Drillstem Test Tool (Unset Position)
76
DETERMINATION OF OIL AND GASRESERVES
Figure 5.6-2 Drillstem Test Tool (Set Position)
r
>
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
to accurately measure the flow rates of the well.Generally, pressure recorders are placed downhole closeto the producing formation. Pressure recorders are available in various pressure ranges. It is unwise to exposethe recorder to more than 75 percent of its maximumrange. Flow rates are best measured on single phases,so test separators are used. A two-phase separator separates gases from liquids, while a three-phase separatorseparates gas, oil, and water. Surface equipment mustbe sized correctly to ensure that it will not be a bottleneck for the producing stream.
In the design, implementation, and analysis of aproduction test, several factors must be considered: thepurpose ofthe test and the data that is required, the reservoir and fluid characteristics, the type of test, the testequipment necessary, and any operating difficulties.
The purpose of a production test often depends upon anumber of considerations, the first of which is the lifeof the well. The data needed from a well that has justbeen completed may be different from the informationneeded for a well that has been on production for several years. The determination of information such asdelivery rate, reservoir damage, drainage area andboundaries, stabilized flow conditions, and the need forformation stimulation treatment must all be factored intothe purpose ofthe test. Many tests are conducted to examine the success offormation treatments, or to recoverrepresentative reservoir fluid samples.
Knowledge of the characteristics of the reservoir andthe fluid is important for the design ofa production test.Many tests yield inadequate data because of avoidableproblems. Reservoir damage may occur due to high flowrates, or the well may freeze offdue to hydrates. Knowledge of reservoir and fluid characteristics will lead tothe collection of data that is as accurate as possible.
There are many different types ofproduction tests, eachof which will yield important data. Each type may berun alone or in combination with other tests. Thefollowing are common types oftests:
• Interference
• Absolute open flow (AOF) of gas wells
• Constant and variable rate
• Pressure buildup
A well is generally "cleaned up" after a zone has beencompleted or worked over. This allows completionfluids to be withdrawn from the reservoir to prevent further formation damage. A segregation test helps todetermine if one zone is in pressure communicationwith another. AOF tests can be one of three types:
conventional, modified isochronal, or single point. Allthree yield information about the AOF potential of agas zone. Drawdown tests are conducted to determinereservoir characteristics such as damage, permeabilityand flow potential. Pressure buildup tests yield muchthe same information as drawdown tests with theaddition of stabilized reservoir pressure.
Another aspect ofproduction test design deals with theduration of flow rates and any corresponding builduptimes. Generally, flow rates should be ofsufficient timeto allow the flow rate to reach stable conditions. As thistime period is usually dependent upon the parametersthe test is designed to determine, field experience andrules of thumb are generally used. Typically, builduptimes must be at least twice as long as the precedingflow rates. Exceptions to these rules occur in some AOFtests, where the flow time and buildup time are set andare independent of whether the reservoir has reachedstabilized conditions. The question of the actual flowrate is usually dependent upon previous production data.It is recommended that the well be flowed at the anticipated delivery pressure, or if the delivery pressure isnot known, at 50 to 70 percent of the well's AOF.
5.6.4 SamplingCollection ofrepresentative samples of reservoir fluidsis necessary for many reservoir engineering applications.Gas, oil and condensate samples are needed forcompositional analysis and PVT (pressure-volumetemperature) analysis. Water samples yield informationrelating to the water salinity and solids content. Specialcare must be taken when sampling, so that samples collected are representative of the fluids found in thereservoir. The inability to gather good samples maycompromise many calculations and studies performedat a later date. Two methods are commonly used in obtaining reservoir fluid samples: subsurface samplingand surface recombination sampling.
In subsurface sampling, a sample chamber is run to thebottom of a flowing well on wire line. The sample iscollected at bottom-hole pressure and then isolatedthrough the closing of the inlet valves. The well is keptflowing during the process to avoid fluid segregation(and thus an unrepresentative sample). The seeminglysimple process of obtaining representative samples iseasily hampered by the presence ofmore than one phasein the wellbore. If the reservoir is initially undersaturated above the bubble-point pressure, an accuratesample is easily obtained. However, if the reservoir isinitially at the bubble point, it is difficult to assess
77
whether the oil and gas are being collected in thecorrect volumetric proportions. Wen conditioning canalleviate this problem. The principal drawback of subsurface sampling is that only small volumes of wen fluidsare sampled. Furthermore, it is necessary to take several downhole samples so that saturation pressure canbe compared at the same temperature.
In surface recombination sampling, separate volumesof oil and gas are taken at separator conditions and recombined to give a composite fluid sample. Samplingpoints should be chosen in order to provide homogeneous, preferably single-phase, sample mixtures. Surfacesampling allows the collection of fluid samples at theoperating conditions of the surface production facilities. Samples are usually collected by fining a cylindricalcontainer with valves at both ends. Due to the locationof the sampling point, a much larger sample may beobtained. Because the samples are taken over severalhours of flow, this method gives a fairly accurate producing gas-oil ratio (GOR). As in subsurface sampling,the well must be conditioned to ensure stability duringsampling. If done correctly, both sampling techniquesshould yield identical samples.
Prior to any sampling of fluids, whether at surface orbottom-hole, it is important to consider whether the fluidto be collected represents the reservoir fluid. When fluidis withdrawn from the reservoir, the pressure changescaused by the withdrawal sometimes cause liquid andvapour to separate. Ifa collected sample contains a disproportionate part of either of the two phases, thesubsequent fluid analyses will give erroneous results.To prevent this problem, it is recommended that the wenbe conditioned to remove from the sample point anyfluid that may compromise the sample.
Conditioning is generally accomplished by flowing thewen at low drawdown rates so that any altered fluid isdisplaced by true reservoir fluid. Well conditioning reduces the amount of free gas present at the wellbore byessentially pushing it back into solution. The first stageof a conditioning program involves producing the wellat a low stabilized rate at constant temperature and gasoil ratio. This reduces the free gas saturation below thecritical gas saturation for gas flow in the formation. Thisfirst stage may take as little as a few hours or as long asseveral days. Any remaining gas is forced back intosolution through pressure buildup (the wen is shut in).The shut-in period is dependent upon the transmissibility of the formation and can last up to 72 hours. If thewen was initially undersaturated, it is flowed at a lowrate during the sampling. If the well was initially at
78
DETERMINATION OFOIL AND GASRESERVES
saturation pressure, the samples are taken while the wenis shut in. Well conditioning procedures are givenin API Recommended Practice No. 44 (AmericanPetroleum Institute, 1966).
In the course of sampling, care must be taken to ensurethat the sample containers are properly purged toprevent air contamination.
Gas Samples
By regulation in Canada and as good operatingpractice, gas samples are obtained whenever a drillstemor production test results in flows of gas. Usually, thesamples are obtained at the surface from the outlet ofaseparator at relatively low pressures (200 to 700 kParange). Steel sample containers are used in the case ofsweet gas. Where hydrogen sulphide (HzS) is present inthe gas, it is important to use special containers becausesteel containers will absorb small concentrations ofHzSand thus prevent its detection during laboratory analysis of the sample. If these are undetected, the resultscould be small concentrations ofHzS, improper designof gas processing facilities, and high costs to effectchanges. Determinations for HzS are often made at thewellsite to ensure that any small amounts of HzS aredetected. In fact, when there is any doubt, Tutweiler orGas-Tech measurements should always be made at thewellsite.
Gas samples are sometimes obtained in conjunction withPVT sampling at bottom-hole conditions and transferredto special high-pressure containers for transportation andanalysis at appropriate laboratories. Conventional analyses usually identify the mole percentages of varioushydrocarbon components as well as carbon dioxide,hydrogen sulphide, helium, and nitrogen. The specific gravity and heating content of the gas are alsodetermined.
Gas analyses are used in reserves determinations tocalculate the compressibility factor of the gas mixtureand to estimate the volumes of sales gas, recoveries ofnatural gas liquids, and processing shrinkages.
In Canada, gas analyses can generally be obtained quitereadily through public sources and, in particular, throughthe conservation and regulatory authorities of eachprovince.
Water Samples
Formation water samples can be obtained from therecoveries of drillstem, wireline, and production tests,and during routine production operations. Care mustbe taken to use only analyses of samples that are
q
...
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
uncontaminated by drilling mud filtrate and the variouschemicals used during production and treating. Inmany cases, determining whether the sample is representative of the formation is based on rather subjectivejudgement.
Analyses ofoil field water samples usually identify themajor constituents and total solids in milligrams perlitre or parts per million. Total solids can range froma few hundred to over 200 000 parts per million inCanadian oil field formation waters. Specific gravityand resistivity are also measured.
Water analyses are generally used to identify the sourceof the water or to obtain the resistivity of the water inorder to calculate interstitial water saturations fromporosity information and electrical well logs.
Analytical results are often presented graphically toenable visual comparisons or "fingerprinting" of waters to be made. The Stiffdiagram (Stiff, 1951) is widelyused for this purpose.
Useful compilations offormation water resistivities areavailable for the majority of productive reservoirs inthe western Canada sedimentary basin and other partsof Canada. One such compilation is published by theCanadian Well Logging Society (1987). The publishedformation water resistivities represent the best information available at the time of publication, but care mustbe taken to use the data most appropriate to the specificapplication.
Oil Samples
Conventional Surface Samples
Crude oil samples are obtained and analyzed for avariety of characteristics that are ofimportance in reservoir work, production operations, wellsite treating,pipelining, and refining. This brief discussion is restricted to crude oil samples as they apply to reservoirengineering. A distinction will be made between conventional crude oil samples obtained at the surface andcrude oil samples obtained at reservoir conditions inorder to measure PVT characteristics in the native state.
Conventional surface crude oil samples are generallyobtained from crude oil storage tanks, at the wellhead,and from drillstem test recoveries. The AmericanPetroleum Institute has published guidelines that shouldbe followed in obtaining reliable oil samples(American Petroleum Institute, 1966).
PVT Samples
For a better understanding of the physical properties ofa reservoir fluid, a PVT study should be performed earlyin the life of the reservoir to obtain truly representativesamples ofthe reservoir fluid. Generally, it is better thatPVT studies be performed on subsurface samples.
Tests
After a representative sample has been obtained, thefollowing five tests are normally performed to assessthe fluid behaviour and properties:
Pressure-Volume Test. A pressure-volume (PV) testinvolves the constant composition expansion of the fluidsample at reservoir temperature. The sample is initiallyundersaturated (reservoirpressure is greater than bubblepoint pressure). As the pressure is reduced towards thebubble-point pressure, the oil compressibility is identified. The actual bubble-point pressure is also measured.Below the bubble point, the two-phase volume ismeasured as a function ofpressure.
Differential Liberation or Vapourization Test. In adifferential liberation test, the sample is subjected to anincremental pressure reduction from the bubble pointto zero. As the solution gas evolves, it is removed fromthe system. As a result, the composition of the fluidsample is always changing. This test identifies the relative density of gas, the gas deviation factor, the gasformation volume factor, the relative oil volume factor,and the gas-oil ratio (the gas remaining in solution at agiven depletion pressure as compared to the volume ofresidual oil at stock tank conditions). During thisprocess, the oil density at each pressure incrementis determined by mass balance. A quality controlcheck compares the calculated oil density at the depletion pressure (through mass balance) to the measuredoil density at this point.
Viscosity. Viscosity is measured at reservoir temperature at a series ofpressures above and below the bubblepoint.
Flash Liberation or Separator Tests. In a flashliberation test, the sample is again subjected to a pressure reduction from bubble point to zero. The oil andliberated gas, however, are kept in equilibrium throughout the expansion. This test identifies the formationvolume factor and the solution gas-oil ratio at separatorconditions. One or more flash liberation tests should bedone to determine the behaviour of the reservoir fluidas it passes up the tubing, through the separator(s), andinto the stock tank.
79
Compositional Analysis. Most reservoir fluidparameters canbe estimatedfromcompositional analysis. In general, the more fluid parameters sought, themore detailedthe analysismust be. A typical compositional analysis includes a separation of componentsthrough C10 as a minimum. More sophisticated equationsofstatemayrequire analysis through C30orhigher.
It is important to note that due to the nature of theexpansion, theflashanddifferential liberation processesyield different vapour-liquid splits. The degree ofdifference depends mainly on the composition of theinitialsystem. In general, in low volatilityoils in whichthe solution gas consistsmainlyof methane andethane,the resulting oil volumes for either form of expansionareessentially the same.Forhighervolatility oils,whichcontain a relatively high proportion of intermediates,the resulting oil volumes can be significantly different.
80
DETERMINATION OFOILANDGASRESERVES
In an undersaturated oil reservoir,depletionbegins as aflash processand eventuallybecomesa combinationofflash and differential liberation processes. Because ofthis, care mustbe taken to ensure that the correctdata isbeing used in engineering calculation. Flash data mustbe adjusted using differential liberationvolumes to reflect thevariouspressureregimesinthe reservoirduringdepletion.
ReferencesAmericanPetroleumInstitute. 1966. "Sampling
PetroleumReservoirFluids." API RP 44,Washington, DC.
CanadianWell Logging Society.C,J. Struyk (ed.).1987. Formation Water Resistivities ofCanada.Sep. 1987,Calgary,AB.
Stiff, H.A., Jr. 1951."The Interpretation of ChemicalWater Analysisby Means of Patterns."JPT., Vol.192,pp. 15-17.
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
after the casing is cemented could be affected by theheat released in the setting reaction of the cement.
The most representative BHT data is probably obtainedfollowing the completion of the well after it has beenshut in long enough for temperature equilibrium to beestablished between the wellbore and the formation. Anideal time to measure BHT is during a static bottomhole pressure survey, or pressure buildup following aflow test, or during the process ofbottom-hole samplingfollowing the completion ofthe well. In some instances,it is a good practice to run a temperature-depth profileon each producing well using a continuous recordingthermometer.
In the early stages of development and production of afield or reservoir, measured temperature data may betoo sparse to provide a reliable estimate ofinitial conditions. In this case, regional correlations may be helpful.The following list provides correlations for estimatingformation temperature for several regions in NorthAmerica [T, = formation temperature in °C (OP);D = depth in m (ft)]:
(I)
Tf = 1.7+ 0.0366D(T, = 35.0 + 0.0201D)
T, = 0.0 + 0.0341D(Tf = 32.0 + 0.0187D)
T, = 9.4 + 0.0304D(T, = 49.0+ 0.0167D)
T, = 0.0 + 0.0352D(T, = 32.0 + 0.0193D)
Tf = 23.3 + 0.0228D(T, = 74.0 + 0.0125D)
T, = 15.6+ 0.0306D(T, = 60.0 +0.01675D)
Tf = 18.9+ 0.0202D(T, = 66.0+ O.OlllD)
Oklahomadeep AnadarkoBasin Tf = 18.9+ 0.0255D(below 21,000 ft) (T, = 66.0+ 0.014D)
In general, formation temperature in the hydropressurezone may also be estimated from thermal gradient mapspublished by the United States Geological Survey ~nd
the American Association of Petroleum Geologists(Cronquist, 1990), using the equation:
T,= Tsa + goD
where T, = formation temperature, °C COP)
Tsa = average surface temperature, °C (OP)
geothermal gradient, °C/m (Op/ft)
= depth, m (ft)
OklahomaAnadarko Basin
Alberta (average)
Alberta Bashaw(carbonale complex)
Alberta Rimbey-Meadowbrook(carbonate complex)
AlbertaWindfall-SwanHills(carbonatecomplex)
LouisianaGulf Coast(hydropressure zone)
NorthTexas
5.7 RESERVOIRTEMPERATURE
5.7.1 IntroductionReservoir temperature is of prime importance in thedetermination of in-place volumes and recovery factorsfor gas and oil. In estimating gas reserves, a knowledgeof temperature is necessary to calculate the gas compressibility factor and gas formation volume factor. T.oestimate oil reserves, knowledge of the temperature IS
critical if laboratory PVT data is to be measured underreservoir conditions. Temperature also affects otherparameters such as oil viscosity and miscibility, andthereby impacts reservoir engineering estimates of OIlrecovery.
Often values ofreservoir temperature are estimated fromdata in the literature or from readings obtained duringlogging or testing operations. Such data may be acceptable under initial conditions, but should always beconfirmed or adjusted using more reliable data as it becomes available. The most reliable source of temperaturedata is a bottom-hole temperature (BHT) measurementtaken with a continuous recording subsurface temperature gauge under stabilized bottom-hole conditions.Other methods, such as using maximum reading thermometers during testing or logging operations, areconsidered less reliable.
Although temperature is usually a function of depth, anumber of other factors affect temperature as well.Isotherms at depth may not always follow surfacetopography.
This section describes various techniques used formeasuring or estimating BHT and points out the shortcomings in some ofthe values obtained.
5.7.2 Data SourcesTemperature measurements are made in conjunctionwith a number of operations conducted on a well. Manyof these measurements will have varying degrees ofaccuracy. Measurements taken while the well is beingdrilled will likely be influenced by the cooling effect ofthe circulated drilling mud and will be only approximate. During open hole logging, errors may occur inBHT measurements unless sufficient time is allowedfor the wellbore to reach temperature equilibrium withthe formation. Measurements taken during flow testscould be detrimentally affected by the cooling effectcreated by gas expansion when fluids enter the wellboreor flow through any mechanical restriction in thewellbore such as a bottom-hole choke, mandrel or flownipple. Temperatures recorded on logs run immediately
81
7
DETERMINATION OFOILAND GASRESERVES
--,,
Thus if two or more BHTs-measured at the same depthin the same well, but at different times-are known, theequilibrium temperature may be estimated.
The Horner method was used by Deming and Chapman(1988) to analyze BHT data gathered from microfilmcopies of log headers on file at the Utah Oil and GasCommission. Figure 5.7-1 shows 18 Horner plots forBHT data from oil and gas fields in the Utah-Wyomingthrust belt. Although the quality of these data is comparatively high, some scatter about the Horner line isinevitable.These plots show that successivelogging runsgenerally yield a series of temperatures that are consistent with the Horner model of conductive heat transferinto the borehole during shut-in.
temperature. To estimate true formation temperaturefrom raw BHT data, a correction must be applied.
The corrections may be made using a Horner plotmethod. This method owes its name to the fact thatit is identical to the equation developed by Homer topredict reservoir pressure recovery. In this method,
BHT = T_ + A In [(t + tcire)/t] (2)
where T_ = undisturbed formation temperatureA the negative slope of the Horner
straight line (an unknown constant)t shut-in timet - circulation timeeire -
5.7.4 Data Analysis on a Regional BasisRecently published technical data provides good insighton variations in BHT in western Canada (Lam and Jones,1984; Lam et aI., 1985). One of the key areas ofinteresthas been southern Alberta where a high density of wellsprovides an opportunity to measure and explaintemperature variations from one region to another.Figure 5.7-2 shows the main topographic features ofsouthern Alberta with respect to the eastern limit ofthedisturbed belt. As might be expected, variations in thetemperature gradient from the calculated mean value(referred to as "spread") are more frequent in the vicinity of the disturbed belt. Figure 5.7-3 shows thesespreads. The spread values vary from a low of 2°C inthe plains area of southern Alberta to 10° - 13°C inareas near the edge of the disturbed belt. These "spreadanomalies" occur between Hinton and Edson, to thesoutheast of Hinton and Edson, and south of Calgary.One notable feature on this map is the coincidence ofthe high-spread area south of Calgary and a fault zoneas indicated on an ERCB Paleozoic surface map. Inaddition, relatively high spread values occur in theMedicine Hat area to the east (as indicated by light
Reservoir temperatures obtained using these correlationsshould be considered preliminary, and they are not asubstitute for actual measurements.
In Alberta, temperatures measured at a mean depthfor each oil and gas pool are shown in the annualreserves report published by the Energy ResourcesConservation Board (1991).
Reservoir temperature is considered to be constant overthe life ofa reservoir, and most reservoir processes, withthe exception of in situ combustion and steam or waterinjection, are considered to be isothermal. Waterflooding can cause significant cooling. In some of the WestPembina Nisku reefs in Albertawhere pools were converted to hydrocarbon miscible flooding after manyyears on waterflood, reverse temperature gradients werestill noted years after the pools had been converted.
5.7.3 Data AnalysisIt is pertinent to give some thought to the means ofarriving at a value for reservoir temperature. The termbottom-hole temperature or sand-face temperature isapplied to the temperature opposite the producing horizon. The logical place to record a single representativemeasurement would be at the centre of the producinginterval or at the pool datum depth. Frequently, measuring tools cannot be run to the desired depth, andtherefore the temperature must be extrapolated. For thisreason, an accurate determination of the temperaturegradient should be established at the run depth. Thiscan be done most conveniently while running a pressure bomb to measure the static bottom-hole pressure. Itis likely that temperature would be extrapolated to thesame datum as pressure.
If it were desired to estimate BHT from open-hole welllogs, some adjustment to the recorded temperaturesmight be necessary (Deming and Chapman, 1988).Following the cessation ofdrilling, the usual practice isto condition the borehole by circulating drilling mudthroughout the hole for a period of time known as thecirculation time. Because the temperature of the drilling mud is usually lower than the undisturbed formationtemperature at the bottom of the well, temperature inthe wallrock drops during mud circulation. When circulation of drilling fluid is stopped, the well is "shutin," and the temperature in the borehole rises. It is during this period of time, usually 4 to 30 hours after theend of circulation, that the well is logged and the BHTmeasured at a shut-in time, which is the time elapsedsince circulation ceased. Thus the BHT measured ishigher than the temperature of the circulating mud,but lower than the true equilibrium or formation
82
s
ESTIMATIONOF VOLUMES OFHYDROCARBONS IN PLACE
Shut-in Time, t (h) Shut-in Time, t (h)50 30 20 15 10 5 50 30 20 15 10 5
140 140
130 130
Wells
120 AR34-02 120 •G 5657m G •~ 110 ~ 110 WellsQ) CC 846 AI ~~ 458 F2::> 5011 m ::>
li! 100 li! 100 • 4700mQ)
ARE 28 - 06Q)
0. 0. ARE36-14E
904595m E
90 4540m~ ~ARE 20 - 16 45801Q)
4145 mQ)
4011 m ARE 28 - 01"0 80 "0 80 4221 m::c ::c, • AR34-02 EE 3544m ARE 28 - 01a
70a
70 2996m'6 '6 AR 4-1CO AR 3-2 CO
2332m60 2737m ARE 30 -14 60 CC846 BI3305m 2186 m
AR 10-1 •50 2367m 50 AR 34 - 2
ARE30-14 1933m
40 1462 m 40IRD #11688m
.1 .2 .3 .4 .5 .6 .1 .2 .3 .4 .5 .6
C+ tel") C+ te;" )In --(b)
In --(a) t t
Source: After Deming andChapman, 1988.
Figure 5.7-1 Representative Horner Plots from Wells in the Utah-Wyoming Thrust Belt
'M~-~'- Lake
Elevation AboveSea Level
(tt)
1120006000
...•••....••.... •... 4000.,....... 3000••••• 2000•• 1000
o
Source: AfterLamat al., 1985.
Figure 5.7-2 Relief Map for Southern Alberta
I Faull FromERCSPaleozoic
\ surface map
'C
1Il~~•. 6
c::JoI
Source: After Lamat at., 1985.
Figure 5.7-3 Contour Plot of Spread for BHTValues in Southern Alberta
83
DETERMINATION OF OIL AND GAS RESERVES
shading in Figure 5.7-3), but these are surrounded by~L'nerally low spread values.
It has been observed that isothermal surfaces do notalwuys tallowtopographic surfaces for a number of reaS,HIS: a rapidlyvaryingtopographic surface and smoothis,'lhemlal surfaces at depth, or distortion to the isothermal surfaces due to a number of influences such astaults, water movement, or subsurface temperature orL,,'ndueti,ity anomalies. Water movement along faultsand fractures increases spread values when water isheated at depth andtravelstowardthe surfacealong faultplanes. Thiscancause large horizontal temperature difti:renees at the same depth level and, consequently, alarge spread in the temperature values.
\\' atcr movement through permeable strata is anothertactor that can strongly influence the temperature,,'giIlle. Hydrodynamics appears to play an important1\'1<' in the distribution of subsurface heat and so influenccs the temperature distribution. Gravity-imposed,l,lwnward water movement occurs in the upper strataas",ciatN with surface recharge while, in other areas,l',-nneable beds allow upward water movement. These
upwardand downwardwater movementsin the sharplydipping permeable formations cause the isotherms todipsharply, giving largespreadvalues as indicated. Suchwater movement is thought to occur in the westernAlberta basin. In the east, where the water movement ismainly lateral, the isotherms lie parallel to the surfaceand the spread values are smaller.
Another reason for an increase in spread values may bethe effect ofthermal conductivitycontrastsbetween adjacent dipping beds. For example, the clastic and shalyformationsabovethe Palaeozoicsurfaceare oflow thermal conductivity,whereas the calcareous and evaporiticformationsbelow the Palaeozoic surfaceare more conductive. In steeplydippingbeds,suchchangesin thermalconductivitymay distort the isothermsso that temperature vs. depth plots over a 3 x 3 =9TWP/RGE area willexhibit large spread values. This is illustrated in Figure5.7-4 in which two 9 TWP/RGE areas of west-centralAlbertaare compared (Lamand Jones, 1984).Althoughthese areas are in the same general region, they exhibita totally different temperature gradient and spread.
Temperature ('C)50 100 150
o-c-'-~-'----'--'-L->--'~-'----L--<"-'---'--+-o
Temperature (OC)50 100 150
to :::.%mc
300
Grad. = 31.7°C/km(17.4'F/l 03ft)
'.
100 200Temperature (OF)
StandardErrorof EstimateS.4°e
... . ......
32
2
4
5
300100
,,, ,
, ".. ,, ,\. ~,-\~ \
\\ ,),",. tit
, "'~ ,, ',,- .,, ,, ,
, ", .. .'~..'-. .. .. .. .. .. .. .. .. .. .. ,. .. ,. .. .
•scar-care Error ofEstimate4.2'C
1-
2-
,-
200Temperature (OF)
,3:..~~: ~~ earnand Jones, 1984.
Grad. = 24.2QC/km
(13.3'FI103ft)
=;sure 5.7-~ Examples of Temperature vs. Depth Plots from Two Areas in Southern Alberta
1 ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
5.7.5 Data QualityDuring the drilling and completion ofa well, there are anumber of opportunities to obtain BHT data. It is important to plan ahead so that the best quality data isobtained at the most opportune time and at minimal cost.
IfBHT data is required while drilling a well, a drillstemtest may provide the most representative data. Temperature derivations from logs run in the open-hole wellborehave been observed to be consistently lower than theBHT measured from drillstem tests despite the use ofthe Horner plot method to extrapolate the temperaturebuildup (Hermanrud et aI., 1990).
The preferred method of obtaining representative BHTdata is to obtain measurements following the wellcompletion and an appropriate shut-in period. An idealopportunity to obtain BHT data is in conjunction with astatic bottom-hole pressure measurement, or a pressurebuildup following an oil or gas deliverability test. Evenunder these circumstances, two factors could influencethe accuracy of a temperature measurement: a largedrawdown during the flow period, and the depth at whichthe temperature is recorded. To improve the quality ofdata, the wellbore drawdown should be moderate, andthe temperature sensor should be within the producinginterval (Hermanrud et. aI., 1991).
It is important to note that temperature gradients oftenvary from one region to another and, even within thesame area, may deviate significantly from the mean average due to the proximity ofcertain geological featuresin the area. Prudence is required to recognize these deviations and not dismiss them as errors in measurement.
Caution is recommended when taking a BHT measurement in shallow wells on hot summer days using amaximum reading thermometer. The maximum reading could be the surface temperature and not the BHT.
In conclusion, BHT data is available from a number ofsources and the quality of this data is often not questioned. Such acceptance stems from the fact that smallvariations in BHT when converted to absolute temperature result in a very small percentage error in the overallreserve estimate. On the other hand, to minimize thiserror and improve the overall quality of the reserve estimate, one should take advantage of the drilling andcompletion process to obtain data that best representsthe true BHT conditions.
References
Cronquist, C. 1990. Reserves Estimation, PetroleumEngineering Manual. IHRDC Publishers, Boston,MA, PE 508, pp. 53-56.
Deming, D., and Chapman, D.S. 1988. "Heat Flow inthe Utah-Wyoming Thrust Belt from Analysis ofBottom-hole Temperature Data Measured in Oiland Gas Wells," Jour. ofGeophys. Res., Vol. 93,Nov. 1988, pp. 13,667 - 13,672.
Energy Resources Conservation Board. 1991.Alberta's Reserves ofCrude Oil, Oil Sands, Gas,Natural Gas Liquids, and Sulphur. Calgary, AB.
Hermanrud, C., Cao, S., and Lerche, I. 1990."Estimates of Virgin Rock Temperature Derivedfrom BHT Measurements: Bias and Error."Geophysics, Vol. 55, Jul. 1990, pp. 924-931.
Hermanrud, C., Lerch, I., and Meisingset, KK 1991."Determination of Virgin Rock Temperature fromDrillstem Tests." JPT, Vol. 43, Issue 9, Sep.1991, pp. 1126-1131.
Lam, H.L., and Jones, F.W. 1984."A StatisticalAnalysis of Bottom-hole Temperature Data in theHinton Area of West-Central Alberta."Tectonophysics, Vol. 103, pp. 273-281.
Lam, H.L., Jones, F.W., and Majorowicz, J.A. 1985."A Statistical Analysis of Bottom-holeTemperature Data in Southern Alberta."Geophysics, Vol. 50, Apr. 1985, pp. 677-684.
85
Ib-. _
5.8 RESERVOIR PRESSURE
5.8.1 IntroductionThroughout the productive life of a reservoir, arecord of its pressure is necessary in order to make anumber of necessary calculations. Initial pressures obtained after the discovery of a pool are needed for thecalculation of volumetric reserves, particularly for gasreservoirs. Reservoir pressure is needed to determinegas compressibility and formation volume factors foroil and natural gas, and to undertake PVT analysis.Material balance calculations for both oil and gas systems require initial reservoir pressures and subsequentpressure history after production has commenced.
Fluids flow when a pressure difference is createdbetween two points. When hydrocarbons are removedfrom a reservoir, a pressure drop is created in thewellbore. This causes the pressure within the formationto drop. When a flow of fluid is stopped or "shut in,"the pressure will equilibrate until it reaches stablereservoir conditions. The time required to reach a stabilized pressure varies from reservoir to reservoir. Analysisof the pressure stabilization or "buildup" will revealinformation about the permeability of the formation, thedistance to reservoir boundaries, and any damage to theformation. If stable conditions are not reached, the pressure buildup data may be extrapolated to estimate thereservoir pressure.
5.8.2 Data SourcesTwo types of pressure recorders are available tomeasure reservoir pressures: mechanical and electronicgauges. The mechanical gauge consists of a coiledbourdon tube pressure element, which spirals outwardas pressure is increased inside it. A stylus on the end ofthe tube scribes a thinly coated metal chart, which isslowly rotated by a clock in the recorder. The distancethe stylus moves is proportional to the pressure insidethe bourdon tube.
Electronic gauges use strain, capacitance transducer,and quartz gauges as pressure-sensing devices. Theserecorders offer the option of programmable samplingtimes, and are generally more accurate than mechanicalrecorders.
All pressure gauges must be calibrated to ensure thatcorrect pressures are being recorded. Generally, regulatory agencies are responsible for setting guidelines forgauge calibration. It is important that gauges used forpressure surveys be calibrated regularly.
It is common practice to use at least two recordersduring pressure surveys to ensure that representativedata
86
DETERMINATION OF OIL AND GASRESERVES
is recovered even if one recorder should fail. Runningtandem recorders also permits comparison between thetwo to verify the accuracy of the measurements.
Pressure measurements are usually obtained bylowering these recorders or "bombs" down the wellbore.As discussed in Section 5.6.2, the first indication of thepressure of a formation may come from a drillstem test(DST), which is usually conducted before productioncasing is run into the wellbore (but cased-hole DSTsare not uncommon). DSTs are also run immediatelyupon penetration ofa prospective formation in order toexamine its potential before drilling fluids damage the
.zone.
After drilling operations are finished and the well hasbeen completed for production, pressure measurementsare usually obtained by lowering pressure recordersdown the wellbore on a wire line. In some instances,the pressure recorders are left downhole for extendedperiods of time. In other circumstances recorders measure the reservoir pressure for only a few minutes. Thelatter type of pressure measurement is referred to asa static gradient. This measures wellbore pressures atdifferent depths, and these pressures are plotted againstthe measurement depth. The resultant plot is usedto identify density changes in the wellbore fluids.Pressure gradients at reservoir depth are also estimated.Production tests are commonly conducted when pressure recorders are left downhole. When left for a periodof time, pressures are recorded vs. time. Figure 5.8-1 isan example of data from a static gradient, and Figure5.8-2, from a flow and buildup test.
Formation pressures may also be measured before thewell is completed by running open-hole wireline tools.These tools push a probe into the formation and recordthe formation pressure.
Bottom-hole pressures are also estimated by measuringsurface pressures and adding the calculated pressure dueto the hydrostatic head offluid in the wellbore. In caseswhere gas and liquid are both present in the wellbore,acoustic level indicators are employed to determine thefluid level. The respective hydrostatic heads ofthe fluids are then calculated and added to the surface pressureto estimate the bottom-hole pressure.
5.8.3 Data AnalysisA major problem in recording pressure data isdetermining whether the reservoir pressure is actuallystabilized. There are three widely accepted methods ofobtaining a stabilized bottom-hole pressure. The firstinvolves the gathering and extrapolation of pressure
..
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
Figure 5.8-2 Pressure vs. Time
Pressure Recorder Data
Time Pressure Comments(h) (kPa)
0 20175 begin flow1 9830 continue2 8750 "4 7290 "8 5570 "
24 5050 "60 5030 "90 4670 "
140 4665 stop flow140.11 5577 continue140.25 5924 "140.50 6435 "140.75 6743 "141.2 7656 "142.25 9 163 "144 11077 "148 13338 "152 14273 "156 14878 "160 15345 "170 16146 "180 16681 "190 17 074 "210 17623 "230 17996 "350 18989 end of test
As previously stated, the time function [(HLlt)/Llt) mustbe calculated. The time, t, is 140 hours, and sinceLlt is the elapsed time since the well was shut in, 140must be subtracted from all the times once the buildup
produced fluid prior to being shut in, and the variable,dt, is the elapsed time since the well was shut in.Plotting the data on semi-log paper theoretically revealsa straight line when the infinite acting radial flowperiod is reached. Extrapolation ofthis data to the semilog value of I yields the theoretical static reservoirpressure. The semi-log value of I corresponds to ashut-in time of infinity.
Example 1
This example shows how to extrapolate builduppressure to obtain a static reservoir pressure.
Pressure recorders were lowered into a new oil well.The well was flow-tested for 140 hours at a constantrate and then shut in to allow the reservoir pressure tobuild. The data shown in the following table wasobtained from pressure recorders.
400300200Time (h)
100
26,.------------------,2422
as 20ll.... 18
(t'jX 16
C14~ 12~ 10
= 8•d: 642o+-~_~-_-~-~~-_--I
o
buildup data. The second utilizes a static pressuremeasurement, where the shut-in time to reach stabilization is determined from previous buildup tests. The thirdmethod is also a static pressure measurement, but theshut-in time of the well is arbitrarily set.
The method most commonly used to extrapolatepressure data was first discussed by Horner (1951). Theprocedure involves the plotting ofpressure data duringbuildup vs. a time function [(Hdt)/dt) on a semi-logplot. The time, t, is the time during which the well
Figure 5.8-1 Static Gradient
0Depth Pressure
200
~(m) (kPa)
0 11784300 12129
400 600 12474900 12819
600 1200 131641500 13509
800
~1800 148622100 17532
10002150 179772200 184222250 18867
g 1200 2300 197572388 20095
=1i. 1400
~----- Slope = 1.15 kPaim•Q1600 -.\1800 \~ Fluid contact @ 1670 mK8
2000Slope =8.9 kPaim/
2200
2400
260010000 14000 18000 22000
Pressure (kPa)
87
b _
--DETERMINATION OFOILANDGASRESERVES
01-02-003-04 W5MTriassic930m
2397.0 mKB930.0m
-2397.0 m
However, if the reservoir is not at stable conditions, orifdepletion is thought to have occurred, a buildup analysis is very useful in the determination ofstable reservoirpressures.
Once pressure data for a reservoir has been collectedfrom two or more wells, the data should be corrected toa common datum depth. Many hydrocarbon reservoirsvary in elevation from one end to the other. In thesesituations, a common pool elevation or datum is generally established. When pressure data is recovered fromwells that have different elevations, the pressure datamust be corrected to this datum depth. The pressure gradient is multiplied by the difference in elevations, andthe result is added to or subtracted from the uncorrecteddata. This procedure will correct all pressures collectedfor a given reservoir to a common datum depth.
Example 2
This example illustrates how to determine the datumpressure for two wells.
Pool Datum is at 1467m subsea
09-02-003-04W5MTriassic983 m
2460.0 mKB983.0 m
-2460.0 m
Well:Formation:KB· elevation:Top of formation:
Formationtop: -I 467.0 mss -1477.0 mss
Date: October 3, 1991 October 3, 1991Recorderrun depth: 2388.0mKB 2453.0mKB
(-1458.0 mss) (-I 470.0mss)Pressure atrun depth: 20095 kPa 20197 kPaPressure gradient(obtained fromstatic gradient) 8.9 kPa/m 8.8 kPa/mPressure at -1458.0 mss -1470.0 msspool datum: -I 467.0 mss -1467.0 mss
9.0m -3.0m
9.0m -3.0mx 8.9 kPa/m x 8.8 kPa/m
80.1 kPa -26.4 kPa
20095.0 kPa 20197.0kPa+80.1 kPa -26.4 kPa
20 175.1 kPa 20170.6 kPa
• KB = The elevation of the drilling platform at the kellybushing.
Time (t+4.t)/M Pressure(h) (kPa)
0 - 46650.11 1273.7 55770.25 561.0 59240.50 281.0 64350.75 187.7 67431.20 117.7 76562.25 63.2 9 1634 36.0 II 0778 18.5 13338
12 12.7 1427316 9.75 1487820 8.00 1534530 5.67 1614640 4.50 1668150 3.80 1707470 3.00 1762390 2.56 17996
210 1.67 18989
2624
"' ~~~Extrapolated pressure of20 175kPa
~ 18x 16
"0 14::. 12~ a
~ 10 D
III 8 . D
~ 6 a a a~ a
42o -I---~-__~__~ -I
1 10 102 103 104[(1 + 61)/61]
portion ofthe test begins. The resultant data is shown inthe following table:
Horner Time Data
When the data has been plotted on semi-log paper, atrend can be seen toward the end of the buildup (Figure5.8-3). When the trend is extrapolated, the intersectionof the line with a time value of I (which means infinitet.t) indicates the theoretical pressure the reservoir willreach. The extrapolated pressure was estimated to be20 175 kPa.
Figure 5.8-3 Horner Plot
In this example, the first pressure point recorded matchesthe calculated pressure found by the Homer analysis. Incases where the initial reservoir pressure is at staticconditions, a buildup analysis is not necessary.
88
s
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
Datum pressures for the two wells are 20 175 kPa and20 171 kPa at 1467 m below sea level.
Once a datum pressure has been determined for all wellssurveyed in a pool, it may be determined that the pressures still vary from point to point. What must be foundnow is the average reservoir pressure; three methodsare commonly used. The first is an arithmetic average.The second is an area-weighted average, where areas ofthe reservoir that have similar pressures are groupedtogether. The area-weighted average is the sum of theproducts of areas times pressures divided by the totalarea. The third method is the volume-weighted average. This method may utilize the rock volume, porevolume or hydrocarbon pore volume. The followingequations summarize the three methods:
Arithmetic average P= l:(P) / n (I)
Area-weighted average P = l:(Pi X AJ / A, (2)
Volume-weighted average P = l:(Pi X VJ / V, (3)
where P = average reservoir pressurePi pressure pointn = total number of points
20000 kPa
Ai = area of common pressure1\ = total reservoir areaVi = volume ofcommon pressureV, = total reservoir volume
Example 3
This example illustrates how to estimate the averagereservoir pressure using the arithmetic, area-weightedand volume-weighted methods.
The porosity volume map in Figure 5.8-4 was found tohave the volumes for the four constant pressure areas asshown in the following table:
Calculation of Average Reservoir Pressure
Pressure Area Volume(kPa) (ha) (ha.m)
20000 115 140420050 179 442520100 155 I 93020150 90 435
20050 kPa20100 kPa
20080 kPa •
20150 kPa
•20000 kPa
o I ha(lOOmx 100m)
20040 kPa: 20060 kPa
• .:····:~20m •
15 m
• 20 090 kPa~.:-:-·-'----- 5 m•20110 kPa
--- om
•:20 120kPa
20130 kPa
•
20 140kPa:
•
•20170 kPa
•20175 kPa
Area of 20 000 kPa pressureArea of20 050 kPa pressureArea of20 100 kPa pressureArea of20 150 kPa pressure
Total area of pool
liS ha179 haISS ha90ha
539 ha
Volume of20 000 kPa pressureVolume of 20 050 kPa pressureVolume of 20 100 kPa pressureVolume of 20 ISO kPa pressure
Total volume of pool
1404 ha·m4425 ha-m1930 ha-m435 ha·m
8194 ha-m
7
Figure 5.8-4 Porosity Volume Map
89
Arithmetic Average
~(P,) = 20 000 + 20 040 + 20 060 + 20 080+ 20 090 + 20 110 + 20 120 + 20 130+ 20 140 + 20 170 + 20 175= 221 115 kPa
n = 11
P = ~(PYn = 221 115 kPa /11= 20101 kPa
Area-Weighted Average
~(Pj x Ai) = (20000 x liS) + (20 050 x 179)+ (20 100 x ISS) + (20 ISO x 90)= 10 817 950 kl'a x ha
A, = 539 ha
p = ~(Pj x Ai)/A,= 10817 950 kPa x ha / 539 ha= 20070 kPa
90
DETERMINATION OF OILAND GASRESERVES
Volume-Weighted Average
~(Pj x V) = (20000 x 1404) + (20 050 x 4425)+ (20100 x 1930) + (20 ISO x 435)
= 164359500kPaxhaxm
V, = 8194haxm=81.94x 106m3
p = ~(Pj x Vj)N,= 164359500 kPa x ha x m / 8194 ha x m= 20058 kPa
It should be noted that in this case the arithmetic andarea-weighted averages result in higher pressures thanthe most rigorous volume-weighted average.
ReferencesHomer, D.R. 1951. "Pressure Build-up in Wells."
Proc., 3rd World Petroleum Congress, E. 1. Brill,Leiden, Netherlands, Vol. II, p. 503.
s
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
In order to calculate the amount of gas in a closedchamber of fixed volume, two more constants must bedefined: the first is the moles of gas, which is essentially the number ofmolecules ofgas; the second is thegas constant. The resultant equation is known as the IdealGas Law and expressed as follows:
(2)
(3 )PXV=ZxnxRxT
PXV=nxRxT
where P = pressure of gas in containerV = volume of gas in containern = moles of gas in containerR = gas constantT = temperature 0 f gas in container
5.9.3 Gas Compressibility FactorThe Ideal Gas Law may be used to calculate theproperties ofgases at moderate temperatures and pressures; however, the law does not hold true at hightemperatures and pressures. To correct for the deviation, a term called the "gas compressibility factor"or "gas deviation factor," Z, must be included iri theequation.
The gas compressibility factor is designed to correct thevolume of a theoretical ideal gas to the volume occupied by a real gas. This factor can be determined in thelaboratory by measuring the actual volumes of a givenamount ofgas at prescribed pressures and temperaturesand comparing these to the ideal volumes calculated bythe Ideal Gas Law. It should be noted that the compressibility factor will change with temperature, pressure andgas composition.
In cases where the gas compressibility factor is notobtained from detailed laboratory work, it can be closelyestimated by first calculating two pseudo-critical properties that are used to determine the compressibilityfactor of a natural gas: pseudo-critical pressure andpseudo-critical temperature. Both of these can be calculated if the composition of the gas is known. Gascompositions are usually determined by gas chromatography on gas samples; each component is expressedas a mole fraction of the total.
To calculate the pseudo-critical properties of a naturalgas, the critical pressure and critical temperature ofall the components are needed. These values are available in numerous publications, such as the EngineeringData Book (Gas Processors Suppliers Association,1980). The pseudo-critical pressure of a gas is definedas the sum of the products ofthe mole fraction of eachcomponent times the critical pressure of that component. The pseudo-critical temperature is the sum of theproducts of the mole fraction of each component timesthe critical temperature of that component. The equations for calculating the pseudo-critical properties areas follows:
(I)
1200 kPa x 0.125 m'
450'K
1000 kPa x 0.1 m'
300'K
where the subscript I signifies the first set of conditions, and the subscript 2, the second set of conditions.Equation (l) assumes that the amount of gas in thesystem does not change, and that the gas behaves as anideal gas.
Example 1
A balloon has a volume of0.1 m3 at 1000 kPa and 300°K.If the contents of the balloon are heated to a temperature of450oK, either the pressure or the volume (or both)must change. In this case, it is assumed that both change,so that the pressure is now 1200 kPa and the volume is0.125 m3• The pressures, volumes and temperatures atboth conditions would be related as follows:
5.9 GAS FORMATION VOLUMEFACTOR
5.9.1 IntroductionIn order to determine the gas formation volume factor,Bg, which relates the volume of gas in the reservoir tothe volume at the surface at standard conditions of'temperature and pressure, it is necessary to fully understandgas behaviour. This is explained in the four subsectionsthat follow. Often the terrns in the Bg determination(Equation 15 in Section 5.9.5) are used directly in theequation for calculating in-place gas volumes, but it isuseful to have Bg as one term for hand calculations andsimple material balance work.
5.9.2 Ideal Gas LawThree properties affect the amount ofgas in a reservoir:pressure, P, temperature, T, and volume, V. The 19thcentury chemists, Boyle and Charles, found that for agiven amount of gas (see Example 1) the followingrelationship holds true:
P, X V, P, xV,=
T, T,
91
b
(8)
(9)
P, = L(Xj x P;) (4)
T, =L(Xj x T;) (5)
where P, = pseudo-critical pressure
T, = pseudo-critical temperature
x j = mole fraction of component i
P j = critical pressure of component iT j = critical temperature ofcomponent i
Thomas et al. (1970) found that the pseudo-criticalproperties may also be estimated using the specific gravity of the gas. The specific gravity, SG, is the ratio ofthe gas density to the density of air.
P, = 4892.547 - (404.846 x SG) (kPa) (6)
T, =94.717 + (170.747 x SG) (OK) (7)
Once the pseudo-critical properties are found for agiven gas, the pressure and temperature of the gasin the reservoir are needed to calculate the pseudoreduced properties of the mixture. The pseudo-reducedpressure is the ratio ofthe actual pressure to the pseudocritical pressure. The pseudo-reduced temperature is theratio of the actual temperature to the pseudo-criticaltemperature.
P, = PIP,
T, =TIT,
where P, = pseudo-reduced pressure
P = pressure of natural gas systemT, = pseudo-reduced temperatureT = temperature ofnatural gas system
Once the reduced properties ofthe natural gas at a givenpressure and temperature have been calculated, the gascompressibility factor can be determined by the use ofagas compressibility factor chart (Figure 5.9-1) publishedby Standing and Katz (In Standing, 1977). The gas compressibility factor may also be determined by the use ofa computer algorithm (Dranchuk et al., 1977).
Example 2
This example illustrates how to estimate compressibilityfactor of natural gas from a southern Alberta gas well.
Well location: 02-03-004-05 W6MFormation: Bow IslandInitial formation pressure: 6790 kPaFormation temperature: 296° K (23°C)
92
DETERMINATION OFOIL AND GAS RESERVES
Gas Analysis
Mole Critical CriticalComponent Fraction Press. Temp.
(kPa) (OK)
Helium (He) 0.0012 227.53 5.23Nitrogen (N2) 0.0469 3399.00 126.10Methane (C1) 0.9322 4604.00 190.55Ethane (C2) 0.0129 4880.00 305.43Propane (C3) 0.0045 4249.00 369.82iso-Butane (iC4) 0.0007 3648.00 408.13n-Butane (nC4) 0.0009 3797.00 425.16iso-Pentane(iC5) 0.0003 3381.00 460.39n-Pentane (nC5) 0.0002 3369.00 469.60Hexane (C6) 0.0002 3012.00 507.40
Total 1.0000
Pc = L(xixPi) 4541.87kPa
T, = L(xi x Ti) 190.16°K
P, = 6790 I 4541.87 1.49
T, = 296 I 190.16 1.56
Z = 0.88 ( from Standing and Katz chart )
In compatison, ifonly the specific gravity were known,P, and T, would be estimated as follows:
Specific gravity = 0.587
P, = 4892.547 - (404.846 x 0.587) = 4654.902 kPa
T, = 94.717 + (170.747 x 0.587) = 194.945°K
P, = 6790 I 4654.902 = 1.46
T, = 296/194.945 = 1.52
Z = 0.87 ( from Standing and Katz chart)
5.9.4 Sour GasCalculating Z using the method described works wellfor sweet gases-natural gases that do not containcarbon dioxide (C02) or hydrogen sulphide (H2S).Natural gases that do contain carbon dioxide and hydrogen sulphide are called sour gases. Estimation ofthegas compressibility factor of sour gases was found tobe incorrect when using the chart published by Standing and Katz, and several methods have been developedto estimate the correct compressibility factor for sourgases. Wichert and Aziz (1972) compared two of thesemethods to one that uses the Standing and Katz chart. Itwas found that the chart could be used if the pseudocritical temperature and pseudo-critical pressure wereadjusted. An adjustment factor, e, was developedby Wichert and Aziz to correct the pseudo-critical
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
0.915141310 11 12
Pseudo-reduced Pressure98
0.97
0.3 1.2
0.25
1.12.8
1.12.4 2.6 2.'
2.2 Compressibility of
'/.~ \.9 Natural GasJan. 1, 1941
1.0 1.01,1
Pseudo-reduced Pressurea 1 2 3 4 5 6 7 8
1.1 1.1Pseudo-reduced
Temperature3,02,8
1.0 2.6 1.02.4 1.052,2 1.2
2.0 0.95
1.90.9 1.8
1,7
1,6
0.8 1.71,5
1.45
1.40.7 1.6
1.35
N N..: 1.3 ..:a a- .. tio 0.6 1.5'" 1.25 '"LL LL>. ,~ >.~ ,~ "":c 1.2
,~:c
'00 '00en
~~(fJ
<ll 0.5 1.4 <ll~ \~
~
0. 0.E '/.~ Ea -» aU U
0.4 1.3
Source: Standing, 1977.
Figure 5.9-1 Compressibility Factors for Natural Gases
93
•
DETERMINATION OF OIL AND GASRESERVES
6056.39 X 254.98
Po' = 273.18 + 0.3003 (1-0.3003) X 5/9 (32.77)
= 5574.83 kPa
P, = :E(xi X P) = 6056.39 kPa
T, = :E(xi X T) = 273.18 OK
e = 120 x (0.3762°·9 - 0.37621.6) +
15 X (0.3003°.5 - 0.3003 4)
= 32.77
T,' = 273.18 - 5/9 (32.77) = 254.98 OK
(11)
properties. The factor may be determined graphicallyor by using the following equation:
e = 120 x (AO.9 - A1.6) + 15 X (B°.5- B4) (10)
where A = combined mole fraction of COz andHzS
B = mole fraction of HzS
The pseudo-critical temperature and pseudo-criticalpressure are estimated in the normal manner and thenadjusted as follows:
Gas Analysis
03-02-004-05 W6~Rundle34300 kPa359 OK (86°C)
(13)
r, x Te'P' = (12)
c T, + B x (1-B) x (5e/9)
where Tc' = adjusted pseudo-critical temperatureP,' = adjusted pseudo-critical pressure
Example 3
The adjustments described are detailed in this exampleof a sour natural gas well from the Foothills area ofAlberta.
Well location:Formation:Initial formation pressure:Formation temperature:
Mole Critical CriticalComponent Fraction Press. Temp.
(kPa) (OK)
Nitrogen (N,) 0.0104 3399.00 126.10Sulphide (HzS) 0.3003 9005.00 373.50Carbon dioxide(COz) 0.0759 7382.33 304.19Methane(Cl) 0.5277 4604.00 190.55Ethane (C2) 0.0358 4880.00 305.43Propane (C3) 0.0079 4249.00 369.82iso-Butane(iC4) 0.0018 3648.00 408.13n-Butane(nC4) 0.0041 3797.00 425.16iso-Pentane(iC5) 0.0020 3381.00 460.39n-Pentane (nC5) 0.0022 3369.00 469.60Hexcane(C6) 0.0059 3012.00 507.40Heptane + (C7+) 0.0260 2486.00 568.76
Total 1.0000
P, = 34300/5574.83 = 6.15T, = 359/254.98 = 1.41Z = 0.87 ( from Standing and Katz chart)
In comparison, if the critical properties had not beenadjusted, the compressibility factor would have beenestimated to be 0.77, a difference of 11.5 percent. Useof the incorrect compressibility factor in estimatingreserves would result in large errors.
It should be noted that the compressibility factorestimated is only correct at the pressure and temperature used in calculating the pseudo-reduced pressure andpseudo-reduced temperature. When the compressibility factor of a gas is required for material balancecalculations, each pressure point requires that a corresponding compressibility factor be estimated.
5.9.5 Derivation of Gas FormationVolume Factor
Gas formation volume factor, Bg• relates the volumeof gas in the reservoir to the volume on the surface atstandard conditions of temperature and pressure and isoften used to simplify hand calculations ofgas reserves.For the purpose of estimating reserves, Bg is generallyexpressed as the amount of space occupied at standardconditions by a unit volume ofgas under reservoir conditions. The dimensions ofBg are unit volume at standardconditions per unit volume at reservoir conditions, andtherefore, Bg is dimensionless.
Derivation of Bg begins with the following equationfor nonideal gases:
P,x V, P; x V;
Z,T, Z;T;
where P" V" Z, and Ts are all measured at standardsurface conditions, and Pi' Vi' Z, and T, are allmeasured at initial reservoir conditions. Transposing
94
r
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
tenus, Bg (as defined in this section) is derived asfollows:
v voIume 0 f gas underB = -' = standard surface conditions
g Vi per unit volume ofreservoir space
Assuming that Vi is one unit volume ofreservoir space,and that the gas compressibility factor, Z" at standardsurface conditions is unity, Bg can be reduced to:
ReferencesDranchuk, P.M., Purvis, RA., and Robinson, D.E.
1977. "Computer Calculation ofNatural GasCompressibility Factors using the Standing andKatz Correlations." Institute of PetroleumTechnology, IP-74-008, Vol. I.
Gas Processors Suppliers Association. 1980.Engineering Data Book, Tulsa, OK.
Standing, M.B. 1977. "Volumetric and PhaseBehavior of Oil Field Hydrocarbon Systems."SPE of AIME, Dallas, TX.
Thomas, H.K., Hankinson, RW., and Phillips, K.A.1970. "Determination of Acoustic Velocities ofNatural Gas." JPT, Vol. 22, pp. 889-895.
Wichert, E., and Aziz, K. 1972. "Calculate Z's forSour Gases." Hydrocarbon Processing, May1972.
(14)
(15)
Bg may now be substituted into the equation forcalculating in-place volumes of nonassociated and gascap gas.
95
DETERMINATION OF OILANDGASRESERVES
1.00 -¥-----,r---r--,----,--.-----,
Figure 5.10·1 Comparison of FormationVolume Factor by Differential andFlash Liberation
60005000
FlashLiberation
I
1.10
1.20
1.90
2.10 Bodb(2.074)
_
j' 1:'0...)t..__ Differential liberation~I.I.- I
4 1.1._4 __.11.
II
Bo1b(1.723)-/-
/' )/A :§l
/ :/ g
A ;-
~!a.e
1'"
2.00
1000 2000 3000 4000Pressure (psig)
Source: Chevron CanadaResources.
fi~ 1.80
~l5 1.70
~Q) 1.60
5~ 1.50
~ t 40..~ 1.30
5.10.3 Data AcquisitionBefore representative samples of the reservoir fluid arecollected, it is important that the well be properly conditioned. A complete well conditioning and samplingprocedure is described in Chapter 5.6.
In most reservoirs, the variations in reservoir fluidproperties among samples taken from different parts ofthe reservoir are not large, and lie within the margin oferror inherent in the techniques of fluid sampling andanalysis. On the other hand, some reservoirs, particularly those with large closures, have large variations influid properties, which may be explained by a combination of the temperature gradients, gravitationalsegregation, and lack of equilibrium between the oiland the solution gas. Methods for handling reservoircalculations where there are significant variations in thefluid properties have been documented in the literature(Cook et al., 1955; McCord, 1953).
5.10.4 Data AnalysisThe composition of the stock tank oil will be quitedifferent from the composition ofthe original reservoirfluid. Most of the methane and ethane will have beenreleased from solution, and sizeable fractions of thepropanes, butanes and pentanes will have vapourizedas the oil moves from the reservoir to the stock tankand the pressure is reduced. The change in liquidcomposition is not a single nor a well-defined process,
5.10.2 Data SourcesA laboratoryanalysis of fluid properties is the best sourceofdata to estimate the FVF. It is preferable that the laboratory analysis be made on a sample obtained duringthe completionofthe discovery well, and that the samplerepresent as nearly as possible the original reservoirfluid. This will ensure that the original FVF is accurately determined with respect to the bubble point and adecline in the bottom-hole pressure.
Figure 5.10·1 shows the oil FVF in a typical high.gravity undersaturated oil reservoir when the reservoirpressure declines from the initial pressure to stock tankcondition as determined from a laboratory analysis (thesymbols shown in this figure are defined in Example 2,Section 5.10.5.)
The oil FVF can also be estimated from empiricalmethods and correlations available from the technicalliterature (Amyx, 1960). A correlation prepared by Katz(1942) from data on mid-continent crudes requires thereservoir temperature, and the pressure, gas-oil ratio,and API gravity ofthe crude. A second empirical correlation developed by Standing (1947) for Californiafluids requires the total gas-oil ratio, the gravity of thestock tank oil and produced gas, and the reservoirtemperature.
5.10 OIL FORMATION VOLUMEFACTOR
5.10.1 IntroductionTheformation volumefactor (FVF) for oil is defined asthe volume in cubic metres (barrels) that one stock tankcubic metre (barrel) occupies in the formation at theprevailing reservoir temperature and pressure. A stocktankcubicmetre(barrel) is defined as the volume occupied by one cubic metre (barrel) ofcrude oil at standardpressure and temperature, which are 101.325 kPa and15°C (14.65 psi and 60°F) respectively. Crude oil inthe ground always contains varying amounts of dissolved gas (solution gas). Because both the temperatureand the solution gas increase the volume of stock tankoil in the formation, the FVF will always be greater thanone. The symbol B, is used in equations to refer to theformation volume factor.
The reciprocal of the FVF is called the shrinkagefactor. Just as the formation volume factor is multipliedby the stock tank volume to find the reservoir volume,the shrinkage factor is multiplied by the reservoir volume to find the stock tank volume. Although both termsare in use, most petroleum engineers use formationvolume factor.
96
1ESTIMATION OF VOLUMES OF HYDROCARBONS IN PLACE
but is a series of flash and differential liberationprocesses.
The difference between these two processes is that inthe flash liberation process, all of the gas remains incontact with the liquid, while in the differential process, some ofthe gas is released (removed from contactwith the liquid phase). For this to be so, the volume ofthe system in the flash process must increase as the pressure declines. Thus the flash process is one ofconstantcomposition and changing volume, and the differentialprocess is one of constant volume and changingcomposition.
In the case of reservoir fluids which are at their bubblepoint when the pressure declines as a result ofproduction, the gas liberated from the oil does not flow to thewell, but accumulates until a critical gas saturation isreached. This critical saturation will be reached soonerin the vicinity of the well where the pressure is lowerthan at more distant points, particularly for wells producing under large pressure drawdowns. With gassaturations greater than critical near the well, the gaswill move more rapidly than the oil (differential liberation), whereas in the remainder of the reservoir theliberated gas will remain in contact with the oil (flashliberation). The volume ofthe reservoir surrounding theproducing wellbore, where the gas is highly mobile, isusually only a small part ofthe total drainage area. Thus,where there is a more moderate pressure decline belowthe bubble point in the larger part of the reservoir, theflash liberation is more representative.
On the other hand, when the gas saturation exceeds thecritical value in most of the drainage area, the gas willflow much faster than the oil. This situation would becharacterized by producing gas-oil ratios considerablyin excess of the initial solution gas-oil ratio. With theremoval of gas from contact with the oil, differentialliberation more closely represents the reservoir behaviour. Consequently, differential liberation data shouldbe applied to the reservoir fluid when the reservoir pressure has dropped considerably below the bubble-pointpressure and the critical gas saturationhas been exceededin most of the reservoir.
Flow through tubing and a choke is a decliningpressure flash liberation in which the gas remains inequilibrium contact with the oil throughout the process.There are, however, important differences betweentubing flash and laboratory flash liberation. Tubingflash liberation is accompanied by declining temperatures and, where the gas-oil ratio exceeds the initialdissolved ratio, the oil is in contact not only with its
own liberated gas but with additional gas producedfrom either the oil zone or a gas cap. In contrast thelaboratory flash liberation is isothermal, and only thegas liberated from the sample is in contact with theliquid.
When the volume of dissolved gas in the crude oilis low (indicating low volatility), there are only slightdifferences between the flash and differential liberationdata. Under these circumstances the residual barrel bythe differential process may be identified with the stocktank barrel, and differential liberation data may be useddirectly in the oil-in-place equation. Experience indicates that low volatility conditions may exist where thefollowing are present: the stock tank gravity is below30° API; the solution gas-oil ratio is less than 70 m3/m3
(400 scf/stb); and the reservoir temperature is below54°C (130°F). These are, of course, only approximatelimits.
When the volatility of the crude is high, as in theexample shown in Figure 5.10-1, more considerationshould be given to the predominant gas liberation mechanism occurring in the reservoir, in the wellbore, and insurface separation facilities. The FVF used may moreclosely approach that of a flash liberation (Craft andHawkins, 1959).
In a simple analysis, where only one FVF vs. pressurerelationship is used, industry practice tends toward using an estimated flash liberation relationship. It may beargued that the flash process in the wellbore is the finalequilibrium that the oil and gas phases must adjust to.Also, the pressure drop from bottom-hole pressure toseparator pressure often amounts to a large fraction ofthe total pressure decline from formation pressure. In acommon industry compromise, the differential liberation FVF curve is shifted by the ratio between the flashand differential liberation FVFs at the bubble-pointpressure (refer to Example 2 in Section 5.10.5).
In reality, however, each producing system is differentand each should be examined closely to determine wherethe major pressure drops are occurring. In some cases,further testing and facility modelling may be warrantedin order to maximize liquid production. Figure 5.10-1shows the FVF calculated by both the flash and differential processes for a more volatile crude oil having agravity of 46.6° API. The difference between these twocurves is significant. This example helps to illustratethe variability of FVFs, and the importance of understanding the impact of each liberation process in theproducing system.
97
.iII? _
...DETERMINAnON OF OIL AND GAS RESERVES
Example 2: At Pressures Below Bubble Point
(2)
= 0.9750 (Table 5.10-1)
= 1.723 (Table 5.10-2)
= 1.723 (0.9750) = 1.680
VIVs. ,
Bod = 1.767 (Table 5.10-3)
Bofb = 1.723 (Table 5.10-2)
Bodb = 2.074 (Table 5.10-3)
d. 1.723
a [usted Bo = 1.767 x -- = 1.4682.074
and
and
for oil compressibility. This is done by adjusting themeasured volume at saturation pressure using thefollowing equation:
adjusted B,
where adjusted B,= Bofbx VIVs•t (I)
= flash formation volume factorfor pressures above saturationpressure
= formation volume factor fromflash at saturation pressure
= relative volume from pressurevolume relations at pressureabove saturation pressure
For example, if the reservoir pressure is 27 600 kPa(4000 psig),
then VIVsat
Bofbadjusted B,
Because oil shrinkage occurs due to gas liberation atpressures below the saturation pressure, flash FVFs thatare referenced to a volume at saturation pressure mustbe corrected to reflect this shrinkage. The adjustment ismade using the following equation:
BOlliadjusted n, = Bod B
, cdb
where adjusted B, = flash formation volume factorfor pressure below saturationpressure
= relative oil volume from differential liberation at pressurebelow saturation pressure
= formation volume factor fromflash at saturation pressure
= relative oil volume from differential liberation at saturationpressure
For example, if reservoir pressure is 14500 kPa (2100psig),
then
5.10.5 Data AdjustmentIn the calculation ofa flash FVF, it is often necessary toadjust the data from a laboratory fluid analysis to moreappropriately represent the true producing conditions.Normally, flash separation data in a laboratory analysisis referenced to reservoir fluid volumes at the saturation pressure (bubble point). The following twoexamples show how the data from a reservoir fluid studyis used to calculate the flash FVF for producing reservoir conditions. The data is provided in Tables 5.10-1,5.10-2 and 5.10-3.
'Table 5.10-1 Pressure Volume Relations
Pressure Relative Volume *(psig) VN••t
6000 0.93985500 0.94735000 0.95564500 0.96484000 0.97503500 0.98673300 0.99213200 0.99493100 0.99793029 1.00003010 1.00272993 1.00512982 1.00672948 1.01172773 1.04082571 1.08052333 1.14042098 1.22061849 1.33091622 1.47171390 1.67321298 1.7740
Source: PVT Analysis by Core Laboratories -Canada Ltd., on Chevron Pembina 1-9-50-12 W5M.Chevron Canada Resources, File 7013-795.
"Relative volume is in barrels at the indicatedpressure and temperature per barrel of saturated oil.
Example 1: At Pressures Above Bubble Point
Flash FVFs are normally referenced to a volume atsaturation pressure. At pressures above the saturationpressure, the flash FVF must be corrected to account
98
5
ESTIMATIONOFVOLUMES OFHYDROCARBONS INPLACE
Table 5.10-2 Separator Tests of Reservoir Fluid Sample
Separator Separator Gas-Oil Gas-Oil Stock Tank Formation Separator SpecificPressnre Temperature Ratio! Ratlo! Gravity Volume Volume Gravity of
(psig) (OF) (OAPI60°F) FactorJ Factor" Flashed Gas
reservoir
to 320 74 795 891 - - 1.121 0.725
to 0 74 288 290 46.6 1.723 1.007 1.226
Source: PVT Analysis by Core Laboratories - Canada Ltd., on Chevron Pembina 1-9-50-12 W5M. Chevron CanadaResources, File 7013-795.
'Cubic feet of gas @ 60°F and 14.65 psia per barrel of oil @ indicated pressure and temperature.
2Cubic feet of gas @ 60°F and 14.65 psia per barrel of stock tank oil @ 60°F.
3Barrels of saturated oil @ 3029 psig and 228°F per barrel of stock tank oil @ 60°F.
"Barrels of oil @ indicated pressure and temperature per barrel of stock tank oil @ 60°F.
Table 5.10-3 Differential Vapourization
Pressure Relative Oil Relative Total Solution Gas-Oil Gas Formation Gas Expansion(psig) Volume! Volume- Ratio! Volume Factor" FactorS
3029 2.074 2.074 1634
2700 1.947 2.184 1406 0.00568 170.65
2403 1.852 2.326 1231 0.00660 151.52
2100 1.767 2.533 1071 0.00764 130.89
1801 1.695 2.818 934 0.00901 110.99
1502 1.627 3.249 805 0.01098 91.07
1202 1.565 3.905 685 0.01384 72.25
900 1.504 5.080 568 0.01884 53.08
598 1.442 7.481 452 0.02882 34.70
300 1.363 14.802 318 0.05791 17.27
0 1.088 - 0 1.32043 0.757
Source: PVT Analysis by Core Laboratories - Canada Ltd., on Chevron Pembina 1-9-50-12 W5M. Chevron CanadaResources, File 7013-795.
IBarrels of oil at indicated pressure and temperature per barrel of residual oil at 60°F (Bg),
2Barrels of oil plus liberated gas at indicated pressure and temperature per barrel of residual oil at 60°F (BJ.
3Cubic feet of gas at 14.65 psia and 60°F per barrel of residual oil at 60°F CR,).4Cubic feet of gas at indicated pressure and temperature per cubic foot at 14.65 psia and 60°F (Bg) .
sCubic feet of gas at 14.65 psia and 60°F per cubic foot at indicated pressure and temperature: \lgas FVF (\lBg) .
99
5.10.6 SummaryProduction from the reservoir rock to the stock tankusually involves a combination offlash and differentialliberation processes. In determining a value for the oilformation volume factor, the overall flow process ofthe oil stream should be analyzed to determine wherethe major pressure drops occur and what weightingshould be given to the flash and differential FVFs. Ifthe volatility of the crude oil is high, there may be asignificant difference between the values of the FVFdetermined by the flash and differential processes(Figure 5.10-1). In such cases, the true FVF may moreclosely approach the flash liberation process. If thevolatility ofthe crude oil is low, only slight differencesbetween the flash and differential data are likely, anduse of the differential liberation data may be feasible.Future changes in producing procedures should alsobe considered in making any assessment of the oilformation volume factor.
100
DETERMINATION OFOILANDGASRESERVES
ReferencesAmyx, J.W., Bass, D.M., and Whiting, R.L. 1960.
Petroleum Reservoir Engineering. McGraw-Hill,New York, NY, pp. 429-435.
Cook, A.B., Spencer, G.B., Bobrowski, F.P., andChin, T. 1955. "A New Method of DeterminingVariations in Physical Properties of Oil in aReservoir, with Application to the Scurry ReefField, Scurry County, Texas." US Bureau ofMines Report, Feb. 1955.
Craft, B.C., and Hawkins, M.F. 1959. AppliedPetroleum Reservoir Engineering. Prentice-Hall,Inc., Englewood Cliffs, NJ, pp. 86-181.
Katz,D.L. 1942. "Prediction of the Shrinkage ofCrude Oils." Drilling and Production Practice,American Petroleum Institute, Vol. 137.
McCord,D.R. 1953. "Performance PredictionsIncorporating Gravity Drainage and Gas CapPressure Maintenance - LL-370 Area, BolivarCoastal Field." Trans. AIME, Vol. 198, No. 232.
Standing, M.B. 1947. "A Pressure-VolumeTemperature Correlation for Mixtures ofCalifornia Oils and Gasses." Drilling andProduction Practice, American PetroleumInstitute, Vol. 275.
2
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
5.11 QUALITY AND RELIABILITY OFDATA AND RESULTS
5.11.1 INTRODUCTIONThe quality and reliability of reservoir data reflectdirectly on the results obtained in preparing reservesestimates. As indicated in preceding sections, the conditions under which basic data are obtained and thelaboratory methods used to generate additional data areboth important elements that must be taken into consideration. Elementary reasoning and common sense arealso important elements in the process of preparingreserves estimates.
In the determination of reservoir rock properties andfluid saturations, it is common practice to rely on coredata as the reference point and to fit log analysis data toit. Consequently, the core data must reflect to the greatest degree possible the in situ conditions ofthe reservoir.Because of cost considerations, it is usually not possible to obtain cores under preferred conditions, such asspecifically prepared oil base muds, lease crudes, andoriented, pressurized, or sponge coring techniques. Thus,in most circumstances, conventional cores comprise thebest data available.
5.11.2 Permeability from CoresPermeability is a particularly important measurementobtained from cores because it provides an indicationof whether hydrocarbons may be effectively producedfrom intervals of interest. The reliability of the permeability measurements can be influenced by the coringprocedure (induced fractures or scale formation), weathering and storage effects, plug sample selection,preparation in the laboratory, and the measurementtechniques applied. Conventional core analyses are performed without the application ofsimulated overburdenpressure, and horizontal permeabilities are measured intwo directions at 90° to each other. The highest measured permeability is designated as "k.n,," and the otheras "~o'" A practical approach in most situations is toassume that the ~o measurements more closely represent the in situ reservoir permeability than the k.naxreadings for the following reasons:
I. Small fractures induced during the coring procedure may result in an excessively high kmax'particularly in limestones and dolomites.
2. Lack of overburden pressure usually results inhigh k.nax and ~o readings, particularly in poorlyconsolidated sandstones.
3. Core plugs represent extremely small samples ofthe reservoir rock and may provide higher or lowerpermeabilities than might be obtained if it werepossible to use much larger samples, particularly inheterogeneous reservoirs or reservoirs characterizedby vuggy porosity. In such cases, permeabilities derived from well production characteristics andpressure measurements may be more representativeof in situ reservoir conditions.
As a general rule, the larger the sample, the better thereservoir representation.
As previously mentioned, however, if the core wasoriented when it was originally cut, the k.nax and k"opermeabilities have greater importance and can berelated to actual directions in the reservoir.
In cases where clays contained in sandstone core sampleshave been dehydrated during the cleaning procedure,erroneously high values may be measured for both k.naxand ~o permeabilities.
Glaze may be created by core bit action, particularly onlimestone cores, and may obscure variations in corecharacteristics during visual inspection and result inunrepresentative sampling and in permeabilities that aremuch too low. Sandblasting is commonly used to remove the glaze during sample preparation. Logs shouldbe consulted during the sample selection procedure.
5.11.3 Porosity from CoresPorosity measurements made on core samples are lesssubject to error than permeability measurements. However, incomplete cleaning during laboratory plugpreparation may result in erroneously low porosity measurements. The laboratory techniques used to measurecore porosities may affect the accuracy of the results.Table 5.4-I in Section 5.4.2 provides a comparison oftechniques.
Since most laboratory porosity measurements areobtained at surface conditions, the porosities are generally higher than in the reservoir, particularly in poorlyconsolidated sandstones, unless compressibility testsare conducted to provide reduction factors to allowfor overburden pressures.
It is worth repeating that the quality of the resultsobtained from core analyses is directly related to thequality and condition of the core when it reaches thelaboratory. Therefore, in cutting and retrieving the core,precautions must be taken to preserve, as much as possible, the conditions that exist downhole in the reservoir.Cutting and retrieval of core to surface results in removal of overburden pressure, introduction of drilling
101
fines, and modification of clays, all ofwhich can affectporosity measurements.
5.11.4 Saturations from CoresBecause ofthe coring and retrieval procedures used forconventional cores, most laboratory saturation measurements obtained are unreliable. At best, the oil saturationsobtained may provide a preliminary indication of whatresidual oil saturations might be after waterflooding. Thewater saturation measurements are usually meaningless.On the other hand, saturations measured on properlypreserved core obtained under well-controlled field andreservoir conditions can give reliable results. .
Oil-base cores normally provide reservoir samples thatshould provide accurate measurements of connatewater saturations. The coring fluid is usually lease crudeor a specially prepared drilling mud that contains weighting material and only very small amounts of water inemulsion form. The following steps are necessary toensure that uncontaminated core is obtained:
I. Set casing and cement to a point immediately abovethe target interval to ensure that the drilling fluiddoes not become contaminated with uphole fluids.
2. Keep coring fluid in a closed system to prevent waterfrom being introduced inadvertently.
3. Analyze samples ofthe drilling fluid for water content at regular intervals during the coring procedure.
4. Avoid penetration of any underlying aquifer.
5. Preserve recovered core in lease crude, or suitablyprotect it from exposure to the atmosphere until itis ready for analysis in the laboratory.
In Alberta, the Energy Resources Conservation Board(1993) publishes each year an updated PVT and CoreStudies Index, which is useful in identifying the reservoirs that have had special core studies performed.However, caution should be used in selecting core analyses and special studies from this index since some coresidentified as being obtained with oil-base muds werenot obtained under properly controlled conditions.Frequently the muds used were oil-water emulsion mudscontaining high proportions ofwater.
Another useful source of connate water saturationdata and relationships derived from oil-base coreanalyses relating to reservoirs in the western Canadasedimentary basin is available in a paper publishedby Buckles (1965).
In instances where suitable oil-base cores areunavailable, capillary pressure studies are performed onsamples ofconventional core to determine information
102
DETERMINATION OF OIL AND GASRESERVES
about pore structure that can be related to connate watersaturations.The results should be used with caution sincethe studies are generally performed on weathered corethat has been cleaned and resaturated with other fluids.The results may differ considerably from those obtainedfrom work on oil core using the Dean Stark extractiontechnique.
The wettability of reservoir rock is another importantconsideration that is often difficult to assess and maybe altered by coring procedures, surface handling, andlaboratory techniques. Generally speaking, the majority of reservoir rock encountered in the western Canadasedimentary basin is considered to be preferentiallywater-wet. However, the term "wettability" is the subject ofmuch debate and is somewhat misleading in thatit implies that it is a property ofthe reservoir rock thatdetermines whether it is water-wet or oil-wet. Someparties hold that wettability ofa reservoir rock dependson which fluid saturated the rock first. Others contendthat wettability is a function of the rock, water, and hydrocarbon properties and their associated oxygen-carbonchains. In fact, most ofthe hydrocarbon reservoirs wereinitially deposited under marine environments wherethe initial saturating fluid, water, was subsequentlypartially displaced by hydrocarbons.
5.11.5 Effective Porous Zone and NetPay from Cores
Effective porous zone and effective net pay refer to thatportion of the porous reservoir rock that has sufficientpermeability to permit the flow of reservoir fluids.Porous rock, with permeability below a certain minimum level in conjunction with capillarity and relativepermeability, will not allow the flow ofreservoir fluids,at least at rates significant in terms of production economics. These minimum permeability levels may differdepending on the production mechanism under consideration. In other words, effective net oil pay under adepletion drive mechanism, where expansion of reservoir fluids is the driving force, may be greater than undera waterflood, where the water displacing the oil tendsto follow the path of least resistance and may by-passlow permeability reservoir rock. In practice, the connate water saturations related to minimum permeabilitylevels tend to be in the range of 50 to 60 percent.
Special core studies and conventional core analysesshould be used to establish cutoffs ofpermeability andporosity below which the reservoir is considerednoneffective for specified depletion and production regimes such as solution gas drive, water displacement,gas displacement, or miscible displacement. Once
s
7
ESTIMATION OFVOLUMES OFHYDROCARBONS INPLACE
these cutoffs have been established from coredata, correlations (cross-plots of water saturationvs. permeability, water saturation vs. porosity, andpermeability vs. porosity) with porosity logs may bedeveloped, thereby permitting a relatively uniform andconsistent approach to the selection ofeffective porousintervals and effective net pays throughout a given reservoir. This approach provides a logical and reliablebasis for the creation ofeffective porous zone maps andnet pay maps. Cutoffs that have been selected arbitrarilyand applied inconsistently throughout a reservoir canlead to unrealistic estimates of in-place hydrocarbons,ultimate recoveries, and costly mistakes in reservoirmanagement.
In reservoirs where core information is unavailable, logporosity cutoff values may be determined from coreinformation using nearby reservoirs as models or byapplying generally accepted porosity cutoffvalues fromthe reservoir rock under consideration (2 to 4 percentfor carbonates; 7 to 10 percent for sandstones). Theseporosity cutoffs are based on experience that shows thatthe corresponding horizontal permeability cutoffs arein the range of0.5 to 1.0 mD, with the lower end of therange used for gas reservoirs and the higher end for oilreservoirs. It should be noted that these cutoffs arerelated to measurements made on unstressed core.
5.11.6 Porosity from Well LogsIt is important to calibrate porosity logs using core datawherever possible since good core-derived data are generally considered to provide the best benchmarks.Cross-plots of log information should be used extensively in order to better characterize porosity.
Uncertainty in the detailed mineral composition of thereservoir rock and borehole rugosity can result in apparent log porosities that are much different than thetrue effective porosities. Bitumen and pyrobitumen contained in reservoir rock can greatly reduce effectiveporosity with contents ranging up to 30 percent ofporespace in some reservoirs. The analyst should be attentive to all indications of the presence of bitumen andpyrobitumen and should make it a point to scrutinizewell cuttings and core descriptions for evidence oftheirpresence.
5.11.7 Water Saturations from Well LogsWater saturations determined from well logs may beinfluenced by the following:
• Thin beds (averaging effect ofresistivity tools due tolack of vertical resolution)
• Conductive minerals in the reservoir rock
• Selection of coefficient "a", cementation exponent""d'm an saturation exponent "n"
• Resistivity of the formation water
With regard to formation water resistivities, care shouldbe taken to use measurements from samples consideredto be representative of reservoir water uncontaminatedby drilling mud filtrate. Water resistivities determinedfrom log calculations over known wet intervals shouldbe compared to those determined from water analyseswherever possible.
5.11.8 Effective Porous Zone and NetPay from Well Logs
As earlier discussions have stressed, the determinationof realistic cutoff levels for permeabilities and porosities are critical to the selection oftruly effective porouszones and net pay from well logs. Errors in determiningeffective net pay may introduce order-of-magnitudeerrors in estimates of effective hydrocarbons in placeand thus lead to costly consequences, particularly in theplanning and implementation of enhanced recoveryschemes.
It is important to use all the data available to ensure thereliability of results. For instance, in situations wherecore information is lacking, correlation of mud cakebuild-up on caliper logs can give a good indication ofthe sections of the reservoir that have effective permeability and can be used in conjunction with porosity logsto select effective net pay.
In summary, it cannot be emphasized too strongly thatrealistic cutoffs ofhorizontal permeability and porosityshould be used in determining effective porous zone and,in conjunction with water saturations, net pays fromcores and well logs. Unless unusual reservoir conditionsexist, such as the presence of large concentrations ofclays, horizontal permeability and porosity cutoffs generally correspond to connate water saturations greaterthan 50 to 60 percent. Based on empirical determinations derived from unstressed core measurements,generally accepted (minimum) cutoffs are as follows:
Horizontal air 1.0mD (medium to high gravityoils)permeability 0.5 mD (wet gas)
0.1 mD (dry gas under specialcircumstances)
Porosity 2 to 4 percent (carbonates)7 to 10percent (sandstones)26 to 28 percent (heavyoil insandstones)
Watersaturation 50 . 60 percent
103
The cutoffs selected for a given oil reservoir may varywidely depending on the type of depletion mechanismbeing contemplated. Fracture porosity in certain gasreservoirs may justify the use of lower porosity cutoffs(0.25 to 2 percent).
5.11.9 Drillstem TestsThe drillstem test provides an indication of the fluidscontained in a reservoir, a measure of the flow characteristics, and a reading of the reservoir pressure. Thereservoir pressures measured during a drillstem test maybe used to assess the quality and reliability ofthe test asfollows:
1. The hydrostatic pressures measured should bechecked to ensure that no significantpressure changetook place during the test. Any significant changein hydrostatic pressure would indicate that a properpacker seal had not been obtained and that the zonebeing tested was not properly isolated from thewellbore fluid column.
2. The pressures measured on different gauges shouldbe checked for consistency, particularly when morethan one gauge is run at any position. Charts shouldbe checked for evidence of tool plugging by comparing inside and outside gauge pressures.
5.11.10 Production TestsGood production tests are a function of the objectivesof the test and the test design, as well as the reliabilityof the equipment used. From the design viewpoint, it iswise to use two downhole pressure recorders so thatcomparisons can be made to check for consistency. Surface and bottom-hole pressures should be compared, andany fluid level changes should be noted during buildups. Flow rates should be ofsufficient duration to permitstable conditions to be reached. Generally, when theobjective is to determine static reservoir pressure,buildup times should be at least twice as long as thepreceding flow rates.
5.11.11 Reservoir Fluid SamplesThe sampling equipment and procedures are of utmostimportance in obtaining representative reservoir fluidsamples. Care must be taken to prevent contaminationof the samples by ensuring that the sample containersare properly purged prior to sampling. Special containers should be used when collecting gas samplescontaining hydrogen sulphide. Proper well conditioning prior to obtaining subsurface oil samples isimportant, especially when more than one fluid phaseis present in the wellbore.
104
DETERMINATION OFOILANDGAS RESERVES
5.11.12 Reservoir TemperatureThe most reliable source of reservoir temperature datais a bottom-hole temperature taken with a continuousrecording subsurface temperature gauge under stabilizedbottom-hole conditions, preferably in conjunction witha static bottom-hole pressure measurement. Other methods, such as using maximum reading thermometersduring testing or logging operations, are considered tobe less reliable.
Small variations in bottom-hole temperature, whenconverted to absolute temperature, generally result inonly a very small percentage error in the overall reservesestimates; nonetheless, care should be taken to obtainthe best measurements possible.
As a general rule, temperatures measured in wells willtend to understate true reservoir temperature becausetemperature equilibrium has not yet been reached in thewellbore. However, in certain situations such as inshallow wells on warm days, maximum reading thermometers may reflect the high atmospheric temperatureon the day the measurement was made.
5.11.13 Reservoir PressureAccurate static reservoir pressures are extremelyimportant in the determination ofhydrocarbon reserves.The accuracyof the measurements is a function of thefollowing:
• The type of measurements being made: surface orbottom-hole
• The reliability of the recorders used for pressuremeasurements
• The duration of the shut-in period
Bottom-hole measurements are considered to providemore reliable measurements of reservoir pressure thansurface measurements, which must then be extrapolatedto bottom-hole conditions. Usually tandem recorders arerun to allow comparisons and verification of theaccuracy of the measurements as well as to ensure thatat least one pressure is obtained should one of therecorders fail.
The duration of the shut-in period is critical in obtaining reliable pressure information and should be afunction of the quality (permeability) of the reservoirrock and the fluids that occupy it. The poorer the reservoir quality and the higher the viscosities of theoccupying fluids, the longer the shut-in period.
s
7
ESTIMATION OFVOLUMES OF HYDROCARBONS INPLACE
5.11.14 Gas Compressibility FactorReliable gas compressibility factors are dependent onthe quality ofthe gas analyses being used and how representative they are of the reservoir fluids. Since acompressibility factor is only correct at the pressure andtemperature used in the estimation, it is important touse reservoir pressure and temperature data of acceptable quality. With gases containing carbon dioxide orhydrogen sulphide, large errors can be introduced intothe reserves estimates if the appropriate sour gas corrections are not made in estimating gas compressibilityfactors.
5.11.15 Formation Volume FactorThe quality and reliability of formation volume factordata are dependent upon whether or not the reservoirfluid samples from which the data were obtained aretruly representative of reservoir conditions. Properselection offlash vs. differential formation volume factors is required to best represent reservoir mechanisms.
5.11.16 Material BalanceErrors in material balance calculations generally fall intothe following categories:
I. Thermodynamic equilibrium not attained in actualfield conditions
2. PVT data obtained using liberation processes thatdo not represent reservoir condition mechanisms
3. Inappropriate average pressures
4. Uncertainty in the material balance "m" ratio
5. Inaccurate production data
6. Inability to recognize the presence of an exteriorsource of energy, such as an aquifer
The amount of pressure decline covered by theproduction history is one of the best criteria in gaugingpotential errors. The material balance is a comparisonof voidage to expansion. It concentrates on evaluatingfluid expansion. Large pressure declines produce largeexpansions, making inaccuracies in production volumesrelatively less significant. Similarly, pressure errors areless critical with more pressure depletion. In general, apressure decline of 10 percent of the original reservoirpressure is needed before the material balance becomesreliable. This critical depletion level is highly dependent upon the quality of pressure, production, and PVTdata.
5.11.17 InterrelationshipsThe interrelationships and interdependencies of thevarious parameters are important in arriving at reliableestimates of in-place volumes. Ifthe sources ofthe dataare reliable, then the quality of the resulting estimatescan be improved by a consistent approach in the selection ofparameters. For example, in a particular reservoirwhere reliable oil core data are available, water saturations can be plotted vs. porosities and vs. horizontalpermeabilities. In tum, porosities can be plotted vs. horizontal permeabilities. Minimum porosity and horizontalpermeability cutoffvalues can then be selected that areconsistent with a selected water saturation cutoffvalue,say 50 percent. The porosity and horizontal permeability cutoffs established from the oil core data can then beapplied to conventional core data. The combined corederived information can then be used to calibrate welllogs and additional interrelationships establishedthrough the use of further cross-plots. This approachensures that the data derived from one source isconsistent in its application with data from anothersource.
Not only does interrelating the various parametersintroduce consistency to the estimates of in-place volumes, it also provides a sound basis for the applicationof recovery factors. Care should be taken to ensure thatthe applied recovery factors are consistent with the inplace volumes and cutoff values used. For example,negotiated in-placevolumes, such as those resulting fromunitization negotiations, should be used with great caution since they are not necessarily an accurate andconsistent representation ofthe reservoir.
ReferencesBuckles, R.S. 1965. "Correlating and Averaging
Connate Water Saturation Data." JCPT, Jan. Mar. 1965, pp. 42-52.
Energy Resources Conservation Board. 1993. PVTand CoreStudies Index. Guide G14, Calgary, AB.
105
Chapter 6
PROBABILITY ANALYSIS FOR ESTIMATES OFHYDROCARBONS IN PLACE
6.1 INTRODUCTIONChapter 5 has addressed the importance of, and thechallenges involved in, obtaining accurate and reliablemeasurements from samples. This in itself is difficultenough, but there is a "fact of life" in the petroleumindustry that further complicates the volumetric estimation procedure: petroleum reservoirs are heterogenous,so parameter values vary from sample to sample evenwhen they are correctly measured. The variation mightbe handled by using many sample measurements andstatistical techniques, but the cost ofobtaining samplesis so expensive that there can never be even close to asufficient number of samples.
To gain an appreciation for the magnitude of theshortfall, imagine trying to predict the outcomes ofpolitical elections from the opinion ofone voter. If thissounds ludicrous, it is; yet a one voter sample is a largerpercentage of the total population than the reserve estimator can realistically hope for. Several approaches tothis dilemma have been tried over the years and eachhas its shortcomings. This chapter is about searchingfor a better way.
Industry's historical approach has been to "guesstimate"a single best value for each parameter, resulting in asingle value for the volumetric estimate. This soundseasy until it is tried. There is never enough informationto justify the selected value. Getting a second opiniondoes not help because no two people will calculate thesame volumetric number, and some data will exist tosupport and contradict both. Thus two technically competent people can have very different opinions and eitheror both could be right or wrong.
The industry's current practice of multi-disciplinarygroup or team decision-making compounds the problem because the multiple opinions will almost certainlybe different. Achieving group consensus is rarely possible because no "right" answer can be determined, andeven consensus does not guarantee truth; in fact, it canprovide a false sense of security that may collectivelylead all those involved into subsequent contradictions
106
between the agreed-to perceptions and reality, and thusintroduce the potential for unfortunate consequences.
The single-value approach presents some organizationaldisadvantages as well. In order to arrive at the "right"number there are only three ways to handle differencesof opinion:
I. Some people have to concede they are wrong,despite evidence that suggests they might be right.
2. The group goes into an endless analysis mode andnever determines the "right" answer.
3. Dissenting opinions are overruled and ignored.
This could hardly be called good team buildingimagine the confrontations generated and the feelingsof the participants! Is it appropriate that, after a certainamount ofdiscussion, the debate is often adjudicated ata higher level of the organizational heirachy? The potential for bias in the assessment likely increases as thedebate proceeds to higher-authority levels, because eachsuccessive level is less familiar with the technical details, but more cognizant of the impact that a particularnumber will have on current plans and operations. Sometimes there may even be personal implications, as withmanagement whose performance assessment is directlylinked to the reserves booked for the year, or the consultant whose opportunities for further work may dependdirectly on the magnitude of the reserve estimate.
A final criticism of the single-value approach is that atthe conclusion of the exercise the participants areexpected to be fully committed to the resulting decisions and to work together to implement them. This isnot a reasonable expectation for a process that is essentially adversarial as winners and losers seldom work welltogether.
In spite of the high organizational costs and the lowprobability of achieving a reliable, accurate estimate,the single-value approach is still used. A plausibleexplanation is that the industry is unaware of a betteralternative. Other approaches have been tried over theyears, including those listed in Table 6.1-1. Of the
S'
PROBABILITY ANALYSIS FOR ESTIMATES OFHYDROCARBONS INPLACE
approaches listed, the Warren Method is the most workable, but it is not widely used at the present time. Themethod was developed by a pioneer in the applicationofprobabilistic methods to the oil industry, Dr. JosephE. Warren (1988). It works because it:
• Is applicable to volumetric theory
• Provides a means to deal effectively with varyingamounts of indirect data that may, at times, seemoverwhelming in volume but are always incompleteand insufficient to support a purely statistical analysis, or justify a single number as the right answer
Quantifies the uncertainty in the estimate by separating the range ofprobable values from the much largerrange of possible values
• Is applicable to all stages of evaluation, from initialassessment of basin potential to individual pooldevelopment
• Is sufficiently flexible to incorporate all the available data, which can differ for every pool and at eachevaluation stage
• Is quick, easy and inexpensive to use
Table 6.1-1 In-Place Volumetric Estimation Techniques
The Warren Method is simple enough that it can be usedon a personal computer or even a hand-held calculator,and successive iterations are actually easier to performthan the initial calculation. These features enable thefocus to be on the quality of the input data rather thanon the arithmetic, and they encourage its use. In addition, the method can be extended to provide reserve andnet present value estimates, while dry-hole risk can beaccommodated in the pre-drilling evaluations.
6.2 WARREN METHOD THEORYThe Warren Method is based on the followingcombination of theory an~ assumptions:
I. It has been proven that the product of unimodalrandom variables is log-normally distributed as thenumber ofvariables approaches infinity (Aitchesonand Brown, 1966, Theorems 2.8 and 2.9), and thatthe product oftwo or more log-normal distributionsis a log-normal distribution (Theorems 2.2 and 2.3).This theory and its application in analogoussituations, plus the tests on artificial samples,suggest that the volumetric hydrocarbon-in-placeestimate may be approximated as a log-normal
Methodology
Single-ValueEstimate
Absolute Minimum!MaximumValue Approach
StatisticalAnalysis
Monte Carlo ComputerSimulation
Warren's ProbabilityAnalysis
Comments
No satisfactoryway to select the "right"value for each parameter in the volumetricequation. No way to resolve differing opinions on prospect potential. Cannot quantifyuncertainty in in-place estimate nor the probability of occurrence.
Consistent use of minimum!maximum parameter values to calculate absolute minimum!maximumhydrocarbonsin place yields a minimumvalue that is uneconomic and amaximumvalue that is too good to be true. Range is too large to be of practical use. Noway to separaterange of probable values worth considering from the much larger possiblevalue range.
Generally insufficientsamples to develop in-placedistribution for the total populationfrom the sample population. Drilling best prospects first biases sampling, yieldingoptimisticpredictions if sample results are extrapolatedto total population. Sufficientsamples for a play are usually available once the explorationist has run out of prospects.For a given pool, they are available after the pool has been developed. The timing isunacceptable for both.
Developmentof in-place probability distribution is a significant advancement overprevious methods. The dilemma is how to model parameter distributions. Developmentof in-placedistribution from multiple single value calculations is computer-intensiveandtime-consuming. The method tends to be too cumbersome to accommodate iterationrequests and time constraints.
Yields similar solutionsas Monte Carlo computer simulation in less time and at lowercosts.
107
---DETERMINATION OFOILANDGASRESERVES
M, (HCIP) = m, (x.) x m, (x.) x m, (x.) x ... (I)
M, (HCIP) = m, (x,) x m, (x,) x m, (x.) x ... (2)
distribution because it is the product of successivemultiplications. The characteristics of thehydrocarbon-in-place (HCIP) distribution maybe calculated from the moments of the parameterdistributions as follows:
Im, (x) = -- (xmi, + .95 xpm b + xm,,) (5)
2.95
maximum error of 2.05 percent in the tests, whileaverage absolute and maximum errors for the variance were 2.2 percent and -7.5 percent respectively.The recommendations balance the need for accuracy with the need for simplicity in the estimationprocedure. In particular, a formula utilizing the moderather than the median of the distribution waschosen to estimate the mean (it is easier to estimatethe mode than the median). The distributionmoments are calculated from the minimum, mostlikely and maximum values for the distributionusing the following equations:
(3)
(4)
"Rio = M, (HCIP) ~,.
6.3 APPLICATIONThe first step in estimating the in-place hydrocarbonsof a pool is the development of value ranges for eachof the parameters in the volumetric equation. Theminimum and maximum values establish the rangefor the pool average value by distinguishing betweenwhat is and what is not within the realm of possibility.It is crucial that the true average value for the pool be
3. Consistent, reliable, unbiased 3-point estimates canbe developed. This assumption, which is alsonecessary to Monte Carlo simulation, may appeardaunting. Capen's (i 976) hypothesis that SPE members will "miss" an average 68 percent of thequestions and the results that support the hypothesis are a sobering assessment of the industry'spresent inability to deal with uncertainty. However,Capen suggests that the skills necessary to providereliable estimates may be developed with practice,and he offers some practice techniques. He notesthat some meteorologists have apparently masteredthis skill and suggests that oil industry personnelcan eventually attain a similar proficiency.
In practice the assumptions are applied in the reverseorder listed.
where
z M, (HCIP)a = In ----=--'--------'-M~ (HCIP)
M,(HCIP) = first moment of hydrocarbonin-place distribution
MiHCIP) = second moment of hydrocarbonin-place distribution
m.Ix,...) = first moment of the nthparameter distribution
mixn•••) = second moment of the nthparameter distribution
xi- •• = parameter distribution (<\>, h,A...)
Rso = median value of the in-placedistribution; plotted at the 50thpercentile on log-probabilitypaper
Rs4., = median value plus one standarddeviation; plotted at the 84.1thpercentile
2. A three-point approximation can be used toestimate parameter distribution moments in theabsence of complete knowledge of the continuousdistribution. This assumption, which is also integral to Monte Carlo simulation, is necessary becausea complete knowledge is seldom, ifever, available.It is supported by the work of Keefer and Bodily(1983), who compared the accuracy ofseveral threepoint approximations in estimating the meansand variances for a set of beta distributions. Therecommended approximation for the mean hadan average absolute error of 0.37 percent and a
[ J'x - x
m, (x) = m~ (x) + m" mi,
3.25
where xmin = minimum parameter value(probability = 0.05)
xprob most likely parameter value(mode)
xmax = maximum parameter value(probability = 0.95)
(6)
108
s
PROBABILITY ANALYSIS FOR ESTIMATES OF HYDROCARBONS IN PLACE
greater than the minimum value and less than themaximum value. However, if unrealistic minimum ormaximum values are used, the variation in the in-placedistribution will be so large that the estimate will haveno practical use. For example, the minimum averagepool porosity value must be slightly greater than thecutoffvalue for the rock type or the discovery well couldnot have produced hydrocarbons on the drillstem test.Using the cutoff value as the minimum average poolvalue is probably acceptable, but using zero as the minimum average value is not. Similarly, assuming the wellflowed gas on the test, the residual gas saturation valuemight be ~n acceptable approximation for the minimumpool average gas saturation value. Values of zero andone are always too extreme when estimating thevolume of hydrocarbons in a pool because they implythat no hydrocarbons exist, contrary to the productionfrom the pool. Warren's methodology does permit anevaluation of "dry hole risk," but the topic is beyondthe scope of this discussion.
The most likely value or modal value is the "poolparameter average value with the highest frequencyof occurrence." By definition, it is greater than theminimum value and less than the maximum value.A suggested interpretation is the "best guess" for thepool average value. Several iterations with differentbest guesses usually demonstrate that the in-placedistribution is relatively insensitive to variation in themost probable value. Because the in-place distributioncan be calculated so easily, iteration using all the potential probable values is often the quickest and easiest wayto resolve which value should be used for thisparameter.
In the absence of sufficient measurements, the sourcefor parameter values is the combined training andexperience ofa company's earth science personnel. Themulti-discipline team approach to in-place estimatesprovides some desirable features. It brings a higher levelof competency to the parameter estimates than can besupplied by anyone discipline working in isolation, andthe inter-discipline discussion tends to highlight anyindividual bias or inconsistency that may exist in theevaluation. For a given prospect, the objective is to identify the models that do not apply, based on the availableinformation, and then develop unbiased parameter valueranges encompassing all the models that may apply tothis particular prospect. A multi-discipline team thatappreciates the unique viewpoints of its individual members and works to include all views in a consistentexplanation has a definite advantage in accomplishingthis task.
Possibly the most challenging part of the evaluation isincorporating parameter interdependence into the volumetric equation. Team members may agree that adependence exists, but that the relationship is vague orunknown. An apparent impasse in the discussion usually signals that the team is grappling with a dependency.This is especially obvious when individuals are basingtheir estimates of one parameter on their estimates of aprevious parameter. Because each case is unique, a singlesolution applicable to all cases does not exist. Resolution requires flexibility and at least one team memberwith the ability to postulate the mathematics ofthe dependence from the discussion. The guiding principlesare as follows:
1. Deal with only one geologic process at a time.
2. Prevent the team from estimating parameters forwhich they have no direct measurements.
3. Ifa parameter can be identified as a product ofotherparameters, estimate the primary parameters andsubstitute them into the volumetric equation.
4. When one parameter is clearly dependent upon another, substitute the dependency into the volumetricequation to minimize the number ofparameter estimates required from the team, and thus reduce thechance ofinconsistencies creeping into the estimate.
An example ofthe application ofthese guidelines is theestimation of pool rock volumes. The rock volumeshould not be guessed at directly because the pool rockvolume is never measured. Teams often find it easier toapproximate the rock volume as a combination ofgeometric shapes and estimate the dimensions for eachshape. For example, a rectangle-triangle combinationmight be used to approximate a reef cross-section(Figure 6.3-1). The rectangle represents the reef crestwhile the two triangles represent the reeffront and backslopes. Now the team's expertise can be used to provide estimates for gross thickness, H, crest width, W,reeflength, L, and slope angles, X.Angle ofrepose controls the front slope, while regional dip is the primaryinfluence on the back slope. This information, plus theequations for triangular and rectangular areas, yields thecross-sectional area of the reef. Multiplication by boththe ratio ofnet pay to gross thickness and the reeflengthyields the volume of the reef considered tocontain hydrocarbons.
The dependency between cutoff values and poolaverage values for porosity and net pay deserves mention. Increasing the cutoff value decreases the net payvalue, but increases the average porosity value. The
109
DETERMINATION OFOILANDGASRESERVES
Reef Back Slcpe
//'
/'
ReefFront Slope
-W-Underlying Water
/'/'
/'/'
/'/'
/'/
//
//
//'
Hydrocarbon BearingRock Volume = (Area Back Slope + Area Crest + Area Front Slope) (Length) (Net/Gross Pay Ratio)
2 2
= (0.5 H + HW + 0.5 H ) (L) (Net/Gross Pay Ratio)tan Xb tan X,
Figure 6.3-1 Estimation of Reef Volume
recommended method of addressing this issue is tocalculate in-place distributions for each of the parameter value combinations corresponding to the differentcutoffvalues. Iteration usually demonstrates that the different combinations yield essentially the same in-placedistribution.
6.4 TYPICAL SITUATION:CONVENTIONAL GAS
The example described in the next few pages is typicalofmany ofthe situations encountered. It serves to showjust how far afield one can go if insufficient attention ispaid to the uncertainty in the in-place estimate. To givethis example some reality and illustrate the economicutility of the method, typical recovery and economicfactors are assumed; however, in practice, equal attention is paid to developing the range of all parameters.
A recent carbonate discovery well flowed gas at a rateof 225 x 103 m3/d from 10 m oflogged pay followingcompletion. Log-derived porosity and water saturationvalues are 0.13 and 0.205 respectively. Movable waterwas not interpreted to exist in the pay interval. Theformation temperature during logging was 74°C. Coreis not available from this well.
Based on the interpretation of the single rate flow andbuildup data, the well is completed in a single porosityreservoir, with 300 mD-m conductivity and a -2 skinfactor. Bottom-hole formation temperature recordedduring the buildup stabilized at 81°C. The Homer plotextrapolation yielded a value of 24 731 kPa(abs).
The gas deviation factor is calculated from the gascompositionas 0.88 at a temperature of81 °C and a pressure of24 731 kPa. Radius of investigation calculationsyield an investigation area of 56 hectares. A singleboundary is interpreted to exist at a distance of 266 mfrom the well. This correlates with the seismic interpretation, which located the eastern edge of the structure200 to 350 m from the wellbore. No insight on the location of the other edges is available from the well test orthe seismic interpretation.
Geological interpretation provides the location ofthe remaining edges, which are inferred from thedepositional model, dip angle, and offset well data.Post-depositional erosion results in a very steep-sidedstructure. Subsequent infilling of these erosional channels with impermeable material provides the trappingmechanism for the structure. From these interpretations,the maximum areal extent of the pool is four sections(Figure 6.4-1). The geologist has also interpolateda mostlikely value, covering about 2.25 sections. The basisfor this contour is solely the assumption that the truevalue is likely nearer the mid-point than the extremes.
The Exploration Department is rumored to becontemplating a bid in excess of $3000/ha for the offsetting acreage. Justification seems to be the four-sectionupside potential ofup to 4900 x 106 m3 ofreserves. TheExploration Department's request for review of theirnumbers has just been received. The sale will take placeat the end of the week.
110
PROBABILITY ANALYSIS FOR ESTIMATES OFHYDROCARBONS INPLACE
7
Optimizing porosity. area,recovery factor, etc.,indicates up to 4900 X 10' m
3
of recoverable gas.
Geologist's most likeiy contour
p -------\--.-"---V/\.' ,, .:'./ ;.. ,. ,. ,
, ,p:
,,, ,, "*-
,,
'\, ,, ,, I
,,, ,
\, j;/,,P/',
~.,, \,,, .,
-- .. \-------- ---A completion test has shownexcellentreservoir with oneadjacent boundary.
Figure 6.4-1 Typical Situation: GasPool Map
The Production Department apparently has no plansto tie in this well at the present time. Volumetricestimates using minimum parameter values yieldin-place hydrocarbons of 44 x 106 m'. The economichurdle volume for the tie-in is 250 x 106 m30freserves.
Environmental concerns preclude flaring additional gasvolumes to perform an economic limits test.
Review of the four analogous pools reveals variousstages of depletion, with pool reserves estimated at 55,120,250, and 550 x 106 m'. Cumulative production fromthe seven wells in these pools ranges from 30 x ]06 m3
to 300 x 106 m3• This statistical review did not persuadethe Production Department to tie in the subject well,but raised questions concerning the size offacilities required. In addition, the Production Department advisesthat they recently abandoned the lone well in the 55 x106 m3 pool, due to reservoir depletion. Several reviewswith increasingly senior levels of management haveresulted because the well tie-in costs were not recouped,and Production's personnel are anxious to avoid anyfuture recurrence. They note that the recently abandonedwell also demonstrated a commercial flow capabilityfollowing completion and had an upside potential of
2000 x 106 m3 and an economic hurdle volume of120 x 106 m3•
Your boss just "volunteered" you to resolve the situation. In addition, he advises that senior managementwould like to review the corporate reserves bookedagainst this well, plus production and cash flow forecasts at the upcoming quarterly review. The pressreports described the well in glowing terms, "possiblythe best discovery ofthe year" and-you agree-it can'tjust sit there.
How will you proceed?
Behind the Numbers
The situation may seem tense but it is not hopeless!Although some sabres are rattling, your boss's insightge~s you in while the majority are still willing to listen.Pnvately, both departments confide that their numbersare not absolute but ...
The ultimate purposes of reserve estimates are as follows:
1. To assess whether the uncertainty in the reservesof a given prospect is of sufficient magnitude tojustify the expenditures required to reduce theuncertainty
2. To assess the safety of the prospect and of theaggregate from an investment viewpoint
3. To provide an indicator of aggregate performance
Ea~h of these different purposes requires a uniqueestimate for the prospect. Additionally, there are timeswhen the prospect estimate is less important than itsimpact on an aggregate ofreserve estimates, such as thecompany reserve profile. An understanding of the responsibilities and COncerns of the different groups andtheir relation to the prospect or the aggregate is vital toresolving this situation. Erroneous conclusions withpotentially disastrous consequences can result whenan estimate intended for one purpose is misused foranother.
In this case, the Production Department is charged withthe responsibility for tying in the well. The concernsthat relate directly to the prospect estimate are the sizeand design of the surface facilities, the type of salescontract to negotiate, and the likelihood that the tie-inwill be economic. Budget allocation requires that theeconomic potential of this prospect be compared andranked relative to the other financial opportunities available to the department. This is an aggregate-relatedissue because the focus now is on the cumulativeoutcome for the budget period and the effect on the
111
overall performance of both the department and thecompany.
The company's future depends on continued access toeconomic sources ofproduction which, in this example,is the responsibility ofthe Exploration Department. Oneway to access new production sources is via the bidding process. To be successful, the bid price must exceedall competitive bids, but it must also be less than the neteconomic value of the reserves acquired. The consequences ofbidding too low or acquiring the prospect atan uneconomic price are equally undesirable. This prospect-related issue can be addressed by comparing thelikelihood of exceeding the prospect economic valuefor a given bid price to the likelihood of acquiring theprospect at that price. The aggregate issue is again budget allocation and the impact of this opportunity onoverall performance.
The issues at the corporate level tend to be aggregaterelated. Both internal and external comparisons toestablished criteria are performed at this level, underscoring the need for aggregate reliability and consistencythroughout the industry. Reliability is required to establish trust in future projections, and is achieved whenpast performance essentially agrees with past projections over some time period. Consistency is necessaryto permit comparison. Comparisons may be betweenproducing horizons, between geographic areas, betweendepartments within a company, between companies, oreven between industries. Comparison criteria are usually economic and incorporate required or desiredobjectives. An example of a required objective mightbe the time component in sales contracts, security ofsupply issues, or possibly safety and environmentalissues.
This section demonstrates that calculating the in-placehydrocarbon distribution cannot satisfy these concernsdirectly. The calculation is only a necessary first step indeveloping solutions that avoid disaster while achieving acceptable results for at least the majority of theprobable reserve outcomes. This approach is based onthe concept that a solution that avoids disaster under allprobable outcomes is preferable to one that performsnearly ideally under a narrow range of conditions, butprovides unacceptable results the majority of the time.The optimal solution is the one that avoids disaster forall probable outcomes while maximizing the desiredresults over the widest range ofprobable outcomes. Foran individual prospect, this requires consideration oftheprobable range of outcomes available to the prospect,while an aggregate question requires consideration ofthe probable variation in the aggregate.
112
DETERMINATION OF OIL AND GAS RESERVES
Pool Parameter Values
Congratulations! You've established sufficient trust thatrepresentatives from both departments have agreed tomeet with you for the purpose of establishing parameter value ranges. An unexpected break is the attendanceof two people whom you've successfully worked withbefore. Several intense discussions prove fruitful andproduce group consensus on the following parameters.
Areal Extent
By group consensus, the pool areal extent must be greaterthan 56 hectares. The most conservative guess is 64hectares, which is deemed to be the minimum possiblevalue. The maximum possible value is quickly set at1024 hectares, but opinions on the most likely valuerange from 1.5 to 2.75 sections. Resolution is reachedwhen you offer to run three cases, using 384, 576, and704 hectares as the most likely value, to demonstratethe impact on the in-place distribution. Discussion ofdeposition and erosional processes, seismic interpretation plus several pictures of badlands terrain producesconsensus that the area ofthe top ofthe pool is less thanthe area of the base. Opinions range from 60 to 95 percent ofthe basal area, with 80 percent as the most likelyvalue. The inter-relationship is handled using an average area, which is equal to 0.5 (base area + top area).Substituting these percentages into the equation yieldsthe average area equal to 80, 90 and 97.5 percent ofthebase area respectively (Figure 6.4-2). These percentagesand the basal area estimates are substituted for theaverage area in the in-place distribution calculation.
Net Pay
Discussion quickly identifies that for this case the pool'snet pay is the product of two geological processes. Thegross thickness of the rock is controlled by depositionand erosion, but not all of the rock is reservoir quality.Only the portion whose porosity and permeability hasbeen enhanced via post-depositional processes is considered to contain hydrocarbons. This interrelationshipis handled by first estimating the gross pay of the pooland then the percentage conversion to reservoir rock.Net pay is the product of the two parameters.
The gross pay thickness is controlled by topographicalvariation on the upper erosional surface and the elevation ofthe gas-water contact, ifone exists, on the bottom.In the worst case, free water exists just below thebottom of the discovery well and, in the best case, it isnot present. Free water is known to exist in two ofthe analogous pools, but at different elevations. This is
'1!
<
PROBABILITY ANALYSISFOR ESTIMATES OFHYDROCARBONS INPLACE
For the minimum case,
Atop = 0.6 Abo" (7)AOVg = 0.5 (A,op + Abo,,) (8)
substituting (7) in (8)Aovg = 0.5 (0.6 Abos• +Abos.)
0.5 (1.6 Abos.)0.8 Abos•
Figure 6.4-2 Conversion of Base Area toAverage Pool Area
consistent with the theory that the hydrocarbons werelocally sourced. From this and the 0.98 degree regionaldip angle, the gross pay thickness estimates are 6.5 mas the minimum case, 19 m as the maximum, and 15 mas the most likely value. At 13 m, the gross pay thickness for the discovery well is slightly below the poolaverage and came in about 2 m lower than expected.
A number of possible mechanisms are discussed for conversion of limestone to dolomite, none of which aredefinitive. In the end the estimates are based on thegroup's experience with the region, gained from theexamination of logs and core from this formation overthe entire geological basin. Based on that experience,the rock encountered by the discovery well is about average in terms of converting gross pay to net pay. Theconversion efficiency for the pool is estimated at 65,80, and 90 percent, respectively.
Porosity and Gas Saturation
Regional experience again comes to the forefront in theestimation of these parameters. The question of bitumen infilling of the available porosity arises but isconsidered remote, based on the group's experience withthis formation. The group also considers the possibilitythat porosity and water saturation are interrelated, butpostulated correlations prove inconclusive. Howeverit is agreed that the greatest variation in the in-placeestimate results from the independent treatment ofthe two parameters, so value ranges are developedaccordingly. The minimum possible pool porosity isestimated at 12percent, the maximum at 17percent and
Similarly for
Atop =
Aavg =
and when
Atop =Aavg =
0.8 Abos•0.9 Abas•
0.95 Abos•0.975 Abos•
the most likely at 15 percent. Water saturation estimatesare 18, 20 and 22 percent respectively.
Pressure
The initial reservoir pressure is uncertain. The Homerplot gives an extrapolated pressure of 24 731 kPa (abs)from the buildup, but this is not the initial reservoir pressure because the boundary's presence violates therequirement for infinite acting radial flow. Regionalpressure gradients suggest an initial pressure of22 000to 26000 kPa (abs). The group agrees that the minimum possible pressure is 24 000 kPa (abs) because thepressure was still building at the end of the buildupperiod, with a final value of 23 966 kPa (abs). A maximum value of26 000 kPa (abs) is assumed, with a mostlikely value of24 700 kPa (abs).
Temperature and Gas Deviation Factor
Recorded bottom-hole temperatures during the buildupranged from 80.97 to 81.25°C. This variation is verysmall relative to the uncertainty in the other parameters.Perhaps parameters with less than I percent differencebetween the minimum and maximum values can betreated as a constant without significantly affecting thein-place distribution? The effect can be observed by firstconsidering temperature as constant at 81°C, and thenas a parameter, with values of 80.97, 81 and 81.25°C.
The gas deviation factor varies from 0.87 to 0.89 overthe 24 000 to 26 000 kPa (abs) pressure range. Thevariation between the minimum and maximum value isless than 3 percent, so perhaps it too can be treated as aconstant? The incentive for doing so is that the increasedaccuracy achieved by incorporating the gas deviationfactor's dependency on temperature, pressure and gascomposition into the calculation(s) may not be worththe effort. Since the gas deviation factor is actually something between a constant and a random variable, thevalidity ofthe assumption might be confirmed by considering the impact of the two extremes on the in-placedistribution. Values of 0.87, 0.88 and 0.89 were usedfor the parameter range, while 0.88 was selected whenthe gas deviation factor was considered constant.
Gas In Place
In-place distribution calculations using 384, 576 and704 hectares as the most likely value for areal extentare presented in Tables 6.4-1, 6.4-2, and 6.4-3. For aconstant, m, (x) = constant and m2 (x) = constantsquared. The in-place distribution is obtained using thecalculated Rso and Rs4.t values to establish a straightline on log-probability paper (Figure 6.4-3). For
113
DETERMINAnON OF OIL AND GAS RESERVES
Table 6.4-1 Gas-in-Place Distribution for Most Likely Area of 384 Hectares
Pool Minimum Most Likely MaximumParameters Possible Value Value Possible Value
xmin xprob xMsx m. (x) m, (x)
Basalarea, Abo" (ha) 64 384 1024 492.5 329783Correction to avg. area, C, 0.80 0.90 0.975 0.8915 0.7977Grosspay, H(m) 6.5 15 19 13.47 196.4Net/gross pay ratio, N/G 0.65 0.80 0.90 0.7831 0.6191Porosity, <p 0.12 0.15 0.17 0.1466 0.02173(l - Sw) 0.78 0.80 0.82 0.80 0.6402Pi(kPa abs) 24000 24700 26000 24903 620557523
Constants 10 000 (288.16) 10000(288.16) 0.000091 8.327 x 10-'10' (101.325) r,z, 10' (l01.325) (354.16) (.88)
M1(OGIP)= 1234.7 M,(OGIP) = 2 298 761
10000 (288.16) Ab", (C,) H (N/GH (l-Sw) Pia' = In
M, (OGIP)OGIP=
10' (101.325) TiZ,0.4107
M; (OGIP)
1 "m, (x) = -- (xmio+ .95 xpmb + xm,,) -- ,2.95 R,o=M,(OGIP)e' = 1005.5 x 10 m'
[X x Jm, (x) = m; (x) + max - mina , ,
3.25R84. , = Rso e = 1908.6 x 10 m
M1(OGIP) = m, (x,) X m, (x,) X m, (x.) X ... M, (OGIP) = m, (x.) X m, (x,) X rn, (x,) X .•.
Note: Pi. Ti• and Zj are respectively initial reservoir pressure, temperature, and gas formation factor.
,I
prospect issues the question is: How much of thedistribution should be considered? The suggested rangeis all values from the R, to R,s values, which can beread from the graph. For this example the range is 400to 3250 X 106 m3 using the 576 hectare most likely valuedistribution. This encompasses 90 percent of the probable outcomes and is consistent with developingsolutions that work the vast majority of the time. Sincehuman nature is inclined to over-estimate the extent ofknowledge, an initial reaction might be disbelief at themagnitude of the range. However, an order-of-magnitude variation in the range is common, especially fornew discoveries. For situations where a single numberis desired to describe the distribution, the mean value(M1(HCIP» is recommended. For the 576 hectare distribution M1(HCIP) = 1389.7 X 106 m3• This value hasno significance to prospect issues, only to aggregatequestions. Misuse it at your own peril!
114
The effect of varying the most likely value of thedistribution can be seen on Figure 6.4-3. In this examplethis variation is insignificant compared to the Rs to R,srange in the distribution. Group consensus on whichvalue to use is usually easy to obtain following the team'sinspection ofthe graph because it does not really matterwhich distribution is used. However, if consensus doesnot exist, a further compromise is to draw a line throughthe smallest R, value and the largest R,s value to establish a composite in-place distribution. The characteristicsofthis distribution can be calculated by reading the Rsoand R84.1 values from the graph and using the equationsto calculate M,(HCIP) and M2(HCIP). Alternatively, onecan carry the two extreme distributions through the decision-making process until everyone agrees that "it doesnot matter."
d
PROBABILITY ANALYSIS FOR ESTIMATES OFHYDROCARBONS INPLACE
Table 6.4-2 Gas-in-Place Distribution for Most Likely Area of 576 Hectares
Pool Minimum Most Likely MaximumParameters Possible Value Value Possible Value
Xm1n xprob XMax m, (x) m, (x)
Basal area, Ab,,,, (ha) 64 576 1024 554.3 394506Correction to avg. area, Cf 0.80 0.90 0.975 0.8915 0.7977Gross pay. H(m) 6.5 15 19 13.47 196.4Net/gross pay ratio, NIG 0.65 0.80 0.90 0.7831 0.6191Porosity, <I> 0.12 0.15 0.17 0.1466 0.02173(I - Sw) 0.78 0.80 0.82 0.80 0.6402P, (kPa abs) 24000 24700 26000 24903 620557523
Constants 10000 (288.16) 10 000 (288.16)0.000091 8.327 x 10'·
10' (101.325) T, Z, 10' (101.325) (354.16) (.88)
M, (OGIP) = 1389.7 MlOGIP) = 2 749 913
10000 (288.16) Ab" , (C,) H (NIGH (I-Sw) P, a' =InM, (OGIP)
OG1P= = 0.353310' (101.325) T, Z, M: (OGIP)
a' a , ,- - 6 3 R84.l =Rsoe =2110.4x 10 mRso = M, (OGIP) e' = 1164.7 x 10 m
Note: Pi.Til and Z, are respectively initialreservoirpressure, temperature, and gas formation factor.
Table 6.4-3 Gas-in-Place Distribution for Most Likely Area of 704 Hectares
Pool Minimum Most Likely MaximumParameters Possible Value Value Possible Value
xmin xprob xMax m. (x) m, (x)
Basal area, Ab,,,,(ha) 64 704 1024 595.5 441 902.6Correction to avg. area, C, 0.80 0.90 0.975 0.8915 0.7977Gross pay, H(m) 6.5 15 19 13.47 196.4Net/gross pay ratio, NIG 0.65 0.80 0.90 0.7831 0.6191Porosity, <I> 0.12 0.15 0.17 0.1466 0.02173(1 - Sw) 0.78 0.80 0.82 0.80 0.6402P, (kPa abs) 24000 24700 26000 24903 620557523
Constants10 000 (288.16) 10 000 (288.16)
0.000091 8.327 x 10'·=10' (101.325) T, Z, 10' (101.325) (354.16) (.88)
M, (OGIP) = 1493.1 M,(OGIP) = 3 080 291
10000 (288.16) Ab" , (C,) H (NIGH (l-Sw) P, a'= InM, (OGIP)
OG1P= = 0.323310' (101.325) T, Z, M: (OGIP)
" a , ,-,= 1270.2 X 10' m' R84.1 =Rso e =2243.0 x 10 mRso =M, (OGIP) e
Note: Pi' Ti• and ~ are respectively initial reservoir pressure, temperature, and gas formation factor.
115
DETERMINATION OFOILANDGASRESERVES
2 5 10 20 3040506070 80 90 95 98 ,10' 10
Figure 6.4-3 Typical Situation: Gas-in-PlaceDistribution
Observations
The purpose of performing the calculations is to showthe ease with which the in-place distribution can be updated. In the working world, this feature translates intomore rigorous estimates that are updated more frequentlyand with less time and effort than is achieved with anyother method. This statement becomes truer as the teamgains familiarity with the methodology, the prospect,and each other. Gradually the emphasis on the reasonsfor performing the calculation shifts from a reactivepostevent exercise to more of a planning and evaluationactivity.
Production's 44 X 106 mJ minimum pool volume andExploration's 4900 x 106 mJ upside number do not appear on the probability distribution. The 44 x 106 mJ
value is the product of all the minimum possible parameter values, while the product of the maximumparameter values and an optimistic 87 percent recoveryfactor yields the 4900 x 106 m' upside number. Consistently using the worst or best parameter values for thein-place estimate always results in a number which isless than or greater than 99.5 percent of the cumulativeprobability distribution and is even more extreme forthe cumulative reserve distribution. The question forboth groups is why they are basing their decisions onsuch improbable numbers.
Some insight on what numbers should be used can begained by preparing a reserve distribution (Table 6.4-5,Figure 6.4-4) and a discounted net profit before investment (DNPBI) distribution (Table 6.4-6, Figure 6.4-5)for the pool. Both distributions are prepared analogousto the in-place distribution. The reserve distribution usesthe in-place distribution moments and recovery factorestimates of 65, 75 and 87 percent respectively asinput, while the DNPBI distribution requires the reservedistribution moments and a unit value for the gas of$8.00, $11.00 and $15.00 per thousand cubic metres.The unit value for the gas is the estimated present valueofthe future profit from the future production, accounting for prices, production profiles, effluent composition,royalties, operating costs, inflation and discounti?g.Multiplying by the prospect reserves and subtractingthe present value of the capital investment yields anestimated net present value for the prospect."
From the reserve distribution shown in Figure 6.4-4,pool reserves are between 320 and 2350 x 106 m'. With
384 haIl /£ L576 ha
i:.~
(!J 102
The previous distributions were calculated assumingthat reservoir temperature and gas deviation factor areconstants. For comparison, in-place distributions werecalculated using 384, 596 and 704 hectares as the mostlikely value and the following temperature and gasdeviation factor assumptions:
I. Variable temperature, constant gas deviation factor
2. Constant temperature, variable gas deviation factor
3. Variable temperature and gas deviation factor
In all cases, the calculated values for M1 (HClP), Rsoand RS4.1 agree with the previously calculated valuesto four significant figures: In-place distributioncalculations for a 576 hectare most likely value withvariable reservoir temperature and gas deviation factorare presented as Table 6.4-4. The inverse (liT, I/Z)of the denominator parameters is used to conform totheory. Calculations for the other combinations are notpresented, but left as an exercise for the reader. For comparison purposes, the time required to prepare all twelvedistributions was approximately 3 hours using aprogrammable calculator.
10 102 5 10 20 3040508070 80 90 95 98
Percentage
• An understanding of Warren's theory governing the unitvalue parameter is necessary to attempt this procedure(Warren, 1988).
116
_________C1
PROBABILITY ANALYSIS FOR ESTIMATES OFHYDROCARBONS INPLACE
Table 6.4-4 Gas-in-Place Distribution for Most Likely Area of 576 Hectares.Variable Temperature and Gas Deviation Factor
Pool Minimum Most Likely MaximumParameters Possible Value Value PossibleValue
xmin xprob xMax m, (x) m, (x)
Basal area, Ab. " (ha) 64 576 1024 554.3 394506Correction to avg. area, Cr 0.80 0.90 0.975 0.8915 0.7977Grosspay, H(m) 6.5 15 19 13.47 196.4Net/gross pay ratio,NIG 0.65 0.80 0.90 0.7831 0.6191Porosity, <I> 0.12 0.15 0.17 0.1466 0.02173(I - Sw) 0.78 0.80 0.82 0.80 0.6402Pi(kPa abs) 24000 24700 26000 24903 620557523
1 1 17.9693 X 10"Temperature
273.16+ 81.250.002823
273.16+ 81 273.16 + 80.97
Gas Deviation Factor 11.89 1/.88 11.87 1.136463 1.291612
Constants10000 (288.16)
0.028439 0.00080910' (101.325)
M1 (OGlP) = 1389.6 M,(OGlP) ~ 2 749 372
10000 (288.16)Ab", (C,) H (NIGH (I-Sw) Pi a' = InM, (OGIP)
OGIP= = 0.353410' (101.325)r,z, M: (OGIP)
" a , ,Rso = M1 (OGIP) ~,-- = 1164.5 X 10' m' R84.1 = Rso e = 2110.2 x 10 m
Note: Pi. Ti• and Z, are respectively initial reservoir pressure, temperature, and gas formation factor.
a 98 percent probability of exceeding the 250 x 10' m3
tie-in hurdle volume, development of this pool shouldbe a sufficiently safe bet for even the ProductionDepartment. Once pool deliverability, pressure, temperature and effluent composition information have beensupplied, the central production facilities, such asthe gathering line to the gas plant, can be sized. Thenumber ofwells required to deplete the pool and interwell spacing can be estimated by comparing welldeliverability to pool deliverabi!ity. Sizing of the individual wellsite facilities can also be determined fromthe well deliverability estimates.
One way of obtaining an estimate for pool deliverabi!ity is to divide the reserve distribution by a desired rateof take. For this case a 1/3650 rate of take yields aninitial deliverability range of88 to 644 x 103 m3/d. Sincethe discovery well flowed at 225 x 103 m3/d, it is notnecessary to design the central facilities to handle theentire 88-644 x 103 m3/d range. Using the discoverywell's capability as the minimum throughput, with 644
X 103 m3/d as the maximum, is technically acceptableand more economical than designing to cover the largerrange. Completion of the equipment sizing exercise inthis fashion provides the input required for sales contract negotiation, and simplifies matching contracteddeliverabi!ity to facility capability.
The purpose of equipment sizing at this stage is twofold. The present value cost ofboth present and futurecapital is required to evaluate the economic attractiveness of developing the prospect. However, only thosefacilities, such as the gathering line to the gas plant, thatare required immediately to initiate production will beconstructed on the basis of this initial estimate. Sizingof future facilities, such as field compression, can beconfirmed prior to their construction because significantly more information will be available by that time.At this stage the optimal design is the one which provides the largest probability ofachieving a positive netpresent value over the prospect reserve distribution. Theoptimal design does not have to provide the capability
117
DETERMINATION OF OIL AND GASRESERVES
Table 6.4-5 Reserve Distribution for Most Likely Area of 576 Hectares
Pool Minimum Most Likely MaximumParameters Possible Value Value Possible Value
xm1n x prob xMax m, (x) m, (x)
aGIP (10· m') 1389.7 2749913Recovery Factor 0.65 0.75 0.87 0.7568 0.5773
M, (RIG)= 1051.7 M,(RIG) = I 587 519
a M, (RIG)a =In =0.3613M: (RIG)
2 5 10 20 3040506070 80 90 95 98 410' 10
10 102 5 10 20 304050.6070 80 90 95 98
Percentage
Figure 6.4-4 Typical Situation: ReserveDistribution
to operate at all the rates specified by the rate of takedeliverability distribution, and probably would not whenits magnitude is very large.
In this case the present value tie-in cost is estimated at$2.6 million, including future field compression. Thepresent value of future development drilling, includingdry hole and wellsite facility costs, is estimated at $3.5
118
"( )
-, 6 JRso = M, RIG e = 877.9 x 10 m
, 6 JR"., =Rsoe = 1601.4 x 10 m
miUion, while sunk costs are $2.5 million. Now theeffect ofbid price on profitability can be observed. Thecumulate exploration and development cost of $8.6million" ($2.6 miUion + $3.5 million + $2.5 million)intersects the discounted net profit before investmentcurve at a probability of42 percent (Figure 6.4-5). Thus,ifthe remaining four sections ofland could be acquiredat no cost, there is a 58 percent probability ofachievinga positive net present value (NPV) through developmentof this pool. At the rumoured bid price of $3000/hectare, the cost for the remaining four sections isapproximately $3 million, which reduces the probability of achieving a positive NPV to 39 percent on a totalcost of$II.6 million (Figure 6.4-5). Is this a good gamble? Unless one is unusually lucky, probably not. A wisercourse might be a minimal bid price and anticipatingthat the rewards (and risks) of development will likelybe shared with others. Then the sharing options can beidentified and their economic merits evaluated.
The example illustrates one way of turninga promisingexploration prospect into a probable money-losing venture. Of course there are many other ways. The key toconsistent financial success is staying true to the purpose ofexploration and development, which is profitableinvestment, not production at any cost. Warren's method ultimately provides a means to do just that, and itstarts with the in-place estimate.
Summary
The example illustrates the use of the Warren Methodto estimate hydrocarbons in place, and some
*Although variablecapital costs can be accommodated,single-value costshave been used to simplify the example.
s
PROBABILITY ANALYSISFOR ESTIMATES OFHYDROCARBONS INPLACE
Table 6.4-6 Discounted Net Profit Before Investment Distribution for Most Likely Area of 576 Hectares
Pool Minimum MostLikely MaximumParameters Possible Value Value Possible Value
xmln Xprob xMax mt (x) m, (x)
RIG (10' rrr') 1051.7 I 587519
Unit Value ($/m3) 0.008 0.011 0.015 0.01134 0.0001332
M, (DNPBI) = 11.926 M,(DNPBI) =211.4759
I
z M, (DNPBI)a = In = 0.3967M~(DNPBI) .
2 5 10 20 30 40 50 60 70 80 90 95 9810' 10'
w0~
x~
CQ)
102§ 10'
~Q)
>E!!!~ID
'" ,e ,Q. 0
,;; 0 0
z 10 ~BidPrice 10'0
/" Sunk CapitalQ)
C~
Development00
'" Drilling Capitalis ..:.:...-
Tie-In Capital
1 12 5 10 20 30 40 50 60 70 80 90 95 98
Percentage
Figure 6.4-5 Typical Situation: Discounted NetProfit Before Investment
applications of the in-place estimate in economicevaluations. For those who accept that a probabilisticanswer is the limit ofhuman capability, when assessingthe future it is an extremely powerful and flexible, yetdeceptively simple, tool for dealing with the uncertainties of reserves estimation. But it is not infallible. Itcannot compensate for unrealistic input, it cannot warn
a'R50 = M, (DNPBI) e- 2" = $9.78 X 10'
, ,R"., = R50 e =$18.36 x 10
when the input is unrealistic, and it cannot identify thereasons for the discrepancies. These limitations restrictits use to knowledgeable, conscientious evaluators andevaluation teams that are comfortable with the method's assumptions and theory and willing to expend theeffort required to attain realistic input. The payoff forthese individuals is an analysis that faithfully summarizes their thoughts and their earth science expertise ina mathematical form and that can be extended to anydesired depth and variables.
Despite this caveat, the Warren Method will undoubtedlybe attemptedby the unthinkingandthe unqualified;the output, if accepted unquestioningly, will provecostly. The only safeguard is a careful examination ofthe evaluators' competenceand the supportingevidencefor the input. If both survive scrutiny, the predictionsfrom the output are worth testing.
ReferencesAitchison1., and Brown J.A.C. 1966. The Lognormal
Distribution. Cambridge University Press, NewYork,NY.
Capen, E.C. 1976. "The Difficulty of AssessingUncertainty."JPT, Vol. 28, Aug. 1976.
Keefer, D. L., and Bodily, S. E. 1983. "Three PointApproximations for Continuous RandomVariables." Management Science, No. 29, pp.595-609.
Warren, J.E. 1988. "Exploration and ProductionDecisions: Risk, Uncertainty and Economics,"Course, OGGl, Houston, TX, Sep. 1988.
119
Chapter 7
MATERIAL BALANCE DETERMINATION OFHYDROCARBONS IN PLACE
...
7.1 INTRODUCTIONOne of the fundamental principles used in engineeringis the Law of Conservation of Matter. The applicationof this law to petroleum reservoirs is known as the"material balance equation" which has proven to be aninvaluable supplement to direct volumetric calculationof reservoir parameters. Numerous articles and papersdescribe all aspects ofits use in the analysis ofreservoirperformance.
The material balance equation is being widely usedtoday, aided by access to computers and the increasingknowledge base in the literature. The results from material balance calculations are significant because theyare largely independent of the factors that contribute tovolumetric estimates. As databases for production, reservoir pressure, and fluid properties improve, theusefulness of the material balance equation increases.
When oil, gas or water is removed from a reservoir, thepressure in the reservoir tends to fall, and the remainingfluids expand to fill the vacated space. The hydrocarbon system is also affected by fluids and energy sourcesthat are in pressure communication with it. Examplesof these include connected natural aquifers, nearby injection or production activities, and other oil or gasreservoirs.
The material balance is the application of the Law ofConservation ofMatter to a petroleum reservoir duringits depletion history. It is important for the reservoirengineer to understand the system at hand and applythe material balance realistically.
Simply stated, the material balance says that the initialmass, plus the mass added, less the mass removed, mustequal the mass remaining in the system. In reservoirengineering usage, mass is often replaced by volume.Thus the bulk volume, plus fluid entry volumes, plusexpansion, must equal the bulk volume remaining plusvoidage. If the bulk volume is considered constant,then at reservoir pressure and temperature, expansionequals voidage. The writing of a volumetric materialbalance is an exercise in describing the expansion of
120
oil, gas, water and rock with changes in pressure andtemperature over discrete time periods. These timeperiods are chosen to extend from initial productionto various later dates when both reservoir pressuresand voidage cumulatives are known.
The pressure-volume-temperature (PVT) propertiesdescribed in Chapter 5 provide the basis for relatingexpansion to voidage. In material balance usage, rockand fluid volumes are normally considered at two conditions: (I) reservoir pressure and temperature, and (2)surface reference conditions. The PVT data is usuallypresented in a format that conveniently bridges theseconditions. Since changes in reservoir temperature arerelatively insignificant except for thermal projects, experimental PVT data is generally based on a constantreservoir temperature, and pressure is treated as theprimary independent variable.
The material balance equation has been used extensivelyto determine initial fluids in place, calculate waterinflux, estimate fluid recovery, and predict reservoirpressures. The use of the equation in defining initialfluids in place is the focus of this chapter. Applicationsof the equation to gas reservoirs, oil pools, and mixeddrives will be discussed.
7.2 UNDERLYING ASSUMPTIONSIn terms of normal physics, the material balanceequation itselfis devoid ofconditions and assumptions,but in regular oilfield usage, a number of underlyingassumptions arise. These may result from the way inwhich the input data is derived or from computationalsimplifications. The material balance calculation isbased on changes in reservoir conditions over discreteperiods of time during the production history. Thecalculation is most vulnerable to many of its underlying assumptions early in the depletion sequence whenfluid movements are limited and pressure changesare small. Uneven depletion and partial reservoirdevelopment compound the accuracy problem.
s
MATERIALBALANCE DETERMINATION OFHYDROCARBONS INPLACE
7
The basic assumptions in the material balance methodare as follows:
Constant Temperature. Pressure-volume changeswithin the reservoir are assumed to occur without related changes in temperature. The pressure changeshappen slowly in most of the reservoir, and the massof adjacent rock volumes is such that the reservoir system very closely approaches constant temperatureperformance.
Pressure Equilibrium. A uniform pressure is assumedto apply across the pool. The model is considered as atank,with infinite permeability. This is a critical assumptiou, since the expansion properties ofthe rock and fluidsare stated in terms of prevailing pressure. Localpressure variations around producing or injection wellbores may generally be disregarded. However, regionaltrends must be recognized and included in the pressureaverages.
Constant Reservoir Volume. Reservoir volume is assumed to be constant except for those conditions ofrockand water expansion or water influx that are specifically considered in the equation. The formation isconsidered to be sufficiently competent that no significant volume change will occur through movement orreworking of the formation due to overburden pressureas the internal reservoir pressure is reduced. The constant volume assumption also relates to an area of interestto which the equation is applied. If the focus is on somepart of a reservoir system, except for specific exteriorflow terms it is assumed that the particular portion isencased in no-flow boundaries.
Reliable Production Data. As measurement technology has improved and regulatory authorities haveconsolidated the data-gathering process, the reliabilityofproduction and injection data has improved substantially. Good well rate data is critical to the materialbalance, as net voidage figures directly in the calculatedoil in place.
Representative PVT Data. The PVT information is theother main ingredient of the material balance equation.It is assumed that the PVT samples or datasets represent the actual fluid compositions and that reliable andrepresentative laboratory procedures have been used.Notably, the vast majority ofmaterial balances assumethat differential depletion data represent reservoir flowand that separator flash data may be used to correct forthe wellbore transition to surface conditions. Such"black oil" PVT treatments relate volume changes totemperature and pressure only. They lose validity incases ofvolatile oil or gas condensate reservoirs where
compositions are also important. Special laboratoryprocedures may be used to improve PVT data forvolatile fluid situations.
7.3 EXPLANATION OF TERMSAs previously indicated, the material balance equationrelates net reservoir voidage to expansion of reservoirfluids. This section describes the various componentsof voidage and expansion used in the conventional blackoil material balance. .
Table 7.2-1 lists reservoir voidage terms. In addition towellbore flow streams, water influx-efflux acts as apseudo production quantity. Various independent water influx formulations are discussed in Section 7.7.3.
Table 7.2-' Reservoir Voidage Terms
Surface ReservoirFluid Volumes Volumes
Gas cap gas Gpe GpeBgeLiberated gas G -N R (G -N R)Bps p s pspsgs
Injected gas -0- -GiBgiI
Oil Np NpBoWater Wp WpBwWater injected -w -WB
I I w
where G = gas subscripts c = gas capB = formation g = gas
volume factor = injected fluidsN = oil a = oilW = water p = produced fluidsR = gas-oil ratio s = solution gas
w = water
In Table 7.2-1, the formation volume factor, B, is thevolume at reservoir temperature and pressure per unitof surface reference volume. The change in formationvolume factor for the various fluids is proportional totheir compressibilities. Rock compressibility usuallyranges from 0.4 x 10,6 to 1.5 X 10-6 vol./pore volume/kPa (kPa,I), and is primarily dependent upon porosity.Water compressibility is linear with pressure, and rangesfrom 0.3 to 0.6 kPa,l. Oil compressibility showssome nonlinearity with pressure. It varies from 0.4 to3.0 kPa,l, relating to its gravity. Gas at 14000 kPa has acompressibility in the order of 60 x 10-6 kPa,l. Thebehaviour of the material balance calculation followsdirectly from the relative compressibilities as manifestedby the formation volume factors.
121
qiit-
DETERMINATION OFOIL AND GASRESERVES
Table 7.2-2 Reservoir Expansion Terms
(3)BOi
(B, -B,;) + I-S (Swcw+cr)dPw
N
all of the factors that could be applied to routine determinations of oil and gas in place. The fifth term inthe numerator, We' is water influx and is defined inEquation (13) in Section 7.7.
(2)
(1)
In Equation (1) the formation volume factors reflect thereservoir volume per unit of stock tank or surface volume. They are dimensionless, i.e., reservoir m3/surface
m3• The terms of the equation represent volumes or
changes at reservoir conditions. Reservoir engineerscommonly use the same formation volume factors forgas cap gas, solution gas and injected gas, the degree oferror inherent in such a simplification depending uponthe circumstances. If such a shortcut is taken, Equation(1) is reduced to the form ofEquation (2), which will beused to illustrate adaptations ofthe material balance forparticular conditions. The engineer is free to re-insertthe distinction between diverse gas compositions whenit is worthwhile to do so.
7.5 SPECIAL CASES OF THEMATERIAL BALANCE EQUATION
7.5.1 Undersaturated Oil ReservoirsSeveral terms of the material balance equation maydisappear when reservoir conditions negate their use.This is particularly true for the volumetric undersaturatedoil reservoir. For this case there is no gas cap, and sincereservoir pressure is above the bubble-point pressure ofthe oil, there is no free gas in the oil zone. Productiondepends largely upon liquid expansion ifreservoir pressure is being depleted. Therefore, rock and connate waterexpansions are significant and should be included.Equation (3) provides a material balance for anundersaturated pool with water injection, production,and influx.
Expansion
NB,j(Hm)--'-----crdP
I-Sw
N(R,;-R,)Bg,
N(B,-B,;)
NB (Hm) S c dP01 1_8 ww
w
compressibility (volumechange/volume/pressure unit)
formationchange in pressuregas cap reservoir volume/ oil zonereservoir volumeoil in placeformation volume/ surfacereferencevolumeratio of gas content / oil volume (surfacereference conditi'ons)connatewater saturation(fractionof porespace)
Gas Cap
Liberated Gas
Oil
Water
Rock
Material
fdPm
R
NB
where c
As pressure is reduced in an oil-gas-water system,liquid volumes increase in the undersaturated fluid region. When the oil reaches its saturation pressure, gasis released and a vapour phase begins to form. Furtherpressure depletion results in diminishing liquid volumesand rapidly expanding gas volumes. Both total fluidvolume and system compressibility then increase.
Table 7.2-2 provides various expansion terms thatoccur in a material balance equation. These terms offset the various voidage quantities in the material balanceequation.
7.4 GENERAL MATERIAL BALANCEEQUATION
The general material balance equation equatesreservoir voidage to reservoir fluids expansion. If thevoidage terms ofTable 7.2-1 are equated to the expansion terms of Table 7.2-2 and N is factored out fromthe expansion terms, rearrangement yields the generalmaterial balance, Equation (I). This form contains
122
______________________1
MATERIAL BALANCE DETERMINATION OFHYDROCARBONS INPLACE
7.5.2 Saturated Oil ReservoirsThe saturated oil reservoir, either with or without a gascap, exhibits a much greater compressibility than theliquid-filled undersaturated system. Even a small gassaturation is noteworthy, due to the relatively high compressibility of gas. In such cases rock and watercompressibility are often neglected in the interest ofminimizing the calculations. Equation (4) is the material balance equation for a saturated reservoir, initially atthe bubble-point pressure. The terms for gas and waterinjection, water influx and water production may beadded as required.
With the usual assumption of an isothermal reservoir,Equation (6) becomes:
(J,,((Z/P),,-(Z/P),;) =(Jp,(Z/P)" (8)
Rearranging, Equation (8) becomes:
(J" =o, C_(P/Z~,,(Z/P)J (9)
Equation (9) can also be transformed to the form shownin Equation (10):
The gas formation volume factor, 13g' may be replacedaccording to Equation (7):
Eliminating the terms for net water voidage, rock andwater expansion, and those relating to oil zone production and expansion gives Equation (6):
7.6 LIMITATIONS OF MATERIALBALANCE METHODS
The basis of the material balance is firm, and theequation can be made to encompass most ofthe factorsrelevant in hydrocarbon production. However, in practical application, several sources of errors limit theaccuracy of material balance methods. The gravity ofthese errors varies with circumstances.
1. Thermodynamic equilibrium is not attained inactual field conditions.
2. PVT data is obtained using liberation processes thatdo not represent reservoir conditions.
3. Inappropriate average pressures are used.
4. There is uncertainty in the "m" ratio.
5. The production data used is inaccurate.
The amount ofpressure decline covered by the production history is one ofthe best criteria in gauging potentialerrors. The material balance is a comparison ofvoidageto expansion and concentrates on evaluating fluid
Equation (10) is in the form of a straight line, y = mx -tb. Hence, plotting P/Z vs. (J and extrapolating the lineto P/Z =0 yields the initial gas in place. This is a traditional method ofcalculating gas reserves for a volumetricpool. Fluid entry or exit from the system is indicated byupward or downward plot curvature, respectively. Suchperformance may be seen in cases ofwater influx froman aquifer, interference with other pools, or interferencewith a portion of the reservoir outside of the area ofinterest. Formation compaction also may cause anonlinear PIZ curve. In this case the historical trend willrun above the gas-defined slope in early years and thentum sharply down to the true gas in place.
P(P/Z)" = (P/Z)"-(Jp,(--),, (10)
(J"Z
(6)
(7)
(5)
(4)
m~13"(J =--
" 13gci
~p13,1f((Jp-~pFt,)13,
(13,-13,)(13,-13,) -l- (Ft,,-Ft,) 13,1fm13'i s,
P = standard or reference pressurescZ = gas compressibility factorT = reservoir temperatureT = reference temperaturescP = formation pressure
where
7.5.3 Gas ReservoirsGas reservoirs are also amenable to the materialbalance treatment. Starting with Equation (1), it is assumed that water production, influx and injection arezero. Since gas has a very high compressibility, rockand water expansion in the gas cap may be safely neglected. Oil production and expansion terms are notapplicable. Cross-multiplying Equation (I) and makingsubstitution gives Equation (5):
123
expansion. Large pressure declines produce largeexpansions, making inaccuracies in production volumesrelatively less significant. Similarly, pressure errors areless critical with more pressure depletion. In general, apressure decline of 10 percent of the original reservoirpressure is needed before the material balance becomesreliable. This critical depletion level is highly dependent upon the quality of the pressure, production andPVT data.
Pressure errors originate from several sources. Gaugeand sonic survey errors can be compounded duringprocessing and conversion to a common datum. Truestatic pressures may be difficult to derive in low transmissibility pools with high viscosity fluids. Areallyimbalanced withdrawal or injection may create regionalpressure gradients in the pool. It is important that suchareal pressure variations be properly reflected in theaverages applied to material balance equations. Volumetric averaging of measured values is the preferredtechnique. Multiple layers ofdiffering permeability andsevere lateral changes in permeability within the formation may complicate the gathering of representativepressures. A study by Hutchinson (1951) presentsthe quantitative effect of pressure errors on materialbalance determinations of hydrocarbons in place.
7.7 SUPPLEMENTAL CALCULATIONS7.7.1 Gas Caps and AquifersMost ofthe material balance parameters are defined bypressures, PVT measurements, and production-injectiondata. Original oil or gas in place can be calculated insome circumstances,but in cases where gas caps or aquifers exist, the material balance equation contains morethan one unknown. Supplementary calculations mustthen be utilized for a solution.
Gas caps can often be estimated by volumetric means.Core and log data from upstructure wells can be usedwith conventional volumetric mapping techniques toestimate the amount of associated gas that is in contactwith the oil zone. The gas cap volume enters the material balance equation through the parameter "rn" inEquation (1). As gas is a high mobility fluid, the gascap can often be represented as having the same reservoir pressure history as the adjacent oil zone. However,when the gas zone is large relative to the oil zone orwhen the gas zone is geographically widespread, theareal pressure variation within the gas cap should beconsidered. Small errors in gas cap average pressure canproduce large changes in calculated oil in place, becausegas is much more compressible than oil.
124
DETERMINATION OF OIL ANDGASRESERVES
If an aquifer is large enough to impact the pressureperformanceofthe hydrocarbon zones significantly,partof the water is likely to be substantially removed fromthe hydrocarbons, due to its low compressibility. Wateralso has much less mobility than gas. Therefore, theassumption of common pressure used for oil zones andtheir gas caps is usually not applicable to hydrocarbonzones and their aquifers.
7.7.2 Water Influx MeasurementsThe simplest method of externally determining waterinflux for use in the material balance equation is tomeasure it directly. In pools where water influx is anticipated, the operators may periodically log selectedwellbores to determine water saturations. The advanceofthe oil-water or gas-water contact can be defined witha selection of logged wellbores distributed across thearea of the hydrocarbon-water interface. The engineermust have reliable data for reservoir porosity and watersaturation adjacent to the water contact. It is also veryhelpful to have an independent source of residualhydrocarbon saturation in the water-invaded zone.Such data may be obtained from relative permeabilitymeasurements in special core analyses.
The accuracy of water influx volumes from periodicwater contact elevation maps varies with the circumstances. The reliability of water saturation and porosityvalues is important.
There is also an element of doubt in the reservoirstratification. Rock capillarity variations and transmissibility barriers may cause undulations in thewater contact as influx occurs. Areal variations in reservoir pressure can also lead to nonuniform wateradvance. The user should be aware of the potential forerror when working with a limited number of watercontact measurements.
7.7.3 Analytical Water Influx ModelsWater influx may be calculated from the materialbalance equation as a function oftime using a volumetric estimate of oil in place. The engineer can thenendeavour to match this influx vs. time trend with ananalytical "model." Ifa reasonable match ofan extendedhistorical period is achieved with a single set of coefficients, the analytical relationship is plausible andprovides a basis for estimating future influx for use inthe material balance.
Schilthuis (1936) provided the simplest aquifer influxmodel. His model assumes that constant pressure ismaintained somewhere in the aquifer and that flow tothe oil zone is proportional to the pressure differential,
•
n
MATERIAL BALANCE DETERMINATION OFHYDROCARBONS INPLACE
W, = BL [~p. Q (t)] (13)
with the remaining factors in D'Arcy' s Law constant.Equation (II) shows the Schilthuis steady stateformulation:
~p = pressure differential, aquifer limit tooil-water contact (kPa) (psi)
Q(t) = dimensionless water influx;function of to
to = dimensionless timelJ. = constant, 0.0863 (6.323 x 10-3)
k = aquifer permeability (Ilm2)(mD)t = time (days)<I> = porosity, fractionalIl = water viscosity (mPa's)(cp)c = effective rock, water compressibility,
kPa-1(psi")rw = equivalent oil zone radius (m) (ft)~ = constant, 6.2792 (1.119)h = equivalent aquifer thickness (m) (ft)El = azimuth angle of aquifer inflow
(degrees)
The superposition theorem is applied to calculate waterinflux, We' The pressure history at the water contact isdivided into a series oftime intervals for which averagecontact pressures can be estimated. These average pressures define decrements between the initial aquiferpressure and the hydrocarbon interface pressure that areassumed to be constant within each time interval. Thesuperposition theorem holds that the aggregate effectof all these pressure differentials is equivalent to thesummation of their individual effects, each operatingover its respective time interval. In practice, reservoirparameters are chosen to calculate to as a function ofthe time intervals. Tables and figures ofQ(t) have beensupplied by Van Everdingen and Hurst (1949) and inthe summary by Craft and Hawkins (1964). Craft andHawkins also provide a good description ofhow to calculate the summation of~PQ(t) to get W as a functionof time. e
Carter and Tracy (1960) developed a method based onHurst's (1958) simplification of the Van Everdingenand Hurst unsteady state influx calculation. The CarterTracy method gives answers similar to those of VanEverdingen and Hurst without the iterative solutioninvolving the conventional material balance equationand the water influx summation equation.
(I I)
(12)
(14)
dW,= c(p;-p)
dT log (at)
where k = water influx constant (m3/d/kPa)
P, = aquifer boundary (initial) pressure(kPa)
p = oil-water contact pressure (kPa)
Hurst (1943) proposed a modification ofEquation (II)wherein the influx constant is altered and a denominatorterm, log (at), is added. The denominator compensatesfor the gradually lengthening flow path of the waterthrough the aquifer as depletion progresses. Hurst'smodification is shown in Equation (12):
where c = water influx constant (m3/d/kPa)
a = time conversion constant that dependson units of time
t = elapsed time from start of influx (h)
Van Everdingen and Hurst (1949) produced an unsteadystate water influx solution which can deal with infiniteor limited aquifers. This model is based on radial flowfrom a concentric aquifer to an interior oil zone, but itcan be adapted to situations where the aquifer underliesor extends primarily in one direction from the oil pool.Van Everdingen and Hurst overcame the site-specificnature of the solutions to the radial form of the diffusivityequation by providing their data in terms ofdimensionless time and dimensionless influx. Briefly, their
. formulation is as follows:
where WeB
ElB = Amcr ' h
t''Y w 360
= water influx (m") (bbl)= water influx constant (m3/kPa)
(bbllpsi)
(15)7.8 MULTIPLE UNKNOWN MATERIAL
BALANCE SITUATIONSThe solution methods outlined rely on separatelydetermining relationships for secondary unknowns inthe material balance equation, namely the gas cap to oilzone ratio, m, or the water influx term, We' A secondtechnique utilizesa simultaneous solution for oil in placeand a secondary parameter. Theoretically, given
125
DETERMINATION OF OIL AND GASRESERVES
where cf = formation compressibilityCw = water compressibilityB, = formation volume of oil and originally
dissolved gas
Using Havlena and Odeh terminology, the left side ofEquation (16), denoted by F, represents the net reservoir volume ofproduction. The expansion terms for oil,rock and water, and gas on the right side, are denoted
multiple pressure and production combinations, thematerial balance equation could be simultaneouslysolved for multiple unknowns. In practice, transient effects, data errors and unrepresentative averages makethe simplistic simultaneous solution unreliable.
Havlena and Odeh (1963) presented an algebraicrearrangement of the material balance. Their techniqueinvolves calculating production and expansion entitiesthat are interrelated as terms of a linear equation. Sincethe pressure-production-time points plot as a straightline, graphical methods can more easily be used to determine the best solution for the dataset. Havlena andOdeh emphasized the idea of examining multiple values of a parameter by means of a statistical variationfactor. In some circumstances, this approach provides auseful supplementary measure of how well the entirepressure-production history is satisfied by a particularreservoir solution.
The straight-line method involves the use of variablegroups. The reservoir circumstances determine whichvariable groups are plotted against each other. Thismethod attaches a significance to the sequence anddirection of the plotted points and the shape of theresulting plot. The variable groups can be effectivelycomputed and plotted with a spreadsheet program,particularly if the derivation of PVT data is automatedthrough macros. The analyst must then examine thesequence and configuration of the plot points to assesstheir meaning.
With minor rearrangement, Equation (2) may berewritten as:
N
N =oil inplace
Figure 7.7-1 Straight Line Plot for Oil Zone andGas Cap Case
The usual criteria for a successful material balancesolution are consistency of the results and agreementwith volumetric calculations. The consistency aspect isoften left as a rather nebulous, unquantified factor, butHavlena and Odeh offer a method to systematize it.Agreement with volumetric oil in place estimates canbe overemphasized. Volumetric calculations tend tofocus on total oil in place due to their reliance on geologic interpretations and petrophysical data. Materialbalance oil-in-place is the active oil that takes part inthe depletion history. The similarity of volumetric andmaterial balance oil-in-place values should not beoverrated as a measure of the accuracy of either.
BtlE,+rnsEg
g'
Source: Havlena and Odeh, 1963.
u,
by Eo, s, and Eg, respectively. The s, components maybe deleted, except in the case of undersaturatedoil pools.The final right term, We' is calculated by the unsteadystate water influx equation, Equation (13). Alternatively,the Carter-Tracy influx formulation could be used.
There are many different formulations of the straightline material balance method. The reader is encouragedto reference the comprehensive and readable presentation by Havlena and Odeh (1963). Figure 7.7-1 showsthe form of the straight-line plot for a pool with unknown oil zone and gas cap size, and Figure 7.7-2portrays one with unknown oil zone and water drive.McKibbon et al. (1963) provide an excellent exampleof the application of the straight-line material balanceto an oil reservoir with active water influx.
(16)mB J+ --" (B.-B,,) +W,n,
N, [B,+ B,(R,-R,,)] + (W,-W,) a, -G,B"
126
$
MATERIAL BALANCE DETERMINATION OFHYDROCARBONS INPLACE
Figure 7.7-2 Straight Line Plot for Oil Zone andWater Influx Case
7.9 COMPUTER SOLUTIONSComputer spreadsheets are valuable tools in materialbalance work. They greatly reduce laborious calculations and allow easy sensitivity analyses with varieddata. A noteworthy advantage of spreadsheets is thatthe user retains complete knowledge and control of thecomputation method.
Although it is theoretically possible to solve formultiple unknowns with the straight-line method, inpractice, difficulty is met in some cases. Highly accurate data are needed to solve simultaneously for a notablegas cap and an oil zone, or for a gas cap, oil zone andwater influx. The difficulty in these two cases relates tothe high compressibility of gas and its large potentialimpact on the pressure response.
In conclusion, the straight-line requirement does notprove the uniqueness of the solution, but is one of theconditions that a satisfactory solution should meet. Asalways, the quality of the solution will depend on thequality and quantity ofthe input data and on the abilityand thoroughness of the analyst. The straight-linemethod is recommended as being robust and effective. Its dynamic nature is a valuable supplement totraditional methods.
Formal computer programs are available to performmany material balance calculations. They handle muchof the repetitive computation and greatly speed thesolution process. However, users must be sure that theyunderstand how such programs work. The methods mustfit the problem and be compatible with the availabledataset.
Havlena and Odeh (1963) caution against total automation ofthe straight-line material balance, because thesequence and direction of successive points provide information as to the nature ofthe solution. The engineershould take care to scrutinize this aspect ifmachine plotsare utilized in the straight-line method.
ReferencesCarter, R.D., and Tracy, G.W. 1960. "An Improved
Method for Calculating Water Influx." Trans.,AIME, Vol. 219, p. 415.
Craft, B.C., and Hawkins, M.F. 1964. AppliedPetroleum Reservoir Engineering. Prentice Hall,Inc., Englewood Cliffs, NJ, p. 205.
Havlena, D., and Odeh, A.S. 1963. "The MaterialBalance as an Equation of a Straight Line."Trans., AIME, Vol. 228, p. 896.
Hurst, W. 1943. "Water Influx Into a Reservoir andits Application to the Equation of VolumetricBalance." Trans., AIME, Vol. 151, p. 57.
---.. 1958. "The Simplification of theMaterial Balance Formulas by the LaplaceTransformation." Trans., AIME, Vol. 213, p. 292.
Hutchinson, C.A. 195I. "Effect of Data Errors onTypical Engineering Calculations." Paper presented at SPE of AIME meeting, Oklahoma City,OK.
McKibbon, lH., Paxman, D.S. and Havlena, D. 1963."A Reservoir Study ofthe Sturgeon Lake SouthD-3 Pool." JePT, Vol. 2, No.3, Fall 1963, p. 142.
Schilthuis, R.l 1936. "Active Oil and ReservoirEnergy." Trans., AIME, Vol. 118, p. 33.
Van Everdingen, A.F., and Hurst, W. 1949. "TheApplication of the Laplace Transformation toFlow Problems in Reservoirs." Trans., AIME,Vol. 186, p. 305.
B=N = oil in place
o0 IdpQ(A1D)
Eo
Source: Havlena and Odeh. 1963.
N
127
i
g
R
PART THREE
ESTIMATION OF RECOVERY
FACTORS AND FORECASTING
OF RECOVERABLE HYDROCARBONS
---
----------------------------71
Chapter 8
OVERVIEW OF PART THREE
8.1 INTRODUCTIONPart Two focuses on in-place hydrocarbons or resources;Part Three addresses reserves, which are the portion ofthe resource, or the quantities ofoil and gas and relatedsubstances that are economically recoverable underknown technologies and a generally acceptable forecastof future economic conditions.
Forecasting of recoverable hydrocarbons may beapproached from several standpoints: recovery factoras a percentage of original in-place resources; statistical analogies, reservoir simulations, and material balancetechniques; or methods such as decline analysis, wherethe determination of in-place hydrocarbons is not arequirement.
Many factors may affect the recovery ofhydrocarbons:
• Depletion mechanisms and the timing of theimplementation of various recovery methods
• Reservoir and hydrocarbon characteristics
• Well spacing, completion techniques, mechanicalconditions, and production equipment
The natural depletion mechanisms for oil include, butare not limited to, primary production mechanisms inwhich reservoir fluids are produced as a result of theenergy of fluid expansion, solution gas drive, waterdrive, gas cap drive, compaction drive, and combination drive. These primary production mechanisms aredescribed in Chapter 9.
Production of natural gas generally involves primarydepletion using surface compression, but recovery ofliquid- and sulphur-rich gases often utilizes re-injectionof dry gas or cycling to maximize recovery. The depletion methods for natural gas recovery are covered inChapter 10.
Primary oil recovery can be improved by secondary andtertiary recovery schemes referred to as "enhanced recovery." Chapters II through 15 describe the variousenhanced recovery methods used in oil reservoirs: waterflooding, hydrocarbon miscible flooding, immiscible
gas injection, thermal stimulation, and carbon dioxideflooding.
Another method of improving recovery from oilreservoirs is by the use ofhorizontal wells, which allowdrainage from larger areas than vertical wells. Chapter16 discusses horizontal wells.
Reservoir characteristics that may affect hydrocarbonrecovery include heterogeneity and reservoir discontinuities, both vertical and lateral; the structuralcharacteristics of the reservoir; the presence of naturalfractures, both open and closed; pore size geometry anddistribution; permeabilities; in situ stresses and fractureorientation; parting pressures (injecting fluids); andreservoir pressure.
Hydrocarbon characteristics that may affect recoveriesinclude viscosity, composition, and the pressurevolume-temperature relationships of the hydrocarbonsin the reservoir. The interrelationship of fluids andreservoir rock, expressed in terms such as interfacialtensions and wettability, control fluid movement in areservoir. The overall contrast between the mobility offluids in a reservoir significantly affects recovery.
The well spacing, completion intervals within wells,completion techniques such as fracturing, and proximity of wells to underlying water or a gas cap are all factorsto consider when analyzing recoveries. Mechanicalequipment such as compressors can also significantlyaffect recoveries as well as the abandonment ofwells.
8.2 PURPOSE OF DEPLETIONSTRATEGY
The purpose of a depletion strategy is to maximizeproject economics and the recovery of hydrocarbons.While this may sound obvious, the current focus onquarterly earnings by most North American shareholders, coupledwith a tough economic climate, often resultsin the need for immediate cash flow, which sometimesoverrides longer term business strategies. However, itshould not preclude companies from investigating other
131
development options and addressing those that meet theirfinancial constraints.
The development of a depletion strategy shouldultimately result in the identification of all potential recoverable reserves and the establishment ofa frameworkthat can maximize revenues from the project.
Developing a depletion strategy early in a project is veryimportant because the timing of the implementation ofvarious production strategies could be critical. It maynot be prudent to continue primary production withoutfully addressing a depletion strategy for a pool. Thefollowing are examples of what could happen:
1. Depleting a gas cap could cause a disastrousdecrease in the recovery factor of an oil pool.
2. Production from an oil pool to the extent that thepressure drops below the critical gas saturation inthe reservoir prior to commencement of a waterflood could have a detrimental effect on recovery.
3. Gas production with the pressure decliningsignificantly below the dewpoint in a retrograde gascondensate reservoir before implementing a dry gascycling scheme could result in a dramatic decreasein liquid recovery.
Planning the depletion strategy during the initialdevelopment stages ofa pool will also identify the appropriate data that should be gathered and accumulatedthrough both the drilling and the production stages ofdevelopment. The availability of this information willassist in identifying the most economically feasibledepletion mechanism.
8.3 TECHNIQUES FOR RESERVESAND PRODUCTION FORECASTING
The techniques used for reserves estimation andproduction forecasting vary depending upon severalcriteria:
• The reservoir depletion strategy
The type of depletion mechanism, both existing andfuture
• The stage of reservoir development and depletion
• The extent of the production history
• The constraints that have been imposed on production by regulation, markets, or the physical nature ofproduction facilities .
132
DETERMINATION OFOILANDGASRESERVES
The reliability of techniques to forecast reserves andproduction improves during the life of the pool as moreoptions become available. In the very early stages, withlittle more than geophysical, geological, and wellboredata and test information available, it is common practice to rely on analogy and statistical data for preliminaryreserves estimates.
During subsequent phases of reservoir depletion, theavailability of increasing volumes of information maylead to the use of two more sophisticated techniquesof reserves estimation: numerical simulation anddecline curve analysis. These are the techniques mostcommonly used for reserves estimation and productionforecasting.
The use of numerical simulation is not restricted toreservoirs with significant producing histories, but theability to calibrate the reservoir model developed bymatching historical performance offers far more reliable results although the technique is often expensive.This technique is of particular value where decisionsare necessary regarding the feasibility of some form ofenhanced recovery mechanism. Numerical simulationis discussed in Chapter 17.
Decline curve analysis is both used and misused inreserves and production forecasting, and it has widespread use in every aspect ofreservoir depletion. Clearly,the more established a decline trend becomes, the morereliable the extrapolation ofthat trend, provided the underlying reservoir or production mechanism that iscausing the decline does not change. Decline curveanalysis is discussed in Chapter 18.
In Part Two, the techniques for determining the mostlikely in-place hydrocarbon volumes are discussed. Theassignment of recovery factors to these volumes at thisstage, particularly in the case of oil, requires anassessment ofthe reservoir environment and the recovery mechanism in order to determine likely performanceby analogy to similar, and preferably nearby, pools.In westem Canada, a wealth of statistical data is available from the Alberta Energy Resources ConservationBoard (ERCB); the B.C. Ministry of Energy, Mines,and Petroleum Resources; and the SaskatchewanDepartment of Energy and Mines. Some ERCB data ispresented in Chapter I9.
____________________..d
Chapter 9
NATURAL DEPLETION MECHANISMSFOR OIL RESERVOIRS
Pressure drops in a reservoir caused by the withdrawalof some of the fluids initiate the expansion of theremaining fluids. Oil, gas, and water are then producedas a result of their expansion and the expansion of thesurrounding reservoir rock. This recovery processis called a natural depletion mechanism. The namesfor the various natural depletion mechanisms-fluidexpansion, solution gas drive, water drive, combinationdrive, and gas cap drive-are associated with the majorcontributing source of expansion energy. When morethan one major source of expansion energy contributesto the depletion process, it is referred to as a combinationdrive.
This chapter discusses the natural depletion mechanisms,the types of predictive tools and their applicabilityat the different stages of development of a reservoir,and the factors affecting recovery.
9.1.1 Fluid ExpansionFluid expansion exists as a natural depletion processwhen only one mobile fluid exists in the reservoir. (Fluidmay refer to either gas or oil.) The withdrawal of someof this fluid will cause a pressure drop. The remainingfluid will expand and displace itself toward the pressure drop. Because ofthe highly compressible nature ofgas, fluid expansion is generally the dominant depletion mechanism in gas reservoirs. Conversely, becauseofthe low compressibility ofliquids, fluid expansion isnot a good source of depletion energy in oil-filled reservoirs. Fluid expansion in oil reservoirs exists by itselfonly at pressures above the bubble point. At the bubblepoint, the gas dissolved in the oil breaks out ofsolution,and the expansion energy associated with the compressive nature of this gas becomes the dominant depletionmechanism. Only oil deposits containing very undersaturated oil will be produced with fluid expansionas their dominant depletion mechanism.
Pressure
SolullonGas Drive
,. .... -- .....
"/ \I \
~I \q!!'1
rY/ 1~I Io
II
//
Cumulative Oil
IIIII
OilProduction
----_ ....
Expansion
9.1.2 Solution Gas DriveThe predominant source ofenergy for solution gas drivecomes from the expansion of gas released from the oil.As the pressure drops in a reservoir, the ability of theoil to keep gas dissolved is reduced, and free gas is released. With further pressure reduction, the free gasexpands and displaces oil towards the producing wells.Because of its highly compressible nature, the gas willexpand and displace significantly more oil than aninitially equal volume of liquid.
In an undersaturated oil reservoir, that is, one withoutany initial free gas, the initial depletion mechanism willbe due to the expansion ofoil. Generally, there will be adirect relationship between the volume and rate at whichthe oil is produced and the pressure reduction, as shownin Stage I in Figure 9.1-\. When the pressure dropsbelow the bubble point, free gas is released and becomesthe major source of expansion energy. Gas-oil ratiodoes not significantly increase during this stage untilthe critical gas saturation is reached. Because of thecompressible nature of the gas, with continued oilproduction, the pressure drop is significantly reducedand the oil rate will be fairly constant, as shown in StageII of Figure 9.1-\.
INTRODUCTION9.1
Figure 9.1-1 Solution Gas Drive Reservoir
133
,DETERMINATION OF OIL AND GAS RESERVES
As the pressure continues to drop, the evolved free gaswill reach the critical saturation; at this point, gas willstart to move and will be produced in conjunction withthe oil. As the gas saturation increases, the ease withwhich gas moves within the reservoir relative to oilincreases, and the gas is then produced preferentiallyover the oil. With continued production and the associated pressure drops, the gas continues to be evolved,increasing its saturation level. The production of gasincreases and the production ofoil decreases. This complicated procedure, represented by Stage III in Figure9.1-1, continues until the rate at which gas is beingevolved from the oil is less than the rate of gas beingproduced. At this point, the pressure and production ratesdrop quickly, as shown in Stage IV.
9.1.3 Water DriveAn oil deposit is considered to be produced by waterdrive when the predominant source of expansion energy comes from the water-filled portion of the reservoir.Since water has a lower compressibility than oil, thevolume of water needs to be significantly larger thanthe oil-filled portion of the reservoir.
The pressure in the oil deposit will drop as productionis initiated. As the pressure gradient reaches the aquifer, the water starts to expand, displacing the oil towardthe producing wells. If the aquifer is large enough andthus has sufficient expansion energy, all the mobile oilwill be produced without any further pressure drops.The oil rate will remain constant until the aquifer contacts the producing well, after which the waterproduction will increase as the oil rate drops.
If the aquifer is not large enough to provide fullpressure support, the pressure drops. When the bubblepoint pressure is reached, free gas will be released, andthis gas will start to contribute significantly to the depletion energy. This type of depletion mechanism is referredto as a combination drive because there is more thanone significant source of depletion energy. Figure 9.1-2shows the relative difference between solution gas drive,full water drive, and a partial water drive.
In many situations, at a localized area around theproducing wells, the water contact will rise dramaticallyand effectively water out the wells. This phenomenonis called "water coning." The consequence of water coning is that large volumes of oil will be trapped and thusbecome unrecoverable. In reservoirs that are subject toconing, recovery factors tend to be very low. The moreviscous the oil and/or the greater the vertical permeability, the more dramatic the effect of coning onrecovery.
134
PartialWaterDrive .,
ty0t\ »>
'\et '5\l.9....... '!\QI.1\ ... '"
'ncteas\~9_~- Full
~ - --~-- ~~~~Solution
Gas Drive
Cumulative Oil
Figure 9.1-2 Comparison of Solution Gas Driveand Water Drive Reservoirs
9.1.4 Gas Cap DriveA reservoir that initially contains free gas as well as thegas dissolved in the oil will benefit from the additionalexpansion energy of the free gas. If the volume of freegas is large enough so that this source of expansionenergy overshadows the effect of other sources of energy such as solution gas drive, the primary depletionmechanism is called a gas cap drive.
As in water drive reservoirs, the oil undergoes aninitial pressure drop until the pressure gradient reachesthe gas cap. The gas then expands and displaces the oiltoward the producing wells. If the gas cap is largeenough, the oil deposit will undergo only minimal pressure drop, and the oil production rate will remainconstant until the gas cap reaches the producing wellinterval. Due to relative permeability effects, the gasproduction rate will then increase quickly as the oil ratedrops off. If the gas cap is not large enough to give complete or nearly complete pressure support, then as thepressure drops, solution gas drive will be contributingfree gas energy. The resultant drive mechanism is alsoreferred to as combination drive. Figure 9.1-3 showsthe response ofa gas cap drive reservoir that becomes acombination drive reservoir.
As in water drive reservoirs, many gas cap drivereservoirs are also subject to coning effects. Because ofthe inherent differences in viscosity of gas and oil,coning is often more serious in gas cap reservoirs thanwater drive reservoirs. In the presence of gas coning,recovery factors tend to be relatively low.
9.1.5 Compaction DriveIn weak, unconsolidated reservoirs, the pressure dropdue to the production of fluids causes an imbalance III
__________________FZ8
NATURAL DEPLETION MECHANISMS FOR OILRESERVOIRS
this "sandwich" effect. The recovery factor in thissituation would be fairly low.
Figure 9.1-3 Gas Cap Drive Reservoir
Time
MaterialBalance ~>
Decline Analysis-)--,
-<-' Numerical Simulation )-
Analytical Methods "-.~ )-
k-c7""c-_- Analogous Methods -~
*a:is
9.2 FORECASTING OFRECOVERABLE OIL
Throughout the productive life of a reservoir, there isalways a need to establish the reserves. Recovery estimates are used to justify capital spending, predict futurecash flow generation and, ultimately, estimate shareholder value. Because of the importance of reserveestimates, al1 available data should be used when determining the size of the oil deposit and the amount of oilthat can be recovered economical1y. The amount andaccuracy ofthe available information increase as an oildeposit passes through the various phases of theproduction life cycle. Thus, the recommended methodologies used to estimate recoverable oil change as thequantity of information increases.
Two basic approaches are used to establish reserves foran accumulation. In the first approach, the ultimate economic recovery factor is established through analogousor analytical methods, and then applied to volumetricestimates based on geological interpretations (as discussed in Part Two). The second approach predicts futureproduction rates, with reserves calculated as the summation of the volume produced above the economiclimit. Table 9.2-1 and Figure 9.2-1 show the recommended methodologies according to stage ofproductionlife and whether recovery factor or reserves arepredicted. Sometimes material balance and numericalsimulation are useful in the development stage
The purpose of establishing a reserves estimate, the sizeand value of the reserves to the corporation, and the
Figure 9.2-1 Recommended Methodsfor the Stages of Exploitation
,,,,,,,,,,,,
___ Pressure
Cumulative Oil
OilProductionRate
the stress within the bulk rock, and the weight ofthe overburden causes the bulk rock to compact.The compacting rock squeezes the internal fluids,thus maintaining the pressure. The resultant drivemechanism is referred to as compaction drive.Compaction drives are found in heavy oil reservoirsand some natural1yfractured reservoirs where fracturestend to close as the reservoir is being depleted. Compaction drives can increase the recovery due to solutiongas drive by more than 10 percent of the original oil inplace.
9.1.6 Combination DriveOften recovery from oil reservoirs is the result ofmorethan one drive mechanism. A reservoir with combination drive poses a difficult problem for reserveestimation. General1y one depletion mechanism is dominant at any stage of depletion or geographic area of thereservoir. In a reservoir that has a smal1 gas cap, initial1y the dominant drive mechanism is solution gasdrive. When significant volumes of gas have evolvedoutof solution, the dominant drive mechanism becomesgas cap drive. For example, in the presence of both agas cap and an aquifer, the dominant mechanism at thegas-oil interface would be gas cap drive, and the dominant drive mechanism at the water-oil interface wouldbe water drive. It is critical for the evaluator to understand the reservoir and which drive mechanism isdominant.
In a combination drive reservoir that has both a waterleg and a gas cap, coning has a double effect in thatthe gas cones downward and the water cones upward.Thus, significant volumes of oil will be by-passed by
135
•DETERMINATION OF OIL AND GAS RESERVES
Table 9.2-1 Recommended Reserves Forecasting Methods
Stage
Exploration
Delineation/development
Early life
Middle/late life
Abandonment
Forecast Method
AnalogousAnalytical methods
AnalogousAnalytical methods
Analytical methods
Numerical simulationDecline analysisMaterial balance
Actual production
What is Forecasted
Recovery factorRecovery factor
Recovery factorRecovery factor
Recovery factor
ReservesReservesOOIP
Reserves
amount and reliability of the data should dictate thedegree of effort put into calculating an estimate. Oftencomparing two or more methods of evaluation isrecommended. For example, an estimate determinedfrom decline analysis could be compared with onecalculated using an analytical method.
Information on a particular reservoir can be obtainedby techniques such as drilling, coring, logging, production testing, pressure testing, and fluid analysis. Priorto obtaining any ofthis information through the drillingof the first well, the evaluator must resort to the useof established information from analogous fields.Analogies can be used to estimate recovery factors,initial production rates and decline rates that are appliedto the geological interpretation. The more similar theanalogous field is in size, depth, fluid properties andformation, and the closer its proximity to the prospect,the better the estimate of recovery factor will be.
In analytical methods, the mathematical equations thatrepresent material balance calculations have been simplified by making certain assumptions about particularparameters. By measurement of some and "guessing"at the remainder, the evaluator can establish the recoveries. Analytical methods have been developed for themore complicated processes such as solution gas drive,water drive and gas cap drive. Fluid expansion is a fairlysimple process, and therefore production forecasting andrecovery estimates are generally solved directly fromthe material balance equation. Analytically predictedrecovery factors along with either early life productionhistory or rates based on analogous fields are appliedto the geological interpretation in order to establishrecoverable volumes of hydrocarbons.
Material balance, whether done graphically ornumerically, attempts to establish initial in-place
136
volumes of oil, gas and water. In order to establish arecovery estimate, the results of the material balanceanalysis must be combined with another prediction technique or assumptions applied to the depletion of thereservoir. For example, assumptions on abandonmentconditions define the pressure or production rate at whichthe field would be abandoned; thus the differencebetween volumes in place and the volumes remainingat abandonment establishes the reserves. The materialbalance method is discussed in detail in Chapter 7.
Decline analysis is the prediction of future rates basedon observed behaviors seen in actual production histories. Typically, reservoir engineers forecast the futurewell flow behaviours by extrapolating production history using a straight line. A single straight line willrepresent the entire life ofa reservoir only when there isone source of reserve energy in a simple homogeneousreservoir with all wells producing at a similar rate. Inother words, a single straight line would represent theentire production life for only a few oil reservoirs. Inusing decline analysis, it is important to know what stageof the natural depletion is represented by the production history and is being represented by the prediction.More than one straight-line segment may be necessary.
Other factors that can invalidate the use ofthe straightline method are the existence of dual porosity systems,layered reservoirs with each layer having different properties, and geographic areas of an accumulation witheach area having different properties. These phenomena, when incorporated into the prediction, change whatwould have been a straight-line segment in a homogeneous reservoir into a curved line. A technique to handlegeographic differences is to subdivide the reservoir i?toareas of similar characteristics and perform dechne
--------------------_....
NATURAL DEPLETION MECHANISMS FOR OIL RESERVOIRS
analyses on each area. Summing the various areas willgive a more accurate picture of the entire reservoir.
Numerical simulation, material balance and declineanalysis are the methods most commonly used in themiddle and late stages of depletion. These methods require a sufficient amount ofreliable data to be effectivepredictors of recoveries. The following subsectionspresent general comments on the use ofthese methodsfor the specific drive mechanisms. Numerical simulation and decline analysis are discussed in more detail inChapters 17 and 18, respectively.
9.2.1 Solution Gas DriveOil recovery as a result of solution gas drive typicallyranges between 2 and 30 percent. The lower recoveriesgenerally occur in low API, shallow, and low pressureoil reservoirs, whereas the higher recoveries occur inhigh API oil, deep, and high pressure reservoirs.
Analytical Methods
The most common analytical methods for estimatingrecovery in solution gas drive reservoirs are based onmaterial balance concepts. Four methods are applicablebelow the bubble point. The most common analyticalapproach used is the Tracy Method, followed by theMuskat Method.
The following are the most commonly used analysismethods:
The Tracy or Tarner Method (Tracy, 1955) is a rearrangement of the basic material balance equation sothat pressure-dependent variables are grouped. Tamerextended the method by incorporating the gas-oil equation based on gas-oil relative permeability curves,resembling the Pirson and Muskat methods.
The Muskat Method (Muskat, 1949) uses the materialbalance equation, written in differential form, in conjunction with the gas-oil relative permeability curves.Because of the importance of these curves, some degree of confidence in the data is crucial.
The Pirson Method (Pirson, 1950) is based on theSchilthuis material balance equation written in finitedifference form. This is essentially a material balanceequation that predicts oil recovery as a fraction of oil inplace at the bubble point as the pressure declines over atime period. The gas-oil relative permeability curve isrequired to define the producing gas-oil ratio.
The Humble (Schilthuis) Method (Schilthuis, 1936)is based on the Schilthuis material balance equation. Inthe forecasting of future production, the equation isapplied to reservoir conditions at the beginning and end
of specified periods, and the interim production orpressure change is obtained by difference.
Short-cut methods are used when there is little data orwhen a recovery estimate is desired quickly. These arenot recommended if a high degree of confidence isdesired. Two short-cut methods are as follows:
Wahl et al, (1958) created various nomographs basedon the Muskat Method using varying fluid propertiesand relative permeability characteristics.
The Roberts and Ellis (1962) Method uses the earlyGaR data to predict future production. Using oil gravity and solution gas-oil ratios, the trend of producinggas-oil ratio is matched to the published predictions.
Decline Analysis
The productive life for a solution gas reservoir thatinitially was above the bubble point is made up of fourdistinct stages as shown in Figure 9.1- I. In a declineanalysis, the analyst must know what stage ofdepletionis represented by the production and must predict whenthe reservoir will enter future stages. Because ofthe difficulty of predicting when these future stages will occur,production decline analysis is generally not used as apredictive tool until the production data reaches StageIII.
Reservoir Simulation
In solution gas drive reservoirs, generally analyticaland decline techniquesare sufficient to estimate reserves.In special situations typically dictated by geologicaldiscontinuities or heterogeneity and in naturally fractured reservoirs, simulation may be warranted toestablish reservoir flow and resultant recoveries.
9.2.2 Water DriveOil recoveries in a water drive reservoir can typicallyrange from 2 to 50 percent depending on factorsinherent in the reservoir.
A common method for evaluating recovery efficiencyof water drive reservoirs uses the observed rise of thewater-oil contact due to the water influx from the aquifer. This requires sufficient production history for thewater-oil contact to rise noticeably and a method ofmeasuring the rise. The relationship over time betweenthe fraction of the reservoir invaded by water and theinitial oil-filled reservoir compared to the oil producedallows the prediction of the total oil recovery.Additional factors that affect reserves include coning,fractional flow, and economic limit.
137
Analytical Methods
If the observation of the advance of the water-oilcontact is insufficient to directly predict recovery efficiency, or direct measurement of the advance is notpossible, theoretical methods based on material balanceare recommended with preference given to the WelgeMethod. Assuming near-constant pressure at any time,the reservoir recovery, ER, can be calculated using therelationship:
where W, = water influxWp = cumulative water productionBw water formation volume
factorWe - Wp Bw net water influx at reservoir
conditionsHCV, = cumulative water-invaded
hydrocarbon volume
Ultimate recovery is then determined from reservoirproduction vs, cumulative water encroachment.
The following are the most commonly used analysismethods:
The Welge Method (Welge, 1952) is recommended ifproduction history data is insufficient to determine theefficiency of the water drive. Fractional flow of water,fw' as a function of water saturation, is used to predictoil recovery.
throughput areaformation permeabilityrelative permeability to oildensity difference, water densityoil densityacceleration due to gravityformation diptotal throughput ratewater viscosityoil viscosityrelative permeability to water
where
138
Ak =!c"o.1.p =
gCJ. =q,Ilw =Jlo ::;:;:
k.w=
W,· w,e,E = --'---'---'-
R HCVe
I . _A_kk-,,"::..:(_.1.,:-:,pg::...s_in_CJ....:.)q,/.lo
I + /.lw k,"J.Lok.;
(I)
(2)
DETERMINATION OFOILANDGAS RESERVES
The last term on the right-hand side of Equation (2)represents the effect of gravity on fractional flow. Fora nontilted reservoir, this term becomes zero. Therelative permeability vs. saturation relationship must bereliable in order for this method to result in a reasonable recovery estimate.
The Dietz Method (Dietz, 1953) predicts oilrecovery in reservoirs where the waterfront flows updip along the base of the formation, causing the frontto assume a tilted position. This is especially noticeable in reservoirs with a water influx rate that exceedsthe critical rate and in reservoirs containing viscous oil.
The MarshaI'Method(Marshal, 1957) uses BuckleyLeverett theory to predict recovery in a stratifiedreservoir. From production history the time required fora given water cut to move between two rows ofwells ina field is obtained, and the velocity of the water frontdetermined. Field-measured water cuts are used to describe oil-water relative permeability curves. Ifenoughwater-cut ranges are available, the fractional flow curvevs. distance in the reservoir, as defined by BuckleyLeverett, can be predicted.
The Schilthuis Method (Schilthuis, 1936) determineswater influx by calculating the water flow from the aquifer to the reservoirin a series ofsteady-state steps. Waterinflux is assumed to be proportional to the pressure difference between the aquifer and the reservoir. Sinceaquifer pressure is assumed equivalent to the initialreservoir pressure, this method is valid only forinfinite-acting aquifers. The weakness in this methodis due to calculation of an aquifer constant fromproduction history.
The Modified Hurst Method (Hurst, 1943) is similarto the Schilthuis material balance method in that it also
. predicts water influx. The Hurst equation extends theSchilthuis Method by accounting for the increase in thedrainage radius in the aquifer.
Correlations have been identified and should only beused for quick evaluations or where data is minimal:Khan and Caudle (1968) for thin oil columns, Caudleand Silberberg (1965) for edge-water drive, Hutchinsonand Kemp (1956), and Henley et al. (1961).
The analytical methods discussed in this subsectionassume that the water-oil contact rises as a flat surface,either from the flank or from the bottom. If the reservoir is subject to coning, these analytical methodswill overestimate oil production rates and ultimate
•
-
NATURAL DEPLETION MECHANISMS FOR OIL RESERVOIRS
recoveries. In the early life of the reservoir, i.e., priorto water break-through, empirical correlations exist toidentify the susceptibility of the wells to coning. Thesemethods forecast recoveries by estimating break-throughtime and the water-oil curve forecast. Using the wateroil forecast, oil production can be estimated. Althoughreservoir simulation is recommended for evaluatingconing situations, the following correlations areavailable for quick evaluation:
I. Kuo (1989) combines various correlations thatdetermine critical rate calculations, break-throughtime calculations, and water-cut performance predictions on a PC spreadsheet for rapid analysis ofcomng.
2. Boumazel and Jeanson (1971) combine experimental correlations with a simplified analytical approachbased on the assumption that the front shapebehaves like a straight line. This method may beapplied to thick homogeneous reservoirs that arehorizontally fed.
3. Sobocinski and Cornelius (1965) developed acorrelation based on laboratory data for predictingwater coning time as it builds from static tobreak-through conditions. This method involvescorrelating dimensionless cone height against dimensionless time.
4. Kuo and DesBrisay (1983) developed correlationsbased on numerical simulation to determine thesensitivity ofwater coning behaviour to various reservoir parameters, including the ratio of vertical tohorizontal permeability, the ratio of perforated interval to oil thickness, the production rate, and themobility ratio.
5. Numerous correlations have been developedbased on the theoretical curves by Muskat forhomogeneous reservoirs. The best known correlations include Muskat and Wuckoff(l935), Chaneyet al. (1956), and Chierici et al. (1964). All thesemethods use the theoretical curves to obtain a critical production rate, the maximum production rateat which oil can be produced without coning. Inorder to estimate recoveries, a way of forecastingwater-oil ratio and oil production must be incorporated. Therefore, these correlations in themselveswill not forecast recoveries.
Decline Analysis
In some water drive reservoirs, the productionforecast might be represented by two straight-linesegments, pre- and post-water break-through. Due to
the difficulty of predicting the timing of water breakthrough using decline analysis, this method is generallyused after break-through has occurred.
Many approaches are available in analyzing productionafter water break-through. Table 9.2-2 outlines the morecommonly used combinations of production data plots.In the analysis ofany data set, it is recommended that anumber of these combinations be used, selecting thecombination that gives the best match.
Table 9.2-2 Decline Analysis Plots Usedafter Water Break-through
1. Logoil ratevs, time(exponential decline)2. Oil ratevs. cumulative oil (exponential decline)3. Logoil ratevs. cumulative oil (harmonic decline)4. Logcumulative oil vs. log cumulative oil plus
water5. Oil andwaterratesvs. cumulative oil6. Logoil andwaterrates vs. cumulative oil7. Log water-oil ratio vs, cumulative oil8. Logwater-Coil + water) ratio vs. cumulative oil
Material Balance
Material balance methods for estimating reserves inwater-drive reservoirs frequently result in erroneousestimates. A detailed understanding of the supportingaquifer is required for any degree ofreliability. Ofteninformation about the aquifer is extremely difficult toobtain. Knowledge that is critical includes the size ofthe aquifer, the strength or pressure support providedby the aquifer, and the areas of the oil reservoir thatreceive pressure support. In addition to an estimate oforiginal oil in place, the parameters defining the aquifermust be solved from the production and pressure history data. With the addition of these unknowns, thematerial balance method has a greater number ofvariabies to solve than it has equations. Because of this,material balance generally results in multiple estimatesof original oil in place.
Early in the production history of a reservoir, materialbalance methods may give erratic results for water influx due to inaccuratepressure measurements or becausewell pressure measurements may not be an accurate representation of actual average reservoir pressure. In theearly life of depletion, an erroneous negative waterinflux may be calculated.
139
F
DETERMINATION OF OIL AND GASRESERVES
and pro-rated back to the individual wells, sometimesresult in erroneous amounts and allocation of gasproduction. The accuracy ofgas production depends onthe frequency and method of measurement and thevariation between wells in the reservoir.
Reservoir Simulation
Because ofthe relatively higher mobility ofgas, carefulplanning is critical if a reservoir simulation model is tobe used. The grid blocks and time steps should be smallenough that the movement ofgas can be physically represented by the simulator. Ifconing is an issue, a radialmodel is recommended. Reservoir simulation isdiscussed in more detail in Chapter 17.
9.3 FACTORS AFFECTING OILRECOVERY
Although the drive mechanism is the primary factorinfluencing recoveries, numerous other factors, eitherinherent to the reservoir or resulting from human intervention, influence ultimate recovery. The followingsubsections address some of these other major factors.
9.3.1 Production RateThe production rate, qo' of a well is defined by theradial flow equation:
9.2.4 Combination DriveIn a combination drive reservoir, generally onedepletion drive mechanism is dominant at a particulartime or in a particular area of the reservoir. Therefore,in generating production forecasts, it is necessary toidentify the predominant sources of energy throughoutthe life of the reservoir and to identify the predominantsources of energy affecting a particular geographic areaof the reservoir. Because of the complexity ofpredicting the start and shape of the future production affectedby different dominant depletion mechanisms, declineanalysis techniques generally are not attempted until thelast stage. Techniques appropriate to the specific depletion mechanism dominant during the last stage ofdepletion should be used.
(3)21tkk"h (Pr- Pw)
q =o IJ)n(r,lrw)
where k = permeabilityk,o= relative permeability to oilh = net payPc = in situ pressure of accumulationPw = wellbore pressure110 = viscosity of oil
Material Balance
Since gas is an important fluid in the recovery of oil ingas cap drive reservoirs, a word of caution is advisedwhen using the material balance method. Oil field measurement practices, where gas is measured periodically
In reservoirs where coning is a key issue, a reservoirsimulation radial coning model is recommended.Reservoir simulation is discussed in more detail inChapter 17.
9.2.3 Gas Cap DriveOil recoveries in a gas cap drive reservoir can be ashigh as 60 percent depending on factors inherent to thereservoir. Three dominant factors influence recovery:
I. Since the gas cap provides the recovery energy, itmust be of sufficient size to displace oil to the producing wells. In general, the longer the gas cap canmaintain the pressure, the greater the recovery.
2. High vertical permeability allows the liberatedsolution gas and oil to segregate, adding additionalenergy to the gas cap.
3. Early gas break-through increases the gas-oil ratiosignificantly, thus removing the main source ofdriveenergy.
Reservoir Simulation
Analytical Methods
Because the drive mechanism in gas cap drivereservoirs is frequently combination drive, generally inconjunction with solution gas drive, the recommendedmethods for prediction of recoverable oil are declineanalysis, material balance and reservoir simulation, allof which take into account the complicated nature ofthe reservoir. Short-cut methods include the following:
The Welge Method (Welge, 1952), as previouslydescribed for water drive reservoirs, may be used forlow viscosity oil reservoirs.
The Dietz Method (Dietz, 1953), as previouslydescribed for water drive reservoirs, may be used inreservoirs where the gas cap overruns the oil along thereservoir flank. In this case, the rate ofadvance must bebelow the critical rate for the method to be valid.
These analytical methods assume the gas-oil contact willadvance as a flat interface. If the reservoir is subject tosevere coning, these methods will overestimate both theproduction rate and the recovery. The correlations describing water coning can also be modified to estimategas corung,
140
--------------------------...
NATURAL DEPLETION MECHANISMS FOR OILRESERVOIRS
r, = external boundary radiusrw = wellbore radius
For natural depletion mechanisms, the only parametersthat can be altered due to human intervention are nearwellbore permeability and producing pressure. Thenear-wellbore permeability can be enhanced throughstimulation techniques such as acidizing and fracturing.The producing wellbore pressure can be reduced by theinstallation and optimization of artificial lift equipment. For a given oil deposit, adjusting the productioncapability of the wells will not alter the theoreticalquantity ofmoveable oil, but will affect the recoverable
. resource through economic limit, as demonstrated inFigure 9.3-1. Ifthe only difference between the two casesshown is the production capacity of the well, the cumulative production at the economic limit will be largerfor the high rate case.
Economic
Limit
Reserves
TheoreticalRecovery
Cumulative Recovery
In general, lower API oil receives a lower price at therefinery. Since the price directly impacts the economiclimit, the limit would be reached sooner for lower pricedcrude.
9.3.3 Reservoir CharacteristicsReservoircharacteristicscan affect recovery factors fromtheoretical calculations primarily because of heterogeneities in the reservoir. Generally, heterogeneities causea reduction in reserves either by (I) decreasing theamount of oil in place that can be effectively tapped bythe wells, or (2) causing uneven depletion of portionsofthe reservoir, in turn resulting in a greater amount ofoil being left in the ground because it is uneconomic toproduce. Some ofthese reservoir characteristics includepermeability variations, dual porosity systems, naturallyfractured reservoirs with cemented fractures, and lowpermeability stringers.
Although a heterogeneous reservoir generally has alower recovery than a homogeneous reservoir, someheterogeneities can assist the drive mechanism, and thusincrease reserves. For example, in bottom-water-drivereservoirs where coning is of concern, shale stringerscan restrict the advance of water, allowing higher oilproduction for a longer period of time. Also, openuncemented, or partially cemented natural fracturescan help improve recoveries from low permeabilityreservoirs that otherwise would be uneconomic toproduce.
In general, the more heterogeneous the reservoir, thelarger the difference in the actual reserves as comparedto the theoretical calculations.
Figure 9.3-1 Relationship Between ProductionRate and Reserves
9.3.2 Oil QualityThe type ofoil in the reservoir directly affects reservesthrough the volume of gas in solution and through oilviscosity. Oils that have less gas dissolved in solutionhave less reservoir energy for oil recovery under solution gas drive; these are generally lower gravity oils.
Oil viscosity influences recovery in two ways. First, ifthere are two fluids in a reservoir with significantly different viscosities, oil production would decline quiterapidly because ofconing or fingering ofthe other fluid.Second, productivity of a well is inversely proportionalto viscosity (Equation 3). All things being equal, a moreviscous oil would have a lower production rate andwould reach its economic limit sooner.
9.3.4 Reservoir GeometryMany factors associated with the reservoir geometryinfluence the amount of oil produced under primarydepletion. Some of these are the shape of the reservoir,the continuity ofthe formation, the layering ofmultiplesands, faulting, structure, and dip. These factors canaffect both the drive mechanism and the economicviability of developing the accumulation.
Depending on the predominant drive mechanism, thegeometric configuration will have varying degrees ofeffect. For example, in a solution gas drive reservoir,vertical relief could allow the formation ofa secondarygas cap, which would maintain the evolved gas as anenergy source.
In general, the less continuous reservoirs would resultin a lower recovery because some parts of the reservoirmight not be in communication with the producing
141
wells. In this case, infill drilling to reach untapped oilwould result in an increase in reserves. Also, due to discontinuities in the reservoir, gas-oil and water-oilcontacts might not advance as a flat interface, and thusoil would be by-passed.
A layered reservoir poses a different type of problem,especially if the multiple zones have significantly different reservoir characteristics. If one zone were moreprolific due to considerably higher permeability, it wouldhave a higher recovery factor than the less prolificzone. In this case, it is often beneficial to estimate therecovery factor separately for the multiple zones.Because ofthe different behaviours of the various zones,a layered reservoir manifests itself as a hyperbolic orharmonic decline if decline analysis is being used.
9.3.5 Effects of Economic LimitWhether a recovery factor is rigorously establishedthrough detailed techniques like numerical modellingor estimated through engineering judgement, innate assumptions are made about the economic limit of thereservoir. In some cases the economic limit is established in the current economic environment using knowntechnology. The key factors affecting the economic limitare the prices for the hydrocarbons, the operating cost,the current fiscal regime, and encumbrances such asoverriding royalties and net profit interests. Thesefactors are discussed in Part Four. The following subsections discuss some of the other factors that influencethe economic limit.
Well Spacing
A single well in a large deposit of oil will theoreticallyproduce all of the moveable oil, but this would take avery large number of years and would not provide theoptimum economic recovery. As the well is produced,a pressure gradient is established in the reservoir. Withcontinued production, the pressure gradient moves further out into the reservoir, effectively reducing theaverage reservoir pressure. As the average pressuredrops, the production rate of the well will drop proportionately. When the radius of the area affected by thepressure gradient becomes sufficiently large, a pseudoequilibrium is established in which the flow at thefurthest boundary reached by the pressure gradientis equivalent to the production rate of the well. Thepressure gradient will continue to move further out intothe deposit, minimally affecting the production rate,until the physical limits of the deposit are encountered.
142
•,DETERMINAnON OFOILANDGASRESERVES
If other wells are drilled into the same reservoir, but arefar enough apart that their respective pressure gradientswill not interact until after the economic limit has beenreached, each will behave as if it were the only well inthe reservoir. If the densities of the wells are suchthat their respective pressure gradients interact atthe economic production limit, the reservoir pressurewould be at the original level at the point of interaction,resulting in an overall high average reservoir pressureat abandonment. Inserting a well midway between thetwo original wells will result in a lower average reservoir pressure at abandonment, and thus a highereconomic oil recovery. However, the oil recovered perwell will be less. With continued reduction in spacing,the average reservoir pressure at abandonment will continue to drop, but in diminishing increments. The resultwill be a typical relationship between the oil recoveredabove the economic limit and the number of wells inthe pool. The intersection of the oil recovery forecastand the economic limit establishes the reserves for thisreservoir. The relationship between well spacing andabandonment pressure is depicted in Figure 9.3-2.
The point at which increasing the number ofwells willno longer markedly increase the oil recovered whenproducing above the economic limit is generally referredto as the optimum spacing (Figure 9.3-3). This assumesthat the revenue benefit from the additional recoverableoil in reducing spacing while moving from point a topoint b offsets the cost ofdrilling, completing,and equipping the necessary additional wells, and provides therequired return on investment. Increasing the density ofwells beyond point b may be economic through the effects of rate acceleration. However, the volume of oilrecovered above the economic limit will remain the sameunless by having more wells and thus larger volumes,the economy-of-scale factors will reduce the averageeconomic limit per well. The optimum well spacing willbe unique for each deposit and should be established bya combined technical and economic assessment.
Facility Sizing and Constraints
Facilities must be installed in order to separate theproduced oil, gas, and water. The size ofthe facility andthe resulting capital and operating costs (the economicsof the project) have an impact on the ultimate reserves.Very simply, if the capital cost of the required production facility is greater than the potential revenue,the reservoir will not be developed and produced, andtherefore cannot be considered to contain reserves, even
- .-sra
NATURAL DEPLETION MECHANISMS FOR OILRESERVOIRS
Original Pressure
Single Well Single Infill Multiple Infills
Average Abandonment Pressure
Constrainedod\.\C\\O{\
F==:::::=::-'l'lQ!ol!!!!alC!F",lu!"id,;..Po-'-
is
~E"o
,,,,,,,,,,,
CumulativeOil
'\
!,
,,,,,,,,,
Present ~ p ~ .....
Value ~ ~
~/
,,,,
.,.~,/I~b" a,,,
r,,,
Figure 9.3-2 Relationship Between Well Spacingand Abandonment Pressure
the decline of the oil rate will be sharper, as depictedin Figure 9.3-4. The decision whether to increasethe capacity of the facility is based on an economicevaluation of the benefit of the additional oil and thecost of expansion.
OilProduction .:»:
Number ofWells
Figure 9.3-3 Optimum Well Spacing
if it has been adequately delineated through drilling. Afacility sized large enough to handle the maximum initial production will continue to have high operating costswhen oil volumes decline in the future, and will reachits economic limit earlier than a smaller, less expensivefacility that limits initial production, but has loweroperating costs.
Sometimes facilities need to be installed in oil fields tohandle increasing production volumes ofassociated gasand water. Installing large facilities that will not beutilized for many years may not be economic, and theuse of constraining facilities may be necessary. Whena naturally declining oil rate reaches a facility constraint,
Cumulative Oil
Figure9.3-4 Effects of Facility Constraintson Economic Limit
Regulatory Constraints
In addition to the standard economic considerations ofdeveloping a reservoir (rate of return, payout, operatingcosts, and facility costs), there are also the regulatoryconstraints imposed by the local government agencies.The purpose of these regulations is to ensure theconservation and responsible exploitation of adepleting resource, to ensure that the equitable rights of
143
competing producers are met, and to protect the environment. Regulations with respect to well spacing,location of wells on a spacing unit, production rate,water-oil ratios, gas-oil ratios, and hydrogen sulphideemissions have been established to meet the objectivesofthese agencies. These regulations will, in some cases,impose constraints on development scenarios and thusaffect the estimates of recoverable hydrocarbons. Thistopic is discussed in more detail in Chapter 23, TheRegulatory Environment.
ReferencesBournazel, C., and Jeanson, B. 1971. "Fast Water
Coning Evaluation Method." SPE 3628.
Caudle, RH., and Silberberg, I.H. 1965. "LaboratoryModels of Oil Reservoirs Produced By NaturalWater Drive." SPEJ, Mar. 1965, pp. 25-36.
Chaney, P.E., Noble, M.D., Henson, W.L., and Rice,T.D. 1956. "How to Perforate Your Well toPrevent Water and Gas Coning." O&GJ, Vol. 55,May 1956, pp. 108-114.
Chierici, G.L., Ciucci, G.M., and Pizzi, G. 1964. "ASystematic Study of Gas and Water Coning byPotentiometric Models." JPT, Aug. 1964, pp.923-929.
Dietz, D.N. 1953. "A Theoretical Approach to theProblem of Encroaching and By-Passing EdgeWater." Proc., Konikl. Ned.-Akad, Wetenschap,Series B, Vol. 56, p. 83.
Henley, D., Owens, W.W., and Craig, F.F. 1961. "AScaled Model of Bottom Water Drives." JPT, Jan.1961, pp. 90-98.
Hurst, W. 1943. "Water Influx Into a Reservoir andIts Application to the Equation of VolumetricBalance." Trans., AIME, Vol. 151, p. 305.
Hutchinson, T.S., and Kemp, C.E. 1956. "AnExtended Analysis of Bottom Water DriveReservoir Performance." Trans., AIME, Vol. 207,pp.256-261.
144
DETERMINATION OF OIL AND GASRESERVES
Khan, A.R., and Caudle, B.H. 1968. "Scaled ModelStudies of Thin Oil Columns Produced by NaturalWater Drive." SPE 2304.
Kuo, M.C.T. 1989. "Correlations Rapidly AnalyzeWater Coning." O&GJ, Oct. 1989, pp. 77-80.
Kuo, M.C.T., and DesBrisay, C.L. 1983. "ASimplified Method for Water ConingPredictions." SPE 12067.
Marshal, D. 1957. "Mathematical Treatment of WaterInvasion of Oil-Bearing Formations." Erd. Kohle,Vol. 10, Dec. 1957, p. 825.
Muskat, M. 1949. PhysicalPrinciples ofOilProduction. McGraw-Hili, New York, NY.
Muskat, M., and Wuckoff, R.D. 1935. "AnApproximate Theory of Water Coning in OilProduction." Trans., AIME, Vol. 114, pp. 144161.
Pirson, SJ. 1950. Elements ofOilReservoirEngineering. McGraw-Hill, New York, NY.
Roberts, T.G., and Ellis, H.E. Jr. 1962. "Correlationof Gas-Oil Ratio History in a Solution-Gas-DriveReservoir," JPT, Vol. 14, Jun. 1962, p. 595.
Schilthuis, RJ. 1936. "Active Oil and ReservoirEnergy." Trans., AIME, Vol. 118, p. 33.
Sobocinski, D.P., and Cornelius, AJ. 1965. "ACorrelation for Predicting Water Coning Time."JPT, May 1965, p. 594.
Tracy, G.W. 1955."Simplified Form of the MaterialBalance Equation," Trans., AIME, Vol. 204, p.243.
Wahl, W.L., Mollins, L.D., and Elfrink, E.R 1958."Estimation of Ultimate Recovery from SolutionGas Drive Reservoirs." JPT, Jun. 1958, p. 132.
Welge, HJ. 1952. "A Simplified Method forComputing Oil Recovery by Gas or Water Drive."Trans., AIME, Vol. 95, p. 91.
_____________n
Chapter 10
DEPLETION MECHANISMSFOR NATURAL GAS RESERVOIRS
10.1 INTRODUCTIOJIIDuring the depletion of natural gas reservoirs, manyfactors affect the production performance. The basiccharacteristics and physical properties ofthe gas and itsassociated constituents or products, and its proximityand interrelationship to other fluids in the reservoir caneither enhance or adversely affect the recovery froma pool. The most significant aspect, however, is thecompressibility and, conversely, in the reservoir, theexpandable nature ofpressurized gas. On average, a significantly higher percentage of the gas in a reservoir isrecovered through natural depletion mechanisms thanof the oil, which has lower compressibility.
This chapter highlights some of the characteristics ofthe gas and the reservoir that influence recoveries andbasic approaches in forecasting recoverable gas reserves.
10.2 CHARACTERISTICS OF NATURALGAS
The gases that constitute natural gas belong mainly tothe "paraffin series." The main constituent is methane.Impurities such as nitrogen, carbon dioxide, helium, andhydrogen sulphide may be present in natural gas.
The Alberta Energy Resources Conservation Boardclassifies natural gas with less than one percent hydrogen sulphide as "sweet." When the hydrogen sulphidecontent is over one percent, the gas is classified as "sour."
Natural gas found by itselfin a reservoir and completelyin the gaseous state is classified as "nonassociated,"(Figure 10.2-1). Gas found in an oil reservoir with nofree gas present except that which is in solution is classified as "solution gas." Gas and oil may be found in areservoir in many different combinations when the fieldis discovered, and the relationship of the gas and oilmayor may not change, depending on the reservoir andfluid characteristics and on drilling, completion and production practices. For example, gas may be foundas free gas above the oil. This is called a "gas cap," andthe gas is classified as "associated" gas. Under some
Associated Gas
NonassociatedGas
Source: Clark, 1960,
Figure 10.2-1 Classification of Gas Based onSource in Reservoir
reservoir conditions and producing practices, thedissolved gas may come out of solution in the reservoirand form a "secondary" gas cap or add to a natural gascap.
At low pressures in shallow fields, natural gas and crudeoil appear as distinct substances in the reservoir (Figure10.2-2, Reservoirs A and B). As the pressure at whichpetroleum is found rises with increased depth, gas dissolves in crude oil, and the high-boiling constituentsdissolve in the gas phase. Some fields have both oil andgas in contact (Figure 10.2-2, Reservoir C). Deeper fieldsat pressures over about 27 600 kPa (4000 psi) and attemperatures ofmore than 95°C (200°F) contain singlephase fluids that are not immediately distinctive as oilor gas fields (Figure 10.2-2, Reservoir D).
"Dry" gas reservoirs normally yield little or no surfaceliquid recovery with processing through normal leaseseparation equipment.
A gas is "wet" if hydrocarbon liquids are extractable insurface separation equipment, and may be producedfrom a single-phase gas reservoir, a retrograde condensate gas reservoir, or an "associated gas" reservoir.
145
----------------~
-/
DETERMINATION OFOILANDGAS RESERVES
Source: Katzet al., 1959.
Figure 10.2-2 Occurrence of Oil and Gas
10.3 DEFINITION OF RESERVOIRTYPES FROM PHASE DIAGRAMS
Various types of reservoirs can be defined usingpressure-temperature phase diagrams (Figure 10.3-1).The area enclosed by the bubble-point and dew-pointlines is the region ofpressure-temperature combinationsfor which both gas and liquid phases exist. The curveswithin the two-phase region show the percentage ofthetotal hydrocarbon volume that is liquid for anytemperature and pressure. Initially, each hydrocarbonaccumulation would have its own phase diagram, whichwould depend only upon the composition of theaccumulation.
A single-phase gas reservoir at discovery is shown bypoint A. Since the fluid in the reservoir during production remains at 150°C(300°F), it retains its gaseous stateas the pressure declines along path A-AI' Furthermore,the composition of the produced gas does not changeas the reservoir is depleted. However, cooling andpressure drop in the wellbore and surface facilitiesallow the condensing of gas along the line A-A2• Thisaccounts for the production of condensate liquid at thesurface from a gas in the reservoir.
Retrograde gas condensate reservoirs or dew-pointreservoirs exist at pressures sufficient to be at or abovethe upper boundary of the two-phase envelope and at a
temperature between the critical and cricondenthermvalues, as shown by point B. Here the fluid is also in theone-phase gaseous state. As pressure declines becauseof production, the composition of the produced fluidwill be the same as for reservoir A, and remain constantuntil the dew-point pressure is reached (Point B1) •
Below this pressure, liquid condenses out of the gas asfog or dew, leaving the gas phase with a lower liquidcontent. The condensed liquid adheres to the walls ofthe pore spaces of the rock, and is immobile. Thus thegas produced at the surface has a lower liquid contentand the producing gas-condensate ratio increases. Thisprocess of retrograde condensation continues until apoint ofmaximum liquid volume is reached (Point B2) .
Vapourization of the retrograde liquid occurs from B2to the abandonment pressure at point B) and can be notedby decreasing gas-condensate ratios on the surface.
When a retrograde gas condensate reservoir hasconditions on or very close to the dew-point line atthe time of discovery, it means that the percentage ofintermediates (C2 - C6) is high.
It is also quite common to find a volatile oil rim. In thiscase, the gas cap would be exactly at the dew point.
If the accumulation occurred as shown by point C, thereservoir would be in a single-phase (oil) liquid state,since the temperature is below the critical temperature.In this case, as the pressure declined, the bubble pointwould be reached (Point CI). Below this point, afree-gas phase would appear. This gas is classified as"solution gas."
Ifthe same hydrocarbon mixture occurred at point D, itwould be a two-phase reservoir, consisting of a liquidor oil zone overlain by a gas zone or "gas cap." As thecompositions of the gas and oil zones are entirely different from each other, they may be representedseparately by individual phase diagrams. The oil zonewill produce as a bubble-point oil reservoir and the gascap will be at the dew point, and may be either retrograde as shown in Figure 10.3-2 (a) ornonretrograde asshown in Figure 10.3-2 (b).
The initial in-place gas and condensate for gascondensate reservoirs, both retrograde and nonretrograde, may be calculated from the availableproduction data by recombining the produced gas andcondensate in the correct ratio to find the composition,average specific gravity (air = 1.000), pseudo-criticalpressure, and pseudo-critical temperature of the totalwell fluid, which is presumably being produced initiallyfrom a single-phase reservoir.
Water
Ground Level
.\ containing Dissolved G........... 0\ Os __......
WaterB
A
146
----------------------_..
DEPLETION MECHANISMS FOR NATURAL GASRESERVOIRS
-18 10
Reservoir Temperature (oG)
38 66 94 122 150 178
4000
3500
til'w 3000oS~::>l:l 2500~a.~
.~ 2000Q)<J)
8!1500
1000
Bubble Pointor
Dissolved GasReservoirs
DewPointor
RetrogradeGas-Condensate
Reservoirs
Single PheseGasReservoirs
'A,IIII
"II·2/1'iiI Ioff/lel I
0..1 I'Cs' I
I I~I "0 I
IJ.J 'S II u::: I
I .: I
" ~ II Q) I<Ill&!I-I°1£1"'I0-
1
I
A,IIII
27600
24150
20700 ~~
~::>
17250 l:l~a.~
13 800 .~Q)<J)Q)
a::10350
6900
Source: AfterCraft,1959.
100 150 200 250
Reservoir Temperature (OF)300
3450350
Figure 10.3-1 Pressure-Temperature Phase Diagram of a Reservoir Fluid
Figure 10.3-2 Phase Diagram of a Cap Gas andOil Zone Fluid
10.4 GAS RECOVERYIdeally, 100 percent gas recovery is the goal. Forreservoirs producing by gas expansion and withoutwater drive, there is no physical reason why the gas may
BP
TTemperature
(a)Source: Craft, 1959.
011-
TTemperature
(b)
not be recovered down to near atmospheric pressure.However, the production rates decrease so rapidly whenthe pressure approachesatmospheric that some abandonment pressure is established for economic production.Most volumetric depletion reservoirs with reasonablepermeabilities will produce 70 to 90 percent of theoriginal gas in place. Sometimes the higher limit ofrecovery can be approached when operating costs are lowand gas prices high. In other reservoirs, substantial losseswill occur. But it is sometimes possible to minimize thisloss through proper reservoir management and theapplication ofbasic principles ofreservoir engineering.
The following are some of the reasons for low gasrecovery:
Drive Mechanism. In terms of drive mechanism, afrontal displacement-probably a gas-water contactalways results in a substantial residual gas saturation.This is often more than 40 percent in sandstones. In thecase of near-total pressure maintenance by water
147
~!DETERMINATION OF OIL AND GASRESERVES
10.5 GAS RESERVES"Gas reserves" refers to the fraction or portion of theoriginal gas in place that is economically recoverable.Consequently, the recovery factor, RF, is defined asthe ratio of gas reserves to initial gas in place and isusually expressed as a percentage:
where Gp, = cumulative gas produced at abandonment conditions
G, = initial gas in place
Gas reserves are assigned to one of three groups:
I. Nonassociated gas reserves
2. Solution gas reserves
3. Associated gas cap gas reserves
The determination of reserves of gas in these threegroups is discussed in the following subsections.
10.5.1 Nonassociated Gas ReservesDetermination
Nonassociated gas reserves are those reserves thatare not associated with recoverable oil reserves. Theirproduction is limited only by market availability andcontract terms.
encroachment, more than 40 percent of the gas may betrapped behind the advancing gas-water contact.
Reservoir compaction drive in soft sediments has asimilarly negative impact on gas recovery.
Over-Pressured Reservoirs. Over-pressured reservoirs,usually at considerable depth, can also have significantreductions in permeability to gas flow at abnormallyhigh bottom-hole pressures during the gas exploitationprocess (Duggan, 1972).
Phase Behaviour. If the reservoir temperature is lessthan the cricondentherm (maximum two-phase temperature), the potential exists for retrograde condensationof some of the heavier hydrocarbons as pressuredeclines and, therefore, a loss of valuable liquids.
Other Reasons. In addition, gas might be trapped dueto the reservoir configuration, position and number ofproducing wells, production rates, water coning, migration offines, damage at the producing wellbore sandface,stratification, and loss of permeability due to facieschanges. Low permeabilities often result in highabandonment pressures when reduced well spacingcannot be economically justified.
(2)
(3)
T~ [Pi Po]G=Ah.p(l-S.) - ---r, r, Zi z;
T" [(I-S.)P, Sg,Po]G=Ah.p- --r., r, z, z,
Ah.pS =wTsc =
If water invasion of the reservoir amounts to less than100 percent at abandonment, a higher effective residualgas saturation for the reservoir will result.
where G = original recoverable raw gas reserves(m") .
= drainage area (nr')net pay thickness (m)porosity (fraction)connate water saturation (fraction)base or standard temperature CK)(2730+0c)
Pso = base or standard pressure (kPaa)Tf = formation temperature CK)
(2730+0c)Pi = initial reservoir pressure (kPaa)Zi = compressibility factor at Pi and Tf
P, = abandonment pressure (estimated)(kPaa)
Z, = compressibility factor at P, and Tf
The base pressure used varies from 99.284 kPaa to103.594 kPaa, but is usually 101.325 kPaa. The basetemperature is normally 15°C (288°K).
Abandonment pressure, P" can be estimated by thefollowing rule of thumb:
P, = 240 kPaa + 80 kPaaflOO m of depth
The initial gas in place in the reservoir, minus theremaining gas at the selected abandonment pressuregives the recoverable raw gas as shown in Equation (2).
In water-drive reservoirs, a residual gas saturation, Sgr'remains in the water-invaded zone. The recoverable gas,G, from the water-invaded portion of the reservoir iscalculated by Equation (3).
Gas reserves in gas fields may be estimated by thevolumetric and material balance methods.
Volumetric Method
The volumetric method is used for new gas fieldsbefore any significant production takes place.
In reservoirs where no water influx is expected,recoverable raw gas, G, is calculated by the following:
(I)Gpo
RF= - x 100Gi
148
-----------_..
DEPLETION MECHANISMS FOR NATURAL GASRESERVOIRS
where G, = volume of produced gas at standardpressure, P'o> and standard temperature,Tsc
If there is no aquifer present in the reservoir, there is nowater influx and water production will be negligible.Then Equation (6) may be written as follows:
(7)
(8)
(9)
Z,T Z,T
P;V, PrV,-----
P,G =b-m-
p Zr
G = P;V,T" _ V,T". P,
p Z,P"T P"T Z,
where
and
or
For fixed values of Psc and Tsc, since Pi' Z, and Vi arealso fixed for a given volumetric reservoir, Equation(8) may be written as follows:
Equation (9) is the equation of a straight line, andindicates that for a volumetric gas reservoir the graphof the cumulative gas production, Gp, vs. the ratioP/Z is a straight line ofnegative slope "m."
Figure 10.5-1 shows a plot of P/Z vs. cumulativegas production. The plot can be extrapolated to zeropressure to determine the initial gas in place or to anyabandonment P/Z to find the recoverable gas.
For the computation of initial in-place gas for constantvolume reservoirs, the following data is required:
• Initial reservoir pressure
• Cumulative gas volume
• Stabilized shut-in reservoir pressure at the end ofproduction '
• Gas deviation factors at these two reservoir pressuresassuming the reservoir temperature remains constant
This method is not applicable to water-drive gasreservoirs. With pressure reduction, when water entersthe space occupied by gas, the pressures are maintainedeither almost completely or only in part depending onthe nature of the water drive (Figure 10.5-2).
In reservoirs where an aquifer provides a high degreeof pressure support, the existence of a water drive isgenerally quite obvious. In reservoirs with only a partial pressure support, an active water drive may not be
(6)P;V, _ P,(V,-W,+BwWp)
Z,T Z,T
Material Balance Method
This method is applicable only to the reservoir as awhole, because of the migration of gas from one portion of the reservoir to another in both volumetric andwater-drive reservoirs. For single-well reservoirs thismethod may be used directly, but in multiple-well poolsthe production information must be combined.
The Law of Conservation of Mass may be applied togas reservoirs to give the material balance as follows:
mass of gas produced = initial mass of gas -remaining mass of gas
For the gas system under consideration, if the gascomposition is constant, the number of moles of gas,both produced and remaining in the reservoir, is directlyproportional to their masses. A material balance in termsof moles of gas may be written as follows:
!1>=n;-nf (4)
where subscripts p, i and f stand for produced, initialand final remaining at some later stage of productionrather than at abandonment.
If there is a water drive, the final volume, Vf afterproducing a volume of gas, Gp, is:
Vf = Vi - We + BwWp (5)
where Vf = final gas pore volume (does notinclude connate water)
Vi = initial gas pore volume (does notinclude connate water)
We= volume of water that has encroachedinto the reservoir at the final pressurePf
Bw= the formation volume factor for waterin reservoir volume per surface volume
Wp= volume of water that has beenproduced from the reservoir
If the real gas law PV = ZnRT is applied in Equations(4) and (5):
149
"4
DETERMINATION OFOILAND GASRESERVES
Cumulative Gas Production
Complete Water Drive
10.5.2 Solution Gas ReservesDetermination
Solution gas reserves are dissolved in the oil in areservoir and can only be recovered if oil is produced.If solution gas cannot be conserved or sold, regulationsmay necessitate that the oil production be shut in. Therate of solution gas production depends on the rate ofoil production and the producing gas-oil ratios (GORs).
During the initial stages of oil production, GORs willgenerally remain at or above solution GOR until thecritical gas saturation is reached. At this point the producing GOR will increase as described in Section 9.1.2.
If decline analysis is used to predict oil production,an extrapolation of the GOR trend can be conductedconcurrently. More rigorous prediction methods can alsobe utilized as described in Section 9.2.1.
As a rule of thumb, the ultimate solution gas recoveryfactor in solution gas drive reservoirs generally rangesfrom 50 to 65 percent.
In oil reservoirs with an active water drive or waterfloods, the final recovery factor for the solution gaswill be influenced by the degree ofpressure maintenanceand sweep efficiencies, as well as residual oil and gassaturations.
I
Nii:
apparent. A plot of P/Z vs. cumulative gas productionin these reservoirs will indicate an overstatedextrapolation of recoverable gas.
Figure 10.5-1 Plot of P/Z vs. Cumulative GasProduction
Cumulative Gas Production
Figure 10.5-2 Effect of Water Drive onPressure Decline
Models are available that use Equation (5), the basicmaterial balance equation, for water drive reservoirs.An example is shown by Guerrero (1968). However,there are multiple unknowns in the material balanceequation for water influx reservoirs, and calculationsgenerally involve several assumptions on the reservoirdescription. Consequently, material balance predictionsare often unreliable when a detailed understanding ofthe reservoir and supporting aquifer does not exist.
10.6 PIPELINE GAS RESERVESThe methods discussed in this chapter give reserves ofraw gas. Before the gas is delivered to the point of sale,there are losses at the surface due to processing shrinkage and fuel consumption. These losses mustbe deducted from the raw gas reserves to calculatemarketable pipeline gas.
10.5.3 Associated Gas ReservesDetermination
The term "associated gas reserves" refers to a gas capabove oil reserves. Most, if not all, of the gas cap driveenergy is required to maximize oil recovery. For thisreason, associated gas reserves must ideally remain shutin until all the oil reserves have been produced. Thesegas reserves will be recovered during blow-down ofthegas cap.
Associated gas reserves are generally estimated usingthe volumetric method and an estimated abandonmentpressure. As a gas cap adds inherent complexities toan oil reservoir, its presence may justify a more rigorous analysis or reservoir simulation to determine theappropriate depletion approach.
t
150.~;-------------- 41
DEPLETION MECHANISMS FOR NATURALGAS RESERVOIRS
In sweet, dry gas fields, the surface loss is usually about2 to 5 percent. For wet or sour gases, the surface losscan be estimated from the gas analysis, the recoveriesof related products that are expected, and an allowancefor plant fuel.
10.7 RESERVES OF RELATEDPRODUCTS
Natural gas liquids and sulphur are recovered from thenatural gas, and the reserves are estimated from the gasanalysis and the gas reserves.
10.7.1 Natural.Gas LiquidsFor the development of reserve estimates, natural gasliquids are defined as those hydrocarbon liquids that, inthe reservoir, are either gaseous or in solution with crudeoil and that are recoverable as liquids by condensationor absorption in field separators, scrubbers, gasolineplants, or cycling plants. Natural gasoline, condensate,and liquefied petroleum gases are in this category.
Natural gas liquids are in a sense an intermediateproduct-lighter than what is usually considered crudeoil and heavier than what is usually considered naturalgas.
Natural gas liquid recoveries can be estimated as shownin Table 10.7·1.
10.7.2 SulphurSulphur is recovered as a by-product if hydrogensulphide is present as an impurity in the naturalgas. Sulphur recovery can be estimated as shown inTable 10.7·1.
Table 10.7·1 Recoveries of Related Products
10.8 GAS DELIVERABILITYFORECASTING
Rawlins and Schellhardt (1935) demonstrated that a gaswell can be tested to predict its deliverability against aspecific bottom-hole flowing pressure.
An empirical relationship has been developed to relatethe well gas flow rate at surface conditions with bottomhole flowing pressure and average reservoir shut-inpressure:
Q" = C (PR2·pl)" (10)
where Q,,= flow rate at standard conditions ofpressure and temperature
C = a coefficient that describes the positionof the stabilized deliverability line
PR = average reservoir shut-in pressurePp = reservoir flowing pressuren = an exponent equal to the reciprocal of the
slope of the stabilized deliverability line
Limits of n vary from 0.5 for fully turbulent to 1.0 forcompletely laminar flow in the formation, reflecting thedegree ofturbulence.
The P/Zvs. cumulative gas production relates the staticreservoir pressure to cumulative gas. The results ofisochronal (back pressure) testing relates static reservoir pressure, well flow rate, and sandface flowingpressure (Figure 10.8·1).
Well performance estimates are made during thedevelopment stage of the gas reservoir and also duringthe depletion of the gas field. Basically, this involvesestablishing well production rates vs. reservoir pressure(gas well deliverability) that exist during the life of thegas reservoir (Figure 10.8·2).
?
Related Recovery For ForProduct SI Units Imperial Units Fraction Shallowcut Deepcut
Range use use
Propane m'/IO'm' = vol. % x 36.9 bbl/lO'cf = vol. % x 6.54 oto 0.90 0.50 0.90(raw gas) x recovery(fraction) (raw gas) x recovery(fraction)
Butane m3/10'm3 = vol. % x 43.0 bbl/.JO'cf = vol. % x 7.62 oto 0.95 0.75 0.95
(raw gas) x recovery(fraction) (raw gas) x recovery(fraction)
Pentanes Plus m3/lO'm3 = vol. % x 57.3 bbl/lO'cf = vol. % x 10.15 up to 1.00 0.95 1.00(raw gas) x recovery(fraction) (raw gas) x recovery(fraction)
Sulphur m3/IO'm3 = vol. % x 13.6 bbl/lO'cf = vol. % x 0.377 0.95 to 1.00(raw gas) x recovery(fraction) (raw gas) x recovery (fraction)
Source: After Gas Processors Suppliers Association, 1981,
151
--DETERMINATION OFOILANDGASRESERVES
P~-----
StabilizedDeliverabilily
Curve
10
Shut-In Reservoir Pressure
i!!"UlUl
i!!n,0>e.~
u::~
.~
"Ul
"a:
AOFGas Flow Rate
o0+------------+-102 10' 10'
Gas Flow Rate
10.1 +----r:-----.:---,-L----110
Figure 10.8-1 Back Pressure Plot
Similarly a wellhead gas deliverability plot in wellheadflowing pressure vs. gas flow rate can be generated fromthe wellhead back pressure plot.
Further discussion on back pressure testing is beyondthe scope of the monograph. For further details, thereader is referred to Theory and Practice ofTesting ofGas Wells (Energy Resources Conservation Board,1975), Back Pressure Test for Natural Gas Wells(Railroad Commission of Texas, 1972) and "Methodsfor Predicting Gas Well Performance" (Russell et aI.,1966).
10.9 WELL SPACINGOptimum well spacing for the exploitation of gasreservoirs may be substantially different than for oil reservoirs. Where spacing regulations govern, spacingwould normally be wider for a gas reservoir than for anoil reservoir. These regulations recognize the increasedmobility ofgas as compared to oil, and the corresponding greater migration capability ofgas during producingoperations; thus the spacing assigned to a gas well isconsiderably greater-typically, 259 hectares (640acres) per well. However, a denser well spacing mayexist in areas with shallow,low-permeability reservoirs.
10.10 CYCLING OF GAS CONDENSATERESERVOIRS WITH DRY GAS
Incentive exists in cycling ofgas condensate reservoirswith "dry" gas in those cases where natural depletionof the reservoir will result in substantial loss ofliquid hydrocarbons in the reservoir. This occurs in
Figure 10.8-2 Gas Deliverability Plot
volumetric reservoirs where retrograde condensationbehaviours exist (liquids forming as the pressuredeclines), and in water-drive gas fields where "wet" gasis trapped. It has been noted that liquid hydrocarbonsformed during pressure depletion of a reservoir are notnormally revapourized at lower reservoir pressures and,therefore, are trapped as a residual liquid saturation.
Under these circumstances, the gas in the reservoir maybe "cycled" to reduce the loss of liquids. In this operation, gas is produced from the reservoir, the liquidhydrocarbons are extracted, and the dry gas is reinjected. This reduces the rate of pressure reduction inthe reservoir, which is responsible for the retrogradecondensation. The dry gas re-injected may be only partof the gas produced, or it may be all of the gas produced, or it may even be gas in excess of thatproduced, so that the reservoir voidage is fully replaced.
There is evidence (Smith and Yarborough, 1968) thatat least part of any liquid saturation that formed priorto the implementation of dry gas cycling operations,will be revapourized into the dry gas. To achievemaximum benefit from dry gas cycling, cycling shouldbe initiated before the dew point of the reservoirhydrocarbon fluid is reached.
In reservoirs where rock characteristics are favourable,cycling with dry gas should provide recovery ofpart ofthe liquids which otherwise would be lost.
Not all cycling projects are successful. Sprinkle et al.(1971) have reported the adverse influence of stratifi-
152
s
D
DEPLETION MECHANISMS FOR NATURALGAS RESERVOIRS
cation on gas cycling operations. The presence of a highpermeability layer in the reservoir was believed to bethe cause for poor liquid hydrocarbon recoveries andresulted in the ultimate abandonment ofthe gas cyclingproject in a Texas Gulf Coast Frio Sand reservoir.
Income from dry gas cycling projects will initially beall or mainly from liquid hydrocarbon sales and, later,during "blow-down," from the sale of both gas andliquids, but the rate ofliquid recovery will be declining.
10.11 SECONDARY RECOVERY OF GASSecondary recovery of gas is uncommon becauseprimary recovery usually yields a high percentage ofthe gas originally in place (70 to 90 percent). New operating practices, however, have sometimes madecommercial deposits out of some that were consideredto be uneconomic.
Boyd et al. (1982) described secondary gas recoveryfrom the watered-out Frio gas reservoir in the DoubleBayou Field, Chambers County, Texas.
10.12 ENHANCED GAS RECOVERYEnhanced gas recovery has been traditionally usedto describe methods of unconventional gas recoveryfrom tight gas sands, Devonian shales, coal-bed methane, and methane from geopressured aquifers. However,many difficult problems such as technology, risk andeconomics remain barriers to progress in this direction.In general these reserves are not commercially viablewithout subsidy.
Higher recovery from conventional gas reservoirs isa more likely place to look for additional gas and gascondensate production.
The largest obvious source of gas from discoveredreservoirs would be those reservoirs that have had strongwater drives. It is worth mentioning that approximatelytwo-thirds of the gas reservoirs of the world have anoriginal gas-water contact, and approximately 50percent of these reservoirs have at least a partialdisplacement with water.
ReferencesBoyd, W.E., Jr., Christian, L.D., and Danielsen, c.L.
1982. "Secondary Gas Recovery from a WateredOut Reservoir." Paper presented at the fall SPEmeeting, New Orleans, LA., Sep. 1982, SPE No.11158.
Clark, N.J. 1960. "Elements of PetroleumReservoirs." SPE of AIME, Dallas, TX.
Craft, B.C., and Hawkins, M.F. 1959. AppliedReservoir Engineering. Prentice-Hall, Inc.,Englewood Cliffs, N.J.
Duggan, J.O. 1972. "The Anderson "L" - An Abnormally Pressured Gas Reservoir in South Texas."JPT, Feb. 1972.
Energy Resources Conservation. Board. 1975. Theoryand Practice ofthe Testing ofGas Wells. 3rd ed.,Calgary, AB, Canada, Second Printing, 1978.
Gas Processors Suppliers Association. 1981.Engineering Data Book (9th ed., 5th rev.).
Guerrero, E.T. 1968. Practical Reservoir Engineering, The Petroleum Publishing Co., Tulsa, OK.
Katz, D.L., Cornell, D., Kobayashi, R., Poettman,F.H., Vary, J.A., Elenbass, J.R., and Weinaug,C.F. 1959. Handbook ofNatural GasEngineering. McGraw-Hill Book Co., New York.
Railroad Commission ofTexas. 1972. Back PressureTest for Natural Gas Wells. Oil and GasEngineering Department, State of Texas.
Rawlins, E.L., and Schellhardt, M.A. 1935. BackPressure Data on Natural Gas Wells and TheirApplication to Production Practices. US Bureauof Mines, Monograph 7.
Russell, D.G., Goodrich, J.H., Perry, G.E., andBruskotter, J.F. 1966. '.'Methods for PredictingGas Well Performance." JPT, Jan. 1966, pp.99-108.
Smith, L.R., and Yarborough, L. 1968. "EquilibriumRevaporization of Retrograde Condensate by DryGas Injection." SPEJ, Mar. 1968, pp. 87-94.
Sprinkle, T.L., Merrick, R.J., and Caudle, RH. 1971."Adverse Influence of Stratification on a GasCycling Project." JPT, Feb. 1971, pp. 191-194.
153
Chapter 11
ENHANCED RECOVERY BY WATERFLOODING
11.1 INTRODUCTIONWaterflooding is the process of injecting water intoa formation for the purpose of displacing oil toproducing wells. The displacement of oil by water isgoverned by wettability, pore size distribution andgeometry, rock heterogeneities, and fluid properties.Waterflooding is a proven technology to improve recovery, but the degree of improvement and economicviability is dependent upon the following:
• The type of flood scheme implemented
• Properties of the reservoir rock
• Properties of the oil
• Well spacing
• Economic factors (i.e., cost of the scheme, oil price,royalties, regulatory constraints)
Waterflooding is classified as "secondary" recoverybecause it supplements recovery of oil by natural or"primary" depletion.
In certain reservoirs, mobility ratios are improved bythe addition of polymers, and interfacial tension is reduced by the addition ofsurfactants to the injectedwater.These processes are "tertiary" recovery schemes andare referred to as "polymer" and "micellar" flooding,respectively.
Based on a statistical review ofwaterfloods in westernCanada, total recovery factors generally vary from 16to 45 percent with an average of 30 percent of originalproject oil in place. These values are typically at leastdouble the primary recovery factor values.
This chapter reviews the waterflooding process, theindustry methods used to estimate reserves and production forecasts and the factors that affect the results, theaccuracy of these methods, when and how to apply thethem, and typical statistical data.
11.2 DISPLACEMENT PROCESSThe displacement process is governed by severalfundamental principles that include mobility ratio,interfacial tension, and fractional flow.
154
11.2.1 Mobility RatioD'Arcy developed an empirical relationship forthe velocity of a fluid through a porous medium as afunction ofpressure differential, viscosity, and a proportionality constant (permeability). The mobility ofa fluidis the effective permeability of the rock to that fluiddivided by the viscosity of the fluid. For a frontal displacement scheme, the mobility ratio, M, is the ratio ofthe mobility of the displacing phase behind the floodfront to the displaced phase ahead of the flood front.
(I)
where I<.w = relative permeability to waterk,o = relative permeability to oilIlw = water viscosity (cp)Ilo = oil viscosity (cp)
For a waterflood scheme, water mobility is determinedat the average water saturation at water break-through.Oil mobility is determined at the initial connate watersaturation. Mobility ratios for water displacing oilgenerally vary from 0.1 to 10. Increased mobility ratioshave a detrimental effect on displacement, areal sweepand vertical sweep efficiencies, as discussed in thefollowing subsections.
11.2.2 Interfacial TensionInterfacial tension is a thermodynamic property of aninterface between two phases. Typical values of interfacial tension between oil and water at reservoirconditions range from 10 to 30 dynes/em. Interfacialtension generally increases with increasing molecularweight ofthe reservoir fluid and decreases with increasing reservoir temperature. In water-wet rocks, interfacialtension tends to create bubbles of oil that block porethroats. In oil-wet rocks, interfacial tension tends to bindthe oil to the rock surface. Interfacial tension is one ofthe major reasons why oil becomes increasinglymore difficult to recover as water saturation increases.
--- 1
ENHANCED RECOVERY BYWATERFLOODING
1
where fw = fractional flow
Fractional flow is a function of water saturation sincerelative permeabilities to oil and water are functions ofwater saturation. Fractional flow curves are constructed
Fractional flow is the fraction of the total fluid flowthat is due to the flow of the displacing phase, and isa function of the saturation of the displacing phase.The simplified form of the fractional flow equation,excluding gravity and capillary forces, is as follows:
using relativepermeabilities to oil and water determinedin laboratory tests. Frontal advance theory and theapplication of fractional flow curves are presented inconsiderable depth by Craig (197Ia) and Willhite(1986). Typical fractional flow curves are illustrated inFigures 11.2-1 and 11.2-2.
These fractional flow curves illustrate that the displacement of oil from a water-wet rock is more efficient thanfrom an oil-wet rock. Water injection and water production volumes will be higher for an oil-wet reservoirthan for a water-wet reservoir.
It is noted that the fractional flow following breakthrough represents the producing water cut at thesandface. In single layer displacement, remaining oilsaturation to waterflooding should be determined fromfractional flow curves at the estimated economic watercut limit. In multi-layerdisplacement, it is common practice to assume that the residual oil saturation towaterflooding is equal to the endpoint saturation fromrelative permeability data. This is a consequence ofproducing well oil cuts being maintained at economicrates by layers that have not broken through with water.
(2)
Fractional Flow11.2.3
Over the range of interfacial tensions encountered inwaterflooding, residual oil saturations are relatively constant. Residual oil saturations decline when interfacialtension is reduced to less than one dyne/em and approachzero when interfacial tension is approximately 0.001dyne/em.
oL-~===----'-_-'---J_-'-_---'
20 30 40 50 60 70 80Water Saturation (% pore vol.)
Source: Craig, 1971a.
0.8
•- 0.7c:
'"-ttl 0.63:-0~ 0.50u:a; 0.4c:0
:;:::o 0.3!!1u.
0.2
0.1
0~::::....J-......L_--'---'--'--
10 20 30 40 50 60 70Water Saturation (% pore vol.)
Source: Craig, 1971a.
Figure 11.2-1 Effect of Oil Viscosity onFractional Flow Curve, StronglyWater-Wet Rock
Figure 11.2-2 Effect of Oil Viscosity onFractional Flow Curve, StronglyOil-Wet Rock
155
n
DETERMINATION OFOILANDGASRESERVES
, 0 A
I I A Injector0 Producer- Principal direction
A 0 of oildisplacement
I I- horizontal
• 0 I A
A----
• Pembina Cardium
• Wainwright - Sparky
Swan Hills - Beaverhill Lake
Steelman - Midale
A---I0----
Figure11.3-2 PlanView for HorizontalWaterflood
In practice, average remaining oil saturations will beslightly higher than endpoint residual oil saturationvalues due to economic limit constraints.
In dipping reservoirs, fractional flow data are adjustedfor gravity and capillary effects. For oil being displacedupdip, the performance ofa waterflood improves as dipincreases. Capillary pressure effects are assumed to benegligible for most reservoir flow systems.
11.3 TYPES OF WATERFLOODSThe two general types of waterflood schemes areclassified by the primary direction of the displacementprocess, i.e., vertical or horizontal.
Vertical Waterflood Schemes. Water is injected atwells completed at the bottom of the formation, and oilis produced at wells completed at the top of the formation (Figure 11.3-1). The higher density of wateras compared to oil results in water gravitating to thebottom of the formation and displacing oil in anupward direction.
Figure11.3-1 Cross Section for VerticalWaterflood
Horizontal flood schemes are typically classified bythe type of injection pattern. The most common, asillustrated in Figure 11.3-3, include the following:
• Five-spot
• Inverted nine-spotLine drive
• Peripheral
A combination of the vertical and horizontal processesis used in dipping reservoirs. Other types ofpatterns arediscussed and illustrated by Craig (197Ib).
11.4 ANALYSIS METHODS ANDWHEN TO APPLY THEM
There are five general types of reserve and productionforecast methods for waterfloods in common use:
1. Volumetric analysis
2. Decline performance analysis
3. Comparison to analogous pools
4. Analytical performance prediction
5. Numerical simulation
The volumetricmethod is used only to calculatereserves,whereas the other methods may be used to calculate reserves and production forecasts. Wherever possible,reserves should be calculated using more than onemethod in order to substantiate the results and increaseconfidence.
The following subsections discuss the applicability ofthe methods at various stages of depletion.
o Completioninterval
Oil production
t t--> --
IPrincipaldirection of oildisplacement
Oil-----------
-' -- WaterWaterinjection
This type of scheme is best suited to relatively thickformations and is most commonly applied to reefreservoirs such as the following in Alberta:
• Rainbow, Virgo, Zama, Shekelie-Keg River
• Pembina, West Pembina-Nisku
Horizontal Waterflood Schemes. Water is injected ina pattern ofwells, and oil is produced from wells completed between injectors (Figure 11.3-2). Pressuregradients caused by injection and production result indisplacement of oil in a horizontal direction.
This type of scheme is best suited to relatively thin orlayered formations and is commonly applied to blanketor channel type sands as well as carbonate reservoirssuch as the following reservoirs in western Canada:
156
______________________d
ENHANCED RECOVERY BYWATERFLOODING
'f -0- -0- -0--9
I I I I II I I I II I I I Ir--b--b--k--*I I I I II I I I II I I I I'f -6- -6- -6--QI I I I II I I I II I I I I~-lr--lr--I:r-"
Direct Line Drive
Source: After Craig, 1971 b.
A Injection wello Production well
Pattern boundary
<;> A Q A QI I I
<?- - -0- - -?- - -0-- - {>I I I
\>A\>A\>I I I
?- - -0- - -9- - -0-- - \>I I I6 A 6 A 6
Inverted Nine-Spot
,A"/ "/ <,
/ -,// <,
/ 0 0 -,
/ "/ "
~ 0 ~-, /
" /"0 0 /" /" /-, /-, /
" /"If
Peripheral
Figure 11.3-3 Flood Patterns for Horizontal Flood Schemes
11.4.1 Pool DiscoveryAt pool discovery, there is normally insufficientreservoir data to accurately calculate waterflood reservesby any method. If the reservoir is seismically defined,waterflood reserves may be calculated using volumetricsor analogies and are normally categorized as "possible"because of the considerable uncertainties in reservoirdefinition.
11.4.2 Delineated Pool: ImmatureDepletion
Once a pool has been delineated and on primaryproduction for a reasonable period of time, waterfloodreserves can be calculated more accurately since reservoir size and configuration will have been established,reservoir properties can be measured at various pointsacross the pool, oil properties will have been established,and the primary depletion mechanism can be established.
At this stage, volumetric, analogous comparison, performance prediction, and numerical simulation methodsmay be utilized. Properly assessed volumetric andanalogy methods are reasonably accurate at this stage
and are normally used to assess waterflood feasibility.Performance prediction methods alone are only approximate, but are reasonably accurate if adjustments aremade to fit volumetric reserves and analogies. Numerical simulation is commonly performed if waterfloodfeasibility has been established by analytical techniques. This technique is generally accurate for ultimaterecovery predictions, "provided" reservoir propertiesare accurately defined and numerical effects areproperly handled. Frequently, however, reservoir rockproperties, layering and heterogeneities are notaccurately known, and unreliable break-through predictions result. Analogies in these cases sometimes yieldmore reliable results if the analogous pools havesimilar heterogeneities and rock properties.
If economically feasible, waterflood reserves at thistime are frequently classified as "probable." Wherestrong analogies can be made to similar successfulflood schemes, a portion of the reserves may also beclassified as "proved." The degree to which provedreserves are assigned depends upon the type ofreservoir, the reliability ofthe data, the commitment of
157
DETERMINATION OFOILANDGASRESERVES
volumetrically ifhistorical oil-water contact movementsare measured. Changes in contact levels compared tomapped pore volumes yield in situ determination ofdisplacement and sweep efficiencies which may be usedto assess remaining reserves. Hydrocarbon pore volumeor original oil in place vs. depth relationships arerequired to evaluate in situ recovery efficiencies.
the operator to implement a scheme, and the strength ofthe analogies.
11.4.3 Post-Injection StartupAfter startup of injection, reserves are generallycalculated in the same manner as that described inSection 11.4.2. Slightly higher confidence may be placedon the calculated results as water injectivity andpotential premature break-through problems can beascertained.
11.5
11.5.1
VOLUMETRIC ANALYSIS
Overview of Method11.4.4 Post-Waterflood ResponseAfter waterflood response has been exhibited (i.e., oilproduction increases and gas-oil ratio (GaR) decreases),more of the possible and probable waterflood reservesmay be reclassified as "proved" or "probable." There isbasically no change in the way volumetric, analogy andperformance prediction methods are utilized at this stageof depletion; the only difference is in the confidencelevel ofthe results. Numerical simulation results becomemore accurate, however, as reservoir and rock properties are tuned to match actual response.
Mature horizontal waterflood schemes exhibit trends ofincreasing water cut and declining oil production. Oncethe trends have been established, decline performanceanalysis may be used to calculate reserves and oil production forecasts. As discussed in Chapter 18, normallyover 50 percent recoverable reserve depletion is requiredbefore decline analysis is performed. Properly assesseddecline analysis is the most accurate conventionalmethod to determine proved and probable producingreserves. Numerical simulation techniques can bemore accurate, but the expense of performing the simulation may not be warranted unless operating andoptimization strategies are being examined. Waterfloodrecoveries obtained from decline analysis are frequently rationalized volumetrically. This procedure willindicate whether all areas of the reservoir are beingefficiently flooded. Additional nonproducing provedor probable reserves may be assigned to areas of thereservoir that require infill or delineation drilling,additional injection well conversions, or recompletionworkovers to improve recovery.
Mature vertical waterflood schemes may not haveestablished oil production decline or water cut trendsas a result of regulatory production rate limitations imposed on oil wells and manual restrictions to preventwater coning. Recoveries can be accurately predicted
E,EHEvEc =
Vsw =
N = '" E V [Sop - ~] (3)pf'l'tswB B
op or
where Npf total waterflood reserves fromcommencement of the flood toabandonment (stm")average porosity within the grossswept area of the flood scheme
= total sweep efficiency = EH x Ev x Ec= horizontal sweep efficiency (areal)
vertical sweep efficiencyconformance efficiency (continuity)gross swept rock volume of the floodscheme (m")
Sop = oil saturation within the gross sweptvolume at the start of the flood(fraction)
Sor = residual oil saturation (fraction)Bop = oil FVF @ start of flood (m3/m3)
Bor = oil FVF @ abandonment of flood(m3/m3)
The equation is straightforward, but the derivation ofeach parameter of the equation may not be.
Waterflood reserves are frequently confused with totalreserves. Total reserves are equal to primary pluswaterflood reserves. Similarly, total recovery factor isequal to the primary plus waterflood recovery factors.Typically, the total recovery factor for waterfloodschemes is at least double that ofprimary recovery.
11.5.2 Parameters and FactorsAffecting Analysis
The individual parameters that make up the volumetricwaterflood equation are discussed in this section. Morecomplete discussions are presented by Craig (1971),Willhite (1986) and Slider (1983).
The volumetric equation for the calculation of waterflood reserves is a relatively simple one (Slider, 1983a):
Mature Waterflood11.4.5
158
______________________51
10
ENHANCED RECOVERY BYWATERFLOODING
Horizontal Waterflood Schemes
1. Porosity
Average porosity, cp, within the gross swept reservoirshould be used in the calculation. It should benoted that this may not equal average pool porosity.
2. Total Sweep Efficiency
Total sweep efficiency, E" has three components:horizontal efficiency, EH , vertical efficiency, Ev, andconformance efficiency, Ec . Many evaluators rearrangeEquation (3) and incorporate SolBop- So/Borin a fourthcomponent term, displacement efficiency, ED:
(4)
Some horizontal waterflood schemes exhibit piston-likeoil displacement. The oil wells produce water-free untilflood front arrival, and then water out within a fewmonths. This behaviour can result from unstratifieddeposition, water-wet characteristics, or the overdisplacement of water injection volumes relative topattern producing rates. When this behaviour occursin a number of wells, the shape and position ofwaterflood fronts can be mapped, enabling in situ measurement of sweep efficiency by the comparison ofswept pore volumes with either injected water or produced oil volumes. The accuracy of this method islargely a function ofthe accuracy of the mapped shapeof the flood front.
3. Horizontal Sweep Efficiency
Horizontal (or areal) sweep efficiency, EH , may bedefined as the areal fraction ofa waterflood pattern contacted by injected water. This fraction is affected bypressure gradients, permeability trends, mobility ratiosand injected volumes. Values of EH at water breakthrough for various waterflood pattern configurationshave been determined through laboratory models innumerous studies (Craig, 197Ic). With continuedwater injection after break-through, EH increases as afunction ofthroughput volumes until it reaches 100 percent. For volumetric reserve calculations, horizontalsweep efficiencies are determined for conditions at economic water cut limits. A number of design correlationcharts have been developed to determine EH; these aresummarized by Craig (1971d). Figure 11.5-1 illustratesthe correlation for a five-spot flood pattern. As canbe seen from this plot, horizontal sweep efficienciesare generally over 90 percent since economic water cut,fw' limits are typically greater than 95 percent.
100
0..80Q)
~(f)
'"~ 70-c
"" 60
50 ~:::::JLU-lWlL_---L---l---LilWJ0.1 1.0
Reciprocal of Mobility Ratio
Source: After Craig, 1971d.
Figure11.5-1 Effect of Mobility Ratio on OilProduction for the Five-SpotPattern
This plot also illustrates that EH decreases as mobilityratio increases. Thus, high viscosity oil (commonly lowAPI gravity) reservoirs will have a lower EH and a lowerrecovery factor than similar low viscosity (high APIgravity) oil reservoirs.
Permeability trends must be addressed when horizontalsweep efficiency is being determined. Unfortunately,these are frequently not identified until after implementation ofa waterflood scheme when wells on trend withwater injectors prematurely water out. These problemsare usually rectified by converting the scheme to a linedrive waterflood with alternating rows of injectors andproducers oriented along the permeability trend. For example, most Cretaceous Cardium reservoirs in westcentral Alberta have southwest to northeast permeability trends resulting from tectonic stress during thebuilding of the Rocky Mountains.
Horizontal sweep will also be affected by nonuniformpressure sinks at production wells. EH is normally notaffected by gas saturations prior to waterflooding.However, ifgas saturations are too high prior to waterflooding, cusping of the waterflood front at theproducing well prior to fill-up may occur and adverselyaffect horizontal sweep efficiency.
Of greater operational significance when high free gassaturation exists is the high reservoir voidage createdby high GORs. To maintain cash flow, it is commonpractice to continue oil production during waterfloodfill-up. High GORs result in high voidage replacementrequirements and defer re-pressuring ifinjectivity is lowor injector-to-producer ratios are low.
159
4. Vertical Sweep Efficiency
Vertical sweep efficiency, Ey , accounts for incompletesweep of reservoir layers at abandonment of the waterflood scheme. Incomplete vertical sweep is caused bythe stratified nature ofmost reservoirs. Strata are flushedwith water in descending permeability sequence. Ateconomic water cut limits at the producing well, not allstrata may be flushed with water, and the vertical sweepefficiency will then be less than 100 percent.
Vertical sweep efficiencies are commonly calculatedfrom methods that order flow capacity thicknesses andpermeabilities from core analyses. The two most common techniques are the Stiles Method, which primarilyconcerns capacity thickness ordering (Slider, 1983b),and the Dykstra Parsons Method, which relates statistical variations in permeability with floodout behaviourof flood pot tests made on California core samples(Craig,197Ie).
In both methods, Ev is a function of mobility ratio andpermeability contrast. Ev decreases as mobility ratio andpermeability contrast increase. Thus reservoirs with thinhigh permeability streaks have low vertical sweepefficiency.
Care must be taken to ensure that the stratified reservoirassumption is valid in both methods. Some reservoirsthat undergo post-depositional porosity alteration havehigh permeability contrasts on core, but these contrastsmay be so random in nature that the reservoir willappear homogeneous, and piston-like displacementmay occur with virtually 100 percent vertical sweepefficiency.
Other factors that affect vertical sweep efficiencyinclude gravity and cross-flow between layers.
Due to gravity forces, water will tend to move at thebottom of the reservoir and, in uniform permeabilitydistributions in horizontal reservoirs, this movementtends to decrease vertical sweep efficiency. Ifreservoirpermeability decreases with depth, however, gravityforces will improve vertical sweep. In dipping and vertical reservoirs, gravity forces can be used to advantageby injecting downdip and displacing oil updip.
Cross-flow between layers tends to improve Ev atfavourable mobility ratios (low) and diminish it atunfavourable mobility ratios (high).
5. Conformance Efficiency
Conformance efficiency, Ec, or continuity, is a term usedto account for discontinuous reservoir pore volume.In the past, engineers widely assumed that all porespaces in a reservoir are interconnected with each other,
160
DETERMINATION OFOIL AND GAS RESERVES
but infill drilling results throughout North Americaindicate that reservoirs are less continuous than had beenassumed. Generally Ec is difficult to quantify and isusually back-calculated in mature producing pools wherereserves from decline analysis do not rationalize volumetrically using only vertical and horizontal sweepefficiencies.
Without considering continuity, infill drilling programstechnically do not usually increase ultimate recoverablereserves; they only accelerate recovery. In reservoirswith poor continuity, infill drilling will improve continuity and, therefore, reserves by accessing additionalpore volume. A more complete discussion of infilldrilling and continuity is presented by Gould and Sarem(1989).
6. Gross Swept Volume
Gross swept volume, Vsw, refers to the reservoir rockvolume that is subject to waterflood sweep. In a horizontal sense this includes the area within waterfloodpatterns and a portion ofthe area outside the waterfloodpatterns. A common error in waterflood analysis is toutilize entire pool volumes instead of gross swept volumes. A procedure for determining gross swept areasdiscussed by Slider (1983c) is dependent on the gas saturation existing at the start ofa flood scheme. The higherthe gas saturation at the start of the flood, the lower theswept fraction of oil outside the enclosed flood pattern.When reservoir permeability trends exist, they shouldalso be considered when 'estimating gross swept areas.
The vertical component of gross swept volume isfrequently overlooked in volumetric waterflood analysis. Gross swept volumes should reflect layers whichare receiving injected water volumes. In thick stratifiedreservoirs some layers may be ofpoor quality and maynot be completed or may not be receiving injectedwater volumes due to formation damage.
7. Oil SaturatIon at Start of Flood
Oil saturation, Sop, at the start of a flood for a solutiongas drive reservoir may be determined using thefollowing equation (Slider, 1983e):
SOP =(N - Npp) Bop (1 - Sw)
(5)NBo;
where N = oil in place (stm')Npp = primary oil production (stm')Bop = oil FVF after primary depletion
(m3/m3)
Sw connate water saturation (fraction)a, = initial oil FVF (m3/m3)
-----------------------
ENHANCED RECOVERY BYWATERFLOODING
Initial oil in place is calculated by either materialbalance or volumetric methods. Connate water saturation is measured by log analysis or capillary pressuretests. This Sop calculation assumes the saturation isuniform at the star! of the flood.
8. Residual Oil Saturation
Residual oil saturation refers to the microscopic oilsaturation left in reservoir rock. Because oil and waterare immiscible, surface tension of fluids with reservoirrock results in incomplete displacement of oil by water.The efficiency of this displacement is a function ofthe reservoir wettabiIity and pore throat size andconfiguration.
Residual oil saturations are most commonly determinedby flooding reservoir core samples with multiple porevolumes ofwater in either steady-state or unsteady-statetests. Since Sor is dependent upon wettability, care mustbe taken to ensure that the rock samples do not havealtered wettability properties as a result of core handling. The effects of core handling on wettability arediscussed at length by Anderson (1986). The accuracyand reliability of Sor measurements generally decreasefrom native state to restored state to cleaned cores.
The most significant conclusions from Anderson'sliterature survey are summarized as follows:
• Removal of a core from the reservoir may increaseoil wettability due to the decreased solubility ofwettability-alteringcompounds as a result of temperature and pressure reduction.
• Core flood tests conducted qt ambient vs. reservoirtemperature and pressure may exhibit oil-wet characteristics resulting in a hig9 estimate of residual oilsaturation.
• Cleaning and drying of core samples prior to use incore flood tests tend to induce water wettability andresult in a low estimate of residual oil saturation.
Ideally, multiple core samples should be tested andaveraged to determine Sor because most reservoirs areheterogeneous, and one sample may not be representative of the average reservoir. Due to cost and coreavailability considerations, this is not always feasible.In Alberta, the Energy Resources ConservationBoard publishes a guide of nonconfidential core floodtests (Energy Resources Conservation Board, 1993).Values of Sor may thus also be estimated by analogyto other pools of similar geologic horizon in the samegeographic area.
Another means of estimating Sor whhe core flushingtests are not available is by examining average Sor
values from conventional core analyses. These valuesshould be adjusted to reservoir conditions using the oilformation volume factor. In situ residual oil saturationsare sometimes taken in waterflooded portions of reservoirs using log or sponge coring techniques. This couldonly be performed in a mature waterflood or pilotproject.
Residual oil saturation may also be affected by trappedgas saturations, Sgt, when initial gas saturationsare present in the reservoir prior to waterflooding.Experimental studies discussed by Craig (1971f) indicate a reduction in Sor with Sg! in water-wet rocks butnot in oil-wet rocks. These correlations assume that nocompression or resolution of gas occurs. In most waterflood schemes,gas saturation is reduced by re-pressuringwhich reduces the impact on residual oil saturation.Dardaganian (1985) discussed the effect of free gassaturation on waterflooding and a method for determining the optimum pressure at which to initiate awaterflood.
Vertical Waterflood Schemes
In vertical waterflood schemes, gravity results in oildisplacement across stratified layers; hence, Ev andEH are usually taken to be 100 percent. Gross sweptvolumes, however, should be adjusted downwards toreflect the following:
Sandwich Loss. This is the volume of oil remaining atthe top of the reservoir after waterflooding. As a resultof water coning, not all of the reservoir can be sweptwith water before producing wells reach economic water cut limits. Also, ifthe reservoir is updip ofproducingwells, attic oil losses may result. Coning correlationshave been developed (Kuo, 1989) to predict sandwichloss; however, they are highly dependent on mobility.Typically, sandwich losses can vary from 2 to 15 feetfor mobility ratios of I to 10 respectively in unfracturedreservoirs.
Unswept Volumes (along the periphery of the pool).Under perfect gravity segregation in a homogeneouspool, water will areally displace the entire reservoir.However, discontinuities, permeability channels, andrestrictions may limit volumes swept by the flood. Theseeffects may be incorporated by reductions in either theswept volume or horizontal and conformance factors.
Vertical waterflood schemes have been implemented inpinnacle reefs in northern Alberta where the pools havebeen essentially depleted under a primary recoverymechanism. The success of these schemes may bequestionable as primary depletion has established
161
high gas saturations. These likely form gas caps thatimprove primary recovery to levels approachingtypical secondary recovery values.
In situ sweep efficiency in vertical waterflood schemeswith a high degree of gravity segregation can be measured by comparing oil recovery to water-flushedhydrocarbon pore volume. The flushed pore volumesare determined using oil-water contact measurementsfrom log analysis and pore volume vs. depth correlations. The accuracy of the sweep efficiency evaluationin this method is a function of the accuracy in the oilwater contact measurement and pore volume vs. depthplots.
Factors affecting the accuracy of oil-water contactmeasurement include the following:
Completion Status. Is the log run in a cased or openhole? Cased hole interpretations are more subtle anddifficult to interpret.
Producing Status. Is the log run in an observation orproducing well? Oil-water contacts measured in shutin producing wells may be higher than the poolaverage if the water cone is not allowed sufficienttime to settle.
• Variability of Measurements. Is measurement madeat one or a number ofwells, and does the value varysignificantly? The more variation, the more interpretation required to derive a pool average value.
The sensitivity ofthe calculated sweep efficiency to oilwater contact variations should also be checked to gainconfidence in the answer, e.g., does a 0.91 m (3 foot)change in interpreted contact change calculated sweepefficiency 5 or 50 percent?
Once sweep efficiency has been derived, the remaininguncertainties pertain to the determination of remaining gross swept pore volume, which is a function ofthe geological mapping and petrophysical properties ofthe reservoir.
11.5.3 Reliability of ResultsThe accuracy of volumetric reserve calculations isa function ofthe accuracy ofthe parameters in the analysis. An engineer using volumetric analysis must assessthe uncertainties in the parameters when assigningproved and probable reserve values. There is usuallyconsiderable uncertainty in assessing volumetricparameters in proposed flood schemes prior to implementation. These uncertainties diminish as additionaldata is gathered.
In certain types of mature waterfloods, total sweepefficiencies can be determined from performance data.
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DETERMINATION OF OIL AND GASRESERVES
This greatly increases confidence in the calculations.Waterfloods of this type include vertical and horizontalbank displacement schemes.
11.6 DECLINE PERFORMANCEANALYSIS
11.6.1 Overview of MethodDecline analysis is used to evaluate mature waterfloodschemes. Historic decline trends are used to extrapolatefuture trends; the two generalized methods are oil rateand oil cut declines. Decline trends may be either expo.nential or hyperbolic. The mathematics of declineanalysis are discussed in Chapter 18.
11.6.2 Factors Affecting AnalysisOil decline trends in waterfloods are a consequenceof increasing water cuts and constant or declining wellbore flow capacity. The shape of the decline trendis a function of relative permeability, mobility and reservoir permeability variation. Ideally, under stableconditions, extrapolation ofoil cut and oil rate declinesshould yield the same reserve value. Economic oil cutand oil rate limits should be determined for design fluidlifting capacity and used as endpoints in the declineanalyses.
Pools with a high degree of stratification, permeabilityvariance, or dual porosity behaviour will tend todecline in a hyperbolic or harmonic fashion. Most reservoirs, however, exhibit exponential decline behaviour.
For horizontal floods, the following points should beconsidered when analyzing production decline trends:
I. Total fluid production should be plotted along withoil cut and oil rate data. Increasing fluid ratesmay be achieved by increased drawdown at producing wells, increased reservoir pressure throughoverinjection, or well stimulation. While total fluidrates are increasing, oil rate decline trends aredampened. The use of oil cut trends is preferred inthese cases as oil rate trends will yield optimisticresults. Conversely, if total fluid rates are declining, the use of the oil rate decline trend will yi~ld
conservative results unless the fluid rate dechnecannot be arrested.
2. When wells are grouped for decline analysis, careshould be taken to ensure that wells within the grouphave experienced water break-through. A preferredmethod is to group wells with similar water cut.s.This ensures that there will be no sudden change III
decline behaviour as a result of water break·through.
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ENHANCED RECOVERY BYWATERFLOODING
3. Generally, oil cut trends should not be used ifwatercuts are still less than 50 percent.
4. Infill wells should be grouped separately fordecline analysis. Decline trends of the infills andoriginal wells, pre- and post-infill drilling, canbe used to assess incremental recovery associatedwith the infill program.
5. Yearly voidage replacement ratios should bechecked when decline trends are being analyzed.Underinjection will cause gradual pressure loss,accelerated oil rate declines and dampened oil cutdeclines. The reverse is true for overinjection. Thisis most sensitive in low GOR and low API gravityoil reservoirs.
6. Decline analysis can be used as a diagnostic tool.Declining fluid production rates when voidage isbeing maintained may be due to formation damageor pumping equipment failure.
7. Producing conditions should be verified whendeclines are being analyzed to ensure that declinesare real and have not been imposed by operatingconstraints.
These comments also apply to vertical waterfloodschemes, which generally exhibit a more sudden waterout behaviour. Flood-out is controlled by coning ratherthan by stratification characteristics. Thick vertical floodschemes will exhibit a relatively extensive water-freeproduction period followed by a steep decline trend.
When reserves are determined by decline analysis invertical flood schemes, completion intervals shouldbe checked to ensure that wells are completed at the topof the productive zone. If not, additional reserveassignments are warranted.
11.6.3 R.eliability of ResultsDecline analysis is one of the more reliable methods ofestimating reserves. The reliability of the method in·creases with the maturity ofthe pool and the smoothnessof the data. At the start of production decline, whentrends are not clearly established, interpretation of declines may vary from engineer to engineer. Mostengineers adhere to exponential trends until hyperbolictrends can be confidently quantified.
Engineers with experience in analyzing decline trendsofpools similar in nature to the subject pool may havemore confidence in assessing a certain type of declineand thus may use a different trend than an engineer withless experience.
11.7 COMPARISON TO ANALOGOUSPOOLS
11.7.1 Overview of MethodPredicting waterflood performance by the analogymethod refers to the comparison of a previous maturewaterflood project to a proposed or current project inorder to predict results ofthe proposed or current project.The method is usually reliable and is best applied inconjunction with the volumetric method. The methodcan be used to determine recoverable reserves as wellas production and injection forecasts. A rigorous analogy involves comparison of all volumetric recoveryparameters.
11.7.2 Procedure and Factors AffectingAnalysis
The first step in a rigorous analogy analysis is torationalize the volumetric parameters in the analogypool. The recoverable reserves in the analogous poolshould be well-established from decline analysis.The oil in place should also be well-established frommapping and volumetric calculations.
The volumetric parameters should be determined asdescribed in Section 11.5. The only unknown variablethat is not definable empirically is the conformance efficiency Ee. Once all the other volumetric parametershave been derived, this value can be back-calculated tomatch recoverable reserves. In addition to continuity,this factor will include any error or anomalies associated with the determination of the other parameters inthe volumetric equation.
The next step of the analogy procedure is to calculatereserves of the proposed or current waterflood schemeusing the volumetric method. Ifdifferences in mobilityratios, oil saturations and permeability variations existbetween the analogy and the proposed waterfloodproject, these differences should be incorporated in theanalysis. The conformance efficiency of the analogyproject should be applied to the proposed project.
The underlying assumption in the analogy methodis that the continuity and anomalies associated withthe analogous pool will also apply to the proposed orcurrent waterflood scheme.
When the analogy project is similar to the proposedproject in terms of geological deposition and oil gravity, the analogy method is usually simplified bycomparing the recovery factor ofthe analogy project tothe proposed project. This is also often performed whenthe specific volumetric parameters are not well-defined
163
in the analogy or proposed waterfloodproject due to anabsence of reliable laboratory core tests.
Analogies can also be used to predict production andinjection performance. Rigorous application of ratedependent analogies is describedby Slider(1983d). Thisprocedure is useful in estimating waterflood responsetime, magnitude of oil productivity improvement andflood-out behaviour after response. The procedure involves plotting oil rate divided by effective injectionrate vs. cumulative effective injection divided by ultimate flood recovery. This plot provides a normalizedrelationship that can be applied to a flood scheme ofany size.
11.7.3 Reliability of ResultsWhen analogies are applied in an analysis, it is goodengineering practice to provide a comparison of reservoir properties so that the reader can judge the strengthof the analogies being made. The strength of the analogy is critical to the assessment of proved or probablereserves.
The closer the analogy project to the proposed projectin terms of geographic area, geologic horizon, oil viscosity,waterfloodpattern and orientation,permeabilityvariation, residual oil saturation and degree of depletionprior to waterflooding, the strongerthe analogyandthe more reliable the results.An analogyshouldbe chosen that is typical of performance and not one that isclearly the best or worst performance.
Analogiesare best utilized prior to or immediatelyafterimplementationof a waterflood project.
11.8 ANALYTICAL PERFORMANCEPREDICTION
11.8.1 Overview of MethodsThe analytical methods summarized in Table 11.8-1yield production and injection forecasts for horizontalwaterflood schemes. The Higgins-Leighton (1962)Methodhas fewerlimitingassumptionsthan othertechniquesand is adaptableto varioustypesof patterns.Themethod models a flood pattern as a series of parallelstreamflow tubes and is available in computerprogramformat.
For composite injection and producing rate, WaR andrecoveryvs. time, Craig (1971 g) recommended the useof the Craig-Geffen-Morse (Table 11.8-1) Methodcoupled with the Caudle and Witte (1959) correlationfor injection rates. This procedure splits a waterfloodforecast into four stages:
164
DETERMINATION OF OIL AND GASRESERVES
Stage I Periodprior to interference of oil banksaroundinjectors
Stage 2 Period from interferenceto fill-up of gas porespace
Stage 3 Period from fill-up to water break-through
Stage 4 Period from water break-throughto flood-out
During Stage I, water injection rates are calculatedusing radial flow equations. Water injection rates during Stage 2 are calculated using the Caudle and Witteconductance ratio. Oil production in Stages I and 2 isassumed to be negligible or zero. If oil production issignificant, then adjustments are made to fill-up timesand volumes. Oil production during Stage 3 is equal towater injection rates.Afterwaterbreak-through in Stage4, the followingare calculated:
• Horizontalsweepefficienciesas a functionof breakthrough areal sweep and injected water volumes
• Water-oil ratios from frontal advance theory
• Injectivities from Caudle and Witte
Oil producing rates from producing WaRs andinjection rates
The method can handle multi-layer effects by normalizing injection, production, and pore volume data foreach layer and multiplying the results by single layercalculations.
11.8.2 Reliability of ResultsAll waterflood predictive methods have underlyingsimplifyingassumptions. The accuracy ofthe methodstherefore relies on the validity of these assumptions inadditionto theaccuracyof the reservoirdescription. TheCraig-Geffen-Morse Method is one of the morerigorous methods; however, the following limitingassumptionsapply:
• Waterflood response is injectivity-driven.
• Gravity effects are negligible.
• There are no cross-flow effects.• There is no lateral variation in reservoir properties.
• Reservoir continuity is 100 percent.
• Oil production is negligible prior to fill-up.
• Capillary effects are negligible.
• There is no bottom water or gas cap.The engineer must judge the significance and validityof these assumptionsto the reservoir being analyzed. Itis recommended that the production profile resultingfromthepredictive methodbe adjusted tomatchreservescalculatedby volumetric, decline or analogy methods.
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ENHANCED RECOVERY BYWATERFLOODING
Table 11.8-1 Classification of 33 Waterflood Prediction Methods
Basic Method Modification
A. Methods primarily concerned with permeability heterogeneity-injectivity
1. Dykstra-Parsons (1950) (a) Johnson (1956)
(b) Felsenthal-Cobb-Heuer (1962)'2. Stiles (1949) (a) Schmalz-Rahme (1950)'
(b) Arps ("Modified Stiles") (1956)
(c) Ache (1957)
(d) Slider(1961)3. Yuster-Suder-Calhoun (1949) (a) Muskat (1950)
(b) Prats et al. (1959)'4. Prats-Matthews-Jewett-Baker
(1959)
B Methods primarily concerned with areal sweep efficiency
1. Muskat (1946)
2. Hurst (1953)
3. Atlantic-Richfield (1952-1959)
4. Aronofsky (1952-1956)
5. Deppe-Hauber (1961-1964)
C. Methods primarily concerned with the displacement process
1. Buckley-Leverett (1942) (a) Terwilliger et al. (1951)
(b) Felsenthal-Yuster (1951)
(c) Welge (1952)
(d) Craig-Geffen-Morse (1954)3
(e) Roberts (1959)
(I) Higgins-Leighton (1960-1964)'2. Craig-Geffen-Morse (1954) (a) Hendrickson (1961)3. Higgins-Leighton (1960-1964)
D. Miscellaneous theoretical methods
1. Douglas-Blair-Wagner (1958)
2. Hiatt (1958)
3. Douglas-Peaceman-Rachford (1959)
4. Naar-Henderson (1961)
5. Warren-Cosgrove (1964)
6. Morel-Seytoux (1964)
E. Empirical methods
I. Guthrie-Greenberger (1955)
2. Schauer (1957)
3. Guerrero-Earlougher (1961)
Source: After Schoeppel, 1968.Note: Complete citations for all of the references listed in this table are given at the end of the chapter.IAlso applies to Stiles method.'Also applies to Yuster-Suder-Calhoun and Schauer methods.3Also concerned with areal sweep problem. Also recognized as basic method.
165
Predictive methods are normally applied at thewaterflood design stage to assist in scoping economics and facility design rates. The methods can be used,however, at any stage of waterflood depletion andhistory-matched to actual performance by tuning reservoir rock properties. The reliability of the procedureincreases if this is performed.
11.9 NUMERICAL SIMULATION
11.9.1 Overview of MethodThe most advanced method for determining waterfloodreserves and performance predictions is numerical simulation, which can be described as the use of digitalcomputers to numerically solve mathematical modelsrepresenting physical reservoir systems. Simulationtechniques are discussed in Chapter 17.Aspects of'simulation that are relevant to waterflooding are presentedin this section.
11.9.2 Parameters and FactorsAffecting Analysis
The following factors may affect numerical simulationresults:
Model Phases. Waterflood simulations are performedusing Beta or black oil models. When the reservoir isabove the bubble point, only two phases (oil and water)are required. Ifthe reservoir is below the bubble point,then three phases are required (oil, water and gas). Therelative permeability and physical properties of thephases are required in the simulation. The physical properties are usually easily measured and accurate; however,the accuracy of relative permeability data is lessreliable and can significantly influence the simulationresults.
Model Dimensions. Waterflood simulations aretypically two- or three-dimensional. Three-dimensionalstudies are required where there is distinct layering orimportant gravitational influences. Two-dimensionalcross-sectional simulation studies are frequently usedto quantify the effects of gravity segregation. Resultsmay then be incorporated in 2-D areal studies on horizontal waterfloods through the use of pseudo-functions.
Grid Block Sizing. Numerical simulation involvesa trade-off between calculation time and accuracy.The more grid blocks used to define a reservoir,the more accurate the calculated results. However,calculation time and cost also increase, and in manycases, prohibitively.
166
q
IDETERMINATION OF OIL AND GASRESERVES I
Sensitivity studies on gridblock sizing should beperformed to ensure that the selected sizing is sufficientlyaccurate. Increased grid definition should be used inhighly heterogeneous areas and around wellbores.
Large areal waterflood simulations should employseveral grid blocks between wells so that pattern modifications and infill drilling may be studied.
If reservoir projects are fairly consistent across aproposed waterflood area, partial pattern waterfloodsimulations are frequently performed and the resultsscaled up to reservoir dimensions. The examination ofa partial pattern can result in better grid definition formore accurate results.
Grid Block Orientation. Grid blocks should beoriented along permeability trends and geological layers. The orientation and size of the grid may affect themanner in which water break-through occurs. This problem is most pronounced where there are high contrastsin the water-oil mobility ratios. More advanced simulators use variational or nine-spot finite differenceapproximations to eliminate this effect.
Timestep Sizing. Also related to grid block sizing istimestep sizing. Saturation fronts cannot pass through agrid block in one timestep. Thus, the smaller thegridblock, the shorter the timestep must be to ensurethis condition is not violated. A smaller timestep meansmore timesteps, and hence a higher number of calculations to be performed ina simulation run. Most modemsimulators utilize automatic timestep selection tooptimize running times.
History Match. Once a reservoir description is set upin the model, a simulation history match is run by entering actual oil production, water injection, or pressureconstraint data. Calculated results such as reservoir pressure, water-oil ratios, gas-oil ratios, and oil rates arecompared to actual results to judge the accuracy of themodel. Model parameters are then revised and the modelrerun to get a better match. This process is a trial-anderror procedure and relies on the judgement of thesimulation engineer to revise the properties in an appropriate manner. The normal practice is to revise poorlydefined properties first.
11.9.3 Reliability of ResultsThe numerical simulation technique is the mostrigorous method of determining reservoir flow behaviour and compensates for most of the shortfallsexperienced by analytical methods. Assuming thatthe model is set up appropriately to compensate for
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ENHANCED RECOVERY BYWATERFLOODING
the numerical factors as described, the limitation ofthesimulation results rests solely on the accuracy of thereservoir description.
When reservoir properties are established to a highdegree of confidence by good well control, productionresults, pressure tests, and core studies, and the simulation history match requires very little alteration to thereservoir description, then a high degree of confidencemay be placed on the results. As the number of alterations performed to achieve a match increases and theduration of the history-match period decreases, lessconfidence can be placed on the results. Confidence is afunction of the reasonableness of the alterations madeduring the history-match process.
Example
This example demonstrates the kind of problem thatsimulation engineers may encounter in a history matchin an immature waterflood.
Water break-through has not occurred at a producingoil well when the simulator predicts that the well shouldbe producing significant water. The engineer mustdecide which of the following applies:
o The relative oil-water permeability data is wrong.
o There is directionalpermeability diverting water awayfrom the producing well.
o The pore volume between the injector and produceris too low.
o There is a flow barrier between the producer andinjector.
o The reservoir model has been layered when nolayering is in fact occurring.
The solution may be anyone of these. An incorrectalteration may still achieve a history match, but willresult in incorrect forecasts.
Simulations performed in proposed waterflood schemeswill only have the primary depletion with which tohistory-match. While these should give a good determination ofoil in place and oil and gas flow behaviour,they do not address directional permeability, reservoirlayering, flow restrictions or actual relative oil-waterpermeability characteristics. In vertical schemes theywill not address water coning characteristics, which arecritical to flood performance.
The assignment ofproved and probable reserves from asimulation study must address these limitations.
11.10 WATERFLOODING VARIATIONS
11.10.1 Naturally Fractured ReservoirsDisplacement of oil by water in naturally fracturedreservoirs is related to capillary and gravity forces acting on individual matrix blocks. "Imbibition" is themechanism by which the nonwetting phase is displacedby the wetting phase in porous media due to the effectsof capillary pressure. Oil recovery by imbibition is animportant process in waterflooding of fractured reservoirs. As injected water advances along the fracturesand is imbibed into the matrix, an equivalent volume ofoil is released to the fractures. A discussion ofthe theoryof waterflooding in fractured reservoirs has beenpresented by de Swaan (1978).
The imbibition process is the dominant displacementmechanism when matrix blocks are small and capillarypressures are high. Gravitational pressure governs displacement when matrix blocks are tall and capillarypressures are low. For oil-wet rocks, external forces(gravity and applied pressure differentials) must overcome capillary pressures to recover oil from the matrixblocks. It follows then that matrix blocks must be of acertain height in order for waterflooding to be successful in oil-wet reservoirs. Knowledge of reservoir rockwettability is important in the evaluation of reserves infractured reservoirs. For rocks that tend to be oil-wet,such as some dolomites, spontaneous imbibition ofwater will not occur. Fortunately, most dolomitic rockshave somewhat low capillary pressure due to large poresizes, and gravity dominates the displacement process.Bridging between matrix blocks may result in a morecontinuous capillary network that will improve oilrecovery.
Oil recovery by imbibition is described by a timedependent transfer function that is determined in thelaboratory and can be modelled mathematically as presented by Aronofsky et al. (1958). Laboratory tests onsmall reservoir samples are scaled according to rulespresented by Mattax and Kyte (1962) to determinerecovery from reservoir matrix blocks contacted byinjected water.
Displacement efficiencies within the fracture system,expected to approach 100percent, are governed by gravity forces and applied pressure differentials sincecapillary pressures are negligible. Often, the original oilin place within the fracture system represents a smallfraction of the total system.
The areal and vertical sweep efficiencies in fracturedreservoirs are expected to be similar to those in
167
unfractured reservoirs provided that injection patternsin horizontal waterfloods properly account for permeability anisotropy. The water injection wells should lineup parallel to the permeability trend. The influence ofvertical fractures on areal sweep efficiency has beenpresented by Crawford and Collins (1954) and Dyes etal. (1953). It is noted that their studies were conductedfor hydraulically fractured wells, but the results can beapplied to naturally fractured reservoirs.
In vertical waterflood schemes, the oil-water contactshould be monitored to determine the in situ sweepefficiency. The measured oil-water contact representsthe fluid contact within the fracture system and corresponds to the free water level since capillary pressuresin the fractures are generally negligible. The recoveryefficiency within the water-flushed portion ofthe reservoir will increase with time and can be history-matchedusing the model presented by Aronofsky et al (1958).The final recovery efficiency is obtained from thehistory-matched model. Waterflood reserves are determined by applying the final recovery efficiency to theestimated gross swept volume to account for sandwichlosses at the top of the reservoir.
The accuracy ofreserve estimates in naturally fracturedreservoirs is dependent on accurate interpretation offracture characteristics such as frequency, width, orientationand distribution, reservoir structure, laboratory tests andreservoir monitoring. Proved and probable reserve estimates must consider the uncertainties and reasonablerange of values associated with these parameters.
11.10.2 Polymer FloodingIn reservoirs with unfavourable mobility ratios, watersoluble polymers may be added to improve displacementand sweep efficiencies. The mobility of the displacingphase is reduced due to an increase in fluid viscosityand an alteration in relative permeability related topolymer retention and modification of pore sizes.Reduction of water mobility has the disadvantageof reducing injectivity, so this limits the economicapplication of polymer flooding to high permeabilityreservoirs. Estimation ofreserves for polymer floods issimilar to that for a waterflood but with a more viscousdisplacing phase. In the assignment ofproved and probable reserves, the polymer slug sizing and potentiallosses due to dissipation and polymer degradation mustbe considered.
11.10.3 Micellar FloodingReduction of interfacial tensions is a major objective inmicellar flooding processes. Surfactants (or surface-
168
DETERMINATION OFOILANDGASRESERVES
active agents) are added along with polymers to injectedwater to reduce interfacial tension, and thereby reduceresidual oil saturation and improve oil recovery. Thereduction of residual oil saturation due to the additionofsurfactants is determined in the laboratory. The technical success of a surfactant flood is dependent uponhow much of the surfactant is lost due to adsorption,precipitation, the irnmobility ofthe surfactant-rich phase,and dissipation. The estimation of reserves for micellarfloods is similar to that for a waterflood, but with a moreviscous displacing phase. In the assignment of provedand probable reserves, the micellar-polymer slug sizingand potential surfactant losses must be considered.
11.11 STATISTICAL WATERFLOODANALYSIS SURVEY
11.11.1 Overview of DatabaseIn order to illustrate typical usage of various reserveanalysis methodologies and resulting recovery factors,reserve data on approximately 200 waterflood unitsin the western Canadian sedimentary basin were compiled from the database of an independent petroleumconsulting firm. Recovery factor statistics are presented in Table 11.11-1, and methodology statistics aresummarized in Table 11.11-2.
The recovery factors presented are proved plus probable values derived by dividing ultimate recoverablereserves by original oil in place within the unit boundaries. Ultimate recoverable reserves are values calculatedby the evaluators using the various assigrunent methodologies. Original oil-in-place values are based onestimates prepared by the operator, a governmental regulatory body, or an independent consultant. Depletionrefers to cumulative oil production at the time of theevaluations divided by original oil in place. The rangespresented represent 7.5 percent of the sample points.Most of the sample points represent horizontal floodschemes.
The data are from a sampling ofwaterfloods in westernCanada, and the table is intended to show typicalvalues and ranges of results.
11.11.2 Discussion of ResultsThe following general observations may be made froma review of the data:
I. The typical total recovery factor is 30 percent; rangeis 16 to 45 percent.
2. The average API gravity ofsamples is 33°; range is23°t041°.
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ENHANCED RECOVERY BYWATERFLOODING
Table 11.11-1 Summary of Recovery Factors: A Sampling of Western CanadianWaterfloods
No. of Total ProvedData Oil Gravity Plus Probable
Geologic Horizon Litbology Points °API Recovery Factor Depletion
Range Range (%)Average (75%) Average (75%)
Upper Cretaceous SS 42 38 37-41 23 15-35 65Lower Cretaceous SS 16 33 20-41 29 18-40 62Mannville SS 27 26 19-36 27 20-35 54Jurassic SS 36 23 21-26 35 16-54 73Triassic SS 13 40 39-42 40 25-51 76Triassic Carb 7 37 36-42 35 25-43 67Permian SS 3 40 40-40 28 6-34 73Mississippian SS 5 21 14-22 17 8-22 36Mississippian Carb 32 34 30-40 33 21-46 74Devonian SS 3 42 41-43 38 25-51 55Devonian Carb 22 39 37-42 32 19-53 65
Average/Total 206 33 23-41 30 16-45 67
7
Table 11.11-2 Reserve Analysis TechniqueDistribution
No. of %of Depletion (%)
Data Points Samples Average Range
Volumetrics 51 25 46 25-75Decline 110 53 72 52-87Vol. & Decline 27 13 68 43-87Analogies 12 6 52 30-74Sim. Studies 6 3 35 26-44
Total 206
3. Assuming a recovery factor of 10 to 15 percent, theultimate recovery under waterflood is typically atleast double that of primary recovery.
4. Very few waterfloods exist for pools under200APIgravity.
Decline analysis is generally not used until depletion isover 50 percent. The reason is the lack ofdefinitive decline trends in immature stages ofwaterflood recovery.The data also suggest that waterflood declines start atapproximately 50 percent depletion.
ReferencesAnderson, W.O. 1986. "Wettability Literature
Survey." JPT, Oct. 1986, p. 1125.
Aronofsky, J.S., Masse, L., and Natanson, S.O. 1958."A Model for the Mechanism of Oil Recoveryfrom the Porous Matrix Due to Water Invasion inFractured Reservoirs." Trans., AIME, Vol. 213,pp.17-19.
Caudle, B.H., and Witte, M.D. 1959. "ProductionPotential Charges During Sweepout in a FiveSpot Pattern." Trans., AIME, Vol. 216,pp. 446-448.
Craig, F.F. 1971a. "The Reservoir EngineeringAspects of Waterflooding." SPE Monograph No.3, pp. 29-44.
------.197Ib.pp.48-49.
------. 1971c. pp. 50-52.
----.. 1971d. pp. 108-111.
----.. 1971e. p. 64.
----.. 1971f. pp. 41-43.
--.. 1971g. p. 93.
Crawford, P.B., and Collins, R.E. 1954. "EstimatedEffect of Vertical Fractures on SecondaryRecovery." Trans., AIME, Vol. 201, pp. 192-196.
Dardaganian, S.O. 1985. "The Application of theBuckley-Leverett Frontal Advance Theory toPetroleum Recovery." Trans., AIME, Vol. 213,pp. 365-368.
169
de Swaan, A. 1978. "Theory of Waterflooding inFractural Reservoirs." SPE Journal, Apr. 1978,pp.117-122.
Dyes, A.B., Kemp, C.E., and Caudle, B.H. 1953."Effect of Fractures on Sweep-out Pattern."Trans., AIME, Vol. 213, pp. 245-249.
Energy Resources Conservation Board. 1993. PVTand Core Studies Index. Guide G-14, Calgary,AB.
Gould T.L, and Sarem, A.M.S. 1989. "Infill Drillingfor Incremental Recovery." JPT, Mar. 1989, p.229.
Higgins, R.V., and Leighton, AJ. 1962. "A ComputerMethod to Calculate Two-Phase Flow in AnyIrregularly Bounded Porous Medium." JPT, Jun.1962,pp.679-683.
170
DETERMINATION OF Oil AND GASRESERVES
Kuo, M.C.T. 1989. "Correlations Rapidly AnalyzeWater Coning." OGJ, Oct. 1989, pp. 77-80.
Mattax, C.C., and Kyte, lR. 1962. "Imbibition OilRecovery from Fractured Water-DriveReservoir." Trans., AIME, Vol. 201, pp. 192-196.
Schoeppel, R.J. 1968. "Waterflood PredictionMethods - 7, Comparative Evaluation." O&GJ,Jul. 1968, p. 73.
Slider, H.C. 1983a. Worldwide PracticalPetroleumReservoirEngineeringMethods. PetroleumPublishing Company, Tulsa, OK, p. 551.
--. .l983b. p. 569.
--. 1983c.p. 557.
--. 1983d. p. 600.
--. 1983e. p. 554.
Willhite, G.P. 1986. Waterflooding. SPE TextbookSeries, Vol. 3, pp. 53-110.
_.s.... I.~ I
,
- 1
Chapter 12
ENHANCED RECOVERYBY HYDROCARBON MISCIBLE FLOODING
12.2 TYPES OF HYDROCARBONMISCIBLE FLOODS
Hydrocarbon miscible floods are the most commontertiary EOR schemes in western Canada. They can besubdivided into vertical or horizontal miscible floods.
Vertical miscible floods are usually implemented inpinnacle reefs or reservoirs with a high relief angle. InAlberta, the majority of these are in Rainbow Lake,Brazeau River, Pembina/West Pembina, and WizardLake. The solvent is injected as a blanket at the top ofthe reservoir to take advantage of a gravity-stabilizeddisplacement. Subsequent chase gas injection drivessolvent downward.
the displaced oil. In contrast, miscible fluids are solublein oil, so there will be no interfacial force between oiland solvent and the theoretical residual oil saturationwill be zero.
This chapter is limited to miscible flooding withhydrocarbon solvents. Miscible flooding is a proventechnology that increases reserves. However, the improvement of the reserves estimation and the economicviability are affected by the following:
• Reservoir geology• Rock properties• Reservoir fluid properties• Solvent composition and slug size• Chase gas composition and slug size• Implementation cost• Well spacing and well patterns• Flood types• Oil, gas and condensate prices• Royalty regime• Stage of implementation
This chapter reviews recognized hydrocarbon miscibleflood processes, the methods for the estimation of reserves, the accuracy of these methods, and the factorsaffecting this estimation as reported in the literature.
12.1 INTRODUCTIONAfter discovery, most oil reservoirs produce under thenatural energy of the reservoir. The primary drivemechanism for these reservoirs varies significantly. Forpools with an initial reservoir pressure above the bubblepoint pressure, the energy is initially obtained by fluidexpansion and rock compaction. Later in the life of thereservoir, when the pressure falls below the bubble-pointpressure, additional energy will result from gas liberation and expansion. Usually these pools have recoveryfactors ofless than 20 percent. For pools with a bottomor edge water drive, oil is displaced by water, and therate of decline of the reservoir pressure is reduced bythe encroaching aquifer. The recovery factor for thistype ofreservoir can be as high as 60 percent (e.g., FennBig Valley D2A Pool, Alberta, Canada).
Reservoirs with a gas cap produce oil because of gascap expansion. Other reservoirs may have both a gascap and an aquifer. The recovery factor for these reservoirs can be as high as 80 percent (e.g., Westerose D-3Pool, Alberta). The high recovery factor is due to richgas sitting at the bottom ofa thick gas pay zone becauseof gravity. This rich gas effectively acts as a solvent,and the result is a vertical miscible displacement ofoil.
In most reservoirs, oil recovery may be improved bythe implementation ofan enhanced oil recovery (EOR)scheme. EOR schemes can be classified as secondaryand tertiary floods. Water injection for pressure maintenance, pattern waterflooding and immiscible gasinjection are secondary EOR schemes. Hydrocarbonmiscible floods and carbon dioxide miscible floods aretertiary EOR schemes. The terms "secondary" and "tertiary" indicate the EOR technology only, and not thestate of the pool being flooded. Therefore, if a projectis being miscible flooded before any waterflood, themiscible project is deemed a tertiary EOR project.
In a waterflood or an immiscible gas flood, thedisplacing fluid is not soluble in the displaced oil. Thedisplacement results in a residual oil saturation due tothe interfacial forces between the displacing fluid and
12.2.1 Vertical Miscible Floods
171
~......, I
DETERMINATION OFOILANDGASRESERVES I·
In horizontal miscible floods, solvent and water areinjected alternately to mobilize residual oil and push itto the producers. After the injection of solvent andwater, chase gas (which is miscible with solvent) andwater are injected to extend the solvent bank size andcomplete the displacement process. After injection of25 to 40 percent hydrocarbon pore volume (HPV) ofsolvent and chase gas, the process reverts to horizontalwaterflood to depletion. In other words, in the early stageof the miscible project, oil is replaced by miscible solvent and moved toward producing wells. Later, residualsolvent is mobilized by chase gas and moved to whereit can contact more residual oil. Through this process,an expensive commodity, residual oil, is replaced witha cheaper commodity, chase gas.
The majority of these floods are implemented in SwanHills (Swan Hills A and B, South Swan Hills, VirginiaHills, Judy Creek A and B), Kaybob (Kaybob BHLAand Kaybob South Triassic), Goose River and FennBig Valley areas of Alberta. The expected incrementalrecovery factor of 5 to IS percent results from gravityoverride, viscous fingering, and the inability to controlinjection profiles.
The highest wells in the structure are usually chosenas the injectors to maximize oil displacement, and theproducing wells are completed at the lowest porousinterval above the oil-water contact. Production ratesare controlled to restrict solvent and water production.Horizontal wells are becoming popular in vertical miscible floods. These wells are usually drilled as producersnear the water-oil contact to reduce water and gas coning problems and thus increase the production rate andreduce the sandwich loss.
Innovative completion techniques such as perforationbelow or at the oil-water contact have also resulted inreduced sandwich losses.
The expected incremental recovery compared to upwardwaterflood is in the range of IS to 40 percent. The highincremental recovery factor in vertical displacement isdue to high volumetric sweep efficiency as a result ofa gravity stable displacement. The vertical miscibledisplacement is ideal in homogeneous reservoirs. Inheterogeneous reservoirs with horizontal shale barriers,a substantial reduction in incremental oil recovery improvement can be expected as a result of poor verticalsweep efficiency (e.g., Golden Spike D-3 Pool, Alberta).
Intermediate
Figure 12.3-1 Pseudo-Ternary Diagram IndicatingFirst-Contact Miscibility
Heavy
•Solvent\
\\
\\
\\
\\
\ ..ReservoirOil
Light
Multiple-Contact MiscibleProcess
In a condensing process, the intermediate hydrocarbonsfrom the injected solvent condense into the reservoir oilto create a mixing zone. Initially, a given volume ofsolvent contacts the reservoir oil, resulting in a mixture,M I, which separates into an equilibrium gas, 01, andliquid, Ll (Figure 12.3-2). Further injection of solventpushes the more mobile equilibrium gas ahead of theliquid, and the solvent contacts liquid, L I, resulting in amixture, M2. The mixture again separates into equilibrium gas and liquid phases (G2 and L2, respectively).This process is repeated and, after a series of chainflashes, results in the formation of a two-phase envelope on the ternary diagram. The composition of the
12.3.2
12.3 METHODS OF ACHIEVINGMISCIBILITY
12.3.1 First-Contact Miscible ProcessThe simplest and most direct method of achieVingmiscibility is to inject a solvent that is completely solublein the oil in all proportions. Such solvents are called"first contact miscible" (FCM) and are the most expensive. As the ternary diagram shown in Figure 12.3-1indicates, combining the oil and solvent in any proportion results in a single phase, i.e., no two-phase regionis developed. Cost savings can be balanced against process risk by injecting less expensive "multi-contactmiscible" (MCM) solvents which are subdivided intocondensing and vapourizing processes.
Horizontal Miscible Floods12.2.2
172
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ENHANCED RECOVERY BYHYDROCARBON MISCIBLE FLOODING
equilibrium liquid travels up the bubble-point curve,becoming richer in the components of intermediatemolecular weight as they condense out of the solventand into the oil. However, as the equilibrium liquidbecomes richer, the amount ofthe intermediate components lost from the solvent into the oil at each contactbecomes less, and the vapour flashed at each contactand pushed ahead into the reservoir also becomes richer.
Intermediate
the reservoir pushes the equilibrium gas, G I, furtherinto the reservoir. This gas contacts fresh reservoiroil resulting in a mixture, M2, which separates into anequilibrium gas, G2, and a liquid, L2. Further injectioncauses gas, G2, to flow ahead and contact freshreservoir. In this process, the composition of thegas at the displacing front is getting richer andprogressively moving along the dew point until it reachesthe composition that is directly miscible with thereservoir oil.
Intermediate
L1
M2
Reservoir OilG~2g~~
Reservoir Oil
Light Heavy Solvent
Figure 12.3-3 Development of Multiple-ContactMiscibility Vapourizing Process
If the reservoir pressure is close to the bubble-pointpressure, small pockets of gas may be formed at thestructurally high area of the reservoir. These pockets ofgas may dilute the equilibrium gas to the extent that themiscibility is lost.
12.4 EXPERIMENTAL METHODS TODETERMINE MISCIBILITY
Four methods have been widely used by the industry todetermine miscibility and design the composition ofsolvent and chase gas:
1. The pressure composition diagram (P-X)2. The multi-contact ternary diagram3. The slim tube test4. The rising bubble apparatus (REA)
12.4.1 poX DiagramA typical poX diagram is perfomed as a screening testby combining reservoir fluid with increasing molefractions of injection solvent, and measuring thesaturation pressure of each mixture. The cricondenbar,critical point, and solubility limit can be determined
Figure 12.3-2 Development of Multiple-ContactMiscibility Condensing Process
This in situ multiple contact generation of miscibilityestablishes a "transition zone of contiguously misciblefluid compositions from the reservoir oil compositionthrough compositions Ll, L2, L3, ... Ln on the bubblepoint curve to the injected gas composition." That is,the solvent is in first-contact miscible with the equilibrium liquid LM-I, which is in first-contact miscible withequilibrium liquid LM-2, and so on. This process dominates the leading edge of the multiple transition zone.
12.3.3 Vapourizing Multiple-ContactMiscibility
In a vapourizing process, the intermediate weighthydrocarbons from the reservoir oil vapourize into theinjected solvent to create a mixing zone. In this process, miscibility can be achieved with natural gas, fluegas, carbon dioxide or nitrogen, provided that the reservoir pressure is above the minimum miscibility pressure.
The development of miscibility in a vapourizingsolvent drive can be explained with the help of the ternary diagram in Figure 12.3-3. Initially, a given volumeof solvent contacts the reservoir oil, resulting in a mixture, MI, which separates into an equilibrium gas, Gl,and liquid, LI. Subsequent injection of solvent into
Light Heavy
173
at the operating temperature (Figure 10.2-1). Thehydrocarbon mixture is deemed acceptable for injection ifthe cricondenbar lies below the reservoiroperatingpressure. This defines an FCM solvent.
12.4.2 Multi-Contact Ternary DiagramThe test is performed at reservoir pressure and temperature by combining the reservoir fluid with solvent. Thecompositions of the resultant equilibrium vapour andliquid are determined and become the first points on thephase envelope. The next step depends upon whichmultiple-contact miscibility (MCM) process is beingsimulated. For a condensing MCM process, the equilibrium gas is discarded and more solvent is added to theequilibrium liquid.
For a vapourizing MCM process, the equilibriumliquid is discarded and more oil is added to the equilibrium gas. The procedure is repeated several times;tie-lines are defined after each step, and the appropriatephase envelope is generated. The hydrocarbon mixture is deemed immiscible if the solvent lies on theextension of a tie-line.
12.4.3 Slim Tube TestThe slim tube test apparatus consists ofa long (usuallymore than 20 m) coiled stainless steel tube packed withglass beads or crushed silica. The porous medium is initially saturated with reservoir oil at the desired testtemperature and pressure. Solvent is injected at one end,and miscibility is determined through visual observation ofthe transition zone, the recovery factor ofthe oiland the break-through performance ofkey solvent components (e.g., CI, C2, C3). Unlike the ternary and PoXdiagrams, which are conducted at static conditions, slimtube tests represent a dynamic process where the degree of dispersion in the reservoir is to some extentreproduced in the lab.
12.4.4 Rising Bubble ApparatusThe rising bubble apparatus (RBA) consists of asmall-diameter vertical tube mounted in a high-pressurecell. A bubble ofsolvent is injected at the bottom ofthetube. The miscibility characteristic is determined byvisual observation of the bubble decay as it rises throughthe reservoir oil. The rising bubble apparatus (RBA)combines the small size and compactness of the visualcell with the dynamic nature ofthe slim tube test. Hence,this method can make miscibility determination muchmore efficient than the other three methods.
174
DETERMINATION OFOILANDGASRESERVES
12.5 SCREENING AND FEASIBILITYSTUDIES
Screening, design and implementation ofa hydrocarbonmiscible project usually involve the following steps:
I. Estimate the incremental oil reserves based on thevolumetric method.
2. Make a preliminary production forecast based onthe break-through ratio (BTR) concept (Section12.5.2) and preliminary economic evaluation.
3. Use a detailed geological model to evaluate thereservoir characteristics; from this model, provideinput data for simulation study.
4. History-match the pool performance with a blackoil simulation model under primary and secondarydrive mechanisms. This model will provide thesaturation and pressure distributions required for asubsequent pseudo-miscible or compositional study.
5. Use a pseudo-miscible or compositional modelto generate a production forecast, evaluate thereservoir's performance under miscible flood, anddesign the project.
6. Use experimental and numerical model studies todetermine the optimum slug size and design thecomposition of the injection fluid.
7. Make an economic evaluation and feasibilitydesign.
8. Obtain regulatory approvals.
9. Design facilities and implement.
10. Develop the data acquisition system, and preparedetailed monitoring programs and detailed fieldoperation guidelines.
II. Monitor performance and reservoir management toimprove the pool performance under the miscibleflood.
Prior to implementationofa hydrocarbon miscible flood,the project goes through several stages. At the earlystage of the screening, usually a crude method is usedto generate a production forecast and conduct an economic evaluation. At this stage, the incremental reservesmay be estimated by the volumetric method, and theproduction forecasts may be generated by the BTRtechnique. For the feasibility study, it is imperative toconduct a detailed geological and reservoir simulationstudy to evaluate the economic viability of the project.Other methods such as statistical models have also beenused to evaluate the feasibility of a hydrocarbonmiscible flood.
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ENHANCED RECOVERY BYHYDROCARBON MISCIBLE FLOODING
The volumetric equation for estimating incremental oilreserves, RE, is:
(3)(
k, kw ) '-+-J..ts u, sWavgM = -'----'--------""'-
(k, kw)
M: + J..Lw oWavg
dead end pore volume, this method requires a carefulexamination of the data obtained and a comprehensivesimulation study.
For a given formation and interval, the remaining oilsaturation obtained from these methods may be different because, besides the question ofaccuracy, the depthof investigation and vertical resolutions of the variousmethods are usually different. For example, the singlewell tracer technique represents a capacity-weightedaverage while pressure coring or logging gives avolumetric-weighted average.
The comparison ofresults provides important measuresof the quantity and distribution of remaining oil. Forexample, if the former is significantly lower than thelatter, the interval may be highly stratified or containdead end pore volume. In all cases, the measured remaining oil saturation will exceed the residual oilsaturation.
where k, = effective permeability to solvent (mD)k; = effective permeability to water (mD)k, = effective permeability to oil (mD)
Estimation of Residual Oil Saturation afterMiscible Flooding
Theoretically speaking, the residual oil saturation aftermiscible flooding should be zero due to the lack of interfacial tension between oil and solvent. However, evenifthe miscibility criteria are met, all the oil may not bedisplaced due to trapping by mobile water or dead endpores. The average oil saturation left behind after hydrocarbon flooding is usually greater than that estimatedfrom the core flood studies. The usual expectation inwestern Canada carbonates is 5 percent HPV.
Estimation of Areal Sweep Efficiency forHorizontal Miscible Floods
Areal sweep efficiency is the fraction ofthe pattern areathat has been contacted by solvent and mainly dependsupon the mobility ratio of the displacement process inthat the areal sweep efficiency decreases as the mobility ratio increases or become more unfavourable. Themobility ratio, M, between an oil bank and the solventdisplacing the oil bank in the presence of mobile wateris defined by Stalkup (1983) as:
(2)
residual oil saturation afterwaterflood (fraction)residual oil saturation after miscibleflood (fraction)connate water saturation
Volumetric Method
ED= (Socw - So,,) / (I-Sw)
where Socw=
S =w
The connate water saturation is the water saturation inthe reservoir at discovery, which can be determined fromresistivity logs.
Estimation of Residual Oil Saturation
The residual oil saturation is the amount of oil leftbehind in a water-swept zone when the relative permeability approaches zero. The residual oil saturation is afunction of wettability, adhesion, and rock properties.Four methods are used to determine residual oil saturation: core flood test, pressure coring, logging, andthe single-well tracer method. The core flood test isdiscussed in Chapter II.
Pressure coring is considered to be an accurate methodfor obtaining a volumetric measure ofremaining oil saturation. However, this method is expensive and requiresthat a new well be drilled in a waterflooded part of thereservoir.
Logging techniques that can be used for obtaining avolumetric measure of remaining oil saturation are loginject log (pulsed neutron, gamma radiation, resistivity), and carbon-oxygen logging. Each method has itsown special advantages and limitations. The resistivitylogs can be run only in open holes.
The single-well tracer method (Deans and Majoros,1980) measures an average remaining oil saturation thatis weighted according to the product of thickness andeffective permeability to brine at remaining oil saturation (capacity) for the various strata sampled by injectedtracer. In carbonate reservoirs, due to the effect of the
RE=EHxEvxEDxOOIP (1)
where EH aerial sweep efficiencyEv vertical sweepED displacement efficiency
OOIP original oil in place
The reserves target for a miscible flood is the residualoil saturation after waterflooding. Therefore, the displacement efficiency, ED, is defined as:
12.5.1
175
~-
DETERMINATION OF OIL AND GASRESERVES
where q,dp
IJ" = solvent viscosity (m Pa.s)Ilw water viscosity (m Pa.s)Jlo oil viscosity (m Pa.s)sw = solvent/waterow = oil/water
Since solvent-oil mixtures have much lower viscositiesthan oil, the solvent-oil mixing zone becomes less stablethan for waterflood, and numerous fingers of solventmay develop and extend toward producing wells. Thisis one explanation for early solvent break-through andpoor sweep efficiency. As can be seen from Equation(3), the concept of injecting water alternately with themiscible fluid improves the overall mobility of the displacement and thus improves the areal sweep efficiency.
Areal sweep efficiency in a miscible flood is also a function of areal heterogeneity, geometry of pattern flood,dispersion/diffusion, pore volume of solvent injected,and water alternating gas ratio (WAG).
Craig (1971) extensively reviews lab measurements fordisplacement with a favourable mobility ratio where thedisplacement front is stable and the effect of viscousfingering is insignificant. For an unfavourable mobilityratio, Habermann (1965), Mahaffey et al. (1966), Dyeset al. (1954), and Kimbler et al. (1969) measured arealsweep efficiency of a homogeneous five-spot patternfor a single-front displacement, where solvent wasinjected continuously and initially oil was the onlymobile fluid. The data indicated that areal sweepefficiency at solvent break-through decreases withincreasing mobility ratio.
Claridge (1973) developed a correlation for areal sweepefficiency by using Dyes' data and applying Koval's(1963) equations for linear displacement efficiency ofan unstable displacement. This correlation applies to aconfined five-spot pattern -in a homogenous, single-layerreservoir where the gravity force is negligible comparedto the viscous forces and in the absence of movable wateror gas. Because of these assumptions, the Claridgemethod can be used only for agross estimation ofarealsweep efficiency.
Estimation of Vertical Sweep Efficiencyfor Horizontal Miscible Floods
In a horizontal miscible displacement, where thedensity of the solvent is much less than the density ofeither oil or water, vertical sweep efficiency is substantially reduced as a result of gravity segregation wheresolvent overrides oil. Parameters that affect verticalsweep efficiency are reservoir stratification, verticaldistribution of flow capacity and segregation of
176
hydrocarbon phases. Obviously, a homogenousreservoir with low ratio ofhorizontal to vertical permeability has a higher chance of incremental recoveryreserves losses. Conversely, diffusion and convectivedispersion may allow solvent to liberate the remainingoil from zones where water would not enter.
In a WAG process, gravity segregation will cause theinjected gas to rise to the top of the formation and waterto settle to the bottom. This will result in a low recoveryfactor since only a thin layer at the top of formation issolvent flooded while the bottom layer is waterflooded.Stone (1982) showed that recovery is primarily a function of the viscous-gravity ratio, VGR, defined as:
VGR= q, (4)
dp k, a (k,. + k,,)Jl, Jl.
= total flow rate= density difference between water
and solventk, vertical permeability (mD)A reservoir area~ = relative permeability to waterJlw water viscosity (m Pa.s)k,., relative permeability to solventJlg = solvent viscosity (m Pa.s)
The recovery factor is also a function of water-gasratio. For the same solvent slug size, higher values ofWAG may result in higher recoveries.
Based on the Stone (1982) model, Jenkins (1984)presented a solution for estimating the verticalsweep efficiency for a horizontal displacement in ahomogenous reservoir with either rectangular or radialgeometries. This model will provide only a rough estimate of the vertical recovery due to the limitation inignoring capillary pressures, nonuniform saturationdistribution, and physical dispersion. Hence, this modelis recommended only for the screening study.
Okazawa et al. (1992) used the Claridge correlation forthe estimation ofareal sweep efficiency, and the StoneJenkins model for the estimation of vertical sweepefficiency to predict the performance of large-scale miscible flood. The Okazawa model may be used for thescreening study or performance monitoring of a largescale miscible flood. However, for a feasibility study, adetailed geological study and a simulation study arerecommended.
The volumetric method can also be used to estimate theincremental reserves from vertical miscible floods. In
______________________a
ENHANCED RECOVERY BY HYDROCARBON MISCIBLE FLOODING
this estimation it is important to calculate with coningcorrelations the sandwich loss due to water and gasconing.
Field Estimation of Volumetric SweepEfficiency
Many experimental and mathematical studies ofvolumetric sweep efficiency have been presented in theliterature. However, little attention has been paid tothe field evaluation of volumetric sweep efficiency.Asgarpour and Todd (1988) used a radioactive tracerprogram along with the simulation study to estimate thevolumetric sweep efficiency for an ongoing miscibleflood in central Alberta. In the simulation study, thehistorical performance of the primary natural waterdrive and the first five years of solvent injection werereproduced with a fair degree of accuracy by a pseudomiscible model. This information, along with the resultsofthe radio-active tracer program, was used to estimatethe volumetric sweep efficiency of 45 percent for thisflood. This study concluded that the effect of gravityoverride and viscous fingering were much moremoderate than had been expected from the lab models.
12.5.2 Break-Through Ratio MethodThe break-through ratio, BTR, is defined as the waterproduction plus free gas production at reservoir conditions divided by the oil production at stock tankconditions.
BTR =(GOR - R,) x Bg + (WORx Bw ) (5)
where GOR = gas-oil ratioR, = solution gas-oil ratioBg = gas formation volume factor
WOR = water-oil ratioB; = water formation volume factor
The BTR vs. cumulative oil production plotted ona semi-log graph for most waterfloods is a straightline terminating at the ultimate recovery and theeconomically limiting BTR. The upward trend of theBTR line for a waterflood is due to the increase in waterproduction. For a miscible flood that is implementedafter a waterflood, the BTR curve is expected initiallyto have a downward trend as a result of a steady declinein water production accompanied by an increase in oilproduction. This downward trend will be followed byan upward trend primarily due to solvent and chase gasbreak-through and later by an increase in water production. The upward trend of the BTR will terminate at theultimate recovery and the economically limiting BTR.The difference between the waterflood recovery and the
ultimate recovery is the incremental oil due to themiscible flood.
The BTR method can be used to generate a productionforecast for the preliminary evaluation of hydrocarbonmiscible floods. The incremental hydrocarbon miscibleflood estimated from the volumetric method, the waterflood reserves obtained from extrapolation ofWOR vs.cumulative oil, and the economically limiting BTR areused to determine the ultimate point on the BTR curve.The BTR curve is then constructed based on waterfloodperformance and the performance of a similar pool under hydrocarbon miscible floods. Finally, the productionforecast is generated using a trial-and-error procedure(i.e., an oil rate is assumed-the total production rateis obtained from the BTR curve and this rate is compared with the injection rate for appropriate voidagereplacement).
The BTR method can also be used to estimate theincremental reserves and monitor the performance ofongoing miscible floods (Asgarpour et al., 1988). Theincremental reserves are estimated by the extrapolationofthe BTR curve to the economically limiting BTR provided that the pool is in a mature stage (i.e., BTR >5).
12.5.3 Geological ModelFor the geological study, structural and stratigraphiccross sections are constructed to evaluate the effect ofstratification for the horizontal miscible flood or theimpact of shale barrier for the vertical miscible flood.The determination of vertical and horizontal permeabilities and the averaging method is also essential for thisevaluation. From this model, input data is provided forthe simulation studies.
12.5.4 Simulation StUdiesA black oil simulation study is conducted to reconcilethe geological and reservoir data by 'history-matchingthe pool performance under primary and secondarydrive mechanisms. This model provides saturationdistribution, pressure, etc. required for a subsequentpseudo-miscible or compositional study. Pseudomiscible or compositional models are used to generateproduction forecasts and predict reservoir performanceunder several miscible flood options. Project design isthen based on the optimum case.
The compositional simulator is capable of evaluatingand predicting changes in compositions and pressures of the hydrocarbon phases. Since the model isdeveloped to simulate flow in three dimensions, it considers cross-flow between layers, gravity segregation,channelling, and the effect of variable mobility.
177
The estimation ofincremental reserves for a hydrocarbonmiscible flood depends on several parameters: porosity,pay thickness, areal extent, residual oil saturation towaterflood, connate water saturation, formation volumefactor, and residual oil saturation to miscible, areal andvertical sweep efficiency. For most ofthese parameters,only a range may be available. In reserves estimation,the uncertainty associated with these parameters shouldbe taken into account. To properly describe the risk anduncertainty associated with the incremental reservesof a proposed hydrocarbon miscible flood in centralAlberta, Asgarpour and Papst (1990) developed astatistical model based on the Monte Carlo simulationtechnique. The input parameters to this model are the
Simulation studies using the compositional simulatorcan be used to estimate slug size requirements and theeffects of mass transfer between phases on miscibilityconditions at the leading and trailing edges of themixing zone. Lack ofphysical dispersion or mixing parameters in the miscible flow calculation is a majordrawback. However, this problem can be overcome byadjusting the numerical dispersion to reflect the physical dispersion. The major problem with this model todate has been the cost, which makes a field study impractical. The advent of a high-capacity PC version isreducing this problem.
There are two types ofcompositional model: one basedon k value correlations, and the other on the equation ofstate. The first is more cost-effectivebecause ofthe lowercomputational cost for the flash calculations. Prior to asimulation study, phase behaviour should be studiedso that the fluid can be properly characterized and theequation of state can be "tuned" to experimental data.
The pseudo-miscible model was developed (Todd andLongstaff, 1972) by modifying an existing three-phasesimulator to forecast miscible flood performance. Thesimulator is capable of modeling the essential featuresof miscible displacment by a fairly coarse numericalgrid. The degree ofdispersion rate between solvent andoil, which reflects the degree of viscous fingering, isrepresented by an input mixing parameter. For most fieldapplications mixing parameters in the range of0.5 to 0.8are used. For a system exhibiting strong gravity segregation, a large number of grid blocks is required torepresent different layers.
Production forecasts from the simulation study areused to conduct detailed economic evaluations, makeproject decisions and obtain management, partner andregulatory approval.
12.5.5 Estimation of Uncertainties
DETERMINATION OF OIL AND GASRESERVES
distribution ofthe parameters required for the reservesestimation and the output is the reserves distribution.Figure 12.5-1 shows a reserves distribution for aproposed miscible flood in central Alberta. Based onthis distribution, a different reserves category can beassigned. For example, this figure indicates provedreserves of 1.375 million cubic metres with 80 percentconfidence.
100
80 ----- - - --
~
~60
:0 tm.c 40ea.
20
o -I---.-,r-'-r----,--.---,--;:=;---.--o 1.0 2.0 3.0 4.0
Incremental Reserves (106m3)
Figure 12.5-1 Reserves Distribution
12.5.6 Determination of Solvent andChase Gas Slug Size
In a miscible flood, the total amount of solvent usedshould be enough to maintain miscibility conditions atthe displacement front in the bulk of the reservoir.Whereas heterogeneity and stratification have a neteffect ofincreasing the solvent losses and consequentlythe solvent requirements, economic considerationsdictate optimizing these amounts. The principal parameters determining solvent losses are the dispersion andmixing coefficient. Unfortunately, no simple methodsfor determining these coefficients are available. Thecomplexity of the flooding process makes the interpretation of data from any of the available methodsextremely difficult. These complexities, besides heterogeneities and stratification, could be a result ofthe frontdisplacement, the geometry of flood propagation(Asgarpour et aI., 1989), dead end pores (Asgarpour,1987), the nature of the miscible flood (Chen et aI.,1986), the presence of mobile water or trapped gas(Asgarpour et aI., 1986, Tiffin, 1982), and wettability.Furthermore, the dispersion observed in a single coresample is different from what is observed a few metresaround a wellbore. These dispersions, in tum, couldbe different from those observed over the inter-welldistance in the reservoir.
178
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ENHANCED RECOVERY BY HYDROCARBON MISCIBLE FLOODING
12.5.7
12.6 CLASSIFICATION OF MISCIBLEHYDROCARBON RESERVES
For the purpose of estimating reserves, it is importantto identify the development stage of the project. Thestage will signify the degree of confidence in recoveryof the reserves and can be linked, therefore, to thetiming of allocation of reserves to various categories.
It is suggested that prior to classifying any misciblereserves in the possible category, a reservoir engineering study should be completed to identify the reserves.An economic evaluation should also be conducted basedon the present, or on a reasonable anticipated, economiccondition. A confidence level of 10 to 40 percent probability of the incremental EOR reserves being recoveredis required to allocate reserves to the possible category.
Caution should be used in estimating possible reservesbased only on analogy to similar pools under miscibleflood. The feasibility of a miscible scheme is dependent upon numerous complex parameters, and simpleanalogy is usually misleading.
Miscible flood reserves in the possible category servefor easy identification of EOR potential for businessplanning. Once the business opportunity is identified, itcan set in motion an action plan for implementation ofthe scheme.
Possible Reserves
mature miscible floods where a large portion of solventhas been injected, horizontal injectors can be drilled toaccess the unswept layers and improve the volumetricsweep.
In horizontal miscible floods, producers should also beequipped with mechanical packer assemblies to controlsolvent cycling. In the latter stages of miscible floods,horizontal producers may be used to improve production from layers with low productivity.
Poor vertical sweep efficiency caused by gravity override can also be partially improved by increasing thesolvent and water injection volumes.
The miscibility process also plays a significant role inthe success and failure of the hydrocarbon miscibleprocess. Usually, the first-contact and condensingmultiple-contact miscible processes have proved tobe more successful than the vapourizing process. Thepoor success of the latter may be due to the presence ofpockets of gas in reservoirs with pressures near thebubble-point pressure. This gas may dilute the solventto the extent that it is no longer miscible with oil.
12.6.1
Field Performance of MiscibleFloods
The performance of hydrocarbon miscible floods hasbeen extensively reviewed in the literature (Griffith andHome, 1975), (Beeler, 1977), (Reinhold et aI., 1992),(Anderson et al., 1992), (Pritchard and Nieman, 1992),(Patel and Broomhall, 1992), (McIntyre et aI., 1991),(Adamache et aI., 1990), (Fong et aI., 1990), (Wood etaI., 1990), (Bennett and Geoghegan, 1990), (Okazawaand Lai, 1989), (Dawson et aI., 1989), (Bilozer andFrydl, 1989), (Sorenson and Griffith, 1988). In general,vertical miscible floods have been more successful thanhorizontal floods due to the gravity stable displacement.However, in some vertical hydrocarbon miscible floods,poor geological understanding of the reservoir hasresulted in lower than expected reserves due to thepresence of shale barriers which resulted in poor volumetric sweep efficiency. Sandwich loss due to gas andwater coning has also been a major factor in reducingthe incremental reserves and economics. Recently, in afew hydrocarbon miscible floods, through innovativecompletion techniques, the volumetric sweep efficiencyhas been increased significantly by the reduction ofsandwich loss.
In vertical miscible floods, horizontal wells can be usedas both producers and injectors. Horizontal producersdrilled at the water-oil interface can reduce coning problems and improve the volumetric sweep efficiency.Horizontal injectors drilled in vertical miscible floodscan provide a stable solvent transition zone, prevent thepure solvent from fingering into oil, and improve thevolumetric sweep efficiency.
The major problems associated with the horizontalmiscible floods are gravity override and viscous fingering. In addition, poor injection profile control hasresulted in a low vertical sweep efficiency in manyfloods. In these, the layer with the highest capacity takesthe bulk of the solvent. Only a small portion of thereservoir can be contacted, and solvent is cycled throughthis layer without improving the incremental reservesfrom the other layers. Therefore in the early stages offloods, equipment of injectors with mechanical packerassemblies is important to control the amount of solvent injected per layer so each layer receives enoughsolvent to meet the miscibility criteria. However, for
The most common method to determine solventand chase gas slug size is on the basis of dispersiondiffusion calculations at the leading and the trailingedges ofthe solvent-oil mixing zone (Asgarpour, 1987).
179
12.6.2 Probable ReservesWhen the project is in the implementation phase,tertiary EaR incremental reserves can be allocatedto the probable category provided there is sufficientconfidence (40 to 80 percent) that these reserves areexpected to be recovered.
12.6.3 Proved ReservesThe amount of incremental tertiary EaR reservesallocated to the proved category should be based onthe performance of the miscible flood. In the year thescheme is started, a small percentage ofthe incrementalreserves could be added to the proved category basedon the confidence level (Mukherjee, 1988).
Additional hydrocarbon miscible reserves may beallocated to the proved category in a gradual mannerover a period of time provided there is sufficient technical confidence in the scheme that the proved reservesfigure has a high probability (80 percent) of beingrecovered.
ReferencesAdamache, I., McIntyre, F.J., Pow, M., Lewis, D.,
Davis, R., Kuhme, A., Bloy, G., Van Regan, N.,and Butler, S. 1990. "Horizontal Well Applicationin a Vertical Miscible Flood." Petroleum SocietyofCIMISPE International Technical Meeting,Calgary, AB; Preprints V3, CIM/SPE 90-125,Jun. 1990.
Anderson, lH., Laurie, R.A., Loder, W.R. Jr., andKennedy, P. 1992. "Brassey Field Miscible FloodManagement Program Features Innovative TracerInjection." Paper presented at 67th Annual SPETechnical Conference, Washington, DC, SPE24874, Oct. 1992.
Asgarpour, S.S. 1987. "Determination of Slug Sizefor Carbonate Reservoirs." Paper presented at38th Annual Technical Meeting of the PetroleumSociety of CIM, Calgary; AB, Paper No. 38-09.
Asgarpour, S.S., Pope, J.A., and Springer, s.i 1986."Effect of Mobile Water Saturation on Slug SizeDetermination." Paper presented at 37th AnnualTechnical Meeting, Petroleum Society of CIM,Calgary, AB, Paper No. 86-36-35.
Asgarpour, S.S., Crawly, A., and Springer, S.J. 1988."Re-Evaluation of Solvent Requirements for aHydrocarbon Miscible Flood." SPE ReservoirEngineer, Feb. 1988.
180
DETERMINATION OF OILAND GAS RESERVES
Asgarpour, S.S., and Todd, M.R. 1988. "Evaluationof Volumetric Conformance for the Fenn-BigValley Horizontal Hydrocarbon Miscible Flood."Proc., 63rd Annual Technical Conference andExhibition, SPE ofAIME, Houston, TX.
Asgarpour, S.S., Card, C., Singhal, AX., and Wong,T. 1989. "Performance Evaluation and ReservoirManagement of a Tertiary Miscible Flood in theFenn-Big Valley South Lobe D-2 Pool." JCPT,Nov-Dec, 1989, p. 6.
Asgarpour, S.S., and Papst, W. 1990. "A StatisticalModel to Evaluate a Hydrocarbon Miscible Floodin an Upper Devonian Field in Central Alberta."JCPT, May-Jun. 1990, p. 61.
Beeler, P.F. 1977. "West Virginia CO2 Oil RecoveryProject Interim Report." Proc., US DOESymposium on Enhanced Oil and Gas Recoveryand Improved Drilling Methods, Tulsa, OK, Aug.- Sep. 1977.
Bennett, F., and Geoghegan, J.G. 1990. "Monitoringthe Performance ofPembina Nisku MiscibleFloods." Paper presented at Petroleum Society ofCIMISPE International Technical Meeting,Calgary, AB; Preprints V2, CIM/SPE 90-73, Jun.1990.
Bilozer, D.E., and Frydl, P.M. 1989. "ReservoirDescription and Performance Analysis of aMature Miscible Flood in Rainbow Field,Canada." Paper presented at 64th Annual SPETechnical Conference, San Antonio, TX; Proc.,G-EOR/General Petroleum Engineering, SPE19656, Oct. 1989.
Chen, S.M., Olynyk, L, and Asgarpour, S.S. 1986."Effect of Multiple-Contact Miscibility on SlugSize Determination." JCPT, May-Jun. 1986.
Claridge,.E.L. 1973. "A Trapping Hele-Shaw Modelfor Miscible-Immiscible Flooding Studies." SPEJ,Oct. 1973, Vol. 1339, pp. 255-261.
Craig, F.F. 1971. The Reservoir Engineering AspectsofWaterflooding. SPE Monograph Series, Dallas,TX,No.3.
Dawson, A.G., Buskirk, D.L., and Jackson, D.D.1989. "Impact of Solvent Injection Strategy AndReservoir Description on Hydrocarbon MiscibleEaR for the Prudhoe Bay Unit, Alaska." Paperpresented at 64th Annual SPE TechnicalConference, San Antonio, TX; Proc., G-EOR/General Petroleum Engineering, SPE-19657, Oct.1989.
2
ENHANCED RECOVERY BYHYDROCARBON MISCIBLE FLOODING
Deans, H.A. and Majoros, S. 1980. "The Single-WellChemical Tracer Method for Measuring ResidualOil Saturation." Final Report for US DOE,Contract No. DE-AS 19-79BC20006 performed atRice University, Houston, TX, Oct. 1980.
Dyes, A.B., Caudle, RH., and Erikson, R.A. 1954."Oil Production After Breakthrough - AsInfluenced by Mobility Ratio." Trans., AIME.Vol. 201, pp. 81-86.
Fong, D.K., Wong, F.Y., Nagel, R.G., and Peggs, J.K.1990. "Combining A Volumetric Model with aPseudo-Miscible Field Simulation to AchieveUniform Fluid Levelling in the Rainbow KegRiver "B" Pool." Petroleum Society ofCIMISPEInternational Technical Meeting, Calgary, AB,Jun. 1990.
Griffith, J.D., and Horne, A.L. 1975. "South SwanHills Solvent Flood." Proc, 9th World PetroleumCongress, Tokyo, Japan, Vol. 4,1975.
Habermann, R 1965. "The Efficiencies of MiscibleDisplacement as a Function of Mobility Ratio."Trans., AIME, Vol. 219, p. 264; MiscibleProcesses, Reprint Series, SPE, Dallas, TX, 1965,Vol. 8, pp. 205-214.
Jenkins, M.K. 1984. "An Analytical Model forWater/Gas Miscible Displacements." Presented at4th Symposium on EOR, Tulsa, OK, Apr. 1984,SPE/DOE 12632.
Kimbler, O.K., Caudle, RH., and Cooper, H.E. Jr.1969. "Areal Sweep-out Behaviour in a NineSpot Injection Pattern." JPT, Feb. 1969, pp.199-202; Trans., AIME, Vol. 231.
Koval, EJ. 1963. "A Method for Predicting thePerformance of Unstable Miscible Displacementin Heterogeneous Media." SPEJ, Jun. 1963, pp.145-154; Trans., AIME, Vol. 228.
Mahaffey, J.L., Rutherford, W.M., and Matthews,C.W. 1966. "Sweep Efficiency by MiscibleDisplacement in a Five-Spot." SPEJ, Mar. 1966,pp. 73-80; Trans., AIME, Vol. 237.
Mcintyre, FJ., See, D.L., Mallimes, R.M., Burger,D.H., and Tsang, P.W. 1991. "ProductionOptimization of a Horizontal Well in a VerticalHydrocarbon Miscible Flood Reservoir."Petroleum Society ofCIMIAOSTRA TechnicalConference, Banff, AB; Preprints V2, No. 91-68,1991.
Mukherjee, D. 1958. Internal File Note, Gulf CanadaResources Ltd., Calgary, AR
Okazawa, T., and Lai, F.S.Y. 1989. "VolumetricBalance Method - To Monitor Field Performanceof Gas Miscible Floods." 40th Annual PetroleumSociety of CIM Technical Meeting, Banff, AB;Preprints VI, No. 89-04-4, May 1989.
Okazawa, T., Bozac, P.G., Seto, A.C., and Howe,G.R. 1992. "An Analytical Software for PoolWide Performance Prediction ofEOR Processes."Paper presented at 43rd Annual Technical Meeting of the Petroleum Society ofCIM, Calgary,AB, CIM 92-89.
Patel, R.S., and Broomhall, R.W. 1992. "Use ofHorizontal Wells in Vertical' Miscible Floods,Pembina, Nisku, Alberta, Canada." 8th SPEIDOEEnhanced Oil Recovery Symposium, Tulsa, OK;Proc., VI, 1992, SPE/DOE-24124, Apr. 1992.
Pritchard, D.W.L., and Nieman, R.E. 1992."Improving Oil Recovery through WAG (WaterAlternating-Gas) Cycle Optimization in aGravity-Override-Dominated Miscible Flood."8th SPEIDOE Enhanced Oil RecoverySymposium, Tulsa, OK; Proc., V2, SPE/DOE24181, Apr. 1992.
Reinbold, E.W., Bokhari, S.W., Enger, S.R., Ma,T.D., and Renke, S.M. 1992. "Early Performanceand Evaluation of the Kuparuk HydrocarbonMiscible Flood." 67th Annual SPE TechnicalConference, Washington, D.C; Proc., ReservoirEng., SPE-24930, Oct. 1992.
Sorensen, L.E., and Griffith, J.D. 1988. "Evaluationof Solvent and Chase Gas Bank Sizes in the SouthSwan Hills Hydrocarbon Miscible Flood." 39thAnnual Petroleum Society of CIM1CGPA 2ndQuarterly Technical Meeting, Calgary, AB;Preprints V3, No. 88-39-100, Jun. 1988.
Stalkup, F.I. 1983. MiscibleDisplacement. SPEMonograph Series, Dallas, TX.
Stone, H.L. 1982. "Vertical Conformance in anAlternating Water-Miscible Gas Flood." Paperpresented at 57th Annual Fall Technical Meeting,SPE ofAIME, New Orleans, LA, Sep. 1982, SPE11130.
Tiffin, D.L. 1982. "Effects of Mobile Water onMultiple-Contact Miscible Gas Displacement."Paper presented at the SPE/DOE Enhanced OilRecovery Symposium, Tulsa, OK, Apr. 1982,SPE/DOE 10687.
181
-I
Todd, M.R., and Longstaff, W.J. 1972. "TheDevelopment, Testing, and Application of aNumerical Simulator for Predicting MiscibleFlood Performance." 1PT, Jul. 1972, pp. 874-82.
182
DETERMINATION OF OIL AND GASRESERVES
Wood, K.N., Cornish, R.O., Lal, F.S., Taylor, H.O.,and Woodford, R.B. 1990. "SolventTracersandthe Judy CreekHydrocarbon Miscible Flood."Petroleum Societyof CIM/SPE InternationalTechnical Meeting, Calgary, AB; Preprints V2,No. CIM/SPE 90-79, Jun. 1990.
....""'"
c
Chapter 13
ENHANCED RECOVERYBY IMMISCIBLE GAS INJECTION
13.1 INTRODUCTIONImmiscible' gas injection (gasflood) was first used toenhance oil recovery before the turn of the century andactually predates the use of water as an injectant. Aswith water, gases are used for both their pressure maintenance and their fluid displacement properties. In thecase ofgas injection, however, displacement takes a decidedly secondary role. A further difference can also beattributed to the fact that gases can have a substantialdegree of mutual solubility with crude oil and hencecan, to some extent, do the following:
• Vapourize various oil components
• Cause contacted oil to expand and mobilize
• Reduce viscosity of contacted oil
All three phenomena may enhance oil recovery beyondthat expected from a simple gas-liquid displacementprocess.
The gasflood injectant that is most commonly used ishydrocarbon-based, not necessarily due to its effectiveness, but rather to its availability and relatively low cost.Other gases that have been or could be successfullyemployed include (but are not limited to) nitrogen (N,),carbon dioxide (CO,), sulphur gases, flue gas, and air.
Despite the fact that the performance ofa gas injectionscheme can, under some circumstances, compete withor even surpass that of a waterflood, the use of gasflooding has diminished with time particularly duringthe last 25 years, when natural gas became an increasingly valuable commodity. In addition to the cost offoregone gas sales, high-pressure gas injection schemesalso carry added costs associated with high pressureinjection flowlines, compression, reprocessing, andpossibly the purchase of gas external to the project.These additional costs often make waterflooding or evenprimary recovery more economic than gasflooding.
• Immiscible refers to gas and oil existingas separate phasesin all concentrations everywhere withinthe system.
Notable exceptions can occur, however, when thesubject reservoir has any of the following:
• A sizable original gas cap
• A remote location where gas sales are not feasible
• A location that lacks a suitable or economicallyattractive water source
• Extremely low permeabilities, making waterflooding impractical
• Water-sensitive minerals
• Extreme attic oil losses (e.g., due to adverse coningcharacteristics)
• Substantial vertical relief
If any of these conditions are present, the feasibilityof employing a gasflood for enhancing the primaryrecovery mechanism should be considered.
13.2 TYPES OF FLOODSGasfloods have historically been categorized as beingone of two types according to where the gas is injectedin relation to the oil zone. Figure 13.2-1 schematicallyillustrates an "external" or updip injection scheme, anda "dispersed" or pattern-style flood. Although both typesare subject to similar physical processes and principles,they have by design, different primary gas flow directions (vertical for external; horizontal for dispersed).This can cause them to have very different performancecharacteristics and hence different prediction techniquerequirements.
External injection schemes are more popular andeffective as they are often used to assist a primary gascap drive, and because they take advantage of the natural phenomenon of gravity segregation or "override,"a process that is detrimental to the effectiveness ofhorizontally flooding with gas. External gravitystable injection projects have exhibited incrementalrecoveries as high as 40-50 percent.
Dispersed gas injection schemes are relatively rare, andwhen used in the absence of a gravity stable process,
183
DETERMINATION OF OIL AND GASRESERVES
Oil GasProduction Injection
EXTERNAL GAS INJECTION
OilProduction
GasInjection
- --Oil
Production
DISPERSED GAS INJECTION
GasInjection
OilProduction
--~---------------------------------
Figure 13.2-1 Gas Injection
they have historically shown themselves to be onlymarginally effective, with typical recoveries of only afew percent. This is due to the adverse impact of thestrong tendency for gas to find the path of leastresistance, either vertically (override) or areally (fingering). Furthermore this tendency is considerablyaggravated by the existence of almost ever-presentgeological heterogeneities.
In addition to this distinction, further subsets can occurdue to the degree ofpressure maintenance invoked (fullor partial) and, in the case of vertical schemes, the existence or nonexistence of a gas cap. Combining bothofthese variables results in vertical floods in which theoriginal gas-oil contact will (I) advance, resulting in atrue gas displacement process; (2) remain stable, allowing for some other mechanism to be used to deplete the
184
reservoir; or (3) recede at a controlled rate with someother mechanism employed to deplete the reservoir.
It should be noted that for a vertical gas displacementconfiguration, gas need not necessarily be injecteddirectly into the gas cap or even the structurally highestpoint as the gas will migrate to these locations of itsown accord. This is a particularly useful attribute whenflooding dipping reservoirs where considerations suchas surface topography may limit access to the structuralhighs.
13.3 PERFORMANCE PREDICTIONThe flood stage at which one of five basic predictiontechniques is most appropriate is treated in considerable detail in Chapter II. The reader is encouragedto review this passage for the rationale behind therecommended methods shown in Table 13.3-1.
___________________a
ENHANCED RECOVERY BYIMMISCIBLE GASINJECTION
Table 13.3-1 Recommended PerformancePrediction Methods
1 A concise set of examples utilizing classicalanalyticalprediction techniques for both external and dispersedinjection witheither complete or partial pressuremaintenancecan be found in Roebuck (1987).
2 If phase behavior effects playa significant role,compositional numerical simulation must be givenseriousconsideration as thepreferred prediction technique.
A word of caution in the use of these recommendationsis warranted: regardlessofthe depletionstage and techniqueemployed, it iswisewheneverpossible tousemorethan one procedure as a cross-check or validationprocess.
When gas injection is used primarily for pressuremaintenance anddisplacement," production performanceprediction methods areeitherforexternal injection methods, which are an extension of gas cap drive predictiontechniques; or for dispersed injection schemes, whicharean extension of solutiongasdrivemethods withmanyelements similar to horizontal waterfloods.
Due to these and previously noted similarities, thevarious analysis techniques will not be described in ascompletea manner as they are elsewhere.To avoid repetition, only those aspects that need to be emphasizedor that are unique to gasflooding are described here.
13.3.1 External Injection SchemesAs noted in Chapter 9, the preferred techniquesinvolvethe use of material balance or numerical simulationmethods. The analytical Welge (1952) method is alsorecommended as a shortcut approach. Further to this,however, often it is important to include the effects ofgravitydrainage as reportedby ShreveandWelch(1956)and Craig et al. (1957).
If decline analysis techniques are to be used for performance prediction purposes, it should be noted thatgas-drive-only reservoirs, after an initial period ofsustained oil production, often exhibit harmonic declines; the initial rapid decline is caused by the adverse
Stage
Exploration/discoveryDelineationthrough
early lifeMiddle through
late life
Prediction Technique
Analogies, volumetricsAnalogies,numerical simulation,volumetrics, analytical methodsI
Numerical simulation.decline analysis
mobilityratio, and the long oil-production tail is causedby gravity drainage.
13.3.2 Dispersed Gas Injection SchemesAs with external gas injection projects, the preferredmethodfor estimatingrecovery and future performanceis numerical simulation-not an easy task as the rapidity and degree of gas break-through are often difficultto simulate. This is a direct consequence of the low viscosity and density of the gas, and its nonwettingcharacteristics, which combine to generate very highmobility ratios (50 to 100 times that of water) and, as aresult, poor sweep efficiencies.
Should the lack of time or data not permit a simulationto be undertaken, the analyticalPirson (1958) techniquefor solution gas drive can be utilized, as can Craig'shorizontal displacement technique (Craig et al., 1955).These methods are discussed and recommended inChapters 9 and II, respectively.
The volumetric analysis technique described inSection 11.5is also applicable, but particular care mustbepaidto theestimation of horizontaland verticalsweepefficiencies. In addition to the expected mobility-ratioinduced reduction in areal sweep (Dyes et aI., 1954),and the layering-induced reduction in vertical sweep(Stiles, 1949),furtherefficiencylosses can occurdue toboth override and fingering. Analogous reservoirs andmechanistic numerical models may be used to evaluatethe significance of these two phenomena.
ReferencesCraig, F.F. Jr., Geffen, T.M., and Morse, RA. 1955.
"Oil Recovery Performance of Pattern Gas orWater InjectionOperations from Model Tests."JPT, Jan. 1955,pp. 7-14; Trans., AIME, Vol.204.
Craig, F.F. Jr., Sanderlin, J.L., Moore, D.W., andGeffen, T.M. 1957."A Laboratory Study ofGravity Segregation in Frontal Drives." JPT, Oct.1957,pp. 275-81; Trans., AIME, Vol. 210.
Dyes, A.B., Caudle RH., and Erikson, R.A. 1954."Oil Productionafter Breakthrough as Influencedby MobilityRatio." JPT, Apr. 1954,pp. 27-32;Trans., AIME, Vol. 201.
Pirson, SJ. 1958. Oil Reservoir Engineering.McGraw-HiIl Book Co. Inc., New York, NY,pp. 484-532.
Roebuck, J.F. Jr. 1987."SPE Petroleum EngineeringHandbook." SPE of AIME, Chapter 43, AppendixA, pp. 10-13.
185
ShreveD.R., and Welch, L.W. Jr. 1956. "Gas Driveand GravityDrainage for Pressure MaintenanceOperations." JPT, Jun. 1956, pp. 136-43; Trans.,AIME, Vol. 207.
Stiles,W.E. 1949. "Use ofPerrneability Distributionin Water Flood Calculations." Trans., AIME, Vol.186,pp. 9-13.
186
DETERMINATION OF OIL AND GASRESERVES
Welge HoI. 1952. "A SimplifiedMethod forComputing Oil Recovery by Gas or Water Drive."Trans., AIME, Vol. 195, pp. 91-98.
s
Chapter 14
ENHANCED RECOVERYBY THERMAL STIMULATION
14.1 INTRODUCTIONThe thermal recovery processes that have been usedextensively for the recovery of heavy oil and bitumenfrom the oil sands have met with mixed success.
The term "heavy oil" is used to designate crude oilshaving an API gravity range of IS to 25 degrees. Heavyoil is literally heavier, thicker and slower to pour thanthe conventional light and medium crudes. Heavy oil,however, is relatively mobile at reservoir conditions andcan be successfully produced by primary recovery methods. Thermal recovery processes are then used to furtherincrease the recovery of heavy oil.
The bitumen found in the oil sands deposits is a viscousmixture of hydrocarbons with an API gravity of lessthan 15 degrees and a viscosity of several thousandcentipoise at room temperature. Thus, bitumen is noteconomically recoverable in its natural state by conventional primary or secondary recovery methods.
The ultimate objective of any thermal process is toimprove the mobility ofthe crude by reducing its viscosity through the introduction of heat into the reservoir.In addition, steam pressure and thermal expansion alsoenhance the driving forces present in the reservoir:gravity drainage, solution gas drive, and reservoircompaction. The following are the thermal processesmost commonly used for the recovery ofheavy oil andbitumen:
• Cyclic steam stimulation
• Steam flood
• In situ combustion
• Electromagnetic oil heating
These are discussed in the sections that follow.
14.2 CYCLIC STEAM STIMULATIONCyclic steam stimulation is probably the most widelyused thermal recovery process at the present time. Thepopularity of this process is mainly due to its relativeease of application, the low initial capital required,
and the quick return on investment. The ultimate oilrecovery from this process (15·20 percent) is generallymuch lower than recovery from steam flood (20·50percent). However, most steam stimulation processesmay be converted to steam flood once inter-well heatcommunication has been established.
Cyclic steam stimulation is a single well process withinjection and production carried out at the same well.Steam is injected into the well for a certain length oftime, usually at a rate and steam quality that are relatively constant (60.80 percent cold water equivalent atwellhead). Generally, the steam injection rate is themaximum rate obtainable at bottom-hole pressures below the formation fracture pressure. The bottom-holesteam quality and pressure may be predicted usingwellbore models ofthe type discussed by Fontanilla andAziz (1982) and others (Farouq Ali, 1981; Durrant andThambynayagam, 1980; Willhite, 1966).
The well is allowed to soak for a period (of at least afew days) that depends on the volume ofsteam injected;soaking allows the injected steam to condense and distribute the heat more evenly. At the end of the soakperiod, the well is put on production. The reservoir pressure during the initial production period is very high,and fluids are able to flow back under the reservoir pressure alone. The production during this flowback periodconsists mostly of hot water, flashed steam, formationgases, and traces ofoil. Upon completion ofthe flowbackperiod, the reservoir pressure will have dropped and abottom-hole pump will be required to lift the reservoirfluids.
These injection-production cycles are repeated until theoil production rate drops below the economic limit. Atthis stage, other thermal recovery methods such as steamflooding or in situ combustion may be considered.
14.2.1 Process VariationThe cyclic steam stimulation process is sometimesmodified in order to improve its sweep and thermal
187
> 10
400 to 1000
> 30
250 to 1000
10 to 34
efficiencies. Laboratory studies and field tests have beenconducted to investigate the addition of chemicals orgases to the injected steam. These include surfactants,carbon dioxide, ethane, naphtha, methane, propane,butane, heptane, natural gas, air, and oxygen (Kular etal., 1989; Ploeg and Duerkson, 1985; Ivory et al., 1991;Pursley, 1974; Waxman et aI., 1980). The following arethe major mechanisms by which steam additivesimprove oil recovery:
I. The diversion ofsteam to higher oil saturation zonesimproves sweep efficiency.
2. The reduction in surface tension ofthe oil improvesdisplacement efficiency.
3. Gas expansion and flashing of solution gasesprovide an additional driving force in the reservoir.
Although steam additives seem to offer some potentialunder certain reservoir and operating conditions, further research and testing are needed to improve therecovery of the cyclic steam stimulation process.
14.2.2 Field ExamplesThe following are some of the steam stimulation andsteam flood projects in Canada and the United States:
• Shell Peace River Thermal Pilot (Waxman et aI.,1980)
• Husky Paris Valley Cyclic Gas-Steam Pilot (Meldauet aI., 1981)
• Petro-Canada PCEl Steam Stimulation Project(Towson and Khallad, 1991)
• Amoco Gregoire Lake In Situ Steam Pilot (Kular etaI., 1989)
• Chevron Keen River Steamflood Project (Oglesby etal., 1982)
• Esso Cold Lake Thermal Project (Mainland and Lo,1983)
• Athabasca Oil Sands Project
14.2.3 Recovery MechanismsCyclic steam stimulation and steam flood recoverymechanisms are as follows:
I. Reduction ofoil viscosity due to increased temperature
2. Steam pressure providing the drive energy for oilto flow towards the producing well
3. Gravity drainage of the liquid phases (Denbina etaI., 1987; Cardwell and Parson, 1949; Farouq Ali,1982)
188
DETERMINATION OFOILANDGASRESERVES
4. Thermal expansion ofoil providing energy for fluidflow (Denbina et aI., 1987)
5. Reservoir compaction maintaining reservoirpressure (Denbina et al., 1987)
6. Steam distillation causing the lighter hydrocarbonsto separate from the heavy ends and form amiscible oil bank ahead ofthe steam front
14.2.4 Design ConsiderationsScreening guidelines have been developed by manyresearchers (Adams and Khan, 1969; Belyea, 1956;Boberg and Lantz, 1966; Buckles, 1979; Bums, 1969;Crawford, 1971; Doscher, 1966; Gontijo and Aziz, 1984;Prats, 1978; Shepherd, 1979; Williams et aI., 1980) inorder to define the reservoir and fluid properties underwhich steam stimulation processes are most likely to beeconomical. The following guidelines are based on theresults of some successful projects:
Formation thickness (m)
Depth (m)
Porosity (% PV)
Permeability (mD)
API gravity (degrees)
Oil viscosity at reservoirconditions (mPa.s) < 15,000
Initial oil saturation (% PV) > 40
The mechanisms involved in a steam stimulationprocess are very complex. Methods used to predict performance are only approximate at best because of themany simplifying assumptions that have to be made.Nevertheless, there are certain prominent factors thatmay affect the oil recovery in a steam stimulation process: the volume of steam injected, steam quality,injection pressure, and reservoir thickness. The amountofheat injected determines the volume ofheated reservoir and ultimately the percentage of oil recovery. Athick pay zone is also desirable for effective gravitydrainage (Butler et aI., 1981; Dykstra, 1978). The depthofthe reservoir is another important factor. Deep reservoirs (2000-3000 m) may not be suitable for steamstimulation, because of the large heat losses from thewellbore. On the other hand, shallow reservoirs (200250 m) may not allow high enough injection pressuresto maintain reasonable steam injection rates andprovide sufficiently high steam temperatures for thereduction of oil viscosity.
The well patterns most commonly used for the cyclicsteam stimulation process are the 5-spot and the 7-spot,which allow the conversion ofcyclic steam stimulation
.,-1C.', !
I
_______________________a
> 50
6 to 20
100 to 500
>30
>500
< 25
5000 to I 000 000
ENHANCED RECOVERY BYTHERMAL STIMULATION
to steam flood later if desired. Single weIl tests(Dillabough and Prats, 1974) are generally conductedto obtain preliminary data on recovery potential, operating costs, and other design factors. Well spacing mayvary from 0.4 to 2 hectares. Infill drilling has also beenused to exploit developed heat zones and achieve earlyinter-well communication. Another common practice incommercial projects is to drill clusters ofdeviated wellsfrom a single well pad in order to optimize the use ofland and surface facilities.
14.3 STEAM FLOODING. In the steam flood process, steam is injected into the
reservoir on a pattern basis, much like a waterflood.Various well patterns, including the 5-spot and 7-spot,have been employed. The injected steam reduces theviscosity of the oil and provides the driving forcerequired to move the oil towards the producing wells.
In the application ofthe steam flood process to oil sandsdeposits, it is essential to achieve flow communicationbetween the injector well and the producers prior toflooding. Frequently, the wells are produced by steamstimulation for a few cycles until communicationbetween wells has been established, and then steamflooding is started. Other naturally existing communication paths in the oil sands deposits, such as bottomwater and high permeability layers, may provide valuable means of improving injectivity for effectivereservoir heating. Lack ofsteam injectivity may requirehydraulic fracturing ofthe wells before steaming.
Steam flooding with continuous steam injection canrecover significantly more oil (up to 50 percent) thansteam stimulation alone (10-25 percent). However, thereare disadvantages associated with steam flooding. It generally results in higher steam-oil ratios than cyclic steamstimulation because of the much larger volume of reservoir that must be heated before any significant oilrecovery is realized. The amount of reservoir heatingrequired in cyclic steam stimulation is confined to thenear-wellbore region, and oil production is thereforerealized much earlier.
14.3.1 Process VariationA number ofadditives have been injected with steam toimprove the oil recovery by the steam flood process.These additives improve the thermal and sweep efficiencies of the injected steam by diverting it towardsthe colder regions of the reservoir.
Patzek (1988) and others (Kular et al., 1989; Ploegand Duerkson, 1985; Sander, 1991; Suffridge, 1991;Butler, 1986) have reported mixed success using a
variety of surfactants. CommerciaIly availablesurfactants are now chemically stable at temperaturesup to 300°C. However, the in situ behaviour offoam isstill not fully understood, and field tests (Kular et al.,1989; Patzek, 1988; Sander, 1991) indicate that its propagation in the porous medium is very slow. In most casesthe cost of surfactants offsets the possible benefits.
Field pilots have been conducted to test the injection ofgas atthe boundaries ofthe steam zone to improve steamconfinement and to maintain the pressure in the steamzone. The injection of air with steam provides anotherless expensive alternative to the use of surfactants. Thesteam-airprocess works on the assumption that low temperature oxidation produces coke particles that tend toplug the pore throats and provide resistance to flow(Ivory et al., 1991). Thus, steam is diverted to other partsof the reservoir, and the result is an improved sweepefficiency.
14.3.2 Design ConsiderationsThe following guidelines may be used to screenreservoirs for potential steam flood applications.However, these guidelines are only approximate asgeological heterogeneities specific to each reservoircannot be accounted for.
Formation thickness (m)
Depth (m)
Porosity (% PV)
Permeability (mD)
API oil gravity
Reservoir oil viscosity (mPa.s)
Initial oil saturation (% PV)
Recovery with steam flood is approximately 40 to 50percent ofthe original oil in place, with steam-oil ratiosin the range of 5 to 7. The steam-oil ratios are dependent upon the nature of the reservoir. Very deepreservoirs (1200-1500 m) may be impractical for steamflooding due to the excessive heat losses in the wellboreand the very high steam pressure required at the surface. The reservoir should be at least 6 to 10 metresthick to minimize heat losses to the overburden andunderburden. Successful steam flood processes are generally in shallow (300 m) reservoirs having reasonablyhigh porosity (30-40 percent pore volume), permeability less than I darcy, and oil saturation of 85-90 percentpore volume.
Injection rates for steam flood are generally designed tocompensate for heat losses to the adjacent formationswhile providing effective heating of the reservoir.
189
During pilot testing, steam injection rates should alsocompensate for the heat flowing out of the pattern dueto the lack of steam confinement. Steam flood processesare usuaIly started at high injection rates, which are lateroptimized once steam gravity override or steam breakthrough occurs (Myhill and Stegeimeier, 1978; Chu andTrimble, 1975; Ali and Meldau, 1979; Bursell andPittman, 1975; Vogel, 1982; Belvins, 1978; Stokes,1978; Van Dijk, 1968). Where fluid communicationshave already been developed through cyclic stimulation of the wells, injection rates can be optimized atstart-up.
However, many factors must be taken into account indesigning a steam flood process: the mineral content ofreservoir rock, the availability of fuel and water, theanalysis of crude oil, sand production, water disposalwells, water treating requirements, production facilitiesto handle hot fluids, emulsion treating, and transportation of heavy crude.
14.4 CAUSES OF FAILURE FORCYCLIC STEAM STIMULATIONAND STEAM FLOOD PROCESSES
The following reservoir and operating limitations maycause the cyclic steam stimulation and steam floodprocesses to become uneconomical:
Lack of Injectivity. Some oil sands deposits havesuch a high saturation of bitumen that the steam hasgreat difficulty penetrating the highly viscous oil bank.As a result, the steam tends to channel to the poorer partof the formation, which has lower oil saturation andhigher water saturation. Clay swelling due to incompatibility between the injected water and the formationwater may also limit steam injectivity.
Bottom Water. The term "bottom water" refers to sandlayers containing mobile water that account for morethan 20 percent of the formation thickness. Such bottom-water layers are detrimental to the cyclic steamstimulation process. Due to the much higher mobilityof steam in the water zone, most of the injected steamwill be lost to the water zone, resulting in very poorthermal efficiency. During the production cycle, the coldwater is much more mobile than the bitumen and willtend to be produced first. In addition, the cold waterwill tend to cool the oil around the wellbore and reducethe volume of the heated zone.
On the other hand, a thin bottom-water sand can be usedeffectively to heat the formation. For example, the steamstimulation process is very successful at the Peace RiverPilot (Waxman et aI., 1980) where the oil sand deposit
190
DETERMINATION OF OIL ANDGASRESERVES
consists of a thin highly water-saturated zone near thebottom of the formation and a fining upward sandsequence. This results in good thermal efficiency andhigh oil production rates.
Gas Cap. The presence of a gas cap will tend tochannel injected steam to the top of the formation, resulting in excess heat loss and poor thermal efficiency.However, the extent of the gas cap is a critical factorespecially if gravity drainage is the predominan;production mechanism (Kular et a!., 1989). Blockingagents may be used to improve the vertical sweepefficiency (Sander, 1991).
Shale. The presence of a substantial and impermeableshale layer near the middle of the formation mayprevent the rise of the steam zone, resulting in poorvolumetric sweep and heat efficiencies.
Thin Formation. Very thin formations may result inexcessive heat loss to the overburden and underburden,leading to poor heat efficiency.
Lack of Steam Confinement. If the oil sand depositcontains natural fractures (e.g., the Carbonate Trend innorthern Alberta), a significant fraction of the injectedsteam may be lost. Poor steam confinement may significantly reduce the energy available in the heated zoneto drive the fluids towards the producing well.
Low Porosity and Permeability. Some heavy oildeposits such as oil shales have such low porosity (lessthan 20 percent by volume) and low permeability (lessthan 100 mD) that the steam injectivity may be seriously limited. Hydraulic fracturing is required to exploitsuch heavy oil deposits (Kular and Chinna, 1988).
Poor Reservoir. Due to the high initial capital investment and operating costs of the steam processes,reservoirs with less than 40 percent oil saturation arenot likely to be economically recoverable by theseprocesses. _.
Shallow Reservoirs. Shallow reservoirs with insufficient overburden will tend to limit the steam injectionpressure, and thus reduce oil productivity.
Deep Reservoirs. Very deep reservoirs have such highreservoir static pressure that the steam injectivity maybe limited. The oil sand deposits in Alberta generallyrequire fracturing before steam can be injected at a reasonable rate. A deep reservoir means a higher steaminjection pressure, which requires the added expense ofhigh pressure steam generators. Also, deep reservoirscause excessive heat losses from the wellbore, resultingin the injection ofpoor quality steam.
______________________1
ENHANCED RECOVERY BYTHERMAL STIMULATION
Applying D'Arcy's law for conditions of gravitydrainage, the rate of oil displacement, qo' in m3/d fromthe steam zone may be written as:
(2)
(4)
(5)
(6)
A(t) = (HiMrhD) f(x)4Kob~T
,2 2x If(x) =e (erfcx) +-
.,fit
2 x 2
erfcx = I - erfx = I -- Ie·' dP.,fit,
where A(t) = area of steam zone (rn-)x = dimensionless parameter
[Hi<P(SOi-SO,) ] (,2 C )qo = e errcxMr~T
where <P = porosity (fraction)So; = initial oil saturation (fraction)Sor = residual oil saturation (fraction)~T = temperature difference between steam
and initial reservoirtemperature (T, - To) (0C)
Ti = injection temperature eC)To = initial formation temperature (0C)erf = error function
K,b = overburden thermal conductivity(kJ/m/d/°C)
~T = injection temperature minus initialformation temperature (0C)
D = overburden thermal diffusivity(m2fh)
t = time (d)P = time (d)A = area of steam zone (m-)
M, = volumetric heat capacity of formation(kJ/m3jOC)
h = pay thickness (m)
Marx and Langenheim's solution to Equation (I) is givenin Equation (2):
= 2f'[ Kob~T J(dA) dP +M,hdT dA (I)o "ltD(t-P) dP dt
where Hi = constant heat injection rate (kJ/d)
Hi = heat loss + heat accumulation
14.5 FORECASTING MODELSA number of options are available to engineers forpredicting the performance of thermal recoveryprocesses. These include numerical simulation models,analytical models and simple correlation equations.Ideally, reservoir simulation models will provide themost accurate answer. However, these models cannotbe utilized in cases where only limited data is available.Time and, to some extent, cost limitations may also workagainst the use of numerical simulation models. As analternative, analytical models may be used quite effectively for process design and forecasting oil recovery.
The analytical models for steam recovery processes aregenerally divided into three types. Figure 14.5-1 illustrates the distribution of fluids as assumed in theseanalytical gravity drainage models.
Frontal Displacement Model. This model assumes acylindrical steam zone, with displacement of oil overthe full thickness of the oil zone.
Steam Overlay Model. This model assumes that thesteam lies directly over the oil zone, and the principaldirection ofsteam zone growth is vertically downwards.
Conical Steam Zone Model. This model assumes thatthe steam zone has the shape of an inverted cone. Thesteam not only rises upward but also expands outwarddue to heat conduction and the drainage of the heatedoil toward the wellbore.
Some of the most commonly used models for predicting the production rates of the cyclic steam stimulationand steam flood processes include those by Marx andLangenheim (1959), Myhill and Stegeimeier (1978),Vogel (1982), Butler (1986) and Butler et al. (1981).The development and applications of these models arepresented in the following subsections.
14.5.1 Marx and Langenheim ModelMarx and Langenheim developed a frontal displacementmodel in which the growth of the steam zone dependson the rate of steam injection and the loss of heat tothe overburden and underburden. The heat balanceequation used in this model is written as:
191
DETERMINATION OF OIL AND GASRESERVES
::::::: Cold Oil·-------------------~-----
Zone
Frontal Displacement Model
----------------------------------------------------------
::::::::::::::: Cold Oil Zone :::::::::::::::::::::::::::
.,' .. Steam Zone:"T
Steam Overlay Model
-------~-----
.-~----- -'.
-------- ---
0,' --::.::, ..0° ,~ -::- <:I _
S". t· e~('('\ · c a,i.. :: - - - -c;L 0 __ -_-
"',one e ;-::----C,/.- P, 0',- - _ - -
.: ~.I - _-_,
.~/-:.:: =--~\O 0\\::'&~-:::-:. z.One. J'-_-_ _-
<:- .-§,'-::~- --::---"'("-,,.- ---- -v-z>: _-::--
e 0/1,.::: _::.:: -
..- -Q fl--c
.:.:
Conical Steam Zone Model
~' " ......, ,, ,, ,, ,, ,, ,, ,, ,
\ 0;
_\ Q o'__ - _~oo
- _-::_.-.. °0
:: - :: - -::~ o- -__-_- \,,0---- --~_ - __ - _ - _'0 0 0 ,.
----:::.-- _"°0-- ----- _-\ e_- _- _-- _-\0 0-- _- -- _-"\00-::--::.--_-::~o 0- -_-_::t..-;:'-::::::::--- - -::::--
,,,,,,,,,,,,,,,,,,
Source: After Gontlio and Azlz, 1984.
Figure 14.5-1 Types of Analytical Gravity Drainage Models
192
c
ENHANCED RECOVERY BYTHERMAL STIMULATION
s, = 1. (e·n erfc-F,; +2~ - 1) (7)tn n
The dimensionless time parameter, tD' is given by:
erfc = complementary error function(Abramowitz and Stegun, 1964)
14.5.2 Myhill and Stegeimeier ModelMyhill and Stegeimeier presented an analytical modelusing a simple energy balance to calculate the steamzone size. This energy balance approach is based on theassumption that the oil ultimately produced from bothsteam stimulation and steam flood processes is proportional to the steam zone volume. Other assumptionsmade in developing the model are that the steam zone iscylindrical in shape, and that the thermal properties inthe reservoir, the heat losses, and the steam injectionrates are constant. It is also assumed that the oil-steamratios of any thermal process can be expressed in termsof a thermal efficiency term, Ehs, that is defined as theratio of heat remaining in the steam zone to the totalheat injected (Figure 14.5-2).
(9)
t =D
35 040 kh,M,tyn
Z; (M I ) '
(8)
where khz = heat conductivity of steam zone(kJ/m/d/°C)
M2 = volumetric heat capacity of cap rock(kJ/m3/
0C)
t)TS = time of injection (years)Z, = gross thickness of reservoir (m)
M1 = average heat capacity of steam zone(kJlkg/°C)
Figure 14.5-2 is a graph of the thermal efficiency,Ehs, vs. the dimensionless time, tD' which can beused to estimate the thermal efficiency of the steamprocesses (Prats, 1986). The ratio, hD, oflatent heat tototal energy injected is given by:
f"L,h = ---:=.....:...-D CwLlT + 1
where fsd = downhole steam quality (fraction)L, = latent heat of vapourization of steam
(kJlkg)LlT = injection temperature minus initial
formation temperature (0C)
Ifthe thermal efficiency and enthalpy ratios are known,it is possible to calculate the maximum oil-steam ratio,OSR, using the following equation:
100100.1
-\ -
<,
""'"hD is the ratio of latent heat to
I\. '\ -, I::-.. total energy injected-, -, -,
I\- -, l-,
-, I'\.,~-, i'--
-, <,-:::: l-, 0.667-, .,f;o. ' I0.5
<,
,,~<,<,
r---...<;,o.~- <, ~- ~ <; r:::: ::::
--- 0.091 ---- --0
0.00.01
1.0
.~w
oj 0.8c:~E
'"c7J 0.6
'01>'cQ)
'0 0.4
ffi'iiiE~ 0.2I-
Snurce: After Prats, 1969.Dimensionless Time, tD
Figure 14.5-2 Thermal Efficiency of Steam Zone as a Function of the Dimensionless Time Parameter
193
DETERMINATION OFOILANDGASRESERVES
14.5.3 Vogel ModelVogel's steam overlay model is based on ultimate heatrequirements determined from simple two-dimensionalheat flow equations. The total heat requirement is equalto the sum of the heat lost from the reservoir, the heatconducted to the produced fluids, and the heat thatremains in the steam zone.
The heat requirement, Q,o,al' is given by:
where Pw = density ofwater (kg/m')C; = specific heat of water (kJ/kg/°C)ho = ratio oflatent heat to total energy
injected
~, = thermal efficiency (fraction)q> = porosity (fraction)
dS = difference between steam temperatureand initial reservoir temperature CC)
Z, = net thickness of reservoir (m)Z, = gross thickness of reservoir (m)
condensate and heated oil flow by gravity to a horizon_tal production well located at the bottom ofthe chamberand are removed continuously. The expression for theoil drainage rate, Q, is based on the gravity drainagetheory and is given by:
14.6 IN SITU COMBUSTIONPROCESSES
(I 2)my,
2q>S,kgo.hQ=2
where Q oil drainage rate (ml/d/m length ofhorizontal well)
q> = porosity (fraction)
So = initial oil saturation (fraction)k = effective permeability to oil (um")g = gravitation constant (9.81 m/s")a. = thermal diffusivity of reservoir
material (rnvd)h = pay zone thickness (m)m = bitumen viscosity exponent
(usually = 3)
v, = kinematic viscosity of oil at steamtemperature (m2/d)
(I 0)
PwCw(l + hD) E"q>dS (~,)OSR= I
M,
where AhPsC,x,
Q"", = Ah (p,C,)<lT + 2K,A<lT~ t + 2K,A<lT- fI1tet I "'Iitii;
(II)
= project area (m")= thickness of steam zone (m)= heat capacity (kJ/mlfOK)= thermal conductivity of overburden
(kJ/m/°K/d)= time (d)= thermal diffusivity of overburden
(m2/d)K2 = thermal conductivity of underburden
(kJ/m/°K/d)0. 2 = thermal diffusivity ofunderburden
(mvd)
14.5.4 Butler Model
The conical steam zone model developed by Butler(Butler et al., 1981; Romney et al., 1991; Dugdale, 1986)is based on the assumption of continuous steam injection into a growing steam-saturated volume or chamber.Steam flows to the boundary ofthe chamber, condenses,and gives up its heat to the surrounding oil sands. The
In a combustion process, air is injected into one welland the formation is ignited. As the burnt front movesthrough the reservoir, a portion of the bitumen is consumed as fuel and combustion gases and steam aregenerated. These hot fluids raise the temperature andreduce the viscosity ofthe bitumen, which is then driventowards the production wells.
In situ combustion projects in Canada and the UnitedStates include the following:
• PetroCanada Viking-Kinsella Wainwright B OxygenFireflood Pilot (Dugdale, 1986; Dugdale et al., 1985)
• Panf'anadian Countess Fireflood Pilot (Metwally,1991)
• BP Cold Lake Pressure-Up Blow-Down WetCombustion Pilot (Mehra, 1991)
• Murphy Eyehill In Situ Combustion Pilot(Farquharson and Thornton, 1985)
• Amoco Athabasca In Situ Combustion Project(Jenkins and Kirkpatrick, 1979)
• Mobil Kern County South Belridge In SituCombustion Project (Gates et al., 1978)
• Home Oil Silverdale Water Alternating Gas Project(Hanna, 1987)
194
- ..a
ENHANCED RECOVERY BY THERMAL STIMULATION
• Texaco Caddo Pine Island In Situ Combustion Pilot(Horne et al., 1979)
14.6.1 Recovery MechanismsThe following are the major recovery mechanisms ofthe in situ combustion process:
Oxidation of Crude. The temperature at whichoxidation takes place depends on the concentration ofoxygen. High-temperature oxidation uses up theoxygen and generates heat. Low-temperature oxidation promotes the formation of fuel and spontaneousignition.
Thermal Cracking. Thermal cracking or pyrolysis ofthe crude generates light hydrocarbons and leaves cokebehind as fuel.
Steam Distillation. Steam generated by oxidation at thecombustion front evaporates the light hydrocarbons fromthe crude. These are displaced ahead of the steam frontto form an oil bank.
Steam Drive. Steam provides the energy to drive theheated oil ahead of the combustion front.
Thermal Expansion. Thermal expansion of crude,combustion gases, and light hydrocarbons also providethe driving force to drive the heated oil towards theproduction well.
Gravity Override. Steam, combustion gases, and lighthydrocarbons are lighter than the crude oil and tend torise to the top of the formation, bypassing some of thecrude oil in the middle or lower part of the formation.
Viscosity Reduction. Heat generated by combustionraises the temperature ofthe formation and significantlyreduces the viscosity of the crude.
14.6.2 Process VariationsAlthough the in situ combustion process is moreenergy-efficient than cyclic steam stimulation or steamflood and can be used in thinner pay zones, the heatefficiency of the dry combustion process is still verylow. About 70 percent ofthe heat generated at the hightemperature combustion front is left in the burnt zone.The following modifications are required to improvethe heat efficiency of the dry combustion process:
Thermal Wave Process. This technique involves thedilution of the injected air with combustion flue gas toincrease the heat capacity of the injected air.
Combined Thermal Drive. This is a wet combustionprocess designed to improve the sweep efficiencyand reduce the volume of air required. It involves thesimultaneous injection of air and water and results in
lower air requirements and higher oil recovery. Fieldresults show that the simultaneous injection of air andwater is more effective than the injection of a slug ofwater following air injection. The most importantconsideration in this process is to ensure that sufficientwater is injectedfor conversion to steam without quenching the combustion. The required water-air ratio (WAR)for a given reservoir is calculated from a material andheat balance.
Combination of Forward Combustion and Waterflooding. In this process, referred to as COFCAW, thewater-air ratio is high enough to quench the combustion. Low temperatureoxidation occurs in the steam zoneto maintain the steam temperature.
Steam Stimulation Followed by Wet Combustion. Inreservoirs containing a very viscous crude oil (i.e., bitumen), the mobility of the crude is too low to alloweconomic production rates for the combustion process.Cyclic steam stimulation has been used in a numberof fields to increase the mobility of the crude, create acommunication path between wells and allow the combustion front to move towards the production well morerapidly.
Enriched Air Combustion Process. Oxygen-enrichedair and pure oxygen are being used in this process. Thefollowing are the potential advantages of using pureoxygen instead of air:
• High displacement rate
• Lower gas injection volumes resulting in feweroperating problems for the compressor
• Increased mobility of the cold oil due to the dissolu-tion of carbon dioxide in the oil
• Higher recovery factors
• Larger well spacing, which reduces the infill drilling
• Flammable produced gases may be separated andused as fuel
An alternative to this process is to gradually increasethe oxygen content of the air from about 30 percent to95 percent. Laboratory results show that the injectionof 99.5 percent oxygen should result in a combustiongas primarily composed of carbon dioxide. This mayreduce the oil viscosity and cause some swelling of thecrude.
14.6.3 Design ConsiderationsFactors influencingthe selection of well patterns includethe reservoir dip angle and the utilization of existingwells. Because of the high mobility of air compared tothat ofoil, usually a few injection wells are sufficient to
195
3 to 15
< 3500
> 35
> 100
10 to 35
< 10,000
> 10
Sand or sandstoneand carbonateswith high porosity,no gas cap orbottom water
sustain the fireflood with a large number ofproductionwells.
In situ combustion pilots usually experiment withdifferent well patterns and spacings. The inverted 9-spotpattern, inverted 7-spot pattern, confined 5-spot pattern,line drive, and single well injection have all been commonly used. For example, Amoco's in situ combustionpilot (Jenkins and Kirkpatrick, 1979) in Athabascastarted with a two-well test with a distance oDO m (100feet) between the wells. Then different well patterns,ranging from a 0.2 ha (1/2 acre) 5-spot to a 4 ha (10acre) 9-spot, and finally a 1 ha (2.5 acre) 5-spot, weretested.
The design criteria for in situ combustion processes areas follows:
Formation thickness (m)
Depth (m)
Porosity (% PV)
Permeability (mD)
Oil gravity ( degree API)
Initial oil viscosity (mPa.s)
Initial oil saturation atreservoir conditions (% PV)
Type of formation
14.6.4 Causes of FailureAn in situ combustion process may fail for any of thefollowing reasons:
1. Low oil saturation in the formation may not depositenough fuel to support combustion. Incompleteoxygen consumption due to the lack offuel or earlybreak-through of combustion gases at the production well may limit inflow into the wellbore andcause reduced pump efficiency.
2. Low air injectivity may be caused by a water zonenear the wellbore, formation plugging, or oil droplets present in the compressed air. Low permeabilityzones in the formation also cause problems in theremoval of the combustion gases, which consistmainly ofnitrogen and carbon dioxide.
3. Reservoir heterogeneities that cause channelling andleaking of the injected air from the burnt zone willresult in poor sweep efficiencies.
4. Low gravity oils characterized by high fuel contentmay require a large volume of air for combustion.
196
DETERMINATION OFOILANDGASRESERVES
5. Explosions could occur in injection lines, injectionwells, and air compressors. Tubulars may bedestroyed by high temperatures due to the breakthrough of fire front at the production well orbackburn at the injection well. Corrosion mayreduce the life ofpumps and surface facilities.
6. Tight emulsions are often created during in situcombustion. Emulsified fluids cause rod fall problems and high flowline pressure because of theirhigh viscosities. The operation of the skim tanksand separators may be affected because the tightemulsions are very difficult to break.
7. Sand production problems caused by large volumesof combustion gases may result in operating anderosion problems in pumps and surface equipment.Severe gas locking may also lead to dry strokingand will accelerate pump failure due to the lack oflubrication.
14.7 ELECTROMAGNETIC HEATINGTwo different methods of electrical stimulation havebeen field-tested in Canada. Both use the reservoir as aresistive element that heats up as electrical power is applied. This reduces the oil viscosity, thus improving oilproduction rates. In the first method (Romney et aI.,1991), electrical current at a frequency of 60 Hz is delivered from one well to another. In the second method,a single well acts as the electrical injector and groundreturn well. This model has been applied to a number offield tests both in Canada and worldwide, with varyingdegrees ofsuccess. The mechanics ofthe second methodrequire electrical current to be transmitted throughthe formation-pay zone and back up the productioncasing. Short-circuiting is prevented by using nonconductive materials on the casing and productionstrings. Romney et al. (1991) discusses the design ofsingle well electromagnetic stimulation in detail.
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Farouq Ali, S.M. 1981. "A Comprehensive WellboreSteam/Water Flow Model for Steam Injection andGeothermal Applications." SPEJ, Oct. 1981, pp.527-534.
---. 1982. "Elements of Heavy Oil Recovery."Course notes (copyright 1982), University ofAlberta, Edmonton, AB, pp. 47-60.
Farquharson, R.G., and Thornton, R.W. 1985."Lessons From Eyehill." Paper presented at theFirst Annual CIM Technical Meeting, SouthSaskatchewan Section, Regina, SK, Sep. 1985.
Fontanilla, J.P., and Aziz, K. 1982. "Prediction ofBottom-Hole Conditions for Wet Steam InjectionWells." JPT, Mar. 1982, pp. 80-88.
Gates, C.F., Jung, K.D., and Surface, R.A 1978. "InSitu Combustion in the Tulare Formation, SouthBelridge Field, Kern County, CA." JPT, May1978, pp. 798-802.
Gontijo, J.E., and Aziz, K. 1984. "A SimpleAnalytical Model For Simulating Heavy OilRecovery by Cyclic Steam in Pressure DepletedReservoirs." Paper presented at SPE AnnualTechnical Conference and Exhibition Houston, ,TX, Sep. 1984, SPE 13037.
197
Hanna, M. 1987. "The Silverdale Water AlternatingGas Project." Paper presented at the First AnnualCIM Technical Meeting, South SaskatchewanSection, Regina, SK, Oct. 1987.
Horne, J.S., Bousaid, I., Dore, T.L., and Smith, L.B.1979. "Initiation of an In situ Combustion Projectin a Thin Oil Column Underlain by Water." JPT,Oct. 1979, pp. 2233-2245.
Ivory, 1., Derocco, M., and Scott, K. 1991."Comprehensive Analysis of the Mechanisms bywhich Air Improves Bitumen Recovery in SteamInjection Processes." Paper presented at CIMConference, Banff, AB, Apr. 1991, CIM 91-106.
Jenkins, G.R., and Kirkpatrick, J.W. 1979. "TwentyYears' Operation of an In situ CombustionProject." JCPT, Jan-Mar. 1979, pp. 60-65.
Kular, G.S., and Chinna, H. 1988. "MultipleHydraulic Fracture Propagation in Oil Sands."Paper presented at SPE Rocky Mountain RegionalMeeting, Casper, WY, May 1988.
Kular, G.S., Lowe, K., and Coonibie, D. 1989. "FoamApplication in an Oil Sands Steam FloodProcess." Paper presented at 64th Annual SPETechnical Conference and Exhibition, SanAntonio, TX, Oct. 1989, SPE 19690.
Mainland, G.G., and Lo, H.Y. 1983. "TechnologyBasis for Commercial In situ Recovery of ColdLake Bitumen." Paper presented at II th WorldPetroleum Congress, London, UK, Aug. 1983.
Marx, 1.W., and Langenheim, R.W. 1959. "ReservoirHeating by Fluid Injection." Trans., AIME. Vol.216, p. 312.
Mehra, R.K. 1991. "Performance Analysis of In situCombustion Pilot Project." Paper presented atSPE International Thermal OperationsSymposium, Bakersfield, CA, Feb. 1991, SPE21537.
Meldau, R.F., Shipley, R.G., and Coats, K.H. 1981."Cyclic Gas/Steam Stimulation of Heavy-OilWells." JPT, Oct. 1981, pp. 1990.
Metwally, M. 1991. "Recovery Mechanisms:Fireflooding a High-Gravity Crude in aWaterflood Sandstone Reservoir, Countess Field,Alberta." Paper presented at SPE InternationalThermal Operations Symposium, Bakersfield,CA, Feb. 1991, SPE 21536.
198
DETERMINATION OFOILANDGASRESERVES
Myhill, N.A., and Stegeimeier, G.L. 1978. "SteamDrive Correlation and Prediction." JPT, Feb.1978, pp. 173-182.
Oglesby, K.D., Belvins, T.R., Rogers, E.E., andJohnson, W.M. 1982. "Status of the lO-PattemSteamflood, Kern River Field, CA." JPT, Oct.1982, p. 2251.
Patzek, T.W. 1988. "Kern River Steam Foam Pilots."Paper presented at SPEIDOE EOR Symposium,Tulsa, OK, Apr. 1988.
Ploeg, J.F., and Duerkson, J.H. 1985. "TwoSuccessful Steam/Foam Field Tests, Section 15Aand 26C, Midway Sunset Field." Paper presentedat SPE California Regional Meeting, Bakersfield,CA, Mar. 1985, SPE 13609.
Prats, M.A. 1969. "The Heat Efficiency ofThermalRecovery Processes." JPT, Mar. 1969, pp. 323332.
---. 1978. "Current Appraisal of Thermal Recovery." JPT, Aug. 1978, pp. 63-69.
-----.1986. ThermalRecovery.SPEMonograph, Vol. 7, pp. 43-50.
Pursley, SA 1974. "Experimental Studies ofThermalRecovery Processes." Paper presented at HeavyOil Symposium, Maracaibo, Venezuela, Jul.1974.
Romney, G.A., Wong, A., and McKibbon, 1.H. 1991."A Preview of Ari Electromagnetic HeatingProject." Paper presented at CIM AnnualMeeting, Banff, AB, Mar. 1991, CIM 91-109.
Sander, P.R. 1991 "Steam - Foam Diversion ProcessDevelopment to Overcome Steam Override inAthabasca." Paper presented at Annual SPEConference, Dallas, TX, Oct. 1991.
Shepherd, D.W. 1979. "Predicting Bitumen Recoveryfrom Steam Stimulation." World Oil, Sep. 1979,pp.68-72.
Stokes, D.D. 1978. "Steam Drive as a SupplementalRecovery Process in an Intermediate ViscosityReservoir, Mount Poso Field, CA." JPT, Jan.1978, pp. 125-131.
Suffridge, F.E. 1991. "Foam Performance UnderReservoir Conditions." Paper presented at SPEAnnual Conference, Dallas, TX, Oct. 1991.
Towson, D., and Khallad, A. 1991. "The PCEJ SteamStimulation Project." Paper presented at the CIM!AOSTRA Technical Conference in Banff, AB,Apr. 1991, CIM/AOSTRA 91-108.
g
ENHANCED RECOVERY BYTHERMAL STIMULATION
Van Dijk, C. 1968. "Steam Drive Project in theSchoone-beck Field, The Netherlands." JPT, Mar.1968,pp.295-302.
Vogel, J.V. 1982. "Simplified Heat Calculations forSteam Floods." Paper presented at 57th AnnualFall SPE Technical Conference, New Orleans,LA, SPE 11219.
Waxman, M.H., Closmann, PJ., and Deeds, C.T.1980. "Peace River Tar Flow Experiments UnderIn Situ Conditions." Paper presented at 55th SPEAIME Annual Fall Technical Conference andExhibition, Dallas, TX, Sep. 1980, SPE 951 I.
Williams, R.L., Brown, S.L., and Ramey, HJ. Jr.1980. "Economic Appraisal of Thermal DriveProjects - A New Approach." Paper presented atSPE Technical Conference and Exhibition,Dallas, TX, Sep. 1980, SPE 9358.
Willhite, G.P. 1966. "Overall Heat TransferCoefficients in Steam and Hot Water InjectionWells." Paper presented at Rocky Mountain SPERegional Meeting, Denver, CO, May 1966, SPE1449.
199
Chapter 15
ENHANCED RECOVERYBY CARBON DIOXIDE FLOODING
15.1 INTRODUCTIONCarbon dioxide flooding, in both the miscible andimmiscible modes, is one of the most widely usedenhanced oil recovery techniques today. There are overforty carbon dioxide floods in operation throughout theworld. In Canada, several pilot and experimental floodshave been tried or are currently in operation. In addition, single-well "huffand puff' stimulations have beentried in various fields. Carbon dioxide flooding has nowbeen proven in both the laboratory and the field as aviable technology when applied to selected reservoirs.
Carbon dioxide flooding may be in miscible, nearmiscible or immiscible modes and may be implementedbefore, in combination with, or post-waterflood.Completely miscible (low tension) processes are usually considered those in which recoveries ofgreater than90 percent occur in slim tube tests and in which there isno visible two-phase flow in lab tests.
Carbon dioxide (C02) is a very powerful vapourizer ofhydrocarbons and, as a dense-state gas, it possesses adissolving power for light to intermediate petroleumfractions that is superior to hydrocarbon, nitrogen orflue gases. This dissolving power can be utilized for insitu fractionation of oil to develop high concentrationbanks of light and intermediate components that havehigh displacement efficiencies (up to 95 percent) andlower minimum miscibility pressures (MMP). Misciblecarbon dioxide floods may also recover oil beyond lowtension effects because ofthe extraction ofcomponentsfrom nonmobile oil in heterogenous rock.
Immiscible carbon dioxide gas drives are useful for bothoil and condensate reservoirs because of the effects ofswelling, viscosity reduction, vapourization, and efficient gravity drainage. Medium heavy oils that may notwaterflood well and that have high intermediate fractions may also be candidates for immiscible flooding.Some evidence also exists that oil- carbon dioxide mixtures may improve waterflood behaviour by resultingin phases that are rich in resins and asphaltenes. Thesemay stabilize fines and clays and alter wettability.
200
The following are crucial for determining reserves andevaluating a carbon dioxide flood:
• The availability and cost of the CO2 supply
• The classification of the process as miscible orimmiscible for recovery purposes
• The efficiency ofthe process in termsofunits ofCO2
injected for each incremental unit of oil recovered(utilization rate)
In Canada, the use of carbon dioxide has been limitedby the location, size, and development and transportation costs ofthe CO2 supplies. The use ofhydrocarbonlight ends for miscible floods has been preferred in thepast because of low prices, proximity, oversupply, andgovernment incentives.
15.2 PROCESS REVIEWThe three classifications of carbon dioxide floods aremiscible (including near-miscible), immiscible, andcarbonated waterfloods. The latter are not currently ofinterest.
Miscible processes are the most common and arecharacterized by phase behaviour effects that cause astable miscible bank with microscopic displacementefficiencies near 100 percent. In comparison withwaterflooding, this increase in displacement efficiencymore than. offsets the adverse mobility ratios betweenthe CO2 and the oil, especially if gravity effects, alternating water gas injection, or horizontal wells can beused to advantage.
Miscible and near-miscible processes are typicallyimplemented in reservoirs containing oils with APIgravities greater than 27, with reservoir temperaturesless than 105°C (220°F) and pressures greater than 9650kPa (1400 psi). Miscibility pressures decrease as t?eC2-C I 0 fraction of the oil increases, and increase Withdecreasing API oil gravity and with reservoir temperature. Miscibility pressures typically range from 26 200to 9650 kPa (3800 to 1400 psi) as API gravity increases.
c
ENHANCED RECOVERY BYCARBON DIOXIDE FLOODING
Miscibilitywith oils having API gravities less than 27have also been reported. For these low-gravityoils, estimates of MMP become scattered, but range from alow ofl4 620 kPa (2120 psi) to over 27600 kPa (4000pSI). If carbon dioxide is available, it is often the "solvent of choice" for miscible flooding because it is apowerful extractor of intermediate components fromcrudeoil andcan lead to a reductioninMMPofas muchas 6900 kPa (1000 psi).
Displacement efficiencies for the miscible process inlaboratory core floods with connate water saturationsare over 95 percent of the original oil in place (OOlP).Lab tests on water- flooded cores may recover 70percent of the residual oil in place. In field applications implemented before waterflooding, overall oilrecovery factors typically vary between 45 and 65 percent for horizontal floods and 55 and 90 percent forvertically directed gravity stable floods.
For miscible CO2 flooding in the tertiary mode, from20 to 30percentofthe residual oil to waterfloodmayberecovered in horizontal floods. In vertically directedfloods, the presence of water may inhibit fingering andaid the areal spread of CO2, resulting in recoveries of40 to 70 percent ofthe residual oil.
Immiscibleprocesses are generally less favoured thanmiscible processes where a choice is possible. In theimmiscible version of the process, mass exchange between the oil and the injected CO2, while not sufficientto cause a 100 percent flush of oil, may result in displacement efficiencies that are higher than eitherwaterflood or inert gas flood. However, as a rule ofthumb,immiscibleprocessesare chosenfor lowergravity oils in the 18·24 API range at temperatures whereswelling andviscosity reductionareconsidered themainrecoverymechanisms.
15.3 RECOVERY MECHANISMSThe following mechanisms contribute to enhancedrecoveryby the use of carbon dioxide flooding:
Viscosity Reduction, which improves the flowcharacteristics of the oil and improves the mobilityratio in the flood
Swelling,which reducesthe amountof stocktank oil inthe residual oil saturationand may improvethe relativepermeabilityto oil
Reduction in Interfacial Tension (1FT), whichallowsthe oil to be released from the rock; in a miscibleflood, the 1FT is reduced to below 0.1 dynes/em, allowing displacement efficiencies of over 90 percent, but
significant reductions in 1FT can also occur in immiscible CO2 floods
~xtractio~/Vapourization, which is especially~mporta~t In oils that have high percentages ofintermediate componentsthat can be extracted into theCO2 phase; the amount of 1FTreduction that occurs isincreased and the MMP is lowered; extraction also allows the recoveryof a portion of the nonswept oil
Dissolved Gas Drive, in which the dissolved CO willhelp recoveries in the blowdown phase of the flood
Injectivity improvements can also occur because ofremoval of oil saturation around the wellbore andbecause of interaction between the carbon dioxide andthe rock.
15.4 DESIGN CONSIDERATIONS
15.4.1 Phase BehaviourThe recoveryof oil by carbondioxidefloodingis highlydependent upon the phase behavior between carbondioxide, water and oil. The phase behaviour stronglyaffectsfluid flowby altering mobilityratios, interfacialtensions, relative permeabilitity, and rates of masstransfer mixing.
Carbondioxide in the densegas state is a verypowerfuldissolverfor lightand intermediate petroleumfractions.The extraction and concentration of these fractions ishighly pressure-dependent and causes the formation ofa stable miscible or near-misciblebank. Typically, thepressures required for the MMP are 10 350 to 13 800kPa (1500 to 2000 psi) lower than for a methane highpressure gas drive.
In reservoirs with lowerpressuresand temperatures, theprocess is more complex as more phases develop.Miscibilitymay not occur, but there will be significantbenefits due to a reduction in 1FT and viscosity, andswellingand solution gas effects.
15.4.2 Displacement EfficiencyThe estimation of the microscopic sweep for gas orsolventdrives in reservoirswith low or immobilewatersaturations is usually based on measured or simulatedoil recoveries that are obtained from multiple contactdisplacement tests in composite cores or tubes packedwith sand (slim tubes). In reservoirs that have beenpreviouslywaterflooded, or where connate water saturations aremobile, corefloods maybe required to ensurethat the oil is not shielded from the CO2 in high watersaturationzones.
The choiceof an optimum floodingpressure or solventcomposition is usually estimated from correlations
201
based on a combination of calculated and measuredlaboratory data. In floods where shielding does occur,optimum operating pressures may be lower than MMPsmeasured by slim tubes. For CO2 floods, the decisionsshould also take into account questions such as possiblereduction of injectivity by precipitation of heavy endsand potential flow interference effects that could benefit the sweep efficiency in partially miscible floods, aswell as the presence or absence of mobile water or gassaturations.
15.4.3 Volumetric Sweep EfficiencyMiscible processes, including CO2 floods, unfortunatelycan suffer from poor volumetric sweep efficienciesas a result of the high mobilities of the low viscosity solvents (less than 0.1 mPa.s) and chase gases.Unfavourable mobility ratios coupled with reservoirheterogeneities can be disastrous to miscible flood processes that rely on maintaining the integrity of smallslugs ofsolvent during the course ofthe flood, not onlybecause low volumetric sweep efficiencies may result,but also because fingering may cause prematuredissipation of the slug and result in greatly diminisheddisplacement efficiency between the (immiscible) chasegas or water and the reservoir oil.
Techniques used to improve the volumetric sweepefficiency of miscible floods include alternate gaswater injection (WAG), presolvent water injectionto reduce permeability contrasts, infill drilling to alterpatterns, and blocking and diverting agents.
Various short-cut methods of estimating volumetricsweep efficiency may be used by considering areal andvertical sweep efficiencies separately. A final design willrequire more sophisticated numerical models. The estimation of sweep efficiency considerations for CO2floods is similar to that for other floods.
Areal sweep efficiency is a function of the mobilityratio (relative permeability, viscosity ratio), permeability trends, saturation distributions, well pattern effects,solvent throughput, and production rates. In verticallydirected floods, areal sweep is also affected by densityratios between carbon dioxide, oil, gas, and water.
Vertical sweep efficiency is often a result of stratification in the reservoir rock in a direction parallel to themain flow direction. The strata are swept in order ofdescending permeability sequence, with the lowest permeability being unswept at the project termination. Othercauses of poor vertical sweep include gravity overrideor underride in reservoirs with little or no stratification.
202
DETERMINATION OF OILAND GASRESERVES
15.4.4 Slug SizingCarbon dioxide floods may be operated with essentiallyhorizontal displacement or, in high dip or reef reservoirs, with gravity stabilization. In either case, theprocess usually entails the injection of a slug of COfollowed by or co-injected with water or flue gas. Th~volumes of CO2 necessary for a particular applicationdepend on the level of gravity stabilization during displacement. For gravity stable floods, the slugs of CO
2range in size from 10 to 20 percent hydrocarbon porevolume (HPV). In horizontal floods, the slug sizes mayrange from 20 to 60 percent HPV depending on factorssuch as water saturation, heterogeneity,well patterns andspacing. A typical formation volume factor for CO
2at 20 690 kPa (3000 psi) and 60 °C (140 OF) is 266m3/res. m3 (1500 scfper reservoir barrel).
15.5 RESERVE EVALUATIONIn reserves evaluation the following are importantconsiderations with respect to carbon dioxide flooding:
I. The availability and cost of the supply must beevaluated. Carbon dioxide is available from naturalsources, from fertilizer plants, and as a combustionby-product (such as from electric power generationplants). The use of carbon dioxide in Canada hasbeen limited by the location, size, and developmentand transportation costs of the CO2 supplies. Itis important to consider the following whenevaluating a supply:
• The maximum available rates and total volumes.
• Contract terms: length, price escalators, performance clauses, and royalty payments.
• The reliability ofsupply and availabilityofbackupor alternative volumes.
• Purity: nitrogen and methane will raise the MMP,and propane, butanes and H2S will lower it.Combustion by-products like oxides may have tobe removed to avoid corrosion.
• The capital required to develop the source ofcarbon dioxide. Dehydration and compressionwillbe needed for a raw source, and the removal ofcombustion products is expensive.
• Transportation costs: These are a limiting factor,either as pipeline length (capital cost) or as trucking costs. Generally, trucking is practical only forsmall pilots, one-well huff-and-puff, small slugssuch as a small vertical scheme, or as a short-termsupplement to lower cost supplies.
..'ilt'
c
•
ENHANCED RECOVERY BYCARBON DIOXIDE FLOODING
2. The viability and the estimation of economicallyrecoverable reserves for a CO2 flood depend on thecombinations of the following relationships:
• The cost of CO2 vs. the netback price receivedfor the oil
• The CO2 utilization or flood efficiency, i.e., theamount ofCO2 injected to recover each incremental unit of oil-estimated values range from 530to 2670 mJ/mJ (3 to 15 mcflbbl)
• The incremental production rates-the amountand timing of the oil production vs. the capital,the operating and injection costs, and the timing
The recovery efficiency depends on the following:
• The oil composition and type-these affectmiscibility and the recovery mechanisms
• The stage of the flood-the CO2 injection canoccur before, during or after the waterflood
• The normal factors that affect all floods, e.g.,water saturations and geology
Some particular situations that may cause problemswith CO2 floods are reservoirs with large gas capsand water legs, depleted pools, zones with high permeability streaks, and low permeability reservoirswith lower gravity asphaltic crudes.
3. Incremental production rates are more difficult toaccurately forecast than recovery factors for manyEOR projects and, especially, early in the life oftheproject. The base production rates may be affectedby such factors as wellbore problems, injection rates,permeability streaks, break-through, recompletions,and infill drilling. Computor simulators improve theability to handle all the variables, but may not significantly improve the accuracy of the forecasts.
Good lab test results should be used in the simulators to help define the effects the recovery processeswill have on the incremental production rates as wellas on the overall recovery factors.
4. To obtain the highest recovery efficiency, it isimportant to provide the maximum contact betweenthe oil and the CO2 (both timewise and areally). Theearlier in the life of the pool that the CO2 can beinjected, the higher the target oil saturation willbe and the lower the potential water blockage.Provisions to increase the conformance, such asalternate gas-water injection and diverting agents,may be necessary.
Injectors and producers should be equipped, ifpossible, to shut off high permeability zones, and
producers should be able to handle sporadic slugsof gas (high and low gas-oil ratios).
5. Gas or miscible floods such as CO2 floods canbe subject to early break-through, so provisionsshould be made for the separation and re-injectionof the produced or break-through CO 2, There-injection may also reduce the overall CO2 requirements, especially if the pool is being flooded instages, and it will provide the maximum contact timewith the oil over the life of the flood.
6. Corrosion is a major problem in CO2 floods. Inproducers, the CO2 can make metal water-wet andaccelerate corrosion by stripping off the protectivefilm ofoil. Also, water and CO2 form carbonic acid,which is corrosive. Chemical inhibitors and coatedtubing should be used. Injected CO2 should behandled in a dry state as much as possible and if aWAG (alternating water and gas injection) is beingused, an alcohol slug should be used between thewater and the CO2 to clean up and dry out theinjection lines and tubing.
7. Carbon dioxide flooding can cause asphaltenes toprecipitate from the crude oil and result in pluggingin the formation, downhole equipment and surfacetreating facilities. This problem would require aflush-squeeze treatment with an aromatic solventsuch as toluene to restore production or injection.
In some floods, calcium carbonate plugging at thehigh water cut production wells is a problem. Thiscan be treated with acid jobs and the injection ofscale inhibitors.
8. Because carbon dioxide is a "greenhouse gas,"possible goverrunent incentives may improve theviability of a project.
15.6 FIELD APPLICATIONSMore than forty miscible and immiscible CO2 pilot,experimental, and mature field applications are inoperation worldwide. Several noteworthy ones aredescribed here.
The Wertz Tensleep Miscible CO 2 Project
This project was undertaken in a reservoir in Wyomingthat had previously been waterflooded to 45 percent ofOOIP. The recovery of an estimated additional 10percent incremental oorp (or 22 percent of remainingoil in place) has been attributed to the injection ofCO2 and water to repressure to above MMP, and thedrilling ofnew injectors and producers at key locations.Carbon dioxide utilization is estimated at 2500 mJ/m3
(14 mcflbbl).
203
The SACROC Miscible CO2 Flood
This project in Texas is one of the earliest and largestapplications of miscible CO2 flooding in the world.Despite many pioneering difficulties, including controversy regarding the MMP, this flood continues. Itis expected to yield incremental recoveries of 7.5 percent OOIP in selected sections of the pool with CO2utilization of 1780 m3/m3 (10 mcflbbl) of incrementaloil.
The Lick Creek Meakin Sand Immiscible CO2 Flood
This immiscible version of the process has used acombination of cyclic stimulation, continuous CO2injection, alternating water and CO2, and continuouswater injection to recover the 160 mPa.s reservoir oil.This project in Arkansas is currently working well andis anticipated to yield an incremental recovery of 13percent OOIP with CO2 utilization of roughly 1780m3/m3 (10 mcflbbl).
The Hansford Marmaton CO2 Flood
This project was initiated in an immiscible mode ina pressure-depleted reservoir containing a secondarygas cap. Recovery from primary was estimated at 13percent OOIP. After the reservoir was repressured,
204
DETERMINATION OF OIL ANDGAS RESERVES
miscibility was developed, and a further 9 percent ofOOIP was recovered during an 8-year period with anestimated utilization of 1246 to 1780 ml/m3 (7 to 10mcflbbl).
The literature contains textbooks and papers thatcontribute to the understanding ofcarbon dioxide flooding (Holm, 1982; Mungan, 1981, 1982; Stalkup, 1978;Klins, 1984).
ReferencesHolm, L.W. 1982. "C02 Flooding: Its Time Has
Come." JPT. Dec. 1982, pp. 2739-2745.
Klins. M.A. 1984. Carbon Dioxide Flooding - BasicMechanisms and Project Design. InternationalHuman Resource Development Corporation,Boston, MA.
Mungan, N. 1981. "Carbon Dioxide FloodingFundamentals." JCPT. Jan.-Mar. 1981, pp. 87-92.
---. 1982. "Carbon Dioxide Flooding Applications." JCPT. Nov.-Dec. 1982, pp.112-117.
Stalkup, F.r. 1989. "Carbon Dioxide Flooding: Past,Present, and Outlook for the Future." JPT. Aug.1978, pp. 1102-1112.
------------------------.rtia
Chapter 16
RESERVES ESTIMATION FOR HORIZONTAL WELLS
16.1 INTRODUCTION~orizontal wells provide an alternative way of draining
. 011 and gas from a pool. They allow drainage from alarger reservoir volume (than vertical wells in the samesetting), along with production at increased rates orreduced pressure drawdown.
Various performance analyses and theoretical studieshave shown that in certain situations, horizontal wellscan yield significantly higher (more than three times)oil rates and reserves than vertical wells; however, theyalso entail higher drilling, completion, and workovercosts.Althoughto date, the technical and economicsuccess of horizontal wells has ranged from spectacular tovery disappointing, there is a growing consensus abouttheir potential to provide significant additions to theworld's oil and gas reserves (up to 2 percent of theinitial in-place volumes).
The most popular uses of horizontal wells have beenin offshore operations, pools that are prone to coning,naturally fractured reservoirs, medium- to heavygravity pools, low productivity pools, and waterfloodor enhanced oil recovery. In many cases, in addition toan increase in the drainage area, the recovery factorsare also improved.From a recent study of Canadianhorizontal wells, it has been concluded that the profitabilityof horizontal wells is directly linked to the reservesdrained. The increased production rate helps to offsetthe increased cost of placing the horizontal wells(Bowers and Bielecki, 1993).
Other factors, such as heterogeneities, damage, andlateral pressure drops within the well, may retard drainage, andoffset the advantages mentioned. Thus, drainagehydrodynamics (within the reservoir, and especially inand around the well) have an important influence onthe reserves. The hydrodynamics around a horizontalwell, in turn, depend upon the geological features anddominant production mechanisms. The hydrodynamicsalso depend upon operationally induced features suchas prevailing pressure and saturation distributions due
to prior depletion, damage, well length, undulating welltrajectory, diameter, and flow rate. The interactionsbetween these factors are extremely complex and notfully understood at the present time. It may be fair tosay that theoretical developments regarding anticipatedproduction declines under various real life reservoirsettings, production mechanisms, and completionconditions are still in their infancy. In addition,industry's database in terms of performance historycost-effective trouble-shooting, and success rates forremedial measures is extremely limited despite the factthat in early 1993 nearly 5000 horizontal wells wereproducing worldwide, including more than 1000 inCanada. The net effect of these problems is to lowerconfidence in reserves estimates for horizontal wells (ascompared to vertical wells), whether they are based onvolumetric determinations, performance, analogies,correlations, or simulation. The challenge is not only tocome up with independent corroboration of reservesestimates, but also to quantify uncertainty.
An ideal procedure would be to project performance tothe economic limit and verify reserves by volumetricdetermination. However, sufficient data may not alwaysbe available to accomplish both of these to the desiredlevel of confidence.
The volumetric method involves determination of therange ofareas and volumes drained by a horizontal welland recovery factors. The drainage volume woulddepend upon the length, orientation and location of thewell; production mechanism; stratification; and fractures. The recovery factors would depend upon theco~pletion parameters, prior depletion, nature of operations, and reservoir variability. In practice, even afterplacement ofa horizontal well, many of the parametersinvolved may not be known to the desired accuracy.The same would be true for the other methods of reserves determination. Besides, various diagnostic andremedial measures for poorer-than-expected performance are slowly being evolved. As experience isgained, they are gradually improving, but there are stilI
205
DETERMINATION OF OIL AND GASRESERVES
*In metric units, the constant is 542.9 and the units areasfollows: permeability, J.lm': pressure, MPa: flow rate,mJ/d.
life would have significant impact on the Overalleconomics. In situations ofmarginal economics, incen_tives could have a major impact on probable reserves.Also, the role of horizontal wells in the overall deple_tion strategy for the pool must be defined prior toreserves determination.
In view of the uncertainties, reserves determinationwould involve several iterations to ensure consistency,followed by a quantification of confidence levels(Springer et aI., 1991).
16.2 RESERVES DETERMINATIONTECHNIQUES
16.2.1 Performance ProjectionHorizontal wells, as already mentioned, mainly provideincreased access to the reservoir. Placement of a horizontal well by itselfdoes not change the basic reservoirmechanism or the type of decline to be expected,although some variations could occur.
Producibility and declines for horizontal wells dependupon the nature of the reservoir, the state of depletion,and the dominant production mechanisms. Theoreticaldiscussions are available for only a few idealized horizontal well systems. Using these as guides, it is possibleto project the behaviour of horizontal wells. Usually,the performance of a vertical well provides importantclues to the performance ofa horizontal well in the samesetting.
Several methods for determining rates under steady-stateconditions have been proposed. Ofthese, Joshi's methodis the most widely used (Mutalik and Joshi, 1992). Oilrate, qh' in barrels per day is expressed as:*
significant uncertainties in reserves determination. Aprocedure would therefore have to be essentially iterative to incorporate reasonable and consistent estimatesof various parameters and their implications on drainage. The evaluator would require good geological andhydrodynamic models of the drainage volumes of ahorizontal well. One way to quantify the range of uncertainties on production projections and reserves wouldbe to use a detailed Monte Carlo computer simulation(Springer et aI., 1991). This, in tum, requires priorknowledge of statistical distribution of various inputparameters.
The drainage to a horizontal well could be improved bycertain geological features (e.g., fractures) and impededby others (e.g., stratification, previously depletedregions, and damage). Therefore, detailed geologicaland hydrodynamic models for the drainage area ofa horizontal well are essential for understanding andquantifying production performance. Interpretation oflogs and cores, well tests, or pressure data for the horizontal well and any offsetting wells would assist in thepreparation of these models.
The examination offlow distribution within and arounda wellbore (as is done during the design of horizontalwells) is of great importance. Significant implicationsto reserves could be due to vertical location, stratification, orientation, undulations, prior depletion,effectiveness of completions, formation damage, andlateral pressure drops within the well.
The overall depletion mechanism or the nature of theproduction decline is not altered by the use of a horizontal well. However, some changes to decline ratesmay occur over time due to the effects ofchanging flowregimes, heterogeneities, cross-flow, and interferencefrom different boundaries ofthe drainage area. The useof smaller pressure drawdown (i.e., a coning situation)or increased flow rates may help to prolong the economic life and hence the reserves in some situations.These may also be helped by gravity drainage to thehorizontal wells. At low pressure drawdown, gravitymay be contributing significantly to the production fromhorizontal wells.
The impact on recovery of regulations concerninghorizontal wells may be hard to quantify. Depletion strategy and economic reserves may change due to factorssuch as allowables, spacing, offset distances, and royalty regulations, so these must all be considered inthe determination of reserves. Due to higher initialproductivities of horizontal wells, production curtailment or fiscal (royalty, tax) relief during their early
206
0.007078 khh Llp
J.l,B,
where kh = horizontal permeability (mD)h = net pay thickness (ft)Llp = pressure drop (psi)u, = viscosity of oil (cp)
(1)
c
•
RESERVES ESTIMATION FOR HORIZONTAL WEllS
B, = formation volume factor (res. bbl/stb)
a = (L/2){O.5 + [0.25 + (2r'h/L)4]O.5}O.5r,h = the drainage radius for the horizontal
well (ft)L = length of the horizontal well (ft)13 = anisotropy = -VkH/kvrw = well radius (ft)
It may be noted that the equation is valid only for singlephase flow and uses single values for various inputparameters. The value of drainage distance, r'h' for ahorizontal well may not be known a priori. As a firstapproximation, the drainage distance, r,v' for verticalwells could be used for r,h'
For horizontal wells in reservoirs under solution gasdrive, producibility under unsteady and semi-steadyconditions has been projected by Poon (1990), Mutalikand Joshi (1992), Babu and Odeh (1989), and others.Poon's analysis uses an analogy between horizontalwells and vertical fractures for projecting performance.It is particularly useful since it provides "type curves"for certain idealized conditions. For other situations,flow equations could be combined with material balance and the semi-steady state treated as a successionofsteady states. The procedure would involve alternatelyobtaining estimates of average reservoir pressure (material balance) and flow rates (steady state) for differentperiods until the economic limit was reached. It mustbe kept in mind that, in some situations, uncertainties inmany ofthe parameters may render these projections oflittle practical value.
Another approach could be to use Babu's method forprojecting performance and study various sensitivitiesto evaluate the impact of uncertainties.
In coning and cresting situations, operations would bediscontinued at certain minimum oil rates or at certainwater cuts or gas-oil ratios. The latter parametersmay be based upon safety, equipment, economic orregulatory considerations. Theoretically, cresting can beavoided by producing below certain critical rates (Freeborn et aI., 1990), which themselves may change withthe changing pressures or fluid levels. Chaperon (1986)presented an approximate method for computing critical rates for horizontal wells. This method is generallyaccepted and used by the industry.
Critical rates for horizontal wells are usually muchhigher than for vertical wells. In practice, only a fewkinds ofreservoirs can produce "clean" oil or gas for anextended period. These include gas pools under activewater drive or some offshore operations with limited
platform space that do not permit installation of equipment to handle large volumes ofwater or gas production.In these cases, oil or gas reserves would be thoseobtained prior to significant break-through. Breakthrough may be delayed by operating at sub-critical rates.This would involve continuously altering rates withchanging fluid contacts until the rates become uneconomic. In other cases where facilities are not majorconstraints, large gas-oil ratio or water cut may result inan uneconomic oil rate. The nondrained part of the oilcolumn is known as the "cresting loss" or, in the case ofboth bottom water and gas cap, as the "sandwich loss."These can be estimated from the design features for.ahorizontal well, as well as from operational and reservoir parameters (Chaperon, 1986; Joshi, 1991). It isgenerally recognized that horizontal wells could significantly reduce these losses (by 20 to 40 percent).
Most often, the bulk of oil production would occurunder increasing water cuts or gas-oil ratios or both.Under these conditions, reserves would again be the sumof oil drained by the mean change of fluid contacts inthe drainage area (ignoring the effects of the crest) andthe volume of mobile oil within the crest. Correlationsare available to estimate the time for the crest to breakthrough at the horizontal well (Papatzcos et aI., 1991;Yang and Wattenburger, 1991). Estimates of breakthrough time would help in estimating the amount ofclean oil production. Oil cuts would harmonically decline thereafter (until interference from offsetting wellswas experienced), yielding a straight line on a semi-logplot ofoil cut vs, cumulative oil. For passive water drivecases, reserves would essentially be due to fluid expansion and drainage of the movable oil within the crest.
The latter can be estimated by a method suggested byButler (1989). He suggested it would be equal to movable oil within half a cylinder between the horizontalwell and the fluid contact.* For an anisotropic reservoir, this would be modified to a half ellipsoid (Figure16.2-1). The distance between the interface and the wellis called "stand-off', h. This would be the vertical axisof the ellipsoid, and the horizontal axis would be givenby the expression h(kH!kv)o.5. For an undulating well ora tilted fluid contact, the minimum distance betweenfluid contacts and well trajectory would be the effectivestand-off. Similarily, ifthe lateral pressure drop causedthe rates to exceed the critical in some parts of the well,localized cresting would tend to reduce reserves for theentire well. In such situations, if heterogeneities could
*Butlersubsequently published more sophisticatedtheoretical models.
207
DETERMINATION OFOILANDGASRESERVES
Source: Joshi, 1991.
(b)
completions are not available to fully assess the reasonsfor these increments. Viscous fingering, heterogeneitiesor hydrodynamics within and around horizontal welIspromoting water or gas channelling could be some ofthe causes resulting in poorer recoveries.
Once the performance after break-through can beprojected, a summation of oil production will provideestimates for reserves.
Whereas horizontal wells have proven to be effective inminimizing water production, their effectiveness in controlling gas cresting has only provided mixed results. Ifgas cresting is a limiting factor, usualIy the reserves are
. much lower than the method as described would indicate. The reasons could be a sharp drop in effective oilpermeability at high gas saturations or viscous fingering as the result ofunfavourable mobility ofoil comparedto that ofgas.
The foregoing discussion pertains to the improvedreservoir drainage by horizontal wells under solutiongas drive and water and gas coning situations. Horizontal welIs can also significantly improve reserves drainedfrom waterfloods as well as thermal and nonthermalenhanced oil recovery. The improvement could be theresult of increased access, injectivity or productivity,and increased volumetric sweep efficiencies. However,fractures or previously drained regions could seriouslylimit the incremental reserves. Careful engineering ofhorizontal well length, orientation, vertical placement,and operation is needed to obtain optimal reservesunder these conditions. As in the case of primaryproduction, the key factors controlling the reserveswould be the hydrodynamics within the drainage regionand the economics.
The role of reservoir variability must be taken intoaccount in all situations. Sufficient details on certainheterogeneities may not be known, even after a horizontal well starts producing. Due to this variability,the performance of horizontal wells tends to besite-specific. Another consequence is the difficulty inidentifying the "average" reservoir parameters.
At this time, in terms of length of performance historyand available geological and operational details,industry's database is extremely limited for use in deriving meaningful analogies and correlations. Well testdata and performance histories, besides confirming production mechanisms, can help to quantify certainreserves parameters. Otherwise, they do not seem to bedefinitive enough for reserve estimation. In a few caseswhere the data are available for a long enough durationto be definitive, the decline curve and material balance
.,
h
I· L~
PiIIII tI
oil : ~rev-
r,
,
(a)
• It can be assumed that drainage distances for verticalwells (r,,) and horizontal wells (r'h - U2) are equal.However, experience withpartiallydepleted Canadianpools indicates that r" couldbe larger than r,h - U2.
Figure 16.2-1 Schematic of Horizontal andVertical Well Drainage Areas*
be adequately characterized, detailed numerical modelling might be the only way ofobtaining reliable reservesestimates under different completion and operatingconditions. For optimizing reserves, it may be necessary to ascertain that the flow along a horizontal well isevenly distributed.
At this time, no methods other than correlations (Yangand Wattenburger, 1991) are available in the publicdomain for estimating post-break-through productionofoil and water (or gas) via a horizontal well. As a firstapproximation, coning correlations of Kuo (1989)for the vertical wells or Butler's method for horizontalwells (Butler and Suprunowicz, 1992) may be used.Computer-generated projections for the Suffield Jennerpool in Alberta appear more optimistic than these correlations. The actual decline ofoil cuts with cumulativeoil was not unlike that for a vertical well after allowances were made for increased drainage area due tolength, and reductions in crest volume due to heterogeneities (Russell and Espiritu, 1992). For some horizontalwells in the Provost Dina pools ofAlberta (Heysel, 1992)very modest increments over vertical wells havebeen reported. However, data on well trajectories and
208
.t,~:
---------------------_...
•
RESERVES ESTIMATION FOR HORIZONTAL WELLS
methodologies for conventional wells could be extendedfor horizontal wells. Generally, the most fruitfultechniques for reserves in vertical wells would alsobe applicable to horizontal wells. A methodology forhorizontal wells is suggested in Section 16.3.3.
16.2.2 Volumetric MethodDetailed flow distribution around a well is the mostimportant consideration in identifying the drainage areafor a horizontal well, which would drain a much largerportion of a reservoir than a vertical well, dependingupon its length. Other factors determining drainage areawould be the distance to the nearest pool boundariesand the distance to offsetting wells as well as the rate ofdrainage by them. For homogeneous reservoirs undersolution gas drive, Joshi (1991) has presented methodsfor estimating drainage areas based upon estimating thetime to reach semi-steady state for different drainagegeometries. From these, effective drainage area can beestimated.
Limited experience to date suggests that drainagedistance for horizontal wells (reh- Ll2 in Figure 16.2-1)would, in many cases, be smaller than that for verticalwells (rev)' The reasons could be heterogeneities andprior depletion.
As a rule of thumb, a 300 m well would drain theequivalent oftwo vertical wells, and a 600 m well-theequivalent of three vertical wells. However, this rule ofthumb must be used with extreme caution.
It has been observed from the performance of severalCanadian oil wells that the reserves for sandstone poolsare generally proportional to their lengths (Bowers andBielecki, 1933). Corresponding correlations betweenwell lengths and reserves drained for fractured carbonate pools are rather weak. It is possible that this is causedby water influx via some of the relatively larger fractures. By and large, horizontal wells in Estevan light oilpools were draining 250 to 300 m in the lateral direction whereas for Lloydminster heavy oil, this distanceis less than ISO m and could be as low as 50 to 70 m(Springer and Flach, 1993). In some Alberta light oilpools, very disappointing reserves were noted (Bowersand Bielecki, 1993), implying small drainage areas orpoor recovery factors.
16.2.3 Role of HeterogeneitiesIn a heterogeneous reservoir, a horizontal well is likelyto traverse many more prolific regions than a verticalwell. For a given pressure drawdown, most of the inflow would be from these more prolific regions. Thus,
one horizontal well would be equivalent to several individual vertical wells placed in the path ofthe horizontalwell. The increased producibility as well as the increasedreserves would be similar to those expected for closelyspaced vertical infillwells. The accelerated drainage mayinduce faster declines (as well as interference withoffsetting wells). Extreme examples of such prolificzones are fractured regions in Austin Chalk in Texas,Bakken Shale in North Dakota, and karstic regions inthe Raspo Mare oil field off the Italian coast in theAdriatic Sea. Variable fracture or vug density in thedolomitic reefs of Alberta and Saskatchewan may alsoconstitute prolific regions ("sweet spots"), but with lessdramatic impact on reserves. On the other hand, thesesweet spots may also act as pathways for water or gas tobreak through at the wells and thus reduce volumetricsweep and recovery factors.
The vertical and lateral extent of the drained regionwould mainly depend upon geological features such asstratification, fractures, barriers to flow, and lateral variations. Effective drainage volume for a horizontal wellwould thus be smaller than the hydrocarbon pore volumes contained within the drainage area if these exist.In order to identify the drainage volume ofa horizontalwell, a geological model would be very helpful. It maybe noted that even in pools with good geologicalcontrol, horizontal wells usually reveal unanticipatedfeatures. A geological model, updated with datafrom horizontal wells, would greatly aid in determiningdrainage volume for the well.
16.2.4 Importance of Channelling inReserves Performance
In certain geological settings, it becomes apparent thatthe production is dominated by water channelling ratherthan the classical water coning. For instance, severalMississippian pools in the Estevan area ofthe provinceof Saskatchewan contain no bottom-water leg, and yetthey produce large quantities of water. They must certainly be receiving pressure support via numerousfractures present in the region. Besides this postdepositional fracturing, these carbonate deposits havebeen witnesses to several events of replacement ofcalcium carbonate by dolomite and anhydrite. Whereasfractures act as conduits for the active waters to invadethe oil zone, dolomitization increases storage (porosity), and vugs and micro-fractures increase permeability.In addition, site-specific 3-D configuration of the reservoir (intercalation of porous and dense intervalsoccasionally traversed by fractures, and poor continuity of dense and porous features over inter-well
209
distances) characterize sweeping ofthe pay zone by theinfluxing water. Therefore, the reserves drained by horizontal wells depend upon factors such as the priorexploitation of underlying zones within the pool (timing), the level ofheterogeneity and occurrence ofdensezones, and the stand-off above the water-oil contactsor the base of the pay. Contrary to what might beanticipated in a classical coning situation, most horizontal wells in developed pools fail to drain significantamounts of incremental reserves over and above whattwo or three vertical infill wells might drain undersimilar conditions.
In this area, the advantage of higher initial oil rates forthe horizontal wells is often negated by sharp declinesas the water production increases. Water rates andcumulative water production are seen to increasedisproportionately to the corresponding increases in oilproduction because of the existence of numerous vertical fractures and the prevailing distribution of theinvaded water (due to prior operations). Under thesecircumstances, lateral pressure drops within the horizontal well due to two-phase (or three-phase) flowassume special significance. Consequently, horizontalwells may be doing a poor job of draining oil aroundtheir "toes." The situation may be further complicatedby the specific reservoir description (porous or tightzones and fractures along the length of the well) andnear-wellbore formation damage.
It follows then that for projecting performance, adetailed knowledge of reservoir description and a properunderstanding ofthe geology and hydrodynamics ofthedrainage region around a horizontal well (within the oilpool, including any supporting aquifer) are absolutelyessential. Viscosity (temperature) of oil plays an important role by way of causing viscous fingering andlimiting volumetric sweep by the invading water.
16.2.5 Recovery FactorsOnce the drainage volume has been estimated, the nextstep is to estimate the upper and lower limits of recovery factors for drainage via horizontal wells.
An understanding of the behaviour of vertical wells inthe same pool in terms of the dominant productionmechanisms and the factors limitingproduction providesimportant clues to the production behaviour of horizontal wells. As previously mentioned, some features wouldhelp in improving recovery whereas others might hinderefficient drainage. The three lists that follow give someof the more important of these characteristics.
210
DETERMINATION OF OIL AND GASRESERVES
1. Features that improve drainage:
• Enlarged drainage volume
• Heterogeneities (sweet spots) within the drainagearea; barriers to the flow of bottom water or gasinto the horizontal well
• Reduced pressure drawdown, which may help tomitigate drainage restrictions (e.g., cresting, finesproduction)
• Effective lowering of the economic oil rate limit(one horizontal well replacing several verticalwells)
2. Features that hinder drainage:
• Heterogeneities (stratification, barriers to substantial drainage in depletion drive, by-passing of oilin water- or gas-drive flooding)
• Previously drained regions within the drainagevolume that may be at lower pressures, or higherpressures (watered-out regions). .
• Wellbore damage (lower effective well radius)
• Lateral pressure drops (turbulence, multi-phaseflow, sediments or debris present in the hole) causing effective drainage from only a part ofthe well
• Undulating well trajectory or "porpoising" (somesections may get closer to fluid contacts or thetops or bottoms of the pay zones; in some instances, some sections of wells may even beoutside the pay zone, reducing the effective welllength in a good part of the pay)
3. By examination of geological and hydrodynamicmodels, some of the questions about the impact ofless than ideal conditions on recovery factors maybe clarified. These questions could be as follows:
• Are small intervals contributing the bulk of theflow?
• If SO, will they continue to be rechargedadequately?
• Is there more severe skin in certain parts of thewell?
• Could a lateral pressure drop within the well berestricting drainage from some parts ofthe well?
• Would early break-through of water or gas bepromoted by the dominant flow routes?
• Once break-through occurs at any point in thewell, would it seriously restrict subsequent drainage by the well?
_______________________sd
RESERVES ESTIMATION FOR HORIZONTAL WELLS
A quantification of these effects on recovery factorscould be obtained by a quick, coarse-grid simulationstudy.
16.3 DETERMINATION OF RESERVES
16.3.1 Determination of ReservesParameters
Average reserve parameters would be difficult todeterminewithout closely examining a geologicalmodelof the drainage region around a horizontal well. Theseparameters could be porosity, permeability (vis-a-visorientation of the well), characterization of the aquiferand the gas cap, net pay thickness (Reisz, 1992), thickness above or below the well in the case of undulatingwell trajectory, location ofpay tops and bottoms withinthe drainage region, fractures, effective well length,reservoir pressure, saturations, damage, and drainagedistances.
16.3.2 Key ElementsAll of the elements of reserves determination forhorizontal wells are similar to those applicable to vertical wells. However, the required analysis is usually morerigorous because a detailed analysis of the hydrodynamics of the drainage around each horizontal wellmust be included.
The procedure is iterative to ensure consistencybetweenreserves obtained from volumetric as well as performance analysis and all available geological, reservoir,and production data.
The procedure calls for sound engineering judgementregarding appropriate values of parameters to be usedfor performance projections and reserves estimationand, in addition, requires a clear understanding of thedominant recovery mechanism and the parameters thatlimit reserves for exploitation of the pool by conventional wells. The possible relaxation of the limitingconditions on drainage using horizontal wells is estimated based on these. A hydrodynamic model for thedrainage area incorporating reservoir variations,current state of depletions, and qualitative visualization of flow distribution within the drainage area ofhorizontal wells is required. Finally, the implication ofoperational and economic factors on reserves must beexplicitly included.
16.3.3 Steps Involved in ReservesDeterminations
The proposed procedure involves iterations of thefollowing steps until an acceptable determination isachieved:
I. Prepare a geological model for the drainage regionof the horizontal well. The model should addressquestions regarding the boundaries, the limits ofthe drainage area due to any barriers to flow,heterogeneities and facies changes, fluid contacts,anisotropy,directional trends, preferred fracture orientations, micro-fractures, and sweet spots.
2. Prepare a qualitative hydrodynamic modelincorporating data on the current state of drainage,the well trajectory, the pressure and saturationdistribution prior to the placement of the horizontalwell, the effective drainage region, and the flowingpressure distribution around the horizontal well,including any possible interference with offsettingwells.
3. Obtain estimates of various drainage and reservesparameters such as effective pay thickness,shape of the drainage area, sweet spots, drainagedistance, porosity, pressure distribution, saturationdistribution, compressibility, permeability, kH/kv,and skin.
4. Estimate the hydrocarbons in place in the drainagevolume and the range ofthe associated uncertainty.
5. Estimate the range of recovery factors for horizontal wells from data on recovery factors forconventional drainage, and possible relaxation ofparameterscontrollingproduction. The roles ofvarious influences may be quantified using coarse-gridsimulation or engineering judgement.
6. Estimate the initial productivity from the estimatesofdrawdown, permeability (vertical as well as horizontal), compressibility, and saturations. Actualperformance or test data may be used for validatingestimates of various parameters.
7. Project the production forecast for the specificsituation. Performance data, equations, materialbalance, and simulation results, if available, maybe used for validating decline performance. In theabsence ofany better data, initial productivity alongwith volumetric reserves may be used for projecting performance. This data may then be input intoeconomic analysis for obtaining economic reserves.
211
Dependingupon the situation,curves of rate-time,rate-cumulative production,volumeratios, and cumulative volume of gas or water vs. cumulativeoilor gas may help to determine the reserves.
Care must be exercised to ascertain that there isadequate history,thattheperformance isdeterminedby reservoir and geological factors only, and thatthe performance is consistent with the knownmechanisms.
Data on the performance of horizontal wells inanalogous situations, if available, could be useful.Some statistical data on performance of horizontalwells in different oil zones from certain Canadianproducingareas over the first 12monthsof production has recently been published (Springer et aI.,1993).
Where uncertainty is high, the production forecastshould be based upon estimates of initial productivity and volumetricallydetermined reserves.
8. Identify any enhancementpotential to reservesdueto prudent operational changes, recompletions,facilities orequipment upgrades. These datacanthenbe used for further refiningthe productionforecast.
Another fine-tuningcould be requireddue to interferencewith offsetwells, if such interference couldbe established fromtheirperformance (Springer andFlach, 1993).
9. Ensure consistency between reserves based onvolumetricdeterminationandproductionforecasts.A few iterations may be required to achieve this.
10. Evaluate the range of uncertainties in the reservesestimates and relevant confidencelevels. This willdepend upon geological control, the amount ofhistorical data from the pool, the success of costeffective diagnostic or remedial operations, andthe length of time the horizontal well has beenproducing.
The Monte Carlo computer simulation methodfor quantifying confidence levels is described inSection22.4.4 (Springer et aI., 1991).
ReferencesBabu, D.K., and Odeh, A.S. 1989. "Productivityofa
Horizontal Well." SPE Reservoir Engineering,Vol. 4, No.4, Nov. 1989,pp. 417-421.
212
DETERMINATION OF OIL AND GASRESERVES
. Bowers,B., and Bielecki, J. 1993. "Horizontal OilWells: Economicsand Potential Impact on theReserves and Supply of Canadian ConventialOil." WorkingDocument,Horizontal WellCommittee of the National Energy Board,Calgary,AB, Jun. 1993.
Butler, R.M. 1989. "The Potential for HorizontalWells for PetroleumProduction."JCPT, Vol. 28,No.3, May-Jun. 1989,pp. 39-47.
Butler, R.M., and Suprunowicz, R. 1992. "VerticalConfinedWater Drive to Horizontal Well - Part I:Water and Oil ofEqual Densities."JCPT, Vol.31, No.1, Jun. 1992,pp. 32-38.
Chaperon, 1. 1986. "Theoretical Study of ConingToward Horizontal and Vertical Wells inAnisotropic Formations." Paper presented at 61stAnnual Fall Meeting, SPE of AIME, NewOrleans,LA, Oct. 1986,SPE 15377.
Freeborn, R., Russell, B., and MacDonald, A.J. 1990."South Jenner Horizontal Wells: A Water ConingCase Study."JCPT, Vol. 29, No.3, pp. 41-46.
Heysel,M. 1992. "Horizontal Well Performanceinthe Dina Sandstonein the Provost Area ofAlberta." Presented at Annual CIM TechnicalMeeting,Calgary, AB, Jun. 1992,CIM-ATM92-34.
Joshi, S.D. 1991. Horizontal Well Technology.PennwellPublishing Co., Tulsa, OK, p. 34.
Kuo, M.C.T. 1989. "CorrelationsRapidly AnalyzeWater Coning." O&GJ, Oct. 1989,pp. 87-90.
Mutalik, P., and Joshi, S.D. 1992. "Decline CurveAnalysisPredicts Oil Recovery from HorizontalWells." O&GJ, Sep. 1992, pp. 42-48.
Papatzcos,P., Herring, T.R., Martinsen,R., andSkjaeveland, S.M. 1991."Cone Break-throughTimefor HorizontalWells." SPE ReservoirEngineering, Vol. 6, No.3, Aug. 1991,pp.311-328.
Poon, D.C. 1990. "Decline Curves for PredictingPerformance ofHorizontal Wells." JCPT, Vol.30, No. I, pp. 77-81.
Reisz, M.R. 1992. "Reservoir EvaluationofHorizontal Bakken Well Performanceon theSouthwestern Flank of the WillistonBasin."Paper presented at SPE InternationalMeeting,Beijing, China, Mar. 1992, SPE 22389.
----------------------",.
=
RESERVES ESTIMATION FOR HORIZONTAL WELLS
Russell, B., and Espiritu, R. 1992. Personal communication.
Springer, S.1., Mutalik.P; Asgarpour, S., and Singhal,A.K. 1991. "Risk Analysis for Horizontal Wells."Paperpresentedat 4th Saskatchewan Symposium,CIM, Regina, SK, Oct. 1991, PaperNo. 13.
Springer, S.1., and Flach,P.D. 1993. "A Review ofthe Drainage Area/lnterwell Spacing Used inSome Established Horizontal Well Projects."DEA44/DEA 67 International Forum"Horizontal Technology - LivingWith Reality,"Calgary, AB, Jun. 1993.
Springer, S.1., Flach, P.D., Porter, K.E., Christie,D.S., and Scott, G.C. 1993. "A Reviewof theFirst FiveHundred Horizontal Wells Drilled inWestern Canada."Paper presentedat 44th AnnualTechnical Meetingof the Petroleum SocietyofCIM, Calgary, AB, May 1993, CIM 93-19.
Yang, W., and Wattenburger, R.A. 1991. "WaterConing Correlations for Verticaland HorizontalWells." Paperpresentedat 66th Annual SPETechnical Conference and Exhibition, Dallas,TX,Oct. 1991, SPE 22931.
213
Chapter 17
NUMERICAL SIMULATION
17.1 INTRODUCTIONNumerical simulation is the most sophisticated tool forestimating hydrocarbon reserves and determining methods to use for optimizing the recovery ofhydrocarbonsfrom a reservoir. Numerical simulation has been usedin reservoir studies since 1960. The rapid developmentof digital computer technology in the early seventiesstimulated the widespread development and applicationofreservoir simulation computer programs. At first, thehigh cost of software development and computing limited the use ofnumerical reservoir simulation; however,the recent availability of powerful low-cost personalcomputers and work stations has made it much moreaccessible to petroleum engineers. Today, numericalreservoir simulators are more efficient and moreaccurate.
This section provides an overview of numericalsimulation practice. Readers who wish to gain anin-depth knowledge ofthe mathematical aspects ofsimulation should read the book by Aziz and Sattari (1979).Excellent discussions on practical applications of reservoir simulation may be found in books by Crichlow(1977) and Mattax (1990).
17.2 TYPES OF RESERVOIRSIMULATORS
Reservoir simulation is based on the physical principlesof mass conservation, fluid flow, and the conservationof energy. From these come a set ofpartial differentialequations describing the behaviour of fluids in a reservoir. According to the type of process and the numberof components required to be modelled, reservoirsimulators may be categorized as follows:
Black oil simulators, which model multi-phase flow ina reservoir without consideration for the compositionof the hydrocarbon fluids. The liquid phase consists ofwater and the oil and gas in solution. The gas phaseconsists of only free gas. Mass transfer of the oil component from the liquid to the gas phase is not taken intoaccount.
214
Compositional simulators (Coats, 1980a; Nolen, 1973;Thele et aI., 1983), which account for mass transfer between liquid and gas phase. The hydrocarbon phase isrepresented by"n" components; k-values and flash equilibrium are used to represent phase behaviour.
Enhanced oil recovery simulators, which include insitu combustion (Youngren, 1980; Coats, 1980b), steamstimulation, (Coats, 1978) hydrocarbon miscible (Toddand Longstaff, 1972), carbon dioxide flooding (Chaseand Todd, 1984), and chemical injection (Todd andChase, 1979). These simulators apply the basic concepts of both black oil and compositional simulatorswith added features to model a particular enhanced oilrecovery process.
Reservoir simulators have also been developed to modelnaturally fractured reservoirs. In addition to modellingthe processes described, a naturally fractured reservoirsimulator must also model the complex flow behaviourin a matrix-fracture system.
Naturally fractured reservoirs are characterized by twosystems: a matrix system which has low permeabilityand high capacity, and a fracture system which has highpermeability and low capacity. The bulk of the fluid iscontained in the matrix system, and fluid flow occursprimarily in the fractures. A comprehensive review ofnaturally fractured reservoirs is given by Aguilera(1980).
The general approach in naturally fractured reservoirsimulation is the dual-porosity formulation shown inFigure 17.2-I(a), in which the rock matrix is considered as a series ofdiscontinuous blocks within a continuous fracture system. The matrix blocks act-as thesource and feed into the fracture system. The fracturescan be thought of as a system of connected pipes. Thismodel was proposed by Warren and Root (1963).
Recent developments allow a more vigorous treatmentof fluid flow in naturally fractured reservoirs to beincorporated into simulators. In addition to fracturematrix interaction, matrix-matrix flow is permitted; this
•
NUMERICAL SIMULATION
gives rise to the dual-permeability formulation (Gilmanand Kazami, 1988) shown in Figure 17.2-1(b).
Figure 17.2-1 Schematic Diagram of MatrixFracture Connectivity
17.3 MATHEMATICAL FORMULATIONMathematical functions for all the cases discussed havebeen presented in detail in the literature, and so will notbe repeated here. In general, the formulations involvethe use of partial differential equations that are solvedusing finite difference schemes. Figure 17.3-1 shows asmall volume element ofthe reservoir with dimensionsdx, liy, and liz. Simulation involves a mass balance overmany elements similar to the one shown.
The exact solution to the partial differential equationsis rarely available. In practice, numerical techniques areused to obtain approximate solutions to those equations.The finite difference method is the one most commonlyused for reservoir simulation. The method transformsthe continuous differential equation into a discrete formin both time and space. The reservoir region is subdivided into elements or grid blocks similar to the blockshown in Figure 17.3-1. The solution to the system offlow equations is obtained for each grid node. The dependent parameters obtained for each grid node representthe average value for the element.
Detailed discussion of the finite-difference method isavailable in the literature (Aziz and Settari, 1979) andwill not be provided here. However, certain concepts
Figure 17.3-1 Mass Balance on ReservoirElement
that will affect the decisions made by a simulationengineer will be discussed.
The early approach to' solving the multi-phase flowequations was the Implicit Pressure Explicit Saturation(IMPES) Method, in which the flow equations werecombined into a single pressure equation. After the pressure has been advanced in time, the saturations areupdated explicitly. This approach assumes that the capillary pressure and transmissibility terms do not changesubstantially within a timestep. The advantages of theIMPES method are its low computer memory requirement and reduced computation per timestep.
The IMPES method has been found to be satisfactoryfor many problems; however, in situations where highflow rates exist, such as in water coning, gas percolation problems and naturally fractured reservoirsimulation, a more stable solution method is required.
The fully implicit method, on the other hand, requiresthe simultaneous solution ofthe multi-phase flow equations (Au et al., 1980).This method requires substantiallymore computing time and data storage. Increased stability ofthe fully implicit method allows larger timestepsto be used.
Most commercial simulators allow the user to specifythe method of solution. More advanced simulators offer semi-implicit and dynamic implicit methods. Thesemi-implicit method solves a subset of the flow equations simultaneously whereas the dynamic implicitmethod switches between the IMPES and fully implicitmethods on an individual grid block according to flowconditions. Unless computer memory and run timelimitations present a problem, it is advisable to use thefully implicit method of solution to avoid unnecessarynumerical problems.
Lly
Llz
- - -l-. Flow• Out
Llx
----...FlowIn
fracture matrix
(b) Dual Permeability
I I
• - •I I
• l- •I I
• l- •
I Ifracture matrix
(a) Dual Porosity
I
• l- •1
• l- •I
• l- •
1
215
17.4 ANATOMY OF RESERVOIRSIMULATION
Reservoir simulation is a complex engineering task. Asimulation study must be planned and organized to ensure that useful results are obtained. The objectives ofthe simulation study must be clearly defined. The engineer should have a list of specific questions the studyshould answer, and preliminary reservoir engineeringcalculations should have been completed. Before carrying out a simulation study, an engineer should bethoroughly familiar with previous reservoir studies. Theresults and conclusions ofprevious studies may be useful to fine-tune current study objectives and help savetime.
Once the objectives and scope of the study are clear,a reservoir simulation study generally involves thefollowing phases:
1. Data collection
2. Model grid design
3. Sensitivity tests
4. History matching
5. Performance prediction
The following sections describe these phases of thesimulation activity.
17.5 DATA REQUIREMENTSA numerical simulator may be used to model anyreservoir. The input data to the simulator describe auniquemodel for a particular reservoir.The data requiredto construct a reservoir model may be grouped asfollows:
Reservoir geometry, which describes the size, shape,internal and external boundaries of the reservoir
Rock and fluid properties, which affect the dynamicsof fluid flow in the reservoir
Production and well data, which describe the welllocations, perforation intervals, skin factors, and flowrates
17.5.1 Reservoir GeometryA geometric description of a reservoir is usuallyderived using a team approach involving geologists,geophysicists and reservoir engineers. A goodunderstanding of regional geology and depositionalenvironment is necessary. Seismic sections are usefulin preparing structural maps and positions of faults.Formation top and thickness of zones to be simulatedmay be obtained from well logs and drilling records.
216
DETERMINATION OFOILANDGASRESERVES
17.5.2 Rock and Fluid PropertiesThe important petrophysical properties of rock requiredin reservoir simulation include porosity, absolute permeability, relative permeabilities, capillary pressuredata, rock compressibility, and fluid saturations.
The average porosity can be determined from coreanalysis. The porosity is also calculated from welllogs. Porosity logs calibrated against core porosity aregenerally more reliable than log data alone.
Absolute permeability is one of the most difficultreservoir properties to define. It is also critical to theprediction of fluid migration in a reservoir. Integratedpermeabilities from cores and well-test data should beused in reservoir simulation.
In a reservoir where more than one fluid is present, therelative permeability of individual fluids as a functionoffluid saturation is required. Relative permeability dataare usually obtained from laboratory measurements oncore samples. The relative permeability relationships areobtained for gas-oil, oil-water, and gas-water systems.Most reservoir simulators use Stone's (I970) modelto approximate three-phase relative permeabilitybehaviour.
The capillary pressure data are determined fromlaboratory analyses. Rock compressibility data areobtained from laboratory analyses of the reservoir rockor from published correlations.
Formation fluid saturation distributions can be derivedfrom log analysis. Another option is to calculate fluidsaturation distributions based on the positions of thewater-oil and gas-oil contacts. The fluids may beassumed to be initially either fully segregated (no transition zone) or dispersed (with a transition zone). Thecapillary pressure curves are used to determine thesaturation in the transition zone.
Fluid properties include formation volume factors, fluidviscosity, solution gas-oil ratio, and fluid density. Thesource ofthese data is usually laboratory PVT analysis.Iflaboratory data are not available, correlations can beused to generate them. For compositional simulation,the equation of state is used for calculating fluid pr?perties. The effects of temperature on viscosity, density,relative permeability and capillary pressure are alsorequired for thermal simulation.
17.5.3 Production and Well DataThe data required to specify well operation include welllocations, perforation intervals, well productivity index,skin and flow rates for each well. Sources ofproduclion
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NUMERICAL SIMULATION
and well data are pressure tests, drilling records, andwell production records.
The constraints imposed on wells due to surfacefacilities or economic limits must also be available.Typical well constraints are water-oil ratio, gas-oilratio, bottom-hole pressure, and maximum andminimum flow rates.
17.6 RESERVOIR MODEL GRID DESIGNA reservoir can be modelled with !D, 2D or 3D gridsystems. Depending on the objectives of the study, oneof the following may be used:
ID models, which have limited applicationsincluding material balance, simulation of experiments,and interaction between two wells. In a vertical or dipping !D model, the effect of gravity override, updip gasinjection, and bottom water injection can be evaluated.
2D areal models (Figure 17.6-1), which arecommonly used in field simulation. The model is suitable when areal flow pattern dominates reservoirperformance, and the vertical variation in rock and fluidproperties in the reservoir is small.
Figure 17.6-2 20 Vertical Model
2D radial models, which are a special type of 20models. While most simulation models are defined bycartesian coordinates, the 2D radial models are definedusing a cylindrical coordinate system (Figure 17.6-3)and have special applications in the study of near-welleffect. The 20 radial models are often called coningmodels because they are used principally to study waterand gas coning behaviour. This type ofmodel is usefulin studying single well operations to determine the optimal completion interval, critical flow rate to avoidconing, well deliverability, and well test analysis.
Figure 17.6-3 20 Radial Model
Figure 17.6-1 20 Areal Model
2D vertical models, which are used to modelvertical cross sections of a reservoir (Figure 17.6-2).The applications include gravity segregation effect,effect of stratigraphy, frontal displacement, effects ofwell completion intervals, and flow into a horizontalwell.
2D vertical models are also used to generatepseudo-functions, which reduce three-dimensional simulation to two-dimensional areal simulation (Jack et aI.,1973; Coats et al., 1971).
•,,.
I
II
-- z
217
3D models, which are used to study large multiple wellreservoirs with thick reservoir pay sections, significantvertical variation in rock and fluid properties, faults, andpartial communication between layers (Figure 17.6-4).3D models are also used to study large reservoirs withseveral noncommunicating producing horizons, multiplecompletions with or without commingled production,aquifer influx, and horizontal well development.
Figure 17.6-4 3D Model
An efficient reservoir model is one that satisfies the studyobjectives at the lowest cost. Since the cost ofa simulation study, including engineering person-time costs andcomputing costs, is proportional to the complexity ofthe model, it is desirable to employ the simplest modelpossible. The model, however, must be able to represent reservoir geometry and positions offaults and wells,and be able to show fluid migration patterns. It is difficult to design an optimal grid system for a reservoir.However, the following guidelines may be useful.
Since the parameter values for each grid node in areservoir model are the average values for the block,the number of grid nodes should be increased in thearea of interest or where reservoir parameters are expected to change rapidly. Typically, smaller grid blocksare required around wells. One caution is that abruptchanges in grid sizes introduce truncation errors. Asa general rule, the ratio of the grid lengths for twoadjacent grid blocks should be less than two.
Local grid refinement features are available in mostreservoir simulators. This feature allows any grid in areservoir model to be subdivided into smaller grids without adding extra blocks in other parts ofthe model. Localgrid refinement can be very useful in areas with wellsand faults. By subdividing a well block vertically intomore layers, local grid refinement provides a means tospecify completion intervals more precisely.
218
DETERMINATION OF OIL ANDGASRESERVES
In areal simulations where the effect ofwell pattern andinfill wells is studied, sufficient grid blocks should beused so that all the wells in the reservoir model are separated by several grid blocks. Ifpossible, the orientationof the grid system should parallel trends of highpermeability.
A full field reservoir simulation may not be necessaryto satisfy the study objectives. In many cases, a studyof an element of symmetry from a reservoir withrepeated well patterns may be sufficient.
17.7 RESERVOIR MODELINITIAL,IZATION
Preceding sections have indicated that reservoir dataare available mainly at well locations. The reservoirsimulator, however, requires reservoir parameters foreach grid node in the reservoir model. The commonpractice is to construct contour maps of the reservoirparameters. The reservoir model grid is then overlaidon the contour map, and values are assigned manuallyto each grid node.
Some simulators utilize reservoir parameters at welllocations and generate the distribution ofparameters foreach grid node using a second or higher order interpolation scheme. The number ofwells and their locationscan affect the quality of interpolation. The reservoirparameters assigned to each grid node by this methodshould be examined carefully and any anomalies corrected. Most reservoir- simulators have the ability todisplay the reservoir model and initial conditions on acomputer display screen for visual inspection.
The initial pressure and fluid saturation distributions inthe reservoir model can be defined using the interpolation scheme described. Alternatively, the simulator canbe used to calculate pressure and saturation distributionbased on specified water-oil and gas-oil contacts andreference pressure.
17.8 MODEL SENSITIVITY ANALYSISThe numerical truncation error associated with timestepsize and grid size can affect the accuracy of simulationresults. Before a detailed history match is performed,the sensitivity of a reservoir model to truncation errorshould be analyzed.
The effect of grid size on simulation results can beevaluated with a simple model of a representative portion of the reservoir that includes an injection andproduction well. A series of simulation runs with decreasing grid size is performed. When the reduction ingrid size does not change the simulation results beyond
__________________________c.
NUMERICAL SIMULATION
the accuracy required, the grid size is consideredacceptable. A smaller 2D model is often used to perform grid sensitivity tests because it is cumbersome tochange the grid block sizes in a complex 3D field scalemodel.
The effect of timestep size should also be investigatedin the reservoir model sensitivity analysis. The timestepsize used in field scale simulation is indirectly controlledby how often the well rates are changed. However, whenthere is no change in well rates and the maximumtimestep size is not controlled, the numerical truncationerror can be significant. A few simulation runs shouldbe made with different timestep sizes to determine themaximum timestep size that will produce no adverseeffect on the results.
Most reservoir simulators use automatic time stepselection algorithms to determine the appropriatetimestep size. The algorithm selects a timestep size thatwill maintain pressure, saturation or temperature changeover a timestep at the level specified by the user. Ifautomatic timestep selection is used, the maximumtime step size determined from the sensitivity studyshould be imposed.
17.9 HISTORY MATCHINGThe data available to construct a reservoir model isoften limited, so it is very unlikely that the initial reservoir model will provide a good representation of thereservoir. However, this data represents the best estimates of the engineers and geologists. The predictionsobtained from a reservoir model are thus not very useful unless the model is able to produce a performancesimilar to the historical data. History matching is a process in which the parameters of the model are adjusteduntil the computed results are similar to the historicaldata. The adjustment of parameters should be carriedout within reasonable orders ofmagnitude; the input ofunrealistic data for the sake ofobtaining a good historymatch is never justified.
The historical data usually includes observed pressures,gas-oil ratio, and water-oil ratio. In cases where a wellis produced at a constant pressure or total fluid rate,the match variable can be the oil or gas rates. In somecases break-through time may be an important matchparameter.
Before any of the historical data is used in the historymatch, an engineer should analyze the data to confirmthe accuracy ofthe recorded information. The engineermust make sure that the data is in comparable units and
the pressure data has been corrected to the properdatum.
When long production history is available, it iscustomary for simulation engineers to specify monthly,quarterly or semi-annually averaged daily rates as inputto the simulator. These daily production rates are obtained by dividing the recorded cumulative productionduring the selected period by the number ofdays in thatperiod. The production data to be matched should alsobe averaged in the same fashion.
History matching is a time-consuming exercise. It cantake more than fifty percent of the time allocated to areservoir SImulation study. There is no system for changing the reservoir parameters that would result in a goodhistory match, so engineers must rely on their reservoirsimulation experience and their knowledge of the reservoir. The general rule in history matching is to changethe parameters that have the largest uncertainty and alsothe largest effect on the results. The engineers must constantly check to make sure the parameters are withinreasonable limits.
17.10 FORECASTING RESERVOIRPERFORMANCE
Following a satisfactory history match, the reservoirmodel may be used to predict reservoir performance.From the objectives of the simulation study, a list ofprediction cases is developed. It is always useful to establish a base case for comparing different proposeddevelopment strategies. The base case is usually thecontinuation ofthe existing operating strategy. The following are typical questions a reservoir model mayanswer:
• Estimate of reserves
• Well pattern and spacing
• Injection well location
• Drilling schedule
• Critical production rates
• Well completion strategy
• Well deliverability
• Vertical vs. horizontal well performance
• Migration of fluid
• Recovery mechanisms
The model provides estimates of fluids in place atinitial and current conditions. Ideally, these estimatesshould compare with the results from volumetric andmaterial balance calculations. The results of the basecase forecast should match reasonably well with the
219
results from decline curve analysis. Any significantdifferences in these results should be investigated andan explanation included in the engineering report.
If the objectives of the simulation study include thedetermination of ultimate recovery for a number ofreservoir development alternatives, these cases aresimulated to the economic limit in order to estimate reserves. It is necessary to define the appropriate criteriafor reservoir abandonment conditions, such as minimumproducing rates, maximum water cut, minimum pressure, and other factors that determine the economic limit.
When a simulation model is used to estimate ultimaterecovery, it is important to recognize that results aresubject to considerable uncertainty, especially if themodel is developed for a reservoir with limited production history. However, the comparison of ultimaterecoveries from different development strategies can bevery meaningful and an excellent basis for choosingbetween alternative development methods for a field.
17.11 USE AND MISUSE OF RESERVOIRSIMULATION
The discussions in the preceding sections highlightsome applications of numerical reservoir simulation.One major advantage ofsimulation models is that it canbe used to evaluate different field development strategies at very small cost and without irreversible damageto the reservoir. The misuse of reservoir simulation,however, can lead to erroneous conclusions and costlymistakes.
The use ofreservoir simulators requires at least as muchexperience and engineering judgement as routine reservoir calculations. In considering the results obtainedfrom reservoir simulation, three questions must be asked:
I. Are the final parameters used to obtain a good history match reasonable?
2. Is the simulator used in the study appropriate forthe process under consideration?
3. Are the simulation results consistent with otherengineering calculations?
Forecasts of reservoir performance are more reliableduring the first few years. Longer term prediction tendsto be less reliable because errors caused by uncertainties in reservoir description become more significantwith time. Predictions of absolute value of recovery,for example, will be less reliable in the long term. However, comparison ofrelative differences between similarprediction cases are less likely to change.
220
DETERMINATION OFOILANDGAS RESERVES
A reservoir model should not be treated as a "black box"for turning out numbers. Reservoir simulation is no substitute for good reservoir engineering. Only intelligentuse of reservoir simulation can avoid costly mistakes.
17.12 SUMMARYReservoir simulation is a very useful tool for studyingreservoir behaviour, for comparing alternative field development strategies, and for forecasting production andestimating reserves. Reservoir simulation involves theuse of complex mathematical formulations, numericalapproximations, and reservoir descriptions, all ofwhichcontain many uncertainties. It is necessary to use goodengineering judgement in conducting simulation studies and in interpretating the results obtained.
The advances in computer technology show no signs ofslowing. This trend will facilitate widespread applications of reservoir simulation technology to petroleumreservoir engineering problems in the future.
ReferencesAguilera, R. 1980. Naturally Fractured Reservoirs.
PennWell Publishing Company, Tulsa, OK.
Au, A.D.K., Behie, A., Rubin, B., and Vinsome,P.K.W. 1980. "Techniques for Fully ImplicitReservoir Simulation." Paper presented at the1980 SPE Annual Technical Conference andExhibition, Dallas, TX, Sep. 1980, SPE 9302.
Aziz, K., and Settari, A. 1979. Petroleum ReservoirSimulation. Elsevier Applied Science Publishers,New York, NY.
Chase, C.A., and Todd, M.R. 1984. "NumericalSimulation of CO, Flood Performance." SPEJ,Dec. 1984, pp. 597-605.
Coats, K.H. 1978. "A Highly Implicit SteamfloodModel." SPEJ, Oct. 1978, pp. 369-83.
---. 1980a. "An Equation of StateCompositional Model." SPEJ, Oct. 1980, pp. 36376.
---. 1980b. "In Situ Combustion Model." SPEJ,Dec. 1980, pp. 533-54.
Coats, K.H., Dempsey, J.R., and Henderson, J.H.1971. "The Use of Vertical Equilibrium in TwoDimensional Simulation ofThree-DimensionalReservoir Performance." SPEJ, Mar. 1971, pp.63-71.
Crichlow, H.B. 1977. Modern Reservoir Engineering- A Simulation Approach. Prentice-Hall, Inc.,Englewood Cliffs, NJ.
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NUMERICAL SIMULATION
Gilman, lR., and Kazemi, H. 1988. "ImprovedCalculations for Viscous and GravityDisplacement in Matrix Blocks in Dual-PorositySimulators." JPT, Jan. 1988, pp. 60-70.
Jack, H.H., Smith, OJ.E., and Mattax, C.C. 1973."The Modeling of a Three-Dimensional Reservoirwith a Two-Dimensional Reservoir SimulatorThe Use of Dynamic Pseudo Function." SPEJ,Jun. 1973, pp. 175-85.
Mattax, C.C., and Dalton, R.L. 1990. ReservoirSimulation. SPE Monograph, Vol. 13.
Nolen, J.S. 1973. "Numerical Simulation ofCompositional Phenomena in PetroleumReservoirs." Paper presented at the 1973 SPESymposium on Numerical Simulation ofReservoir Performance, Houston, TX, Jan. 1978,SPE4274.
Stone, H.L. 1970. "Probability Model for EstimatingThree-phase Relative Permeability." Trans., SPEof AIME, Vol. 249.
Thele, KJ., Lake, lW., and Sepehrnoori, K. 1983."A Comparison of Three Equation-of-StateCompositional Simulators." Paper presented atthe 1983 SPE Symposium on ReservoirSimulation, San Francisco, CA, Nov. 1983,SPE 12245.
Todd, M.R., and Chase, C.A. 1979. "A NumericalSimulator for Predicting Chemical FloodPerformance." Paper presented at the SPESymposium on Reservoir Simulation, Denver,CO, Feb. 1979, SPE 7689.
Todd, M.R., and Longstaff, WJ. 1972. "TheDevelopment, Testing, and Application of aNumerical Simulator for Predicting MiscibleFlood Performance." JPT, Jul. 1972, pp. 874-82.
Warren, r.s., and Root, PJ. 1963. "The Behaviour ofNaturally Fractured Reservoirs." SPEJ, Sep.1963, pp. 245-55.
Youngren, G.K. 1980. "Development and Applicationof an In Situ Combustion Reservoir Simulator."SPEJ, Feb. 1980, pp. 39-51.
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Chapter 18
DECLINE CURVE METHODS
18.1 INTRODUCTIONThe decline curve is a basic tool for estimatingremaining proved reserves, and can be applied once thereis sufficient history to show a trend in a performancevariable that is a continuous function of either timeor cumulative production. Forecasts are made byextrapolating trends to an endpoint where productionis expected to cease (i.e., an economic limit or a relatedparameter such as water-oil ratio). Such forecasts areparticularly useful in the latter stages ofdepletion whentrends are clearly evident and there is insufficient revenue to justify a more comprehensive analysis.
The origin of decline curves is uncertain, but theirusefulness to monitor day-to-day operations likelypredates their use as a forecasting tool. Indeed, priorto the general trend to centralize and use computers forproduction accounting and engineering functions, itwas common practice for field offices to maintainproduction graphs to assist with day-to-day operations.
Decline curve methods have a universal appeal becausethey provide a simple visual representation of a complex production process. In some cases a visualinterpretation is too simplistic, and some backgroundknowledge is needed in order to draw reliable conclusions. In particular, it should be appreciated that forecastsare usually based on linear extrapolations of historicaltrends. Such extrapolations are strongly affected by anytransformation used to obtain a linear relationship. It isalso implicitly assumed that the factors causing the historical decline will continue during the forecast period.Some factors causing the decline are physical processes(e.g., pressure depletion, coning, interface movement)that are not easily changed. However, other factors suchas regulatory environment (e.g., well spacing, gas-oilratio penalties, maximum rates) and operating practices(e.g., type and size of artificial lift, hours of operation,frequency ofwork0 vers, gas gathering system pressure)can quickly change from time to time and from lease tolease.
222
18.2 SOURCE AND ACCURACY OFPRODUCTION DATA
It is worthwhile to review the source of the basic dataused to prepare decline curves. Production accountingfunctions such as royalty payments, allocation ofgroupproduction to individual wells, gas plant balances, andreports to regulatory agencies usually have a monthlyreporting and reconciliation period. Daily records ofhours ofproduction, test rates, system pressure and otheroperating variables are kept to make these monthly reports, but they are often discarded or placed in deadfiles after a few months. The permanently accessiblerecord ofproduction and injection data usually consistsofmonthly totals for gas, oil, and water production (injection), operated hours, and wellhead pressure. Monthlytotals are usually converted to daily rates for graphingpurposes because facility capacity, contract rates, andeconomic limits are usually expressed as daily rates.
The frequency and quality of well tests are the mostimportant factors affecting official production records.For gas wells, it is common practice to measure raw gasproduction for each well and to run annual deliverability tests. The measured production helps to ensurereliable well-by-well cumulatives; however, the seasonaland variable demand for gas can result in highly variable rates, and this tends to complicate decline analyses.For oil wells, it is common practice to measure groupproduction, and test individual wells monthly. The dayto-day demand for oil is less affected by markets, andmany oil wells are produced at capacity, which tends tosimplify decline analyses.
The least complex production facility is a single wellserved by a single-well battery. In such a facility, thereis no doubt about the source of the production. Themeasurement accuracy will also be reliable if the facility is properly sized. Among the most complex facilitiesare central treating facilities that serve several multiwell satellite batteries equipped with three-phase testseparators and operating at high pressure. In this case,the total (group) production of oil, gas, and water is
5
DECLINE CURVE METHODS
allocated to individual wells on the basis of theiroperated hours and test rates. The accuracy ofthis allocation depends upon the frequency of well testing andthe variation ofoil, gas, and water rates among wells. Agood indication of the allocation accuracy is given bythe quotient of theoretical production and measuredproduction for each fluid (e.g., oil, gas, and water).
Theoretical production is the piece-wise sum of theproduct of test rate and time interval. These quotients(called proration or allocation factors) are usuallyconsidered to be acceptable if they are in the range of0.95 to 1.05. It should be noted that errors in test ratesor producing hours will cause misallocations amongwells and pools. Errors in gas-oil and water-oil ratioscan be somewhat larger because the allocation factorfor each fluid may differ (e.g., an oil allocation factorless than 1.0 and a water allocation factor greater than1.0). Thus, gas-oil ratio and water-oil ratio curves oftenshow more "noise" than their corresponding rate curves.
18.3 TERMINOLOGYThe following are definitions of terms used in thischapter:
Decline curve: the generic label applied to manydifferent types of charts, graphs, and data representations. The most basic decline curves show the changein oil, gas, or water production rate with time (rate-timegraphs). The production rate is usually expressed asvolume per day to facilitate understanding; however,hourly, weekly, monthly, and yearly rates may also beused. Graphs with time as the independent variable areeasily understood and the rate-time data is directly applicable to economic evaluations. The other commonindependent variable is cumulative oil or gas production (rate-cumulative graphs). The advantage of theseis that an extrapolation to the economic limit yields adirect estimate of the proved reserve.
Calendar-day rate: the monthly total production(injection) divided by the number ofdays in the month.
Operated-day rate: . the quotient of monthlyproduction (injection) and actual operated hours in themonth multiplied by 24. If calendar-day and operatedday rates are plotted on the same graph, any separationof the curves is a measure of the shut-in or down time.Ifthere are no rate controls, the area between the graphsis a measure of "lost production." Operated-day ratesmay define a better decline trend than calendar-day ratesbecause they smooth out the variation caused by downtime.
Ratio curves: the gas-oil ratio (GOR) and water-oilratio (WOR) curves that are commonly plotted for oilwells, These ratios are a measure of the efficiency ofthe oil production process. An increase in either oftheseratios is usually accompanied by a decrease in the oilrate. GOR penalties are often applied as a rate controlmeasure to limit the amount ofreservoir voidage causedby high-GOR wells. For gas wells, the correspondingratios are condensate-gas ratio (CGR), liquid-gas ratio(LGR), and water-gas ratio (WGR). The CGR is a measure of the richness of the raw gas. In gas cyclingschemes, the CGR decreases with increasing dry gasbreak-through. The WGR ratiois a measure of'production problems associated with liquid buildup in wells,hydrates, and water coning.
Cut curves: the fraction ofoil or water cut in the liquidproduction from oil wells. These curves are anothermeasure of the efficiency of the oil production process.Their fixed range (i.e., 0 to I) provides an alternativecriterion for an economic limit.
Reservoir performance charts: the compositepresentation ofrate-time graphs supplemented with reservoir data (e.g., reservoir pressure, interface depth) andperformance variables (gas-oil ratio, water cut, numberof producing wells, water injection, cumulative oil).These charts are often maintained for a lease or unitby the operator, and for a field or pool by a regulatoryagency. Figure 18.3-1 is an example of a reservoirperformance chart for the gas-cycling and gas-capoperations for a pool in Alberta. In the figure, IR is theinjection rate and cd is the calendar day. WGR is thewater gas ratio.
Production performance charts: charts graphed onsemi-log paper which utilize the fact that the product orquotient of two straight lines on semi-log paper is another straight line with a slope related to the slopes ofthe other two. The idea is to use this slope interdependence to help estimate the decline rate. The advantageis that the decline should be more reliable because moreofthe data has been used to estimate it. Figure 18.3-2 isan example of a production performance chart for apumping well where the production is controlled by theartificial lift. The gas production is not shown becauseit is not a factor in the decline. The slopes of the oil,water and WOR curves are interrelated.
18.4 SINGLE·WELL VS. AGGREGATED·WELL METHODS
Decline curve methods may be classified many ways;however, any classification should recognize the difference between analyses for a single well and analyses
223
DETERMINATION OF OIL AND GASRESERVES
100
(I)
q. (rna/d)
- - - - - - - Operated-day Rate--- Calendar-day Rate
d (dq~dt)-b= ---'--
dt
10
40
Figure 18.3-2 Production Performance Chart
18.5 DECLINE CURVE METHODS FORA SINGLE WELL
Decline curves are a visual tool, and it is easy tooverlook that trends and extrapolations (linearor curved)are defined by mathematical equations. The most common equations were given in classic papers by Arps(1945,1956). Table 18.5-1 summarizesArps'rate-timeand rate-cumulative equations along with dimensionless time and production groups proposed by Gentry(1972). The decline relationships in Arps' first paperwere based on the loss ratios between equal time intervals. While these relationships were useful for tabulardata, they are ofless interest today with the easy accessto computers and graphing programs. Mead (1956) refined the loss ratio and series methods and was amongthe first to attempt to associate the type of decline withthe drive mechanism. The equations in Table 18.5-1 aresolutions to the following differential equation:
'C M-e.Q •Me~~ 24
~ :E'£!; •
16 •~ '"'" E,'C 8 o
M.Q eMe 8 24 ·0
~o G
16~oE,
8 o
Figure 18.3-1 Reservoir Performance Chart
a:
~01::7-';47=5T-7"".n:I7::'. 7"'91""". ",,0 6"',T""6""26"'3T""64"T6=-=5T""9."T6=7T""66:r6=-9f:"90:r9""f:"92:r9::13
for aggregated production from a group of wells.Decline curve analyses for single wells are widely usedand readily interpreted because they have the followingadvantages:
• All the raw data can be displayed.
• Decline trends are easy to recognize and oftencorrelate with the total fluid production rate.
• The economic limit can be directly applied toestimate reserves.
• The conventional decline equations have been shownto have a strong foundation based on reservoirengineering principles.
On the other hand, decline curve analyses and forecastsfor aggregated production from a group of wells arealso widely used, but may be misinterpreted for thefollowing reasons:
• Only part of the raw data can be displayed.
• Decline trends may be masked by the number andvariability ofthe wells contributing to the aggregatedproduction.
• The economic limit cannot be directly applied toestimate reserves.
• The analyses are largely empirical (may be enhancedby statistical analysis).
224
_______________________1
DECLINE CURVE METHODS
where b decline exponentq = producing ratet = time
At the time they were formulated, the equations wereconsidered to be empirical and were classified as exponential, hyperbolic or harmonic. The classification wasbased on the value of the exponent, b, used to characterize the change in decline rate with the rate ofproduction. The classification is still widely used, but itis now recognized that the value of b is not limited tothe range 0 ~ b ~ 1.
Table 18.5-1 Decline Curve Equations
18.5.1 Exponential DeclineExponential decline is most commonly used becauseboth the rate vs. cumulative and the log (rate) vs, timegraphs are linear. Figure 18.5-1 is an adaptation ofa normalized rate, q/q., vs. a normalized cumulativerelationship, N'/(NP)l yr s by Schoemaker(1967) showing both decline rate, d, and time, t, as parameters. Thediagram uses one year as the reference time, anddecline rates are expressed as percentage per year. Thechart illustrates a subtle difference between the slope,a, and the annual decline rate, d. Various combinationsof decline rate and time (such as d = 5%, t = 10 years;
Type of Decline
Characteristics
Exponent
Rate-timerelationship
Rate-cumulativerelationship
Dimensionlesstime, td
Dimensionlessproduction, q"
Exponential
Decline is constant.
b=O
-]
I_(~qi)N,=
q, t In (~)
Hyperbolic
Decline varieswithinstantaneous rateraised to power "b."
-1q= qJI + ba, t)'
b
(~) -Ia.t> ---, b
Harmonic
Decline is directlyproportional to theinstantaneous rate.
b = 1.0
a,t=(~)-I
In (~)~---q-
qt m- l
where a = decline as a fraction of producing rate (slope of line)ai = initial decline rateb = decline exponente = natural logarithm base 2.71828Np = cumulative productionq = producing rate at time (t)qi = producing rate at the beginning of the declinet = time
Source: After Arps, 1956;Gentry, 1972.
225
-----=-r-/;;"', IDETERMINATION OFOILAND GASRESERVES
Schoemaker shows how Figure 18.5-1 can be used tosolve many practical exponential declineproblems. Hepoints out that fiveparametersare used in the equations(q, q, Np, t, and either a or d) and, when any three areknown, the other two can be determined from thefigure. For example, if a new well has a capacity of
d = 10%, t = 5 years; and d = 50%, t = I year) do notresult in the same final rate, q/qi' Values of 0.6,0.59and 0.5 can be read from Figure 18.5-1.The differencein rate is due to the number of times the annual declinerate is applied(becauseofthe similarityof declinecurvecalculations to compound interest or depreciation calculations). The slope, a, corresponds to very shortcompound periods,and inthemathematical limitingprocessis calledcontinuous compounding. The decline rate,d, is related to the decline slope, a, by the expression:
d = I - e' (2)
100 m3/d and is expected to decline at 10 percent peryear, what will the rate and cumulative production beafter 10years? The answers can be read from the intersection of the 10 percent decline and 10-year lines(i.e., q/q; = 0.35 N/(Np)1 r = 6.18). Thus, after 10years, the rate will be 35 m /d and the cumulative willbe 100 x 365 x 6.18 =225660 m3•
18.5.2 Hyperbolic DeclineWith hyperbolic decline, the decline is proportional tothe productionrate raisedto the power b. Unfortunately,hyperbolicdeclinedoes not plot as a linear relationshipon commongraph papers (i.e., linear, semi-log, or loglogco-ordinates). Priorto the widespread use ofpersonalcomputers, this lack of linearity was the main reasonfor the restricted use of hyperbolic declines. Slider(1968)preparedtransparent overlays (each overlayhada fixed b-value and a family of decline rates) that couldbe visually matched to log (rate) vs. time graphs. Once
10983 4 567Normalized Cumulative Production, Np/(Np)1 y'
2
0.3 1-----hI-+--\-iL.IJ-~:.+¥W~_",._¥~¥~_J!."___A.,._,,A.,._,,jL~.L-_bA=Lj__r::::::,"5<""1 \'0 'lIS
ZO'lIS
Source: After Schoemaker, 1967.
Figure 18.5-1 Exponential Decline Chart
226
---------------------_..".
DECLINE CURVE METHODS
f(b) = Y(x" - I) (1- b) - b (1 - x·· I) (3)
where x = q/qy = N/(qjt)b = decline exponent
The authors then used standard numerical techniquesto find the roots of this equation (i.e., f(b) = 0). Theequation was demonstrated to have at least two roots,one at b = 0 and another at b = 1. In general the equation behaves as a cubic equation with three real rootsincluding b = 0 and b = I. If the decline is truly exponential or harmonic, then the data will also satisfy thedimensionless production equations for these declinesin Table 18.5-1. The value of "b" need not lie betweenoand I. Because this is a general solution, it shows thatnegative values are also possible. The method is actually a numerical equivalent of Gentry's graphicalsolution based on Figures 18.5-2 and 18.5-3. It shouldbe noted that both methods assume that any typeof decline is specified by two rates, the cumulativeproduction, and the actual time on production (i.e., qj'q, Np' t). Ifthe production rigorously followed the Arps'equations and there were no measurement or reportingerrors, then everyone using the method would get thesame answer. Unfortunately, because real data does notrigorously follow the equations and has some noise, themethod is data-dependent. When different data pairs areused, different values may be calculated for botha and b. The method does not give a quality or"goodness-of-fit" criterion, but if the theoretical curve
o0.20.6 0.4q, = Np/(q,t)
0.8
1.0:f- ~~~,y
Source: AlterGentry, 1972.
Figure 18.5-3 Decline Curve Analysis ChartRelating Production Rate toCumulative Production
10.0the overlays were prepared, the visual matching technique could be applied with about the same ease as anexponential decline extrapolation.
The next development in handling hyperbolic declineswas based on the dimensionless groups shownin Table 18.5-1. Gentry used these groups to developthe generalized rate-time and rate-cumulative graphsshown in Figures 18.5-2 and 18.5-3, respectively.Figure 18.5-2 is simply the family of rate-time graphsfor a unity decline rate (a, = 1.0). It should be noted thatthe exponential decline (b = 0) plots as a straight lineas expected on the log rate vs. time co-ordinates.Figure 18.5-3 is more difficult to understand becausethe transformation to dimensionless production changesthe character of the graph. This figure is not directlycomparable to standard rate-cumulative graphs. It shouldbe noted that the harmonic decline (b = I) does not plotas the expected straight line on the log rate vs. cumulative co-ordinates. Figure 18.5-3 shows that thecumulative production is strongly related to b, but somecalculations are required to quantify the sensitivity inevery case. To apply Gentry's method, two rate-timepairs are read from a decline graph, and these valuesalong with cumulative production over the time periodare applied to Figure 18.5-3 to determine b. With aknowledge of b and the time period between points,Figure 18.5-2 is used to calculate the decline rate.
Agbi and Ng (1987) showed that the dimensionless production equation for hyperbolic decline in Table 18.5-1can be expressed as a nonlinear equation with "b" asthe only unknown.
Figure 18.5-2 Decline Curve Analysis ChartRelating Production Rate to Time
Source: After Gentry, 1972.
227
DETERMINATION OFOILANDGASRESERVES
is plotted on the same scale as the raw data, a visualcomparison is always possible.
In many cases the purpose of decline analysis is toestimate the value of future production. Experiencedevaluators avoid extrapolating hyperbolic declines overlong time periods because they frequently result in unrealistically high reserve and value estimates. Thecharacteristic of hyperbolic decline (i.e., continuouslydecreasing decline rate) can result in extremely longproducing lives that are incompatible with experienceelsewhere and with expectations for equipment life.Many wells are observed to trend toward an exponential decline in their later life. Figure 18.5-4 is a log ratevs. time overlay developed by Long and Davis (1988)to cope with this problem. Each line on Figure 18.5-4is for a fixed b-value. The range extends from 0.3 toI.7, which allows handling of those wells whereb-values greater than 1.0 have been observed, e.g., inAlberta tight gas (Milk River) and fractured and heterogeneous reservoirs (Austin Chalk and Spraberry). Thenumbered dots on Figure 18.5-4 correspond to tangentpoints where an exponential decline would start with
the specifiedexponential decline rate (slope). The powerof the method is that it uses all of the data to establishthe nature ofthe decline, but allows selection ofa pointat which the decline is expected to hold the decline rateand follow an exponential decline. The method is particularly suited where monthly production rate is plottedon standard three-cycle graph paper.
Robertson (1988) developed the following productionrate equation, which is hyperbolic initially, butasymptotically exponential with time:
(4)
where ~ = a dimensionless constant to controlhow strongly hyperbolic the initialdecline is before asymptoticallybecoming exponential
The value of ~ ranges from 0 to 1.0 and is related tothe abandonment pressure and the rock and fluidproperties. This equation provides for another slack
10' ,------------------------------------,
b=1.7 3
b = 1.3
b= 1.5
b = 1.1
b = 1.0 5
5
4
6
Hyperbolic Decline Type Curves3-Cycle Semilog x 20 Years
95
8060
5040
30
10 Li-L..1-.LJe-.J.-L..1-l.2l.-L...L.LJe-.J.-L...LL..l-l..-L-L..L.l-L...L.J.:::J=--....L-L...LL.l-L...LL..l..-LJ-J
o 12 24 36 48 60 72 84 96 108 120 132 144 156 168 180 192 204 216 228
Source: Long and Davis. 1988. Time (months)
Figure 18.5-4 Hyperbolic Curve Overlay
228
_______________________ I,
DECLINE CURVE METHODS
parameterto fit actualdataby an analytical decline equation. Although the author did not recommend it, theequation provides a mathematical framework toperforma fully numerical curve fit with results very similar tothe manual and visual process of Long and Davis (i.e.,similar to the Agbi and Ng extension to the Gentrygraphical solution).
Lack of linearityof hyperbolic declines is no longeranobstaclewhendataare displayedandprocessedby cornputer. There are numerouslow-cost softwareprogramsfor performingdecline curve analysis. Most programsapply a least-squares criterion to find the value of "b"which best fits the reported production data. Once "b"has been determined, the production data are displayedon the samegraphwith the theoreticaldeclineand forecast. Some programs allow manual changes to theleast-square parametersto obtain a personalized visualfit to the data.
18.5.3 Harmonic DeclineHarmonic decline is a special case of hyperbolicdecline in which the decline rate is directly proportional to the instantaneous production rate. The ratecumulative relationship from Table 18.5-1 shows thatharmonic declinewillplot as a straightline on a log ratevs. cumulative plot. Figure 18.5·5 is a productionperformance graph for a Blairmore oil well, whichillustrates severalsegmentsof harmonic decline(Purvis,1987).
The rate and ratio curves are somewhat erratic due tomeasurement andbatteryprorationerrors. Thetotal fluidproductionrate, qw + qo' is determinedby the size andoperatingspeed of the artificial lift equipment. Duringthe past 30 years the total fluid rate has varied widelywith a few periodsof relativelystablerate. It is interesting to note that during these dramatic changes in rate,the WOR + I graph has shown moderate sensitivity torate.This is surprisinggiven that duringtheperiod 1974to 1976, the qw + ~ rate was about 10 times the initialrate.
Anotherinteresting feature of Figure 18.5-5 is the shapeof the cumulative water plus cumulative oil (Qw+ Qo)graph. Thegraphisinitiallyconcavedownward, butaftera periodofcontinuous waterproduction, thegraphtrendstoward a straight line. In fact, three rectilinear sectionsof this graph are evident.The slopes of these three segments were transferred to the WOR + I graph. This isa useful characteristic of harmonic decline, whichcan be applied after a period of continuous waterproduction. The reason for this particularcharacteristicis that the derivative, d(Qw+ Qo)/ d(Qo)' equals
10' 0------------------,2 ,
Qw+Qo(10 mid) _
q. + q, (m'/d)
10
10
o 20 40 60 80
Cumulative Oil Production (10' m')Source: AfterPurvis. 1987.
Figure 18.5-5 Production Performance Graphs
WOR + I. The functional relationship can be demonstrated as follows. Any linear segment of the Qw+ Qograph has the functional form
(5)
which, when differentiatedwith respect to Qoyields
d(Q. + Q,) = WOR + I = C 10"· '2Q, (6)d(Q,) 3
where ct, c2' cl = data-specificcoefficients
Consequently, the dash line approximations of the ~graphweredrawnto honour the usual slope interdependence among the graphs. Because the well is part of amulti-well pool, no conclusions can be drawn on theeffect the well ratehas on pool recovery.However, it isclear that increasedrates have increasedrecovery fromthis particularwell.
229
18.5.4 Dimensionless Solutions andType-Curve Matching
Fetkovich (1980) used simplified material balance andinflow performance relationships for both gas and oilwells to show that the Arps' empirical equations matchup with some ofthe classical solutions to the radial flowdiffusivity equation. Exponential decline was shown tobe the long-time solution to the constant terminalpressure case (constant bottom-hole pressure). Theshort-time (transient) solution is a function of thereservoir size expressed as r/rw ratios (r, = externalboundary radius, rw = wellbore radius). Fetkovich demonstrated that for oil wells (slightly compressiblesingle-phase flow) the type of decline does not changewith the drawdown. On the other hand, for gas wells(compressible single-phase flow) it was demonstratedthat a change in back pressure changes the type of decline. This finding helps explain the reliability ofdeclineanalysis for oil wells. In many practical cases, wells areproduced at capacity and the bottom-hole pressure doesnot change significantly over time (i.e., the well ispumped off). Fetkovich demonstrated that empiricaldecline curve analysis has a solid theoretical base.
10
DETERMINATION OF OIL AND GAS RESERVES
Figure 18.5-6 shows his analytical transient type curvescombined with Arps' empirical depletion type curves.The depletion type curves are essentially the same asthose proposed by Gentry; however, Fetkovich plottedq/qj instead of q/q and used log-log coordinates tofacilitate type-curve matching. It is apparent from Figure 18.5-6 that the transition from transient to depletionbehaviour occurs at a dimensionless time of approximately 0.3. Figure 18.5-6 also shows that until thedimensionless time exceeds 0.3, it is impossible to knowthe type of decline that ultimately develops. Thus, thesafest approach to extrapolating trends early in the lifeof a well is to assume an exponential decline.
Type-curve matching was first used to interpretpressure buildup and drawdown data. The procedure involves comparing the pressure-time data from a wellwith a family ofdimensionless solutions. The same general procedure is used for decline data. Fetkovichsummarizes the procedure as follows:
I. The actual rate-time production data are plotted ona log-log tracing paper of the same size as the typecurves to be used. Any convenient units can beused for rate or time because a change in units
~I:~, I
,
So <0
<00 100
100 1000
Transient+ Depletion
1.0r'/rw = 100000
ExponentialCommon to Analyticaland Em irical Solutions
Analytical Type Curve Solution
10.1
tdO
10
Source: After Fetkovich, 1980.
Figure 18.5-6 Composite of Analytical and Empirical Type Curves
230
__________________________6
DECLINE CURVE METHODS
simply causes a uniform shift of the raw data on alogarithmic scale.
2. The tracing paper with the data curve is placed overa type curve and shifted until a good match is obtained. The axes of the two curves must be keptparallel during this process. Several different typecurves should be tried to obtain the best fit ofall thedata.
3. To make a forecast, the type curve is traced ontothe tracing paper overlay. Future rates are then simply read from the real-time scale on which the rawdata was plotted.
4. To evaluate deciine-curve constants or reservoirvariables, the type of decline is noted and a matchpoint is selected anywhere on the overlapping portion of the curves. With a knowledge of the typeof decline and the coordinates of the match pointon both sheets, the constants or variables areevaluated from the appropriate dimensionlessrelationship.
Many software programs for performing declineanalysis facilitatea computerized Fetkovich overlay procedure. These programs greatly facilitate matchingactual data to any of the numerous type curves and areparticularly useful for analyzing gas wells and otherwells with extended transient behaviour.
18.6 DECLINE CURVE METHODS FORA GROUP OF WELLS
Estimating the reserves for a group ofwells could be anonerous task if a decline analysis were performed foreach well. Consequently, it is common practice to perform one decline analysis for the aggregated productionfrom all the wells in a lease or pool. While this is common practice, it is not as reliable as one might assume.When the production from a group of wells is aggregated (summed), only the total is available for plotting,and much of the raw data is omitted from the analysis.Sometimes the average-well rate is plotted to make theanalysis appear more like that for a single well. Another major difficulty is that the economic limit is notclearly defined for aggregated production. This difficulty also makes forecasts hazardous because some ofthe wells will be abandoned during the forecast and willno longer be contributing to the aggregate. Clearly, thetheoretical base for aggregated production is not as solidas that for single wells.
Despite the foregoing problems, decline curve analysiscan be successfully applied to aggregated production.For example, if there is a wide variation in rates, the
analysis can be improved by splitting the wells into afew groups having similar characteristics (e.g., rates,water c~ts, remaining life, well spacing, gas-oil ratios).By making sub-groups of wells with similar remaininglives, an economic limit can be applied with more confidence. To establish a reliable decline for tight gas pools,the wells should be grouped on the basis of their onproduction date and initial production rate. In general,aggregate rate vs. cumulative curves exhibit declinetrends which are easier to interpret (i.e., better defined)than those for aggregate rate vs. time curves.
Figure 18.6-1 is a production-performance graph for theLeduc D-3 A Main Pool showing its final 19 years ofoil production. The pool had an oil zone of11.6 m sandwiched between a large gas cap and an aquifer. By 1974the oil zone's thickness had decreased to about 2.5 mand, by the start of gas cap blowdown in November1989, the oil zone was less than 1 m thick. Figure18.6-1 shows that three correlation segments are requiredto account for the distinct change in the slopes of thecurves related to pool oil operations. The gas production from oil wells (solution plus coned gas) wasconstrained by the portion of the Devon gas conservation plant capacity available to the pool. Thus dependingupon the available capacity, many ofthe highest-GORwells would be shut in. Also in September 1978, thepool water handling (artificial lift and treating capacity) became another constraint and contributed to thechange in slope of the '10, qo + qw' and oil cut curves.From 1984 to 1988, several wells were worked overand every effort was made to maximize oil recover;prior to the impending gas cap blowdown. Afterblowdown commenced, wells were shut in as the aquifer displaced the extremely thin oil zone past thecompletion intervals of the oil wells.
It is apparent from the linearity of the dash lines thatvalid rate forecasts could have been made after a shortbit of history in each correlation segment. Figure18.6-2 is the corresponding rate vs. cumulative graph.A good estimate of ultimate recovery could have beenmade from this graph as early as 1975. Note also thatthe straight-line segments on Figures 18.6-1 and 18.6-2are characteristic of exponential decline.
18.6.1 Statistical MethodPurvis (1990) showed that many of the deficiencies ofdecline analysis for a group of wells can be overcomeby using a log-normal distribution to quantify thechanges in well rates over time. The method provides ameans of forecasting future well counts through properapplication of the well economic limit. The method
231
DETERMINATION OF OIL AND GAS RESERVES
Figure 18.6-2 Rate-Cumulative Production Graph
was applied in Alberta to the Redwater 0-3, SwanHills BHL C, Twining Rundle A, and Viking KinsellaWainwright B Pools.
Figure 18.6-3 shows some historical and forecastdistributionsofwell rates for the Pembina Cardium Pool.The pool has been penetrated by over 5000 wells. InJune 1990, there were 3411 producers and 1426 injectors, but only 2716 producers and 1037 injectors wereoperated. The number of inactive producers and
injectors indicates the maturity of the waterflood andthe fact that, at current prices, it is uneconomic to operate over 1000 wells. In December 1970, the median wellrate was 4.25 m3/d, and by October 1990, it had decreased to 1.53 mvd. The dash lines show that themedian well rate is forecast to decline to 0.45 m3/d bythe year 2030. The variance of the distribution has continuously decreased, as shown by the decreased slopeof the distributions. A significant feature of the plot isthat the lines for years 1982, 1986 and 1990 tend tofocus and pivot at about 0.3 m3/d/well and 2 percent ofwells. This focus is taken to mean that the economiclimit is about 0.3 m3/d/well and that typically 2 percentof the wells are at, or below, the economic limit at anytime.
The coordinates of Figure 18.6-3 are representative ofthe log-normal distribution, the properties ofwhich arethe subject ofa classic textbook (Aitchison and Brown,1966). The linearity of the well rate distributions indicates that they are approximately log-normal. Themedian for the log-normal distribution is the arithmeticaverage of the logarithms of the population (i.e.,numerically the geometric average). The small circlesat 50 percent of the wells in Figure 18.6-3 are the geometric averages of the numeric values used to plot thedistributions. These values are in good agreement withthe values that would be read from the graph. Indirectlythe circles show that the distribution is approximatelylog-normal. Table 18.6-1 summarizes other numericalaverages and also summarizes the results of chi-squaregoodness-of-fit tests of the raw data when divided into13 equally spaced class intervals.
The log-normal is characteristic of phenomena orprocesses defined by multiplication (or division).Examples oflog-normal distributions range from sedimentary petrology (Podruski et aI., 1988) to the probitmethods used for biological assays. There are good reasons to expect well production rates to have a log-normaldistribution.The radial flow equation that defines steadystate production rates simply multiplies anddivides parameters that are constant or that change veryslowly. The two most important terms are the pay thickness and permeability which are often log-normallydistributed. These actually help to ensure a log-normalrate distribution because the product of two log-normaldistributions is another log-normal distribution.
The rate-ratio-cumulative graphs in Figure 18.6-4 showthat the pool has been on continuous decline for 20 years.The linearity ofany rate graph on the linear coordinatesis characteristic of exponential decline. The most
33
0.1---Oil Cut
q, (m'/d/well)
Producing Wells
27 29 31
Cumulative 011 Production (106 m3)
.,--- ---,1
10
TImeLine(years)
-
10'
l!.E 2
"0
Figure 18.6-1 Production Performance Graph
232
--------------- ..sa
DECLINE CURVE METHODS
10.1 L--J..._'----'-_'--.L-.L-.L--'---'-_-'-_----'2 5 10 20 30 40 50 60 70 80 90 95 98
Percentage of Wells
notable change in Figure 18.6-4 is the levelling ofpoolwater production at about 20 000 m3/d in 1975.The levelling occurred after the pool was put on goodproduction practice and voidage replacement was relaxed. The pool oil rate exhibits different decline ratesbefore and after the water production rate levelled. Themedian well decline rate was less affected by the change.It is not clear from Figure 18.6-4 if the decline is several segments of exponential decline or if the levellingofoil rates is due to harmonic decline. Some ofthe mitigation ofpool oil-rate decline from 1980 through 1986was due to increased well count (re-activations and newdrilling) and through judicious selection of the wellsto be operated. Since 1986 the pool performance hasdeteriorated significantly.
The forecasts shown by the dash line were calculatedon the basis of exponential decline rates of 3 and 4 percent per year for the median well rate and the pivot pointshown in Figure 18.6-3. The same forecasts on logarithmic coordinates are shown in Figure 18.6-5 whichillustrates that it would not be realistic to assume alinear (i.e., harmonic) extrapolation of either the poolrate or median well rate. The median well rateonly changes from 4.25 to 1.53 m3/d so it appears linearon both linear and logarithmic coordinates. Thecalculations for Pembina support the pragmatic approachof limiting a harmonic decline to some time periodfollowed by an exponential decline. Forecasts based onharmonic declines of 3 and 4 per cent for the medianwell rate resulted in ultimate recoveries of 212 and207 million m3, respectively. These forecasts were not
+2Standard Deviation
-1 0 +1
12 197012 197412 197812 198212 198610 1990
a;
roi(])
1iiII:
(5
1
10
Figure 18.6-3 Distribution of Well Rates,Pembina Cardium Pool
Table 18.6-1 Statistical Parameters for Pembina Cardium Pool
Statistics for Raw Data Date (month-year)
12-1970 12-1974 12-1978 10-1982 12-1986 10-1990
Numberof wells 2681 2490 2481 2514 2658 2615Arithmetic average 8.61 5.89 4.01 3.20 2.77 2.07Geometric average 4.25 3.33 2.57 2.20 1.90 1.53Harmonic average 2.43 1.88 1.58 1.45 1.30 1.13Standard deviation 13.35 7.79 4.84 3.33 2.90 1.84Coefficient of variation 1.55 1.32 1.21 1.04 1.05 0.89Variation 0.68 0.65 0.60 0.57 0.58 0.54
Lorenz measure 0.59 0.55 0.48 0.45 0.46 0.42X' Goodness-of-fit test forlog-normal (13 class intervals) 4.15 17.15 14.53 16.79 6.48 7.87
233
7
--.rDETERMINATION OF OIL AND GAS RESERVES
24 ,---,-"7"<--,-----.----r--..,.--.,.---, 105r--------- ~
o
'"'"oco'" ~
! , " ,', I" '.",1,, , I
Oil and Water Rate (m3/d)
~,."Oil Rate (m3/d) ~,
"\ \\ \" \ \
" I I" \ 13%\\4%
"\III
Well Count (x 10') II_______- .........~%113%
""\\1\I I113%
4%
:=><--3 ~-Median Well Rate (m Id) "-, -_, ,
\ \\ \3%
4%
10
103
10'
-~--4%" '3%-
,,--.
"4% ~~ -, 3%g'"~ ~
" ""'''''11'11'
Pool Oil Rate (10' m'/d)
---
WaR (m'/m')
Pool Water Rate (10' m'/d)
Median Well Rate (m'/d)4
2
4
a
8
2
16
16
24
220100 140 180
Cumulative Oil Production (10' m')220100 140 180
Cumulative Oil Production (10' m')
a I---.--=r--,--,.-....,...---r----r--i60
Figure 18.6-4 Rate-Ratio-Cumulative Graph,Pembina Cardium Pool
Figure 18.6-5 Production Performance Graphs,Pembina Cardium Pool
believed because of the extremely long producing lifefor the pool.
18.6.2 Theoretical MethodsSimple theoretical models are sometimes used to makeforecasts of pool production. These models can oftenbe rearranged into rate-time or rate-cumulative equations to prepare a family of forecasts which have somekey, but uncertain, reservoir property such as permeability as a parameter. The family of forecasts can thenbe used for matching aggregated pool production (i.e.,similar to the type curve matching of individual wellproduction).
The performance of pools where oil is displaced byeither natural water drive or by water injection canoften be characterized by a semi-log plot of WOR, oilcut, or water cut vs. cumulative recovery. To provide atheoretical basis of these cut-cum curves, Ershagi andAbdassah (1984) proposed a co-ordinate transformationbased on fractional flow and Welge's recovery formula.
Lohec (1984a) demonstrated the effect of reservoirgeometry on production rate in reservoirs involving frontal displacement mechanisms. He noted that reservoirgeometry is one of the first characteristics ofa reservoirto be defined and understood (e.g., seismic structure definition, well control, gas-oil and water-oil contacts). Ifthe frontal displacement is gravity-dominated, theremaining hydrocarbon volume often approximates asimple geometric shape (e.g., a cone, wedge, or cylinder) and simple expressions may be developed for thechange in hydrocarbon volume with hydrocarbon recovery. Next, the rate ofproduction is assumed to havea simple power law relationship to the remaininghydrocarbon volume. These simple expressions providethe theoretical basis for calculating rate-cumulative andrate-time performance (i.e., the same role that materialbalance and inflow performance relationships play indeveloping type curves for wells). Lohec (1984b)applied the method to the East Texas, Friendswood,Conroe, and Hawkins fields.
234
7
DECLINE CURVE METHODS
Richardson and Blackwell (1971) showed that severalreservoir flow mechanisms have an element ofsymmetry and a single dominant force such that a simplemathematical model could be developed to forecast reservoirperformance. Their models for gravity segregationand water under-running are simple enough to be usedas the theoretical basis for some decline curve analysis.
18.7 SUMMARYDecline curves are widely used to convey informationabout past production performance and to forecast future performance and reserves. The following tips andprecautions should be noted:
I. Production decline is caused by one factor or acombination of factors including reservoir depletion, equipment wear, operating practice, andregulatory environment. It is risky to extrapolatehistorical trends without understanding the factorscontributing to the decline or anticipating new factors that can come into play. For example, thedecline ofan oil well in an undersaturated pool willchange as the pool pressure decreases below thebubble point. Failure to anticipate such a changecan negate what would otherwise be reasonable extrapolation of past performance.
2. The product or quotient of two exponentials isanother exponential. This recursive characteristicis useful for any linear functions on semi-log paper.For example, if the oil rate and gas rate are linearon semi-log paper, the gas-oil ratio must also belinear, with a slope related to the oil and gas rates.Similarly, iftotalliquid production is constant (typical ofpumping wells) then both oil rate and oil cutmust have the same slope. Another example ofslopeinterdependence is that a trend of increasing totalfluid production will tend to offset or mitigate anoil rate decline.
3. The misallocation ofgroup production to individualwells can cause ratio curves to be more erratic thanthe corresponding rate curves.
4. Decline curves for single-well pools produced atcapacity have the strongest theoretical base followedby single-well analysis in multi-well primaryproduction pools. Well-by-well decline trends inmulti-well pools subject to pattern floods can bedifficult to recognize and forecast due to fluidmigration.
5. Decline curves for aggregated production from agroup ofwells do not have a strong theoretical base,but with appropriate caution and understanding, theanalysis can be reliable.
6. Experienced evaluators often use an exponentialdecline to extrapolate a hyperbolic decline to prevent unrealistically long lifetimes and reserveestimates.
7. Dimensionless type curves are powerful tools foranalyzing and forecasting individual well behaviour.These curves are particularly useful for tight-gasand other wells with extended transient behaviour.
8. Well production rates for a group ofwells producedat capacity can be characterized by a log-normaldistribution. Consequently, the decline rate for themedian well is the statistically significant declinerate for aggregated production.
9. All of the available data (e.g., reservoir pressure,gathering system pressure, injection volumes, etc.)should be plotted and considered when extrapolating a decline trend to make a production forecast.
10. The results of simple theoretical models andvolumetric calculations may be used to constrainand enhance forecasts starting from an observeddecline trend.
ReferencesAgbi, B., and Ng, M.e. 1987. "A Numerical Solution
to Two-Parameter Representation of ProductionDecline Curve Analysis." Paper presented atPetroleum Industry Applications ofMicrocomputers, Montgomery, TX, Jun. 1987,SPE 16505.
Aitchison, J., and Brown, J.A.C. 1966. TheLognormal Distribution. The University Press,Cambridge, U.K.
Arps, U. 1945. "Analysis of Decline Curves." Trans.,AIME, Vol. 160, pp. 228-247.
---,. 1956. "Estimation of Primary OilReserves." Trans., AIME, Vol. 207, pp. 182-191.
Ershaghi, L, and Abdassah, D. 1984. "A PredictionTechnique for Immiscible Processes Using FieldPerformance Data." JPT, Vol. 36, pp. 664-670.
Fetkovich, MJ. 1980. "Decline Curve Analysis UsingType Curves." JPT, Vol. 32, pp. 1065-1077.
Gentry, R.W. 1972. "Decline-Curve Analysis." JPT,Vol. 24, pp. 38--41.
235
s
Lohec, R.E. 1984a. "Analytic Approach EvaluatesFrontal Displacement Mechanism." O&GJ,Vol. 82, No. 38, pp. 83-89.
---. 1984b. "Analytic Approach Applied toKnown Reservoirs." O&GJ, Vol. 82, No. 39, pp.92-97.
Long, D.R., and Davis, M.J. 1988. "A New Approachto the Hyperbolic Curve." JPT, Vol. 40, pp. 909912.
Mead, H.N. 1956. "Modifications to Decline CurveAnalysis." Trans., AIME, Vol. 207, pp. 11-16.
. Podruski, lA., Barclay, lE., Hamblin, A.P., Lee, PJ.,Osadetz, K.G., Procter, R.M., and Taylor, G.C.1988. ConventionalOil Resourcesof WesternCanada. Geological Survey of Canada, Paper87-26.
236
DETERMINATION OFOILANDGASRESERVES
Purvis, R.A. 1987. "Further Analysis of Production_Performance Graphs." JCPT, Vol. 26, No.4, pp.74-79.
---.1990. "Pool-Production and Well-CountForecasts." JCPT, Vol. 29, No.6, pp, 80-87.
Richardson, lG., and Blackwell, RJ. 1971. "Use ofSimple Mathematical Models for PredictingReservoir Behavior." JPT, Vol. 23, pp. 11451154.
Robertson, S. 1988. "Generalized HyperbolicEquation." Unsolicited paper, Aug. 1988, SPE18731.
Slider, H.C. 1968. "A Simplified Method ofHyperbolic Decline Curve Analysis." JPT, Vol.20, pp. 235-236.
Schoemaker, R.P. 1967. "Graphical Method forSolving Production Decline Problems." WorldOil, Vol. 165, No.5, pp. 122-125.
-------- ..a
Chapter 19
RECOVERY FACTOR STATISTICS
-I
19.1 INTRODUCTIONProper management ofa hydrocarbon reservoir requires
. a reasonably accurate estimate of reserves early in thelife of a pool when important decisions are made respecting the depletion strategy. The notion that a simplecorrelation exists between recovery factor and readilydefinable parameters has considerable appeal; however,attempts to find one have been largely unsuccessful(American Petroleum Institute, 1984). While there isno substitute for detailed geological and engineeringevaluations, recovery factor statistics are useful forbracketing expected recoveries before such evaluationsare possible. Average recoveries are generally reliablefor estimating the aggregate reserves in a given geological play, but they can be very misleading ifused toestimate the reserves ofan individual reservoir. For newdiscoveries, it is common practice to obtain a preliminary recovery factor from similar mature pools in thesame geological play. Unfortunately, this method ofanalogy can be risky because the available pools maybe immature or a poor match for the pool in question.When using analogous pools to estimate recovery, theevaluator is well-advised to monitor the early performance of the pool for deviations from expectedbehaviour, and to revise recovery estimates accordingly.
This chapter focuses on natural or primary oil recovery,which results from the natural energy sources availablein oil pools. These natural energy sources take the formof six drive mechanisms that can operate alone or incombination. The range of recoveries and relative importance of these drive mechanisms are discussed inSection 19.3 with reference to some Alberta poolexamples. Unfortunately, a breakdown ofrecoveries bydrive mechanism is not possible because many poolshave combination drives, and this information is generally not captured in a reserve database. Recovery factordistributions and average recovery values are presentedfor various pool groupings to examine differences related to pool size, fluid density, lithology, and geologicalage. In addition, average recoveries by geological
play are included with a brief discussion of their use.Several plots of recovery factors vs. common reservoirparameters are also included to illustrate the problem offinding a simple correlation for recovery. Section 19.4covers the drive mechanism for gas pool recovery.
19.2 DATA SOURCE AND RELIABILITYThe Alberta Energy Resources Conservation Board(ERCB) maintains several databases that store a widevariety of information useful in reserve studies. Thesedatabases are shown in Table 19.2-1. The recovery datapresented in this chapter was taken from the ERCB'sreserve database, which contained information for about6800 oil pools and 23 800 gas pools at year-end 1990(Energy Resources Conservation Board, 1991). Sincemost of the reserves in the western Canadian sedimentary basin are found in Alberta, this reserve database isrelatively complete and, because of its size, should berepresentative of other major producing basins.
Table 19.2-1 Public Data Available forReserve Studies
Category Types of Data
Geological Core, well logs, regional maps
Basicwell Completions, treatments, drillstem tests
Performance Production, pressures, deliverabitily tests
Analyses Pressure-volume-temperature, conven-tional and special core; oil, water, and gascompositions
Reserves In-place volumes of oil and gas,recovery factors, reserves, cumulativeproduction, pool area, net pay, porosity,water saturation, formation volume factor,fluid density, reservoirtemperature, initialpressure, datum depth
Other Progress reports for enhanced oilrecoveryschemes, applications
Source: EnergyResources Conservation Board, 1993.
237
The reliability ofan individual reserve estimate is largelya function of data quality and quantity, which are intum related to available technology, and the quality, size,and stage ofdepletion ofa reservoir. The reliability ofareserve also depends on the knowledge and experienceof the evaluator. When setting a reserve, the ERCBoften has the benefit of company geological andengineering estimates to compare with its own. Sincerecovery factors are obtained from the division of reserves by in-place volumes, they can be no more reliablethan the least accurate of these two estimates.
In general, recovery factors for large pools should bemore reliable. Other things being equal, large pools willhave more wellbores to help define the areal extent ofapool and other reservoir parameters. This added information should improve in-place volume estimates. Largepools are normally developed first in most producingbasins; therefore, they will have accumulated the mostperformance data. Arps (1956) discusses how reserveestimates improve with the addition ofperformance data.Ofcourse, the rate and stage ofdepletion in a large poolwill depend on reservoir quality, economics, and regulatory constraints. Another factor that affects recoveryestimates is the cost of gathering and analyzing data.In pools with large reserve potential, it is much easier tojustify these costs. On the other hand, advances in dataacquisition technology will benefit new discoveriesmore than the large mature pools. There is one thing tokeep in mind: a small change in recovery factor cantranslate into significant reserves for a large pool.
As a producing basin matures, new discoveries becomesmaller. Many small pools have only a single wellborepenetrating them. In these pools, in-place volumes arebased on an assumed area, usually some fraction of thedrilling spacing unit of the well. In the future, 3-D seismic data may help to overcome this problem byproviding a much improved understanding of pool geometry. Today, when a small pool is suspended orabandoned prematurely, it is seldom clear whether thedisappointing recovery is due to an optimistic in-placevolume or an optimistic reserve. When this situationoccurs, the ERCB sets the pool's reserve equal to itscumulative production for administrative purposes. Inmany cases, the resulting recovery factor is less than1.0 percent, but appears in the database as 1.0 percentdue to rounding.
The importance of reservoir quality in assessingrecovery or reserves cannot be overstated. Whenreservoir quality is being characterized, the first itemsusually compared are average values of porosity,
238
DETERMINATION OFOILANDGASRESERVES
permeability, and water saturation. Well-establishedmethods are used to define these parameters. Some otherimportant factors include layering or stratification, fractures, pool geometry, and rock wettability. These factorsare not as easy to quantify using single numerical values. The inability to properly account for all theseparameters and how they vary throughout a reservoircreates the largest errors in reserves.
19.3 CONVENTIONAL CRUDE OIL
19.3.1 Natural or Primary DriveMechanisms
The six primary recovery mechanisms are gravitysegregation drive, solution gas drive, bottom-waterdrive, edge water drive, gas cap drive, and expansiondrive. It could be argued that there are really only five ifthe water drive mechanisms are combined. In general,the different recovery mechanisms are additive with theproper combination of reservoir and operating conditions; however, they can also compete with one another,and they can be rate-sensitive.
Guerrero (1961) provided recovery ranges for oil poolswhere each of these mechanisms dominate (Table19.3-1). His ranges suggest that gravity segregationdrive will give the highest recoveries. While this mechanism operates in all pools, it requires a pool with largevertical reliefand sufficient time for drainage to realizethese high recoveries. In Alberta, Bonnie Glen D-3has the vertical relief, buta strong bottom-water drivecoupled with a gas-cap drive did not give the gravitysegregation mechanism enough time to fully develop.
Table 19.3-1 Primary Oil Recovery by DriveMechanism
Drive Mechanism Recovery(% OOIP)
Range Average
Expansion 2-5 3Solution-gas 12 - 25 18Gas-cap 20 - 40 30Edge-water 20 -40 30Bottom-water 35 - 60 45Gravity-segregation 50 -70 60
Source: After Guerrero, 1961.
Solution gas drive (also known as dissolved-gas drive)is the most common primary recovery mechanism inAlberta oil pools. As it happens, this drive mechanism
--------------------_..
RECOVERY FACTOR STATISTICS
Pools = 5918OOIP (1 Oem') = 8302
Mean = 11.67Weighted-Mean = 18.68
Median = 10.00Standard Deviation =10.76
Co-Variance = 0.92
10
50
40
~30~e..-(/)
"0o0.. 20
The gas cap drive mechanism can have a wide range ofrecovery efficiencies depending on the relative size andorientation of the gas cap to the oil zone. About 20percent of Alberta's oil pools are discovered fullysaturated with an original gas cap. Secondary gas capsmay also form in pools with good vertical permeabilityunder solution-gas drive. One of Alberta's highest primary recovery pools (75 percent), Westerose D-3, hada large original gas cap (64 metres), but it also had athick oil zone (73 metres) and a strong water drive.Considering that most high recovery pools in Albertahave bottom-water drives or combination drives,Guerrero's recoveries for gas-cap drive also appearoptimistic.
Expansion drive results from fluid expansion withpressure depletion and is only significant for highly undersaturated pools. The majority of Alberta's oil poolsare discovered at or near their saturation pressure; therefore, expansion drive normally contributes only a smallfraction of the primary recovery. One of the most undersaturated pools in the province is Snipe LakeBeaverhill Lake. This pool had an initial pressure of26MPa and a saturation pressure of 9 MPa. The pool'sprimary recovery is only 12 percent.
19.3.2 Oil Recovery Factor DistributionsWhen oil recovery factors are plotted on a frequencyhistogram (Figure 19.3-1), they produce a skewed distribution with a long tail at higher recoveries. This shapeis characteristic ofa log-normal distribution. McCrossan
oo 10 20 30 40 50 60 70 80 90 100
Recovery (% OOIP)
operates in Alberta's largest oil pool, Pembina Cardium,which has a primary recovery factor of II percent. Theefficiency of a solution-gas drive is largely a functionofpool production characteristics. As the pressure dropsbelow the saturation pressure, dissolved gas comes outof solution and reduces oil flow in two ways: first, theoil becomes more viscous as it loses its lighter ends;second, the escaping gas soon reaches the point whereit becomes mobile (critical gas saturation) and competeswith the oil for access to the wellbore by lowering theoil relative permeability. Recovery seldom exceeds 20percent, and values in the 5-15 percent range are morecommon. Guerrero's recovery range for solution-gasdrives appears somewhat high for Alberta's light andmedium density oil pools, but it is clearly too optimisticfor heavy density oil pools, as will be shown later.
Bottom-water drive is the most important recoverymechanism for many of Alberta's Devonian (carbonate) reef pools. A review of Leduc (D-3) pools alongAlberta's Rimbey-Meadowbrook reef trend is instructive with respect to the relative efficiency of thebottom-water drive mechanism. Glen Park D-3 has ahigh primary recovery factor of 72 percent. The poolhas a thick oil zone (39 metres), high permeability,littlestratification, and no original gas cap. On the other hand,Homeglen-Rimbey D-3 has a recovery factor of only9 percent with a thin oil zone (7.5 metres) and a largegas cap (53 metres). Leduc-Woodbend D-3 is similar toHomeglen-Rimbey with a thin oil zone (II metres), butit has less volatile oil, a less active bottom-water drive,and a smaller gas cap (18 metres). The primary recovery factor for the pool is 56 percent, but water injectionwas used to enhance the natural water drive, resultingin a total recovery factor of 66 percent. Further updipon the trend, Redwater has a recovery factor of 62percent. The oil zone here is about three times as thickas at Leduc-Woodbend and there is no original gas cap.Of interest is the high salinity brine encountered atRedwater. The density contrast between the advancingwater and the by-passed oil may be assisting recoveryby a buoyancy effect.
Edge water drives are less common in Alberta, and theyare not as effective as bottom-water drives. Often whereedge water is present, it is relatively inactive; where itis active, other factors tend to reduce its effectiveness.For example, Joarcam Viking has an edge-water drive,a gas-cap, a thin oil zone (3 metres), and small reservoirdip. These factors contribute to premature water and gasconing. The pool's primary recovery is 37 percent.
Figure 19.3-1 Oil Pools
239
t
~DETERMINATION OFOIL AND GASRESERVES
Figure 19.3-2 Distribution of Primary OilRecovery Factors
12 5 10 20304050607080 90 95 98
Percent of Pools
19.3.4 Pool SizeLargepools (original oil in place over lOx 106m3) thathave reached an advanced stage of depletion (over 50percent) were used to generate Figure 19.3-3. Whencomparedwith therecovery distributionfor the totaloilpool sample (Figure 19.3-1), the fraction of pools withrecoveries less than 10 percent drops considerably andthe average values are significantly higher; however,the mode(mostcommon)recovery remainsat about 10percent. While the distribution tapers off at higher recoveries, it ismoregradual. This supports thesuggestionthat large pools have better recoveries. However, it
The difference between the arithmetic-mean andmedian recoveries is usually insignificant, but thearithmetic-mean recovery is consistentlyhigher.
The mode,or most common recoveryvalue, is only 1.0percent if the completepool sample is considered. Thisvalue is artificially low because of the procedure mentioned earlier for handling small pools that becomeinactive prematurely. If these pools are excluded, themode recoveryjumps up to 10 percent; this is a morereasonable valuefora viablepool, andprobablythebestrecovery toassumefornewpoolsas a lastresort. It couldbe arguedthat this recovery level becomes more likely
.as a producingbasin matures and pool size drops. Thismode recovery of 10 percent will be used in later sectionsas a baselineto compare recoveriesfromdifferentpool groupings.
Table 19.3-2 shows average primary and enhancedrecoveries by crude oil type and recovery mechanism.Theseareweighted-mean values.The datasuggests thattwo-thirds of Alberta's reserves come from natural orprimary depletion mechanisms, and this represents 19percentof the total oil in place. It is interestingto notethat light and medium pools under waterflood have alower primary recovery than those under straight primary depletion. This indicates that enhanced recoveryis targeted for pools where the natural drives are lesseffective. Solvent floods appear to be very successfulbased on the enhanced recovery component. It shouldbe remembered thatwaterfloodingis a viableoptionformost solvent flood pools; therefore, the success of asolvent flood should be measured against waterfloodrecovery. If this is done, the averageincremental recovery for the solventmechanismdropsby halfto about 14percent. In general, vertical solvent floods, which aregravity stable, have the highest recoveries. Horizontalsolvent floods generally sufferfromgravityoverride andrapid break-through of the solvent. In Alberta, mostsolvent floodsuse hydrocarbon-based solvents.
+2Standard Deviation
-1 0 +1
1Liso~ Primary- 10e
~IJ!
the plot results from roundingrecoveries to the nearest5 percent for new and immaturepools.
19.3.3 Average Recovery FactorsSeveral average values are used to suggest the centraltendency of distributions: theweighted-mean, the arithmetic mean, the median, and the mode. Since oilrecovery distributions are skewed, caution must beexercisedwith any use of these average values.
The weighted-mean recovery is a value commonlyreported (EnergyResources Conservation Board,1990).The weighting parameter used is usually the in-placevolume. This average recovery is particularly usefulfor aggregate reserves in a geological play. A quickmethod to calculate it is to divide the total reserves fora group of pools by the total in-place volume. Thisweighted-mean recovery is consistently higher thanarithmetic-mean, median, or moderecoveries forskewedoil recoverydistributions. One explanation is that largepools dominate the weighted-mean recovery and thatthey tend to have higher recoveriesthan smallpools.Ofcourse,this generalization will notbe true in everycase.
(1969) showed that both oil in place and oil reserves inwestern Canada have log-normal distributions. A plotof oil recovery factors on probability paper (Figure19.3-2) gives a reasonablystraightline,whichalso suggests a log-normaldistribution. The stair-step nature of
240
RECOVERY FACTOR STATISTICS
Table 19.3-2 Average Oil Recoveries
Oil Type & Original Oil No. of Average RecoveryMechanism In Place Pools (% OOIP)
(10' m3) Primary Enhanced Total
Light-MediumPrimary 3374 4485 22 na 22Waterflood 2675 213 16 14 30Solvent flood 844 53 27 31 58Gas flood 69 8 41 5 46
HeavyPrimary I 184 1433 8 na 8Waterflood 270 63 9 20 30
Total 8416 6255 19 8 27
Source: Energy Resources Conservation Board, 1990.
Pools = 4485OOIP (10'm3
) = 6884
Mean = 13.01Weighted-Mean = 20.78
Median = 10.00Standard Deviation = 11.42
Co-Variance = 0.88
10 20 30 40 50 60 70 80 90 100Recovery (% OOIP)
40
Pools = 374OOIP (106m3
) = 5787
Mean =25.34Weighted-Mean = 22.09
Median = 20.00Standard Deviation = 16.86
Co-Variance = 0.67
10 20 30 40 50 60 70 80 90 100Recovery (% OOIP)
40
10
~30
~
'"oo
Cl.. 20
Figure 19.3-3 Large Mature Oil Pools
should be noted that most of the higher recovery poolsare Devonian reefpools with active natural water drives.
19.3.5 Fluid Type: Light and Medium vs.Heavy
The density ofAlberta's conventional crude varies from730 to 990 kg/m", Since oil density is closely related tooil viscosity, recovery would be expected to be sensitive to oil density. Figures 19.3-4 and 19.3-5 confirmthat light and medium density pools will recover a higherpercentage oftheir oil in place than heavy density pools.
Figure 19.3-4 Light and Medium Oil Pools
Using the mode recovery of 10 percent for comparison,40 percent of light and medium pools will exceed thisrecovery level, but only IS percent of heavy pools dothis well. Average recoveries for light and medium poolsare about double those ofheavy pools.
Most of Alberta's oil pools are classed as light andmedium density. A cutoff of 900 kg/m! generally distinguishes light and medium from heavy; however, theERCB may also classify a pool by the type ofmarket inwhich the crude oil is sold. Most ofAlberta's heavy oilpools are found in shallow, Lower Cretaceous rock in
241
•
~I:",DETERMINATION OF OIL AND GASRESERVES .
Pools = 3941OOIP (106m' ) = 4865
50r----------::--:------.,Pools = 1433
OOIP (106m' ) = 1418
60,---------------,
50
40
.!Il30ooa.
20
10
Mean = 7.46Weighted-Mean = 8.49
Median= 5.00Standard Deviation = 6.81
Co-Variance= 0.91
10 20 30 40 50 60 70 80 90 100Recovery (% OOIP)
40
~30~t.-Il)(;oa. 20
10
Mean = 8.92Weighted-Mean = 11.33
Median = 10.00Standard Deviation= 7.41
Co-Variance = 0.83
10 20 30 40 50 60 70 80 90 100Recovery (% OOIP)
Figure 19.3-5 Heavy Oil Pools Figure 19.3-6 Clastic Oil Pools
Pools = 1977OOIP (106m' ) = 3437
Mean = 17.14Weighted-Mean = 29.09
Median = 15.00Standard Deviation = 13.85
Co-Variance = 0.81
10 20 30 40 50 60 70 80 90 100Recovery (% OOIP)
10
40
50..----------------,
Cardium, is an Upper Cretaceous clastic pool with aprimary recovery of II percent. The pool's recoverydominates the calculation of the weighted-mean recovery for clastics, and this explains the small difference inaverage recovery values for clastic pools.
Considering the different depositional environments ofcarbonate and clastic reservoir rock, it is not surprising
Figure 19.3-7 Carbonate Oil Pools
19.3.6 Lithology: Clastics vs, CarbonatesThe type ofrock encountered in a reservoir can be veryimportant in determining the level and range of recoveries expected. Figures 19.3-6 and 19.3-7 show recoverydistributions for clastic and carbonate pools, respectively. There is a clear difference in the shape of thesedistributions; the carbonate group has more pools withhigher recoveries. Two of every three carbonate poolsexceed 10 percent recovery, but only one of every fourclastic pools do this well. Average recovery values areconsistently higher for carbonate pools. The weightedmean recovery for carbonates (29 percent) is more thandouble the value for clastics (11 percent).
As previously mentioned, carbonate pools are veryimportant in Alberta. Many have very efficient primarydrives, mainly bottom-water. They represent justone-third of the pools and have one-third of the oil inplace, but they contribute two-thirds of Alberta's conventional oil reserves. Alberta's largest pool, Pembina
east-central Alberta. The initial gas in solution and theinitial pressure in heavy pools are low relative to lightand medium pools. Heavy oil pools assigned the higherrecoveries (up to 45 percent) are usually associated withan active regional aquifer like the one found in theProvost Dina play. In many heavy oil pools, reducedwell spacing is used to improve drainage and recovery.It is not uncommon to have a well every two to fourhectares.
242
c
RECOVERY FACTOR STATISTICS
50
50,--------------,
Figure 19.3-8 Upper Cretaceous Oil Pools
Pools = 625OOIP (106m3
) = 1982
Mean = 8.31Weighted-Mean = 9.74
Median = 10.00Standard Deviation = 5.06
Co-Variance = 0.61
Poois = 2585OOIP (106m3
) = 2111
Mean = 7.62Weighted-Mean = 9.53
Median = 5.00Standard Deviation = 6.67
Co-Variance = 0.87
10 20 30 40 50 60 70 80 90 100Recovery (% OOIP)
10 20 30 40 50 60 70 80 90 100Recovery (% OOIP)
10
40
40
10
~30~~
'"'0oa, 20
~30~~
'"'0oa, 20
Figure 19.3-9 Lower Cretaceous Oil Pools
similar depositional environment). Podruski et aI.,(1988) used this approach in a Geological Survey ofCanada paper, Conventional Oil Resources ofWesternCanada. They considered only light and medium poolsand divided them into 78 plays. Table 19.3-4, taken fromthis report, lists average recovery factors for each play.The data were taken from provincial databases and
that many ofthe parameters affecting recovery are quitedifferent. For example, carbonate reefs tend to be quitethick. This provides the opportunity to complete wellsin a fashion that avoids excessive coning of water orgas. Many are connected to active regional aquifers.With the vertical relief, gravity stable displacement bywater is common. The porosity of carbonate rocks isgenerally low, in the 5-15 percent range, but permeability is very high, especially in dolomitized rock that isfractured. Clastic deposits are generally much thinner,and oil recovery relies on less efficient horizontal displacement processes that are controlled by viscousforces. In clastic rock, the granular nature of the matrixgives higher porosities; however, permeabilities tend tobe lower through the combined effects of compaction,cementing, grain size distribution, and fines migration.
19.3.8 Geological PlayPerhaps the best way to group pools and recoveries isby geological play. This approach is more meaningfulbecause it honours regional geology (e.g., pools have a
19.3.7 Geological PeriodRecovery distributions are shown for eight geologicalperiods in Figures 19.3-8 to 19.3-15. The.most significant variation in the shape of these distributions occursin the Devonian Period. Average recoveries for boththe Upper and Lower Cretaceous pools are under 10percent and vary only slightly. The median recoveryfor the Lower Cretaceous pools is only 5 percent because about half the pools are heavy. Average recoveriesincrease to the 10-15 percent range as one moves downthe stratigraphic column to the Jurassic and Triassicpools. Ofcourse, the sample ofpools drops to one-tenththat of the Cretaceous Period. Although there are toofew Permian pools to be of any statistical significance,the average recoveries are higher there as well. TheMississippian Period breaks from the trend, with average recoveries dropping back slightly to the 6-13 percentrange. Mississippian pools are generally considered tobe in the carbonate family, but their recovery distribution more closely resembles the one for clasticpools. Average recoveries continue to increase in theDevonian Period to the 15-34 percent range. TheUpper Devonian group has the pools with the highestrecoveries, in particular, the Leduc (0-3) zone. Table19.3-3 provides a more detailed breakdown by zonefor the Upper Devonian. In the Middle Devonian,recoveries do not get as high, but the number of poolswith recoveries in the 20-40 percent range increasessignificantly.
243
•
•DETERMINATION OF OIL AND GASRESERVES
Pools = 700IP(10'm3) = 11
50,-------;::--:-;----..,Pools = 220
OOIP (10'm3) = 162
50,-------------~
Mean = 11.00Weighted-Mean = 21.61
Median = 10.00Standard Deviation = 6.99
Co-Variance = 0.64
40
10
oo 10 20 30 40 50 60 70 80 90 100
Recovery (% OOIP)
Mean = 11.68Weighted-Mean = 16.34
Median = 10.00Standard Deviation = 8.57
Co-Variance = 0.73
10
40
~30
~
'"oo0.. 20
oo 10 20 30 40 50 60 70 80 90 100
Recovery (% OOIP)
Figure 19.3-10 Jurassic Oil Pools Figure 19.3-12 Permian Oil Pools
Pools = 321OOIP (1 0'm3
) = 617
50Pools = 214
OOIP (10'm3) = 228
50,---------------,
Mean = 10.91Weighted-Mean = 14.48
Median = 10.00Standard Deviation = 5.98
Co-Variance = 0.55
10
oo 10 20 30 40 50 60 70 80 90 100
Recovery (% OOIP)
40
-30~
'"oo0.. 20
10
Mean = 7.96Weighted-Mean = 13.01
Median = 6.00Standard Deviation = 7.16
Co-Variance = 0.90
10 20 30 40 50 60 70 80 90 100Recovery (% 001 P)
Figure 19.3-11 Triassic Oil Pools
included both primary and secondary recovery; therefore, the average recoveries will be slightly optimisticfor primary recovery mechanisms.
An acceptable way to make a preliminary recoveryestimate ina new pool is by analogy. The success ofthemethod depends on whether or not there are sufficientpools with reliable recovery data in the same geologicalplay. Once the correct play has been identified,
Figure 19.3-13 Mississippian Oil Pools
analogous pools may be found by comparing rock andfluid properties, pool geometry, and fluid contacts. Poolsshould also have a reasonable amount of performancehistory before the analogy is accepted. It is important toremember that this is only a preliminary estimate, and itmust be confirmed with performance. If the earlyperformance is inconsistent with the analogous pool,the evaluator should suspect that a different drive
244
c
RECOVERY FACTOR STATISTICS
Pools = 1239OOIP (1O'm') = 897
50r------------------,Pools = 706
OOIP (10'm') = 2292
50 r---------::-----:---=-:-.,.--,
Mean = 18.59Weighted-Mean = 26.38
Median = 20.00Standard Deviation = 11.65
Co-Variance = 0.63
oo 10 20 30 40 50 60 70 80 90 100
Recovery (% 001 P)
10
40
~30
Cen(;oa.. 20
Mean = 19.21Weighted-Mean = 33.93
Median = 15.00Standard Deviation = 16.47
Co-Variance = 0.86
10 20 30 40 50 60 70 80 90 100Recovery (% OOIP)
40
Figure 19.3-14 Upper Devonian Oil Pools Figure 19.3-15 Middle Devonian Oil Pools
Table 19.3-3 Recovery Factors for Upper Devonian Zones
Upper Devonian No. of OOIP Recovery Factor (fraction) Pay (m)Pools (10' m3)
Avg. Min. Max. W-Avg. Avg. Min. Max. W-Avg.
Devonian System I 0.429 0.040 0.040 0.040 0.040 4.82 4.82 4.82 4.82
Wabamun (D-1) 112 44.183 0.157 0.010 0.350 0.162 33.34 0.91 108.30 40.20
Stettler I 0.053 0.200 0.200 0.200 0.200 2.80 2.80 2.80 2.80
Blueridge 5 2.432 0.096 0.010 0.200 0.125 17.12 6.43 30.20 15.27
Arcs 24 15.233 0.125 0.010 0.360 0.167 6.61 2.10 16.20 9.18
Nisku (D-2) 178 342.719 0.243 0.010 0.650 0.405 16.17 1.00 90.35 21.55
Camrose 11 1.992 0.134 0.010 0.250 0.145 7.48 3.40 10.36 7.95
Ireton 2 0.742 0.110 0.070 0.150 0.105 9.29 3.05 15.54 10.05
Leduc (D-3) 148 812.328 0.291 0.010 0.750 0.568 16.17 0.90 135.64 42.40
Cooking Lake 2 0.541 0.125 0.100 0.150 0.106 4.66 3.70 5.63 5.39
Beaverhill Lake 53 944.084 0.142 0.010 0.350 0.164 9.89 1.62 37.00 18.79
Sulphur Point 133 108.224 0.119 0.010 0.450 0.132 7.14 0.88 27.90 7.99
Totals 670 2272.960 0.198 0.010 0.750 0.343 16.18 0.88 135.64 27.46
245
T. I
DETERMINATION OFOILANDGASRESERVES""'" '
Table 19.3-4 Recovery Factors for Geological Plays in Western Canada
Geological Period Play Recovery Factors Geological Period Play Recovery Factors
and Plays Depth Average Small and Plays Depth Average Small(m) Pool (m) Pool
Cretaceous Carboniferous
Cardium Sheet 1000 0.20 0.10 Midale 1400 0.36 0.20Viking-Alberta 1800 0.19 0.10 Frobisher-Alida 1100 0.24 0.20Lower Mannville 2100 0.15 0.10 Pekisko Edge 1650 0.13 0.07Viking-Saskatchewan 500 0.14 0.10 Elkton Edge 1700 0.28 0.10Upper Mannville 1000 0:15 0.10 Lodgepole 1100 0.16 0.07Belly River Shoreline 1000 0.21 0.10 Souris Valley-Tilston 1100 0.16 0.11Cardium Scour 2000 0.19 0.10 Banff Edge-C. Alberta 1500 0.20 0.12Cantuar 1000 0.15 0.06 Ratcliffe Stratigraphic 1800 0.20 0.10Dunvegan-Doe Creek 750 0.09 0.09 Ratcliffe Structure 1100 0.20 0.10Belly River Fluvial 1500 0.21 0.10 Desan 700 0.08 0.Q3Ostracod 2200 0.15 0.10 Carb.-Sweetgrass Arch 2000 0.10 0.101" & 2nd White Specks 2000 0.10 0.10 BanffEdge-S. Alberta 1300 0.10 0.10
Debolt-Peace River 1500 0.08 0.08
Jurassic Devonian
Shaunavon 1200 0.23 0.10 Beaverhill Lake 2950 0.42 0.10Roseray-Success 900 0.30 0.10 Leduc-Rimbey-Meadowbrook 1700 0.61 0.30Gilby-Medicine River 2200 0.25 0.10 Keg River 1800 0.41 0.30Sawtooth 900 0.22 0.10 Nisku-Shelf 1700 0.55 0.25Rock Creek 2200 0.16 0.10 Leduc-Bashaw 2000 0.61 0.20
Leduc-Deep Basin 2000 0.61 0.15Triassic Nisku-West Pembina 2800 0.40 0.30Boundary Lake 1300 0.27 0.10 Middle Devonian Clastics 1800 0.25 0.20Montney 1596 0.17 0.12 Slave Point-Sawn 1600 0.20 0.10
Peejay-Milligan 1130 0.32 0.20 Zama 1600 0.17 0.17
Halfway Stratigraphic 2150 0.28 0.12 Leduc-Nisku-S. Alta 1700 0.15 0.15
Inga Structure 1600 0.15 0.10 Wabamun-Peace River 1250 0.16 0.13
Charlie Lake Sandstone 1800 0.18 0.18 Slave Point-Golden 2000 0.35 0.30
Halfway Drape 1900 0.19 0.10 Nisku-Meekwap 2000 0.40 0.15
Charlie Lake Algal 1800 0.15 0.15 Keg River-Senex 1300 0.20 0.10
Doig Structure 1900 0.08 0.05 Wabamun-Crossfield 2500 0.15 0.10
Bistcho 1600 0.15 0.07
Permian Muskeg 1600 0.20 0.20
Belloy-Peace River 1850 0.28 0.12 Wabamun-Eroded Edge 2050 0.14 0.14
Belloy-Erosional Edge 2000 0.37 0.10 Leduc-Peace River 2800 0.20 0.15
Source: Conn and Christie, 1988.This table is reproduced with the permission of the Minister of Supply and Services Canada, 1993.
246
RECOVERY FACTOR STATISTICS
25
Figure 19.3-16(b) Porosity Distribution
Figure 19.3-16(a) Oil Recovery vs. Porosity
Pools = 5915
Mean = 14.42Weighted-Mean = 14.16
Median = 13.00Standard Deviation = 7.44
Co-Variance = 0.52
o 4 8 12 16 20 24 28 32 36 40Pool Average Porosity (%)
5
20
;g 15~
'"'8a. 10
100
90 Pools = 5915
80 ..ii:' 70 ;
5 ..... oo •
0 60 ...~
~ \,' ...50 .:::",: .
~ .r., __ ·:"0 ... . ... . ..~,:-...> 40 ... ... .-a''''~~''''-'.''c .. •..
30'. '0..... . .a: .._~..~•• _ .._ ........._00 ••••_.
• 00 : : ...:..:.,..::.•• ....i............20 ,,+::··.;;f~-::,i:.:·;-,:,::- r : '.
'''~'''''l;l1'''''''''''''' .,10 .~ ~~~·;r;;-H1~"''::': :.:.: ..
•••.1.; -l-.......·~i ....- ~j, "[,"1 l. '.-1,.W' •• {. II ••
0. ..". . .....!-.jjijjil:.:i i ...l.rj!~ r..
0 4 8 12 16 20 24 28 32 36 40Pool Average Porosity (%)
the water-invaded zone can lower recoveries to 50percent or less.
The recovery distribution for some 9000 gas pools thathave produced in Alberta is shown in Figure 19.3-19.As expected, recovery factors are in the 50 to 90 percent range. It is interesting to note that, unlike oil, thegas recovery distribution appears to be normal (e.g.,symmetric about a mean value of 75 percent). About
mechanism is operating and be prepared to gather orre-examine data to revise the recovery estimate.
19.3.9 Recovery vs. Common ReservoirParameters
Ideally, recovery estimates should fall out of a simplerelationship between several reservoir parameters thatare readily quantifiable. Unfortunately, this relationshipcontinues to elude everyone. One possible explanationis that the methods used for quantifying these parameters over-simplify reservoir heterogeneity. Another isthat the interplay of rock properties, fluid properties,drive mechanisms, and production strategies is toovariable and dynamic for simple solution's to workconsistently. Whatever the reason, simple correlationshave yet to be found.
To help illustrate the problem, recovery factors wereplotted against three familiar reservoir parameters:porosity, net pay, and water saturation (Figures 19.3-16to 19.3-18, respectively). The parameters used were poolaverage values. In each case, there is considerable scatter of the data, but some general trends are evident. Forexample, maximum recovery increases as porosity andwater saturation decrease. Intuition might suggest therelationship between water saturation and recovery, butthe one with porosity is less obvious. If the data is reexamined by rock type, clastic and carbonate, the reasonis clear. Many of the higher recovery carbonate poolshave lower average porosities and water saturations.
19.4 CONVENTIONAL GASThe dominant natural drive mechanism that operates inmost gas pools is fluid expansion. Recovery from a volumetric gas reservoir largely depends on how low areservoir abandonment pressure can be achieved withthe production facilities available. A simple correlationis used to estimate the abandonment pressure as a function of well depth. Normally a value around 1500 kPaper 1000 m ofdepth is used (Stoian and Telford, 1966).Two additional corrections are sometimes required toadjust for well deliverability, and fluid invasion at thewellbore. This fluid invasion can be oil, but can also bewater either from an active aquifer or coning. Gas flowsthrough reservoir rock far more readily than oil becausegas viscosities are several orders of magnitude lower.In general, recoveries for gas pools without an activewater drive are expected to exceed 75 percent and canreach 90 percent or more. On the other hand, if waterinvades a gas pool too quickly (e.g., with little or nopressure depletion), the residual gas trapped behind
247
d
DETERMINATION OF OIL AND GASRESERVES
Pools = 5915
... i.. d,
,O,::L:.::.
10 20 30 40 50 60 70 80 90 100Pool Average Water Saturation ('Yo)
..·f;:I·......•···.•.•. ·•. :....:;:,.:;1.: .1,: ....... :,' .·:: ...•.. •.. ····,····· .. 1..••••.. ···1·....
Bllfu,;'u
100
90
80
a:- 70(5o 60;ft.~ 50~
"1; 40o
"c: 30
20
10
oL...J=iilillli!illllil==iLhlli!.li....;~~~--'
o
100
90 Pools ~ 5915
80 ..a:- 70(5 ... .. , ..0 60 ..~ ..e, ..~ 50 ° 0 .... 0 ... 0 .. .."
._. '. .. , ..> 40 . .., . .- .•0. :a ':~:""
._...... -.. i" :" .0
"; __.'!'.\O:.. ........ '_0",,",: .- .. - ...
c: • 0 .' ;0 ••0.30. .------..- ..... - .. .
0.... ' .' '.,..r_•••__.:..:.... ':" .t: _\":..0" ,0 • .. ..20 -oo '0, ,0 .j:-=_ ,:........:..: : "1 '0' • '0' .0••
'!!rfi-':' i '':.J~.... :. ',1° •• • ::.. to ' .... ':. •
10 ~::•...;~....:;l~:' ~~:!:'.:::~..;:. :.~:: :.~~':O• .:7::vl.r...;:'>::....... 0:: 0: :
0 10 20 30 40 50 60 70 80 90 100Pool Average Net Pay (m)
Figure 19.3-17(a) Oil Recovery vs, Net Pay Figure 19.3-18(a) Oil Recovery vs. WaterSaturation
60 25
Pools ~ 5915 Pools = 5915
Figure 19.3-17lb) Net Pay Distribution
7600 of the pools used have an original gas in placeunder 300 X 106 m', A separate distribution was not included for this group, but it looks very similar to Figure19.3-19. The remaining 1400 larger pools have arecovery distribution that is slightly skewed to the left
Figure 19.3-18(b) Water Saturation Distribution
Mean = 29.08Weighted-Mean = 21.74
Median = 30.00Standard Deviation= 11.78
Co-Variance = 0.41
5
20
~ 15Cen'0oa. 10
oo 10 20 30 40 50 60 70 80 90 100
Pool Average Water Saturation ('Yo)
(Figure 19.3-20),unlike oil recovery distributions, whichare skewed to the right.
The same problem encountered with the reliability ofreserves for small oil pools also applies to small gaspools. Warren (1990) discusses the impact of overlyoptimistic area assignments for Alberta's growinginventory ofsmall gas pools, and provides area defaultsfor use in setting the initial reserves ofsingle-well pools.
Mean ~ 10.20Weighted-Mean = 15.15
Median = 4.40Standard Deviation= 15.86
Co-Variance = 1.55
10 20 30 40 50 60 70 80 90 100Pool Average Net Pay (m)
20
50
40
10
~
C2! 30sa.
248
____________________..iII
RECOVERY FACTOR STATISTICS
often no better alternative until performance databecomes available. The best approach is to find an analogous pool in the same geological play, preferably nearbythe pool in question. If an analogous pool cannot befound, it may be necessary to look at an expanded dataset; however, it should be understood that the reliabilityof recovery statistics decreases each time this is done.Recovery factor distributions will give an idea of therange of recoveries that are possible, and the probability ofdifferent recovery levels within the range. In caseswhere the range of recovery is small, the use ofaveragerecovery factors may be satisfactory. For new, light andmedium pools that are small, a recovery of 10 percent,the mode, is a reasonable assumption for a solution-gasdrive mechanism. It should be less if the pool is heavy.For a carbonate pool, there is more risk with the use ofaverage recovery factors because they often have a combination drive at work, which can have a wide range ofefficiencies. If aggregate reserves are being assessed,weighted-mean recovery factors should be quite reliable. The most important thing to remember is thatrecovery statistics should only be used for a preliminary estimate until more detailed analyses are possible.
ReferencesAmerican Petroleum Institute. 1984. "Statistical
Analysis of Crude Oil Recovery and RecoveryEfficiency." APIBulletin, 014, 2nd ed., Apr. 30,1984.
Arps, J,J. 1956. "Estimation of Primary OilReserves." Trans., AIME, Vol. 207, pp. 182-191.
Conn, R.F., and Christie, J.A. 1988. Conventional OilResources ofWestern Canada (Part II).Geological Survey of Canada, Paper 87-26,p. 131.
Energy Resources Conservation Board. 1990.Alberta's Reserves ofCrude Oil, Oil Sands, Gas,Natural Gas Liquids and Sulphur. Report ST91-18, Dec. 1990, Calgary, AB.
---. 1993. Catalogue - Publications, Maps andServices. Guide G-I, Calgary, AB.
Guerrero, E.T. 1961. "How to Find UltimateRecovery and Performance of Oil Reservoirs."O&GJ, Vol. 59, No. 35, p. 101.
McCrossan, R.G. 1969. "An Analysis of SizeFrequency Distribution of Oil and Gas Reservesof Western Canada." Canadian Journal ofEarthSciences, Vol. 6, pp. 201-211.
Pools = 1411OGIP (109m' ) = 3655
Mean = 74.89Weighted-Mean = 75.24
Median = 75.00Standard Deviation = 12.61
Co-Variance = 0.17
Pools = 9016OGIP (109m' ) = 4143
Mean = 71.08Weighted-Mean = 74.74
Median = 70.00Standard Deviation = 9.26
Co-Variance = 0.13
Gas Pools (Producing)
40
10
40
50 ,-----------"---,--,,..,...,-::--1
~30~~so'0oa. 20
10
OL~-~~---"--
o 10 20 30 40 50 60 70 80 90 100Recovery (% OGIP)
50,-------------
oL_~_dJi!ib"o 10 20 30 40 50 60 70 80 90 100
Recovery (% OGIP)
Figure 19.3-19
These area defaults are expected to improve aggregatereserves in a geological zone, but may not significantlyimprove the reliability of an individual pool's reserve.
19.5 USING RECOVERY FACTORSTATISTICS
It should be clear from the data presented that cautionmust be exercised in the use of recovery factor statistics. Nevertheless, for many new discoveries, there is
Figure 19.3-20 Large Gas Pools (Producing)
249
-
Podruski, lA., Barclay, J.E., Hamblin, A.P., Lee, PoI.,Osadetz, K.G., Procter, R.M., and Taylor, G.C.1988. Conventional Oil Resources ofWesternCanada (Part I). Geological Survey of Canada,Paper 87-26.
250
-.DETERMINATION OFOILAND GASRESERVES
Stoian, E., and Telford, A.S. 1966. "Determination ofNatural Gas Recovery Factors." JCPT, Jul.-Sep.,1966, pp. 115-129.
Warren, A. 1990. "Alberta's Small Gas PoolReserves." JCPT, Vol. 29, No.4, pp. 34-40.
PART FOUR
PRICES, ECONOMICS, AND MARKETS
a
Chapter 20
OVERVIEW OF PART FOUR
Technical principles, supplemented by empirical data,form the basis for estimates ofpetroleum resources. Anestimate of.reserves, on the other hand, is based on theprinciple that only a portion of these resources is economically recoverable. Assessment of economicviability requires information from areas such as financial analysis, regulatory guidelines, and marketconditions.
Part Four provides the basis for including these areas inthe process of estimating economically recoverable reserves. The impact of these parameters on the reservesestimate is illustrated by an example from the Albertaoil sands. While the resource is estimated at 3800 x106m3, the reserves are only 280 x 106m3 (EnergyResources Conservation Board, 1991). Until the economics become more favourable through either reducedcost or increased revenue, the recognized reserves willnot increase.
Reserves evaluation isbased on analysis ofthe cash flow.Chapter 21 summarizes the major components ofa cashflow analysis using the Alberta (Canada) fiscal regimeas a reference. The principal sources and uses of cashare addressed, including some ofthe details ofAlberta'sprovincial royalty regulations and federal corporateincome tax. Some aspects of accounting and businessfinance that illustrate how these areas correlate with cashflow analysis are also discussed.
In all evaluations there is a degree of uncertainty.Indeed, it could be argued that every parameter involvedin an evaluation is more accurately defined as a rangeofpossible values. These uncertainties exist as a resultofeverything from physical measurement to changes ingovernment regulation. Chapter 22 discusses the concepts of risk and uncertainty and presents criteria foridentifying situations where risk analyses are warranted.Chapter 6 in Part Two discusses stochastic modellingof resource estimates.
The impact of government regulations on reservesevaluations is discussed in Chapter 23, using the
regulatory environment for the petroleum industry inCanada as an example. Reference is made to the AlbertaEnergy Resources Conservation Board and its role indefining production practices. Government policy initiatives, including tax and royalty regulations, have amajor influence on reserves evaluations.
One of the most important factors in any economicevaluation is commodity pricing. The two major commodities involved in reserves evaluations are crude oiland natural gas.
Chapter 24 provides an overview ofCanadian crude oilmarkets in the context of a globally traded commodity.There is particular focus on Alberta and other westernCanadian provinces, including a description of transportation networks and major markets. The basics ofprice forecasting are examined, as well as price riskmanagement and some of the products that areavailable to mitigate price volatility.
Natural gas markets in North America are addressed inChapter 25 with particular emphasis on the dynamicsimposed through changes in government regulations.The chapter focuses primarily on the Canadian market,but its virtual integration into the United States markethas effectively blurred any boundaries between the two.Important demand forces are examined as well asvarious contract options that have evolved.
The contents of reserves evaluations are available for avariety ofuses and users. These range from governmentsdeveloping resource planning policy to companies contemplating production development or an acquisition.Chapter 26 decribes some of the uses of reservesevaluations.
ReferencesEnergy Resources Conservation Board. 1991.
Alberta's Reserves ojCrude Oil, Oil Sands,Natural Gas Liquids and Sulphur.ERCB ST 91-18, Dec. 1990, Calgary, AB.
253
Chapter 21
CASH FLOW ANALYSIS
21.1 INTRODUCTIONIn any industry, accurate analysis of cash flow is anessential part of investment decision-making andoptimum capital budgeting. Like all resource-basedindustries, the oil and gas industry depends on suchanalysis to quantify its resource base; remaining reservesare actually defined in the context of economics.
Methodology for cash flow analysis in the energy industry is consistent with the general principles ofbusiness finance. The purpose of this chapter is to discuss the cash flow analysis in the context of individualproperty analysis as well as in the corporate context,with particular reference to western Canada, andspecifically Alberta.
It should be noted that the chapter is an overview.Parties utilizing cash flow analysis in contemplationof making business decisions are advised to retainprofessional advice.
21.2 MINERAL RIGHTS OWNERSHIPParticipants in the oil and gas industry lease the right todevelop the minerals from the holders of the mineralrights. A number of different forms of property interestevolve from the leasing of these rights, with differencesthat are typically based on the sharing of risk and therequirement to provide development capital.
Mineral Interest. Subsurface mineral rights areusually separate from surface rights. Ownership maybe held privately, in which case it is known as a freehold interest, or by the government, in which case it isknown as a Crown interest.
Most of the mineral rights in Canada reside with theCrown; however, some do reside with individuals under freehold rights. These rights originate from twosources: (I) in 1869 the Hudson's Bay Company transferred to Canada what was to become the provinces ofAlberta, British Columbia, and Saskatchewan, and thecompany retained some ofthe mineral rights; (2) in thenineteenth century, the federal government granted
254
certain mineral rights to railway companies asconstruction incentives.
Royalty Interest. When a property is leased, theinterest retained by the mineral rights holder is knownas royalty interest. Freehold royalty interest would becontractually defined. Crown royalty interest is definedin legislation. The interest participant shares in therevenues, but has no obligation to fund development.
Overriding Royalty Interest. This is an economicinterest that is retained by a lessee when property rightsare "farmed out" to another party. If the original lesseeretains the economic interest without obligation tocontribute to development costs, it is called a "grossoverriding royalty" (GORR). If the original lesseeallows the lessor to deduct certain defined expensesbefore paying royalty, it is called a "net overridingroyalty" (NORR).
Production Payment Interest. This is similar to anoverriding royalty but would typically be limited toeither a production amount or quantity, or to a certaintime.
Working Interest. This is the most commonly heldinterest. The holder receives the net benefits after thepreviously mentioned interests are realized and isresponsible for development costs.
Typically, there is more than one working interestowner. These owners would normally develop a property under the terms ofa joint venture agreement whichdesignates one ofthe owners as Operator. This arrangement is not usually considered a partnership as allthe working interest owners are free to take their ownproduction and dispose ofit on their own terms. Whetherthe business arrangement is a joint venture or a partnership can be significant from the perspective ofcalculating income tax.
Carried Interest. This results when one party "carries"the development costs of another party. Working interests of the carried party would differ before and afterpayout of the carry amount. When the party has opted
c
•
CASH FLOW ANALYSIS
out of a development under an existing agreement, itwill likely have to wait until an additional "penalty"amount has been earned by the other parties beforereverting to a working interest position.
Net Profits Interest. The net profits referred to will becalculated according to a contracted accounting procedure. In this case, the holder has no obligation to sharedevelopment costs.
Pooling and Unitization. These terms refer to arrangements made, voluntarily or in accordance withgovernment regulation, to jointly develop a resourceproperty. Pooling generally refers to agreements within a drilling or production spacing unit, these typicallybeing one quarter section for oil and one section forgas. Unitization normally has a broader context andwould address a development that extends beyond thestandard spacing units.
Individual participants can also undertake differentconventional business arrangements such as joint ventures and partnerships. These structures also have taximplications that must be addressed.
21.3 PRINCIPAL SOURCES AND USESOF CASH
Ultimately, the revenue generated by the industry as awhole is through the sale ofcrude oil, natural gas, natural gas liquids (NGL) and sulphur. Estimated totalrevenue for the Canadian oil and gas industry for 1991was approximately 18.4 billion dollars (Curran, 1992),ofwhich 61 percent was from crude oil, 27 percent fromnatural gas, 10 percent from NGL, and 2 percent fromsulphur. These percentages are, of course, subject tochange as product prices and relative volumes change.A lower average gas price in recent years has been partlyresponsible for the decease in the ratio of revenuefrom natural gas to crude oil from 0.54 in 1988 to anestimated 0.43 in 1991.
Within this broader context of industry gross revenues,cash flows originate from a variety of other sources,including such things as overriding royalties andprocessing fees.
Most cash flows are determined with the wellhead orlease as a reference point; however, there are other usesofcash that have to be considered at the corporate level.
Production Revenue. Custody transfer of productusually takes place at the lease boundary where the product is metered. Gross revenues are then the product ofquantities sold and prices received.
It is important to differentiate between productionrevenue and processing revenue as the income tax treatment for these two items is different. In broad terms,production of crude oil stops at the exit of the batterywhile production of gas stops at the downstream end ofthe inlet separator ofa gas plant. Revenue Canada usesthe gas cost allowance calculation, from provincialCrown royalty calculations, as the basis for determining production vs. processing revenue for tax purposes.
Crude oil prices are typically posted by the buyer oftheoil on a volume basis. The price is at a specific location,either in the field or at the refinery gate, and transportation tariffs must be deducted to bring the price to thewellhead. Future projections of price can be based onany number of approaches, ranging from a functionof inflation to models that incorporate anticipatedinternational supply and demand.
Gas prices are, for the most part, set by buyer and sellerat a price per energy unit. These prices will be set inreference to a delivery point such that a transportationtariff correction may be required to bring the price tothe wellhead. Forecast future pricing will vary fromfixed escalation to an index reflecting current marketconditions and should include an awareness of marketdynamics, regulatory issues, and the amount ofcontracted gas a buyer is likely to be able to purchase.
Natural gas liquids is a term that includes ethane,propane, butanes and pentanes plus. Ethane, ifextractedat source, will usually be priced on the basis of a contract with the buyer. Propane and butanes (normal andiso), known as liquefied petroleum gas (LPG), are normally sold as a mixture with pentanes plus. The wellheadprice of this mixture will be based on individual product prices with corrections applied for transportation andfractionation. Product price forecasts would incorporatethe basics employed in crude oil and natural gasforecasting.
Processing Fees. In most cases, production will requiresome treatment prior to sale (in a few cases, productionis sold as is at the wellhead). Oil typically requires removal ofdissolved gas and produced water. Natural gasmay require removal of water, heavier hydrocarbons,hydrogen sulphide, and carbon dioxide.
If the producing company has its own treatmentfacilities, associated capital costs and ongoing operating costs will have been recognized in the economicevaluation of the property. If the producing companydoes not have the necessary facilities, it will have toincur an expense by paying another party to providethem.
255
Methods of determining fees range from "what themarket will bear" to a contractually defined fee and mayinclude minimum charges that must be paid irrespective of quantities processed. Some fees consist of twoparts: a capital recovery component, and a separate operating component, which is a pro rata share of facilityoperating costs.
A facility owner with spare capacity can make itavailable to other producers. In this case, processing feesbecome a source ofcash rather than a use ofcash. Theseare processing revenues and, as discussed later, shouldbe included in taxable income after the resource allowanceand earneddepletion deductions. (These two termsare discussed in Section 21.5).
Another source of cash for one of the parties is theoverhead fee paid by the owners of a facility to theoperator of the facility. This fee will be specified in theoperating agreement among the owners as a percentageof direct operating costs.
Operating Costs. Field costs are typically somecombination ofa fixed cost, a unit cost per volume produced, and a monthly well cost. Disposal of producedwater will sometimes involve off-lease disposal and anassociated cost which can be based On the volume ofwater handled or can be a fixed fee per haul.
Facility operating costs are generally considered to be acombination of fixed and variable costs. When facilityownership is shared, operating costs are usually apportioned on the basis of throughput or contractedcommitments.
Capital Costs. One of the more significant things toconsider about a capital expenditure is the tax treatmentof its components. This is addressed in greater detail inSection 21.5.
Another consideration is funding. Ifa company can notfinance its capital requirements from cash flow, it hasto consider other sources, and the risk associated withthe planned development can affect both the source andcost of this funding. When debt financing is contemplated, the development may not on its own qualify forthe balance of needed funds, and additional security oradditional equity may be required. Either alternativecould restrict the company's options On further development.
Other avenues available include the various leasingarrangements already mentioned.
Site Restoration and Reclamation. This aspect of oiland gas operations has recently been receiving muchmore attention, and costs for decommissioning of
256
DETERMINATION OFOIL AND GASRESERVES
facilities and reclamation and restoration ofthe wellsiteshould be included in cash flow analysis. While thes~costs may be accrued Onan annual basis for accountingpurposes, they are not actually incurred until the end ofthe economic life ofthe producing property. (Quite apartfrom facility decommissioning and wellsite reclamationand restoration costs, there may be ongoing operatingcosts to satisfy regulatory requirements.)
Well abandonment costs can be estimated on the basisofpublished regulations. Decommissioning and site restoration costs depend in part on the final condition ofthe site and the regulations in effect at the time. As suchthey are more difficult to estimate. '
General and Administrative. Commonly referred toas G&A, these are the costs a company incurs in otherthan the direct operation of its properties, such as at adistrict or head office, and they must be recognized atsome level in cash flow analysis.
Ifany G&A costs are allocated to a property that is lessthan 100 percent owned by the company, they will thenbe shared by the other participants in that property. Theeffect of charging this expense to the field will be tomarginally reduce field economics, with a corresponding impact on company economics. While the impacton the economics ofa particular field will likely be minor, if enough costs are allocated to enough fields, theimpact on company economics can be significant.
Interest Expense. Financial charges incurred infunding investments are often not included in cash-flowforecasts. From the perspective ofdiscounted cash flows,these charges, which include interest on debt or shareholder returns, have already been considered in thedetermination of the discount rate. If they were to beincorporated into discounted cash flow calculations,they would effectively be counted twice.
From the perspective ofannual cash flow, however, theamount of interest to be paid and, for that matter,principal, should be taken into account. This is particularly important at the corporate level because of theimplications with respect to corporate liquidity.
One area where interest must be considered is in thedetermination of income tax. Interest is tax deductibleand, as discussed in Section 21.5, it is deducted afterresource allowance and before earned depletion.
Topgas. Derived from take-or-pay (TOP) gas, thisrefers to two agreements that were developed to alleviate problems associated with TransCanada Pipelines'contractual obligations to pay for natural gas which,because of the absence of markets, the company could
_______________________11
CASH FLOWANALYSIS
not take delivery of. In exchange for reduced TOPcommitments, producers were pre-paid in excess of $2billion.
These amounts are being repaid over a lfl-year period,scheduled to end in 1994. A minimum of 10 percent ofthe gas recovery is made annually in the period fromNovember to February, inclusive, that being the traditional period of highest gas deliveries. A producer'sannual payments consist of what is in effect a combination of principal and interest, with the interestnetted out of its gross revenue for gas.
It should be noted that the producer does not have topay royalty on this gas until it is produced, even thoughthe producer will have already been paid for the gas.Appropriate cash flow and accounting considerationmust therefore be given this issue ..
Working Capital. Changes in working capital are notgenerally considered in cash flow analysis at the fieldlevel; however, it must be recognized that a companywill have to fund any increase in its working capitalposition. This is a particularly relevant item in a startup situation when funds for working capital have to beprovided.
21.4 ROYALTIES AND MINERAL TAXGenerally speaking, Canadian provincial governmentsown and administerCrown lands within the provinces.The territories are the domain of the federal government, and the offshore is the domain of negotiation.Responsibility for mineral rights on aboriginal lands maylie with the aboriginal peoples. Royalties will be takenin cash or in kind and according to the regulations andformulae determined by the administrative authority.
O'Dell et al. (1991) provides a summary of the fiscalregimes, addressing both tax and royalty, in the Canadianpetroleum industry. The British Columbia royaltysystem is described in more detail in the BritishColumbia Oil and Gas Royalty Handbook (BritishColumbia Ministry of Energy, Mines and PetroleumResources, 1992). The Saskatchewan royalty system isoutlined in Statutes and Regulations (SaskatchewanEnergy and Mines, 1990) and in information circularspublished by the Economic and Fiscal Analysis Branchof the Department of Energy and Mines.
Royalty regimes are administered by provincialgovernments and thus are subject to change at their discretion. This is best exemplified by the present situationin Alberta where recently announced changes havesignificantly altered royalty calculations.
As an example of a provincial royalty structure, a briefdescription of basic royalty calculations for theprovince of Alberta follows. This description encompasses the changes being implemented starting inOctober, 1992.
Natural Gas Royalty. Royalty is basically a functionofage, price and production rate. Age refers to the classification ofthe gas as "old" or "new," new gas effectivelybeing gas which is discovered or brought on streamafter January I, 1974. Price refers to the "average Albertamarket price" (AMP), as prescribed by the Minister andpublished in Department ofEnergy information letters.Price also refers now to "select price," for both old andnew gas, again as published in information letters. Production rate refers to the average daily production forthe month, with 16 900 m3/das an amount below whichroyalty is reduced.
Prior to October of 1992, Alberta Regulation 246/90(Province of Alberta, 199Ia), as amended, was thebasis for natural gas royalty calculations in Alberta, anddetails of the application of the regulation wereprovided in Gas Royalty Guidelines (Alberta Energy,1990). With the introduction of changes to gas royaltycalculations, these documents will require some changesas well.
Schedule I of the regulation formerly described thecalculation of royalty for natural gas and residue gas,and is presently being updated to reflect the royaltychanges.
Minimum royalty on natural gas, both old and new, isnow 15 percent, the rate charged when the AMP is lessthan or equal to the select price. When the AMP is greaterthan the select price, the royalty rate, R%, is calculatedaccording to Equation (I):
R = [(.15)(GSP) + (.4) (AMP.GSP)] x~ (I)AMP
where R = the Crown royalty share (%)GSP = the old or new gas select price
AMP = the average Alberta market price
Maximum royalty on natural gas is now 35 percent forold gas and 30 percent for new gas. Table 21.4·1 summarizes the changes to calculation of Alberta naturalgas royalty as announced by the provincial governmentin October of 1992.
A low productivity allowance is also available. If theaverage daily production during a month is less than16900 m3/d, the basic royalty is calculated accordingto Equation (2):
257
DETERMINATION OF OIL ANDGASRESERVES
Table 21.4-' Summary of Alberta Natural GasRoyalty Changes
Base Rate Marginal Rate Rate Cap(%) (%) (%)
Current New Current New Current New
New Gas 22 15 30 40 30 30Old Gas 22 15 40 40 40 35
Source: News release, Alberta Energy, October 21,1992.
(5)S
R=-xIOOQ
where R = the royalty rate (%)S = the basic royaltyf = the royalty factorA = the par priceB = the select priceQ = the monthly productionrate
When the par price is less than or equal to the selectprice, the equation simplifies to Equation (5):
R = [S + fS«A-B))] x 100 (4)A Q
In Alberta, gas royalties are taken in cash with theproducer paying from the proceeds of sale. Gas costallowance (GCA) is an amount deducted from the royalty obligationto account for the fact that Crowngas isbeing processed. When the gas is processed by a thirdparty, the processingfee can be consideredthe GCA.Ifthe producer is processing its own gas, the GCA iscalculated according to an accepted formula which includesoperatingcosts, depreciationoverremaining lifeand a 15percent return on averagecapital employed. Agooddescriptionof GCA and customprocessingfees isprovided in Chapter 6 of the Gas Royalty Gn/defines(AlbertaEnergy, 1990).
Crude Oil Royalty. Alberta Regulation 248/90(Province of Alberta, 1991 b), as amended, was thebasis for crude oil royalty calculations in Alberta,but itwill have to be updated after the changesannounced inlate 1992.
Crude oil royalties are a function of age, gravity, priceand production rate. "Age" refers to the classificationof oil as old, new, or third tier. "Old oil" is basicallyoildiscovered prior to April, 1974; "new oil" dates fromafter March, 1974. "Third tier oil" was introducedas ofOctober, 1992 and initiallydescribed asoil from"newlydiscovered pools," with any further definition to becontainedin revisions to regulations.
"Gravity"refersto theclassification ofoil aseitherlight,mediumor heavy with the intention that heavy oil willbe subject to a lower royalty. Price adjustmentis basedon a "par price" and a "select price," both as publishedin Alberta Department of Energy information letters."Productionrate" refers to monthly productionrate.
Crude oil royalty is calculated according to Equation(4):
(2)
(3)R = ::.:22'-'.(B=c),---+---,c,-,,(F,---=."B)F
where R = the Crown royalty share (%)B = the select price for the monthc = the royalty factor for the monthF = the producer's averageselling price for
the month
Royalties on pentanes plus are presently under reviewand changes are potentially forthcoming in the nearfuture.
From Schedule3 of the regulation, royalty payable onsulphur obtained by processing natural gas is 16'/3percent of the sulphur. Sulphur royalties, unlikeother royalty payments, are deductible against incomein calculating federal income tax; however, sulphurrevenuesalso do not qualify for resource allowance, asdiscussed in Section21.5.
From Schedule 4, the percentage rate of royaltypayable on any product obtainedby processing naturalgas and to which Schedules 1,2 and 3 do not apply is30 percent of the product. This rate is presentlyappliedto propane and butane; however, with the royaltyreview, this rate is also subject to change.
R=R _[(R,-5)(16.9-P)']c (16.9)'
where R., = the normal royalty payableP = the average daily production
Effective January 1, 1994, calculations of Crownnatural gas royalty share will be based on either theAMP or a corporate average price, the choice havingbeenmadeby theproducer. Forpurposesofthis calculation, the corporateaverageprice cannotbe less than 90percent of the AMP.
From Schedule 2 of the regulation, pentanes plusroyalties are determinedaccordingto Equation (3):
258
_______________________.-sft
CASH FLOW ANALYSIS
There are two kinds of basic royalty: one defined fornew and old oil and the other for third tier oil. In turn,the basic royalty for new and old oil is calculated byusing one of two equations: one for production ratesless than or equal to 190.7 m3/month and one for production rates over that value. The basic royalty for thirdtier oil has three values. It is equal to zero for production less than or equal to 20 m3/month and is calculatedusing one equation for production between 20 and 190.7m3/month and another for production over 190.7m3/month. Table 21.4-2 summarizes the equations usedto calculate basic royalty.
Table 21.4-2 Summary of Equations for BasicRoyalty
r = (O.IB+O.4 (A-B)) x 100 (7)A
It should be noted that while the same formula is usedfor all types ofoil, there is a different maximum royaltyintent set for each. This maximum is 35 percent for oldoil, 30 percent for new oil, and 25 percent for third tieroil.
The royalty rate, R, is price sensitive only up to the parprice that causes "r" to reach its cap. Above this parprice the royalty factor is reduced to maintain R at itsmaximum. Table 21.4-3 summarizes the changes to calculation of Alberta crude oil royalty as announced bythe provincial government in October of 1992.
where r = the royalty intent (%)
The royalty intent is based on a well reference rate of572.1 mvmonth and is calculated according toEquation (7):
The par price, A, is a representative wellhead price.There are now separate par prices for light and heavyoils for purposes of determining royalty rates.
There is one select price, B, for old oil which applies toboth light and heavy oil. There are two select prices fornew oil with one set for new heavy and another for newlight oil. Still another select price will be set for thirdtier oil.
The royalty factor, f, is further identified as k for oldoil, y for new oil, and z for third tier oil. These threefactors are all calculated using Equation (6):
Rateimvmon) New Oil TOld Oil ThirdTierOil
0-20 0Q2
2755.04
20 - 190.7(Q-20)'
2207.46
> 190.7 [(Q-190.7) x 0.115385] + 13.2
Source: Newsrelease,AlbertaEnergy,October21,1992.
•
k z = [(r%)(572.1) -I] / (A-B)],y, 57.2 [A (6)
Table 21.4-3 Summary of Alberta Crude OilRoyalty Rate Changes
BaseRate Marginal Rate RateCap('Yo) ('Yo) ('Yo)
Current New Current New Current New
ThirdTier n.a. 10 n.a. 40 n.a. 25New Oil 212/ J 10 30 40 30 30OldOil 212/ J 10 40 40 40 35
Source: Newsrelease, AlbertaEnergy, October21,1992.
Royalty factors, par prices and select prices are to belisted in the Alberta Energy information letters.
The Operator, as Agent for the Crown, is responsiblefor delivering Crown royalty crude oil volumes to theAlberta Petroleum Marketing Commission (APMC), agovernment-sponsored agency. The APMC markets thecrude oil and, since the buyer of the APMC crude maynot be the same as the buyer of the producers' crude,the price received for the Crown royalty volumes willnot necessarily equal the producers' sale price.
Royalty Tax Deduction. As discussed in more detailin Section 21.5, certain Crown charges, principally royalties, are not deductible in calculating federal taxableincome. Instead, the provinces of British Columbia,Alberta and Saskatchewan make available a royalty taxrebate that is based on the difference between theseCrown charges and resource allowance.
Alberta taxpayers can deduct from Alberta tax payablean amount which is essentially the product of the provincial tax rate and the "attributed Canadian royaltyincome" (ACRI), the amount by which provinciallevies exceed resource allowance. Any unclaimed
259
where R tax rate: 0.269 for liquids, 0.069 forsolution gas
V = price per m3 for liquids, or 103 scm forsolution gas
M = annual production
Further details on the present ARTC program areavailable from the Corporate Tax Administration groUpof Alberta Treasury.
Production Royalty. Production royalty is defined withreference to the recipient. If the recipient is subject toCrown charges, such as Crown royalties, provincial minerai taxes and road allowance levies, i.e., nondeductibleCrown charges for income tax purposes, the royalty istermed a production royalty. This definition is important for tax purposes because production royalty incomeis eligible for resource allowance (Section 21.5).
Resource Royalty. Resource royalty is royalty receivedby a recipient; it is not subject to Crown royalty chargesand is ineligible for resource allowance.
Oil Sauds Royalty. Royalty for oil sands development,such as the Syncrude operation, is usually determinedaccording to contract terms negotiated between the developer and the provincial, and sometimes the federal,government.
Freehold Royalty. Where mineral rights are held by aparty other than a government, they are classified asfreehold mineral rights, and the lands are generallyreferred to as freehold lands. Royalty obligations associated with production by other than the owner of therights are negotiated between the lessor and thelessee.
Mineral Tax. In the absence ofownership rights on oiland gas produced from freehold lands, and the concomitant right to impose a Crown royalty, governmentsimpose a mineral tax, typically calculated on an annualbasis. To illustrate, the following is a discussion of theFreehold Mineral Rights Tax as levied on productionfrom nonCrown lands in Alberta. However, the mineraltax structure is presently being reviewed with a view topossible updating.
This tax is a function of both price and rate, and issubstantially lower than Crown royalty, to account forthe fact that the producer is paying royalty to the ownerof the freehold mineral rights. For crude oil, solutiongas and condensate, the tax formula is:
deduction can be carried forward indefinitely. Ifresourceallowance exceeds the provincial charges, no royaltytax deduction is available; however, neither is there taxon the excess.
Saskatchewan has a royalty tax deduction similar toAlberta's; the rebate is the lesser of Saskatchewan taxotherwise payable or the royalty tax credit. The tax creditfor the year is a function of the Saskatchewan tax rateand the "adjusted attributed Canadian royalties andtaxes" (AACRT). Unclaimed credits can be carried forward, and any excess ofresource allowance over Crowncharges is not taxed.
In British Columbia, a taxpayer first computes a basictax, using resource allowance and nondeductible Crowncharges. A notional tax is then calculated based on noresource allowance and deductible Crown charges. Thedifference between the two is the rebate, which is addedor subtracted as an adjustment to the total tax payable.
Alberta Royalty Tax Credit. As royalty is a government program, there is opportunity for government tomake incentives available. One such incentive programis the "Alberta royalty tax credit" (ARTC). First implemented in 1974, it was updated as ofJanuary I, 1990 toa 5-year program providing a variable percentage taxcredit. While there is now no specified limit on the refund itself, there is a limit of $2,500,000 on the amountofroyalty base that is eligible for the credit in each year.The credit is a function of the "par price" of oil and isset quarterly by reference to average par prices in thepreceding quarter. It varies from a high of 85 percentwhen the average par price falls below $100 per cubicmetre, to a low of25 percent when the average par pricerises above $210 per cubic metre.
A number of amendments were made to the originalprogram to limit the multiplication of royalty tax credits that could otherwise occur if a corporation that wasclaiming the maximum credit disposed of producingproperties to a party claiming less than the maximum.Briefly, an above-limit, or restricted, corporation is onethat has a royalty obligation in excess ofthe amount onwhich it can eam a credit. A restricted resource property is an interest in a producing property that wascompleted before 1989 and disposed of after 1989 by arestricted corporation. Royalties on production attributed to that interest cannot be included in the AlbertaCrown royalty base for any of the holders of the interest. Also, as a general rule, the maximum allowablecredit under the existing program must be allocatedamong corporations that are associated in a taxation year.
260
tax=RxVxM (8)
CASH FLOW ANALYSIS
tax s Ax Vx M (II)
For solution gas, M is the production in thousands ofstandard cubic metres. For crude oil and condensate:
for annual production, Q, less than 2288.4 cubicmetres, and:
A ~ R _[ (R-.Ol) X (16.9-ADP)' (I 2)
(16.9)' ]
Amounts in the accumulated CDE account may bededucted from taxable income at rates of up to 30percent of the remaining balance.
Canadian Exploration Expense (CEE). Defined inparagraph 66.1(6)(a) of the Income Tax Act, CEE isexploration cost incurred after May 6, 1974 and includessuch things as geological, geophysical and geochemical expense, the drilling of exploration wells, and thecost of dry holes. A principal business corporation, asdefined in paragraph 66(15)(h) of the Tax Act, mustdeduct the lesser of the amount in the account andthe company's income for the year (exclusive of dividends from foreign and Canadian corporations' that areexempt from tax, and before any amount is deductedfor depletion.)
For all other taxpayers, deducting the full value of theirCEE pool against their income is an option.
Canadian Oil and Gas Property Expense (COGPE).Defined in 66.4(5)(a) of the Income Tax Act, COGPEis basically the cost incurred in acquiring a Canadianresource property after December 11, 1979. This isdefined in paragraph 66(15)(c) of the legislation andcan include drilling and production rights and royaltyinterests. Cumulative COGPE, the amount in the taxaccount balance, may be deducted at an annual rate ofup to 10 percent ofthe balance in the account.
Nontangible portions of property sales are chargeddirectly to this account. If a negative balance resultsat year end, this balance is transferred to the CDEaccount. Any resulting negative balances created in theCDE account must go into income.
Resource Allowance. With the exception of sulphurroyalties, provincial Crown royalties are not deductibleagainst federal income tax. While not explicitly identified as such in tax legislation, resource allowance existsas a means of recognizing this inequity. "Resourceallowance" is a deduction against income and is calculated as 25 percent of adjusted resource profits (Table21.5-1), using only production-related income anddeductions.
In an ongoing debate between tax authorities andtaxpayers as to what constitutes "production-relatedincome and deductions," it has been Revenue Canada'sposition that, for principal business corporations, allG&A expense is to be deducted in calculating resourceallowance. This interpretation has now been successfully challenged, and the courts do not agree withRevenue Canada's interpretation [see The Queen v .Gulf Canada Ltd., 92 DTC 6123 affirming 90 DTC6622(FCTD)].
(9)
(10)
M ~ (0.0833Q)'
105.94
M ~ ( Q ) -228.044
where R ~ tax rate; currently 0.069ADP ~ average daily production per well
If the average daily production for a year is greater thanor equal to 16.9 thousand standard cubic metres, theformula is the same as that for solution gas.
21.5 FEDERAL CORPORATE INCOMETAX
Tax rules are constantly being updated, either throughlegislative change or court interpretation, and taxplanning is, at least in part, a function of corporateobjectives. Consequently, planning and calculation ofincome taxes should be done with professional advice.
With the rules of the game constantly changing, itis difficult to find an up-to-date reference for theCanadian tax system. Nevertheless, Krukowski (1987)provides not only a good overview, but also someuseful background on the oil and gas industry.
Canadian Development Expense (CDE). Defined inparagraph 66.2(5)(a) of the Income Tax Act, CDE isdevelopment-related cost incurred by the taxpayer afterMay 6, 1974. The cost is an intangible cost which,generally speaking, is expended in the drilling ofwells.It includes the drilling, completing or converting ofany well that does not qualify as a Canadian exploration expense, the cost of recompleting a well afterNovember 16, 1978, and the cost of any Canadian oiland gas resource property acquired before December12, 1979.
for Q greater than or equal to 2288.4 cubic metres.
For natural gas, ifaverage daily production for a year isless than 16.9 thousand standard cubic metres:
261
Table 21.5-1 Cash Flow and Income Tax Summary
Income Earned Resource CashTax Depletion Allowance Flow
Gross RevenueWorking Interest XX XX xx XXProduction Royalty XX XX XX XXDeemed Income XX XX XX -
ExpensesCrownRoyalty - - - yyMineral Tax - - - yyProduction Royalty yy yy yy yyLease Operating yy yy yy yyCrownLease Rentals yy - - yyCCA - Production yy yy yy -G&A - Production yy yy yy yyCEDOE - - yy yy
--Adjusted Resource Profits (ARP) ZZResource Allowance (25%of ARP) yy yy -
Resource RoyaltyIncome XX XX XXResource Royalty Expense yy yy yyCCA-Other-Resource Profit yy - -G&A-Other yy yy yyInterest yy yy yyCOGPE yy yy -CDE yy yy -CEE yy yy -
-Resource Profits(RP) ZZEarnedDepletion (25%of RP) yy -Other
ForeignIncome XX , XXForeignExpense yy yyNonproduction Income XX XXNonproduction Expense yy yy
- -Net Income For Tax Purposes ZZ Cash Flowbefore IncomeTax ZZ
Source: University of Calgary and Canadian Petroleum Tax Society, 1991.
Notes: XX represents an addedamount.yy represents a subtracted amount.ZZ represents a sum.
262
,» ,_____________________Fi1
CASH FLOW ANALYSIS
Table 21.5-1 is a simplified summary of the federalincome tax calculation and the cash flow calculationfor an oil and gas company. The four columns illustratethe calculation of income tax, eamed depletion, resourceallowance and cash flow by identifying the parameterswhich are employed in the determination of each.
Earned Depletion. While this item has been effectivelyeliminated for oil and gas producers, some companiesstill have an unclaimed earned depletion base that maybe utilized as a deduction against income. A taxpayer ispermitted to deduct the lower of the earned depletion,which would have existed under prior legislation, or theremaining base. The calculation of earned depletion isillustrated in Table 21.5-1.
Capital Cost Allowance (CCA). This is the taxequivalent ofaccounting depreciation and in theory allows a business to recover its original tangible assetinvestment without having to pay tax on it. CCA accumulates in pools of prescribed classes which arededucted, at the option of the taxpayer, on the basis ofafixed percentage of the declining balance.
Tangible costs, which are grouped into CCA, should bedifferentiated from intangible costs, which are groupedinto CDE and CEE. As a first approximation, tangibleassets are located above ground, although they wouldalso include production tubing and sucker rods.
Production-related assets, which reduce resourceallowance, must be differentiated from nonproductionassets, which do not. Again, as a first approximation,equipment which is upstream of an inlet separator isproduction-related. Production-related CCA is a deductible expense when calculating resource allowance,thereby reducing its effectiveness as a tax shelter forresource income by 25 percent. Accordingly, a taxpayerwould be motivated to maximize not only the amountofCCA which is deducted against nonresource income,but also amounts of COGPE, CDE and CEE.
Disposal of a tangible asset yields a credit (not toexceed the original cost of the asset) for the pool intowhich the assets were originally grouped. Ifa negativebalance in the pool results, this balance must be includedin income. If the assets in question are productionrelated, this income will qualify as resource profits.
Canadian Exploration and Development OverheadExpense (CEDOE). This G&A expense is not substantially directed toward exploration and development andmay be completely written off in the current year,or capitalized. If capitalized, it would be deducted incalculating resource allowance in the year it was
incurred, added back in the income calculation, and thenincluded in either CDE or CEE.
Successor Rules. Alterations in a corporation's status,brought about by such things as mergers, acquisitionsand changes in control, receive particular treatmentwithin the Income Tax Act. A proper understanding ofthe associated rules and regulations is best left toprofessional advisors.
21.6 FINANCIAL STATEMENTSCompanies produce annual financial statements as anaccounting of their performance during the year and theirstatus at the end ofthe year. The information containedin these statements can yield historical annual cash flownumbers.
Balance Sheet. If a company follows the full costmethod ofaccounting, whereby all costs ofacquisition,exploration for, and development ofoil and gas reservesare capitalized, the value ofthe asset identified as "Property, Plant and Equipment" is limited by a "ceilingvalue." This ceiling value is effectively determined byperforming a cash flow analysis on the company's reserves. It would include the value ofthe proved reservesplus the lower of cost and estimated value of undeveloped properties.
"Depletion and Depreciation," listed on the asset sideof a balance sheet, are accounting terms and are notequivalent to "Earned Depletion" and CCA, as used inthe income tax calculation.
On the liability side, anticipated future costs for "SiteRestoration and Reclamation" are listed. These amountsare the company's estimate of future liabilities-attoday's prices-and should be consistent with those usedin the cash flow analysis, although they will have to besegmented into annual amounts and escalated to theappropriate year.
Statement of Income. Revenue from petroleum andnatural gas is usuallynet ofroyalties and includes ARTC.G&A, with the exception ofamounts capitalized, shouldbe similar to that used in cash flow analysis, while, asmentioned previously, depletion and depreciation arenot. Current income tax should correlate with that usedin cash flow. Deferred income tax is a noncash itemrelating mainly to the timing difference between claimsfor tax purposes of CCA, exploration and developmentcosts, and the amounts of depletion and depreciationlisted in the financial statements.
Statement of Changes in Cash Position. Thisstatement can be derived from the balance sheet and thestatement of income. Typically, the amount listed
263
as "cash flow from operations," when added to theinterest expense listed in the statement ofincome, givesthe cash flow being discussed. When interpreting thesestatements, the reader should also check to see howchanges in working capital are addressed.
Investments (such as capital expenditures andacquisitions) listed on this statement may have exceededthe company's cash flow for the year. In that case, thecompany will have had to either borrow money or getan injection of equity. These investments should haveeach been the subject ofan investment decision processwhich would have included a cash flow analysis.
21.7 FINANCE AND ECONOMICCONSIDERATIONS
Cash flow analysis and investment decision-makinghave a basis in theory, and to appreciate them someunderstanding of this theory is important. The following is a simplified discussion ofthe theory. For a morein-depth review, the reader is advised to consult a business finance text such as Lusztig and Schwab (1988).
Net Present Value (NPV) and Internal Rate ofReturn (IRR). These are the two most widely usedterms in investment decision-making. "Net presentvalue" is the value obtained when all cash flow streams,including the investment, are discounted to the presentand totalled. "Internal rate of return" is the discount ratewhich will give an NPV ofzero, meaning the discountedcash flow stream is equal to the cost of the investment.
For investments involving initial expenditure andsubsequent inflows of cash, a plot of NPV against discount rate yields a downward slopingcurve which showssteadily decreasing NPV with increasing discount rate.This curve intersects the discount rate axis (NPV equalto zero) at the IRR. The apparent drawback ofusing theIRR is that it, by definition, assumes that the unrecoveredinvestment can be re-invested at this rate. On the otherhand, the NPV is expected to be positive, which normally implies that the IRR exceeds the cost of capital.When NPV is used, the investment is to provide a benefit beyond the cost of funding. When IRR is used, theyield is to exceed the cost of funding. In that respect,the two methods are complementary.
Project Abandonment. Use of NPV as a decisionmaking tool should not be limited solely to the initialinvestment decision. Rather, a project should be checkedthroughout its life to ensure that it has a positive NPV.If at any point it does not, a sponsor should seriouslyconsider abandoning the project since, from that pointon, the investment will be incapable of generating its
264
DETERMINATION OF OIL AND GASRESERVES
funding costs. In this regard, the concept of "sunk costs"is introduced; monies that have been spent should nolonger be incorporated into the investment decision.
Weighted Average Cost of Capital (WACC). The"weighted average cost of capital" is the average aftertax cost to the company of all the components of itscapital structure. These are not just loan interest costsbut the cost of all forms of debt, including the cost ofpreferred shares and common shares. Lusztig includesinternally generated funds, such as retained earnings anddepreciation, when discussing a firm's WACC.
All components should be included at their current costsince they will be used when making new investmentdecisions. The proportions of each can be based on theexisting capital structure or a targeted new capital structure with total capitalization based on current marketvalue.
Discount Rate. By definition, an after-tax cash flowstream that is discounted at a firm's WACC and yieldsa positive NPV will pay for the project's funding costsand generate a residual gain for shareholders. In mostsituations, therefore, the appropriate discount rate to useis the WACC.
The use of one discount rate for a firm's decisionmaking presumes that all ofthe firm's projected investments carry the same degree of risk. This may not bethe case. Where a project is perceived to carry a higherrisk, an investor would reasonably expect a higher yield.This would result in a higher WACC and a concomitanthigher discount rate for the project.
While theory suggests the derivation of a uniquediscount rate based on a project's WACC, other optionsare often employed. One common practice is to calculate the discount rate by adding a risk premium to thefirm's normal WACC. This risk premium is usuallybased on intuition and is therefore, by its very nature,somewhat arbitrary. Nevertheless, it is often a practicalway around the difficulties inherent in calculating aproject WACC.
Apart from the problems associated with determining arisk premium, there is normally some uncertainty attached to deriving any WACC, particularly the equityportion. This is one reason why, in actuality, thediscount rate used is often the one that is in popularuseage at the time, especially if two parties arenegotiating a value.
'-1" !
___.-.a
CASH FLOW ANALYSIS
ReferencesAlberta Energy. 1990. Gas Royalty Guidelines.
Alberta Energy Report, Dec. 1990, Pub. No.T/205·1990.
British Columbia Ministry of Energy, Mines andPetroleum Resources. 1992. British Columbia Oiland Gas Royalty Handbook.
Curran, R. 1992. "Slow Out of the Gate." Oilweek,Apr. 1992.
Krukowski, J.V. 1987. Canadian Taxation ofOil andGas Income (2nd ed.). CCH Canadian Limited,Don Mills, ON.
Lusztig, P.A., and Schwab, B. 1988. ManagerialFinance in a Canadian Setting (4th ed.).Butterworths, Toronto, ON.
0'Den, S., Pearse, J., Miller, c., and Tarvydas, R.1991. Petroleum Fiscal Systems in Canada (rev.3rd ed.). Energy, Mines and Resources Canada.
Province of Alberta. 1991a. Mines and Minerals Act,Alberta Regulation 246/90. Office Consolidation,Queen's Printer for Alberta (amendments to33/91).
---. 1991b. Mines and Minerals Act, AlbertaRegulation 248/90. Office Consolidation, Queen'sPrinter for Alberta (amendments to31191).
Saskatchewan Energy and Mines. 1990. Statutes andRegulations, Release No.9 (amended Ju\. 1991and Sep. 1991).
University of Calgary and Canadian Petroleum TaxSociety. 1991. Taxation ofCanadian Oil and GasCompanies: An Introduction. Calgary, AB.
265
Chapter 22
UNCERTAINTY AND RISK IN RESERVES EVALUATION
22.1 INTRODUCTIONThere is always uncertainty in an estimate of thevolume or value of oil and gas reserves because few ofthe factors involved are known with certainty. The traditional deterministic approach does not make anyallowance for uncertainty, and stochastic, or statistical,methods are required to assess it. Stochastic methodsmay be more time-consuming, but they make better useof available data and can yield important informationthat cannot be obtained from a deterministic evaluation.The degree ofuncertainty can be of critical importanceto investment and planning decisions, and an inadequateappreciation of it can lead to costly failures. For everyevaluation, a decision has to be made as to whether theimproved understanding resulting from a stochasticevaluation warrants the additional time that is required.The high cost of failure for most petroleum venturessuggests that stochastic methods should be used morethan they are at present.
This chapter examines concepts of uncertainty in theestimation of oil and gas reserves and discusses the aspects of statistics and decision theory that provide themethods for stochastic reserve assessments.
Masters (1984) reviews the background of theapproaches discussed in this chapter and emphasizes theneed for common sense in their application.
22.2 CONCEPTS
22.2.1 Definition of Risk and UncertaintyThe terms "risk" and "uncertainty" are used in manydifferent ways, and caution is required when using them.In this chapter, risk is defined as the probability oflossor failure and is relevant only in the context of decision-making; uncertainty is defined as the spectrum ofpossible outcomes of an evaluation. More completedefinitions of various types of uncertainty are givenin Section 22.2.3, and the relation of uncertaintyand risk to probability distributions is illustrated inFigure 22.2-1.
266
22.2.2 Describing UncertaintyThe uncertainty in a reserve estimate can be describedin a number of ways, one of which is the use of thetraditional terms, proved, probable and possible. However, there is no ready way of quantifying the level ofdifferences expressed by such "point" estimates. Statistical measures such as ranges, standard deviations,confidence limits, and frequency, especially when showngraphically, convey a large amount of information thatcannot be grasped readily in other ways and that is notgiven by point estimates.
Expectation is the mean of all possible outcomes ofanevent and is a commonly used single-value summarymeasure that incorporates some of the effects ofuncertainty. It is often used as a decision criterion, but thefollowing discussions on alternative approaches todecision-making are worth noting: Newendorp (1975a);McCray (I975a); and Tversky and Kahneman (1985).
22.2.3 Areas of UncertaintyUncertainties arise in the following areas of reservesevaluation (Garb, 1988; Robinson, 1990):
Technical Uncertainty, which can be further dividedinto the following:
• Geological Uncertainty, which is concerned withthe estimation ofhydrocarbon volumes in place. Onceestablished, geological parameters are not usuallychanged significantly.
• Engineering Uncertainty, which arises from therecovery process. Once engineering parameters havebeen established, significant changes usually occuronly as a result of technical advances.
Economic Uncertainty, which arises f;om marketforces, and includes the major uncertainties in price,costs, taxes, and royalties. Economic uncertainty canbe difficult to estimate because changes are usually lesspredictable than for the more stable technical areas.
Political Uncertainty, which includes political aspectsof local and national taxes, environmental regulations,
--------------------_...
UNCERTAINTY ANDRISK INRESSRVES EVALUATION
(a) Probability Density Function (PDF) of Net Present Values (NPV)
Risk: Loss will occur in about20% of the possible outcomes.
0.4
0.1
Confidence Interval: There is about a70% probability that the outcome willfall within this confidence interval.
Chance of Success = 80%
·100 -50 a 50 100 150 200
Net Present Value, NPV ($ x 10')
(b) Cumulative Distribution Function (CDF) or Expectation Curve of Net Present Values(i.e., the cumulative area below the frequency distribution curve in "greater than" form)
0.8
1.0,----__
0.6
~c:Q)::l0-~u..
.~1ij:;E::lo
0.4
0.2 Loss ~--- ---. Gain
•
a .L__~-~-_1_-_,_---,--__.;.::::::::O=r--
-100 -50 a 50 100 150 200
Net Present Value, NPV ($ x 10')
Notes: 1. Uncertainty is represented by the fact that an outcome could fall anywhere on the NPVaxis with differing probabilities.
2. Chance of success is 80%.
3. Risk of loss is 20%.
4. The mean outcome or expectation is $50 x 10'.
Figure 22.2-1 Risk and Uncertainty
267
market control, price control, and threats of nationalization, civil unrest, and war. Because political uncertainty operates ultimately through the same factorsas economic uncertainty, political uncertainty maybe regarded as an aspect ofeconomic uncertainty. However, the unpredictability and the potential for abruptdistortion of the market warrants the separate category.It is very difficult to quantify, and an assessment ofseveral scenarios is often the best approach. .
Uncertainty may also be classified as:
Parameter Uncertainty, which is associated with thenumbers used for an assessment, for example, porosityvalue taken as the average of core plug measurements.
Model Uncertainty, which is a consequence of thedegree to which a model used for the evaluation of reserves represents the real world. The effect is more likelyto be one of "bias" rather than "error." This effect canbe very significant, and may be difficult to assess.Examples of models used in reserve valuation are geological maps drawn assuming a particular depositionalenvironment (e.g., beach sand or tidal channel sand?)and the algorithms used for log interpretation or for aneconomic evaluation (including the discounted cash flowmodel). Drew's (1990) account of the evolution of methods used for estimating undiscovered hydrocarbonvolumes is a good illustration of the gradual reductionof uncertainty as progressively better models areadopted.
The uncertainty in a reserve estimate decreases asproduction and knowledge increase until, at the time ofabandonment, there is little or no uncertainty. Figure22.2-2 is an idealized schematic representation of this.The range of reserves estimates is shown by the upperand lower limits of the estimates. As time passes andthe well is produced, the range decreases and the limitsconverge until the range becomes zero, and they meetat the time of abandonment.
In a real case, there would be:
• A bias in the estimates
• An asymmetry in the range of uncertainty
• Changes in economics and technology over the lifeofa project that would result in a curve not as smoothas this one
22.2.4 Causes of UncertaintyReserve estimation is fundamentally a measurementprocedure, and the relationships that exist betweenactual and estimated reserves and the associated
268
DETERMINATION OFOIL AND GASRESERVES
uncertainties can be summed up by the stochasticreserve relation:
actual value of reserves = estimated value ± uncertainty
whereuncertainty = error ± bias
All of the factors in the relation will change withtime and with time-dependent factors such as priceand technology. The relation applies to all parameters involved in the assessment of reserves, and theindividual uncertainties are combined according to established statistical procedures to give the uncertaintyin a final result. Although it is usually not possible toseparate "error" and "bias," an understanding of theseconcepts is essential to improving the quality ofreservevaluations. The effects of error and bias are showndiagrammatically in Figure 22.2-3.
Actual Value is never known except, perhaps, at thetime of abandonment of a property, as shown in Figure22.2-3(g).
Estimated Value, as shown in Figure 22.2-3(a) and (b),is determined by technical estimation procedures andeconomic evaluation and reported in reserves reports.Changes in technical and economic conditions result inchanges to estimated and actual reserve volumes andvalues, even if the error and bias are zero.
Error, as shown in Figures 22.2-3(e) and (t), resultsfrom the inherent uncertainty of measurement and analytical procedures, and can be positive or negative. Theactual value lies at an unknown position within a confidence interval, the size of which is determined by theconfidence level specified as shown in Figure 22.2-3(t).For example, "proved reserves are 250 ± 35 x 103 rn'"may mean that there is a 70 percent probability that theylie between 215 and 285 x 103 m3. The probability ofthe actual value lying within a confidence interval of aparticular size is represented by a frequency distribution (an envelope of all possible confidence intervals)as shown in Figure 22.2-3(e). Although errors cannotbe eliminated, they can be minimized by careful technical work and quantified by statistical techniques. Errorsalso result from mistakes (e.g., arithmetic, clerical), butthese are generally ofless importance and can be minimized by careful work and checking.
Bias, as shown in Figures 22.2-3(c) and (d), is asystematic deviation from the actual value or distribution and is a combination of two effects. Campbell(1986) provides excellent examples of bias and otherfactors that can affect petroleum evaluations; the
•-------------- .aIIIIiI
UNCERTAINTY ANDRISK INRESERVES EVALUATION
-Exploratlon -.-,------ Production
Actual Reserves
<J)
~Q)<J)Q)
a:
-<:Ql
E<:o
"C<:
1l<t:
Time
Source: Garb, 1988.
Method ofDeterminingReserves
Analog - - - - - - .....-- - - Volumetric - - - - - - - _ ~
- Material Balance - - - - - - - ~- - Decline Curves - - - - -
Figure 22.2-2 Level of Uncertainty in Reserves Estimates during the Life of a Producing Property
discussion and quotation that follow are from Spetzelerand Stael von Holstein (1975):
• Displacement Bias is a shift ofthe whole frequencydistribution curve to higher or lower values. This isshown in Figure 22.2-3(d).
• Variability Bias is an alteration of the shape ofa frequency distribution curve. This is shown inFigure 22.2-3(c). This is usually a central bias thatmakes a distribution narrower than is warranted (i.e.,represents a greater degree of certainty than is justified by the state of knowledge). Capen (1976)convincinglydemonstrates this tendency and suggestsa method of minimizing the problem.
The following are the origins of bias:
Motivational Bias, which is defined as "eitherconscious or subconscious adjustments in thesubject's responses motivated by a perceived systemof personal rewards for various responses. He maywant to bias his response because he believes that hisperformance will be evaluated by the outcome.Finally, the subject may suppress the full range ofuncertainty that he actually believes to be presentbecause he believes that someone in his position isexpected to know with a high degree of certainty whatwill happen in his area of expertise" (i.e., he wishesto appear more decisive than is really warranted).
269
,'"',"'''''''''0'''''''"'_ ,
(a)Result of Deterministic Evaluation
Estimated Value (May not coincide with the peakof the frequency distribution)-
(b)Result of Stochastic Evaluation
Positive Displacement+ Central Variability Bias
(c)
/Broadening"" "/ (Less common) " " Variability Bias
(d)
(e)
Negative Displacement Bias~"'~ ...,,,,,, -
Positive Displacement Bias
Displacement Bias
Error (Frequency Distribution)
(f)
Range of UncertaintyIntroduced by Error
I I
Actual Value
Confidence Limits
(g) ______t _Reserve Volume
Figure 22.2-3 The Effect of Error and Bias on a Reserve Estimate
270
c
UNCERTAINTY AND RISK IN RESERVES EVALUATION
for 73% of the companies
for 27% of the companies
100
Figure 22.2-4 Expectation Curves: Comparisonof Results
Project B
Risk
(%)o
15
\ __- Project A
EMV'
($ x 103
)
100100
20
~60~.c 40e0..
Project AProject B
'Expected Monetary Value
I. Project evaluation, for which there would be an overall improvement ifthere were a better understandingof the risks involved.
2. The comparison of projects in order to select themore appropriate one. For example, Figure 22.2-4shows the expectation curves 1 for the evaluationsof two projects with the same median NPVs of$100,000, but with very different risk profiles.
Project A is a low-risk venture that will not losemoney, but has little chance ofmaking a great profit.Project B has a 25 percent risk that it will losemoney, but it has a potential for a higher reward(e.g., a 20 percent probability ofa net present value(NPV) greater than $250,000). Without the additional information provided by an analysis of theuncertainties, there is no objective way to choosebetween the two projects. Which of the projects ispreferred will depend upon the risk acceptance levelofthe decision-maker and the budget available. Thisapproach can also be used to analyze a portfolio ofprojects in order to avoid "Gambler's Ruin.'? With
-100 -50 0 50 100 150 200 250 3003
Net Present Value, NPV ($ x 10 )
22.2.5 Magnitude of UncertaintyThe uncertainty in an evaluation ofhydrocarbon reservesdepends on the particular property. However, for a singleproperty in western Canada, at the start of production,the uncertainty in volume will typically be about±25 percent. Uncertainty generally decreases as cumulative production increases and as more informationbecomes available (Figure 22.2-2).
A feeling for the magnitude of uncertainty in volumeestimates can be gained from a study of the revisions inthe reported proved reserves of 70 oil and gas companies over a period of7 years (Campbell, 1984, 1988) inwhich 86 percent of the companies displayed positivebias for oil (i.e., proved reserves were initially overestimated, and annual reductions were needed). The averageannual reserve revision (mostly downwards)for oil was as follows:
o- 10% for 72% of the companies
10 - 50% for 26% ofthe companies
> 50% for I % of the companies
Companies generally displayed neutral to negative biasfor proved gas reserves. Average annual reserve revisions (almost equally up and down) for gas were asfollows:
1-10%
10 - 34%
• Cognitive Bias, which depends on an individual'smode ofjudgement. This arises from factors such ashislher knowledge base, method ofprocessing information (e.g., a judgement may be biased to a recentpiece of information because it is the most easily recalled), or the representative nature ofan analog usedto make an assessment. Cognitive bias is probablyan important source of model uncertainty.
Specific, clear procedures, quality control, experience(i.e., a large knowledge base), competent technical work,the use of statistical techniques and third-party review,common sense, and a determined effort to maintainobjectivity are all required to minimize the effect ofbiason reserves evaluation.
22.2.6 Use of UncertaintyAn appreciation of uncertainty and the associated riskof a reserve volume or value estimate is an importantelement in making decisions. Many ventures wouldbenefit from a more thorough analysis that includedestimates of uncertainty; for example, the eliminationof one dry hole would justify a substantial amount oftime spent on risk analysis. Other applications include:
1 An expectation curveis a cumulative distributionfunction showing the probability that a value on thex-axis willbe exceeded.
2 Gambler's Ruin is the probability that in a series ofventures that will be profitable in the long run, a shortrun oflosses will exhaust the financial resources of tbeparticipants.
271
Sourcesof Funds
100
80
;?~ 60>.."":0<U-" 400~
0-
20
~-- Debt .---~--------- Equity
Low RiskLow Reward
Banker
Development Engineer
-«;mell!
DETERMINATION OF OIL AND GASRESERVES
---------------------
High RiskHigh Reward
Development Geologist
Low-Risk Exploration(Western Canada Basin)
High-Risk Exploration(Frontier)
-Proven Probable--Possible ---
Hydrocarbon Volume or Value
Figure 22.2-5 Expectation Curve: Reconciliation of Different Views of Hydrocarbon Volumesand Values
a strong enough budget, for example, the probability of Gambler's Ruin may be sufficiently low thata series ofhigher risk ventures like Project B can beattempted in the hope of a larger reward.
3. The reconciliation of different views of hydrocarbon volumes or values, arising from different levelsof risk acceptance. This is illustrated schematicallyin Figure 22.2-5, which shows, for example, thatthe views of a banking organization, although different from that of a frontier explorer, are part ofthe same spectrum of possible results ofa venture.This figure is schematic and, in reality, there willbe considerably more variation, but it shows thefollowing:
• The probability ranges within which development,appraisal and exploration take place
• Typical levels ofactivity for various professionalgroups
• Risk acceptance levels for different fundingsources
• Typical probability cutoffs for proved, probable,and possible reserves
272
4. The analysis of options for risk reduction. Thestrategies for this will be varied, for example:
• The acquisition of additional information (e.g.,shooting more seismic before drilling a well)
• Cost reduction as a result of spending more onproject design
• Forward contracts at a guaranteed price for productsales
• Carrying out a project in partnership, rather thanat full interest
Some of these can be analyzed deterministically,but a stochastic analysis will yield a deeper level ofunderstanding and consequent better decisions.
5. The estimation of undiscovered hydrocarbon volumes on undeveloped lands. This is discussedfurther in Section 22.5.
6. Classification of reserves. Although there isconsiderable debate on the definitions of variousclasses of hydrocarbon volumes, stochastic methods provide the only fully consistent approach.Without such an approach, there is only a limited
-------------------_....
UNCERTAINTY AND RISK INRESERVES EVALUATION
" A subjective approach is essentially an opinion basedonprevious experience, whereas anobjective approach relieson the analysis of data (e.g., core data or previous wellresults).
understanding of the probability of recovering aquoted volume.
Further examples ofthe uses ofuncertainty can be foundin several of the references cited.
Most of the parameters used to estimate reserve valuesare derived using a combination of subjective" and objective methods. All evaluations require ownership andfiscal information, but the technical parameters dependon the evaluation method being used. Volumetric evaluations require reservoir parameters (pay thickness,porosity, water saturation), drainage area, and recoveryand formation volume factors. Produced volumes andpressures are needed for material balance and declinecurve methods. More complex evaluations will requireadditional factors to be estimated, for example:
• High, medium and low case maps or alternativeinterpretations, to estimate reservoir areas
• A histogram of core porosities to represent reservoirporosities
• A price forecast, with a spread of values at anyparticular time
• Production decline curve parameters estimated byanalogy with nearby wells
• Market volumes that depend on predictions ofweather and levels of economic activity
• The availability ofpipeline capacity
• The probability ofwar or embargo
• Tax levels
The sources ofdata used to estimate uncertainty are thesame as those for deterministic estimates althoughstochastic methods generally make better use ofthe data.The sources vary from proprietary to public. In Canadathey include federal agencies (National Energy Board;Energy, Mines and Resources; Geological Survey ofCanada), provincial agencies (Alberta Energy ResourcesConservation Board; Alberta Petroleum MarketingCommission; and their equivalents in other provinces),business organizations (Canadian Association ofPetroleum Producers; Canadian Energy Research
-
22.3
22.3.1
ESTIMATION OF UNCERTAINTY
Parameters to be Estimated
Institute), businesses whose purpose is the provision ofthis information and, ofcourse, internally generated data.
Much of the data used in reserve valuation is obtainedin quantitative form (e.g., well log data, production),and a wide variety of statistical techniques can be usedfor the assessment of the data. Although objective quantitative approaches should be used as much as possible,there will always be a major subjective component toany assessment. For data not available directly, andespecially for geological parameters, analogy is particularly important. The selection of appropriate analogs isa critical element of the skill ofa professional involvedin a reserve valuation.
22.3.2 Empirical ClassificationTime limitations mean that, despite the availability ofmore rigorous methods, most oil and gas volumes areclassified as proved, probable and possible using apredominantly subjective empirical approach. Examplesofthis are the assignment ofa one-section square drainage area for a gas well, or the classification as proved,of an undrilled spacing unit lying between two provedunits. The major problem with this approach is consistency; what is reasonable to one person in one reservoiris not necessarily reasonable to another person, or evento the same person in another reservoir. An individual,or a group, may be consistent if clearly defined rules(i.e., in a "Reserves Manual") are prescribed and followed, but the results will almost invariably differ fromother individuals or groups. Despite the advantages ofthe empirical approach, an inconsistent application ofempirical rules is undoubtedly the source of many ofthe differences between reserve evaluations.
When empirical methods are used, the probabilityassociated with their recovery is, at best, poorly known.As an example, it is common to visually fit a straightline to the pressure decline in a gas reservoir, and extrapolate it to an abandonment pressure in order todetermine the reserves. The value obtained in this wayis usually called proved but, if quantified, it is oftenclaimed to represent a 80 percent probability level (i.e.,there is a 80 percent probability that a greater volumewill be recovered). However, by definition, a best-fit,straight-line extrapolation will yield a value close to themean (usually near a 50 percent probability level). Thisis a substantial inconsistency that is probably presentin many, if not most, gas reserve estimates. Similarinconsistencies occur for other empirical approachesused for both oil and gas reserves evaluation.
273
22.3.4 Quantitative EstimationThe quantitative determination of uncertainty us.esthe concepts of statistics and probability. Detailson methods mentioned here and also on other methods
VerbalDescription
Almost neverSeldomInfrequentSometimesLess than an even chanceEven chanceMore often than notOftenHigh probabilityVery high probability(Virtually) certain
The criticism must be placed in perspective. A full-scalestochastic exercise can be time-consuming and is oftenneither practicable nor necessary. Sometimes, for instance, a reserve classification is not required, merelythe assurance that a particular cutoff value or volumewill be exceeded. The empirical approach is commonbecause it is relatively easy to apply and, in many cases,will give an adequate answer. However, it should notbe used carelessly or uncritically, and more sophisticated methods should be used when warranted.
22.3.3 Quantifying Subjective EstimatesA subjective estimate is essentially the opinion of theperson making the estimate. Although it depends ultimately on this person's expertise and objectivity, somemeasures can be taken to improve the quality of a subjective estimate.
The Delphi Method uses the consensus of a team of"experts" to generate the required data. Estimates oftheprobability distributions of the parameters are madeindependently and perhaps anonymously by the expertsand combined either by averaging or by consensus.The opinions ofthe experts can be weighted (that ofthe"expert in a related field" receiving the greatest weightin some schemes), and a number of iterations can bemade. The Delphi method reconciles different opinions,including quantitative estimates, and the methods thatthe experts use can vary from entirely subjective tohighly statistical.
Familiarity with a problem will often allow the directsubjective estimation of a frequency distribution, andquestions such as, "What are the maximum, minimumpossible, or most likely values?" or "Is it likely to belog-normally or normally distributed?" are helpful. Several types of distribution can be used, although thenormal, log-normal and triangular distributions, histograms, and some discrete distributions will cover mostcases. These distributions are described in most statistical books and, more specifically in the context ofreserves evaluation, in Newendorp (1975a) and McCray(l975a). A graphical sketch of a frequency distributioncan sometimes be made; interactive graphical computerdisplays are particularly useful for this purpose.
Subjective estimates can be "disciplined" to someextent. For instance, if the distribution is consideredto be normal or log-normal, then an estimate of theprobability confidence interval corresponding to aparticular range (or vice versa) can be made and plottedon the appropriate probability paper (e.g., if data is
274
~I-,DETERMINATION OFOILAND GASRESERVES~"
considered to be log-normally distributed, and thevalues estimated cover ±20 percent on either side ofthemedian, then the high at 70 percent and the low at 30percent are plotted on log-normal paper). From the linedrawn through these points, the range at other levels ofprobability (e.g., at 90 percent to 10 percent) can beread and a decision made as to whether it is reasonable'
•ifnot, revisions can be made. Tests have shown that therange at a particular probability level is usually underestimated (i.e., there is usually a central bias). Thismethod is described by Capen (1976), whose papershould be consulted for details.
Qualitative expressions such as "good chance of," "lowrisk," "very unlikely," or "probable" may be adequatefor everyday use, but the lack of a common standardmeans that they are oflimited use for describing uncertainties in reserve estimation. Attempts have been madeto interpret these terms quantitatively, and a useful summary is given by Mosteller and Youtz (1990). It isinteresting to note that their study showed that differentperceptions of the word "possible" are so varied thatthe word is virtually useless.
A table presented by Kadane (1990) in a comment onthe paper by Mosteller and Youtz is a useful codification of terms that can be used as.a guide to quantifyingqualitative expressions. It is not ideal for oil and gasvolume estimation, and questions would have to beframed appropriately, for example, "Will the porosityfall in the range of 10 to 12 percent?" This is an activearea of statistical research, and improvements may beexpected.
Range ofProbability (%)
oto 55 to 1515 to 252'5 to 3535 to 4545 to 5555 to 6565 to 7575 to 8585 to 9595 to 100
4~_~______________________..n
22.4
22.4.1
•
UNCERTAINTY ANDRISK INRESERVES EVALUATION
(e.g., Bayesian statistics," time series, sampling,regression) may be found in statistical texts and inMegill (1984 and 1985), Newendorp (l975a), andMcCray (1975a), who describe their use in theevaluation of petroleum projects, and more generallyin Rock (1988) and Davis (1986).
Methods of determining factors such as reservoirvolume, petrophysical parameters, reservoir volume factors, and production forecasts are described in otherchapters in Parts Two and Three. From the point ofviewof estimating uncertainty, the traditional deterministicapproach to these factors must be expanded to generatethe required distributions, ranges, and high-mediumlow values, primarily using the methods of classicalstatistics.
Alternative maps (e.g., high, medium and low case) canbe drawn to derive some of the geological parametersneeded. Geostatistical methods that incorporate spatial relations have recently become available. Thesemethods generate a weighting function that is used tointerpolate or extrapolate reservoir parameters and alsoto provide an estimate ofthe uncertainty. The resultingdata is relatively objective and is particularly useful forapplications such as unitization or building models forreservoir simulation. Details can be found in Clark(1979), Hohn (1988), and Isaaks and Srivastava (1989).
Estimates of uncertainties in costs rely on subjectiveestimates, analogy, engineering analysis, and bidquotations. The type of estimate will depend on theevaluation scenario that is adopted and, in some cases,contingency costs and associated probabilities are required. The time that production starts or the phasing ofexpenditure in a major venture can affect the economicviability of a project. Improved estimates may requirethe use of techniques such as Critical Path Method(CPM) and Program Evaluation and Review Technique(PERT). CPM is a deterministic method for which high,medium- and low-case estimates can be generated, whilePERT is a probabilistic technique that generates afrequency distribution (McCray, 1975a).
Product pricing is usually the most important factor inthe valuation of an oil and gas project. The forecasting of oil and gas prices is notoriously difficult, andmethods range from purely subjective "guesses" tosophisticated, analytical probabilistic models that mayinclude the effects of weather and levels of economic
• Bayesian statistics considers the ideaof conditionalprobability in whichthe probability of an eventdependson preceding events, as in decision tree analysis.
activity. Alternative scenarios can be used to assess theeffects of different price forecasts, although a proliferation of scenarios can make the results meaningless.
METHODS OF ANALYSIS
Carrying Out a StochasticEvaluation
Stochastic evaluation methods use values that are expressed by probability distributions, not by single values.
The approach taken for a particular evaluation dependson the magnitude of the expenditure, the data, the timeand expertise available, and also the environment inwhich decisions are made. There are no hard and fastrules that prescribe the use of a particular method but,in general, the less familiar and the more complex, expensive or risky a venture is, the more sophisticated anevaluation will need to be.
At least one scenario must be established for everyproject, and several scenarios may have to be constructedto examine sensitivities or to determine the most profitable course of action. Scenarios should be constructedwith care as the same activities carried out under different scenarios can yield different results. For example,when several wells are to be drilled, the order ofdrilling and timing can make a difference to the probable outcome, as could a decision to reduce the risk byshooting seismic.
Although scenarios can vary greatly, there are usually anumber of common steps in an evaluation. The following steps (modified after Megill, 1984) assume that adecision has been made to assess uncertainties and carryout a stochastic evaluation:
I. Collect data. The old adage of"garbage in, garbageout" is relevant, and time spent on ensuring thatnecessary data has been collected and is of goodquality is usually well spent.
2. Isolate the key variables. Which parameterscontribute most to uncertainty? Trial runs may haveto be carried out. It is always better to spend moretime on the assessment of a critical parameter thanon a less important parameter.
3. Decide on the scenario and on the types andparameters of the distributions (high-medium-low,triangular, log-normal) and the method to be used(e.g., decision tree, Monte Carlo). Several scenariosmay be evaluated and sensitivities investigated inorder to optimize a project or reduce risk.
4. Carry out the evaluation.
5. Ask "Does the result make sense?" Ifnot try again.
275
DETERMINATION OF OILANDGASRESERVES
22.4.2 Decision Matrices
6. Express the answer in the fonn of a cumulativedistribution (expectation curve) or probabilitydensity function although a single-value answer(e.g., an expectation or a cut-offvalue) may also berequired.
A sensitivity analysis, which shows the effect ofvariation in individual parameters, may also beappropriate.
Area Low Medium High(m'x 103)
Net Oil Value 0.5 1.5 2.5(m) Probability 0.30 0.6 0.10
Low 50 25 75 125OJ 0.09 0.18 0.03
Medium 200 100 300 5000.5 0.15 0030 0.05
High 300 150 450 7500.2 0.06 0.12 0.02
Nine values of So<l>h x area and associated probabilitiesresult from the calculation. New high-medium-low casevalues are generated by combining the three lowest (25,75, 100), the three medium (125, 150, 300), and thethree highest (450, 500, 750). These may not be in thesame row or column of the matrix. If preferred, reservoir parameters and probabilities may be laid out inseparate matrices or programmed using simple matrixalgebra.
Low Case
Checksum: Sum of probabilities = I
The following matrix contains the calculation for thefactor So<l>h x area:
(25 x 0.09) + (75 x 0.18) + (100 x 0.15)
0.09 + 0.18 + 0.15
=73.214x 10'm'
with a probability of 0.09 + 0.18 + 0.15 = 0.42
Medium Case
Probability
0.300.500.20
LowMediumHigh
Not everyone has the capabilities for sophisticatedsimulation procedures, nor does every project warrantsuch an approach. In many cases, a simple manual orspreadsheet method of calculating an expectation canbe used.
A decision matrix is a simple method of combiningprobabilities that can be used when a computer program is not available. The simple example given hereis the calculation of an oil-in-place expectation fromthree parameters: net oil column (Soq,h), area, andrecovery factor).
High, medium and low case estimates and theirassociated probabilities are as follows:
Net Oil Column (Soq,h) in metres
Estimate Probability
0.5 0.301.5 0.602.5 0.10
Area in square metres x 103
Estimate
Low 50Medium 200High 300
Recovery Factor
Estimate Probability
Low 0.10 0.30Medium 0.20 0.40High 0.25 0.30
Calculations are performed using a matrix layout withone parameter and probabilities across the top and oneparameter down the side. Each cell of the matrix contains the value of the parameter at the top left and theprobability at the bottom right. The products ofthe parameters and probabilities are placed in the appropriatecell of the matrix. This method may be used for morethan three-point (high-medium-low) estimates, butbecomes more laborious.
(125 x 0.03) + (150 x 0.06) + (300 x 0.30)
0.03 + 0.06 + 0.30
= 263.462 x 103 m'
with a probability of 0.03 + 0.06 + 0.30 = 0.39
High Case
(450 x 0.12) + (500 x 0.05) + (750 x 0.02)
0.12 + 0.05 + 0.02
= 494.737 x 10' m'
with a probability of 0.12 + 0.05 + 0.02 = 0.19
These values are entered into a matrix with recoveryfactor (RF) as the other parameter:
276
________________________1
UNCERTAINTY AND RISK IN RESERVES EVALUATION
Recovery Low Medium High
Factor
NetOilx Value 73.214 263.462 494.737Area
(10' m') Probability 0.420 0.390 0.190
Low 0.10 7.321 26.346 49.474
0.3 0.126 0.117 0.057
Medium 0.20 14.643 52.692 98.947
0.4 0.168 0.156 0.076
High 0.25 18.304 65.865 123.684
0.3 0.126 0.117 0.057
Checksum: Sum of probabilities = I
If the result of this calculation is to be used for furthercalculations (e.g., for economic high-medium-lowcalculations), new high-medium-low values would begenerated:
Low 13.545 x 10' m' Probability0.42Medium 42.795 x 10' m' Probability 0.33High 89.105 x IO' m' Probability0.25
However, if this is the end point of the exercise, anexpectation can be calculated:
(13.545 x 0.42) + (42.795 x 0.33)+ (89.105 x 0.25) = 42.088 x 103 m3
While this method does not have the sophistication ofafull stochastic simulation and requires some simplifying assumptions, it will usually provide a reasonableanswer.
22.4.3 Decision TreesA decision tree is a graphical summary of the possibleoutcomes and probabilities of the events that comprisea project. It is a powerful analytical tool that allows thecalculation of expectations and various risk-relatedparameters.
There are several types, varying from simple trees withthe decision nodes absent, to trees with stochasticdecision nodes. The type chosen will depend on the particular problem being investigated; a simple tree thatcan be solved manually will suffice for most problems.McCray (1975a) and Newendorp (1975a) provide a detailed discussion ofthe construction and use ofdecisiontrees.
22.4.4 Probabilistic SimulationProbabilistic simulation (often referred to as MonteCarlo computer simulation)' is the combination offrequency distributions ofvariables in order to producethe frequency distribution of a final outcome. Decisionmatrices and most trees are relatively crude approachesto combining distributions, and this can be done muchmore thoroughly using simulations. Analytical approaches have also been developed that, under the rightconditions. produce a similar result to simulation.They depend on the transformation ofthe frequency distributions of the various parameters to normal (orlog-normal), the mean and variance of which can be.easily manipulated. Care must be taken to ensure thatthe transformations are valid, as significant errors canbe introduced if they are not.
For simulation, frequency distributions are generatedfor the significant parameters, a value is randomly selected from each one, and a calculation is carried outusing these randomly selected values. The process isrepeated many times (typically 300 - 1000), and the result is presented as a frequency distribution or anexpectation curve. The most common method ofselecting a random value is Monte Carlo sampling; the LatinHypercube method/ has computational advantages, butis less commonly used. Programs of various levelsof sophistication have made simulation a much easierprocess.'
1 "Monte Carlo" is a probabilistic simulation method.Probabilitydistribution functions are prepared for theparameters in anevaluation and, usingrandom numbersgeneratedby a Monte Carlo (or similar) samplingprocess, values are selected from the distributions. Acalculation is carried out using the selected values, andthe process is repeated many times (typically 300 - 1000).The resultingvalues define a probability distributionfunction from which parameters such as median, mean,and mode may be determined.
2 Latin Hypercubeis a method of sampling a probabilitydistribution by a stratified random sampling process. Itperforms the same function as Monte Carlo sampling, butwith fewer samples required for the same result.
3 Computerprograms are commercially available(Palisade Corporation's sophisticated stand-alone PRISM,or spreadsheetadd-on, @RISK) or can be found in theliterature (McCray(1975b) p. 215, gives a program inFORTRAN: Garb (1988) presents a simple Monte Carloprogram in BASIC; Crovelli and Balay (1991) describe aPASCALprogramthat is available from the USGS).
277
The parameters being simulated must be mutuallyindependent (e.g., pay thickness should not depend onporosity), or results may be seriously wrong. Methodsof handling dependent parameters include combiningthem (e.g., using tbe product <l>h rather than <I> and h separately) or setting up dependencies as part of thesimulation. This facility is available in some of theprograms.
Simulations can be carried out for different purposes,for both technical and financial reasons, and at different levels of complexity. It is possible, for example, tosimulate a gas field development project that, in addition to the technical aspects, includes tbe possibility ofdifferent market levels or the impact of an embargo onprice.
A more detailed discussion of simulation for projectevaluation is given in Newendorp (1975b) and McCray(1975c).
22.5 EVALUATION OF UNDEVELOPEDLANDS
Uncertainty plays a major role in the estimation ofundiscovered hydrocarbon volumes and their values. Avariety of methods is available, many of whichespecially the statistical approaches-are still underactive development. Details and further references canbe found in Haun (1975); McCray (1975d); Newendorp(1975a); Megill (1984, 1985), Masters (1984); Rice(1986); Drew (1990); and Campbell (1970).
Estimates of undiscovered hydrocarbon volumes arerequired at scales ranging from poorly known basins tosingle well offsets in known pools. The method adoptedwill depend on tbe scale and the information and timeavailable for making the estimate. Most estimates willbe for relatively small projects using a subjectiveestimate based on analogy. Larger projects will usuallywarrant the use of a more sophisticated approach.
The methods available can be summarized as follows(after Miller, in Rice, 1986):
Areal and Volumetric Yield Methods with GeologicAnalogy. The area or volume of the petroliferous sediments in an unknown area is multiplied by the volumeof hydrocarbons per unit area or volume in a knownanalogous area. This method depends critically on theidentification and the validity ofan appropriate analog.It is always difficult to know how good an analog is,and the result is uncertain, usually to an unknown degree. Areal and volumetric methods are of the mostuse when there is little other information, but once
278
DETERMINATION OFOILAND GASRESERVES
addi~idonal informI' abtilon is available, other methods willprovi e more re ra e results.
Delphi or Subjective Consensus AssessM th d Thi h i " mente 0 s, IS approac IS descnbed 10 Section 22.3.3.
Historical Performance or Behaviouristic Meth dThese methods are based on the extrapolatio 0 Sf'hi . I d n 0Iston.ca ata, such as discovery and drilling rates andfield sl~es. The data are entered into mathematical models WhICh are then used to make extrapolations. D(1990) gives an interesting account of their evolut~W
d k · ~an new wor continues to appear.
Geochemical Material Balance Methods. Thesemethods estimate the volume of hydrocarbons generated, the volume involved in migration and loss, andthe volumes trapped and lost. By their nature, geochemical material balance methods are useable only on arelatively large scale. Considerable information and anappropriate model are required for this method to besuccessful, and it has had limited use (Sluijk and Parker1986). '
Combined (Integrated) Methods. Combinations oftheabove methods, often with sophisticated statistical andmathematical models, are becoming more common. Ingeneral, they involve the following:
• Geological basin analysis
• Play or prospect analysis techniques
• Statistical, economic and supply projection models
• More comprehensive petroleum province analogsystems
The Geological Survey of Canada (GSC) reviewofpetroleum potential (Podruski et a!., 1987) used twoapproaches to the estimation ofremaining undiscoveredvolumes in western Canada.
The discovery process model described by Lee andWang (1983, 1985, 1986) and also described in a lessmathematically daunting way by Drew (1990) is astatistical model that assumes that discoveries made todate represent a biased sample of the underlying poolpopulation. To understand the characteristics of thepopulation and make predictions, the discovery processis modelled, using the pool size and sequence of discovery. Economic cutoffs can be built into the model todetermine the undiscovered volumes at various pricelevels. Both Podruski and Drew claim this to be tbe mostreliable method.
The second approach used by the GSC was a subjectiveprobability model, using probabilistic (Monte Carlo)simulation. This may incorporate an assumption that
s
UNCERTAINTY AND RISK INRESERVES EVALUATION
the underlying pool population has a log-normaldistribution.
A recent series of papers, in a thematic issue of theAAPG Bulletin in 1993, which includes papers byMasters (1993), Houghton et al. (1993), Drew andSchuenemeyer (1993), Root and Mast (1993), Root andAttanasi (1993), Attanasi et al. (1993), provides anextensive summary ofthe current practices ofthe USGSon petroleum resource assessment. It is interesting tonote that one of these papers (Houghton et aI., 1993)recommends the use of a modified Pareto distribution,as being better than the more traditional log-normaldistribution for modelling pool sizes.
The development ofmethods ofestimating undiscoveredreserve volumes and values is an active field, with newpapers continuing to appear in the literature.
ReferencesAttanasi, E.D., Bird, KJ., and Mast, R.F. 1993.
"Economics and the National Oil and GasAssessment: The Case of Onshore NorthernAlaska." AAPG Bulletin, Vol. 77, No.3, p. 491.
Campbell, A.D. 1984. "An Analysis of Bias andReliability in Revisions of Previous Estimatesof Proved Oil and Gas Reserve QuantityInformation: Replication and Extension."Petroleum Accounting and FinancialManagement, Summer 1984.
---. 1988. "An Analysis of Bias and Reliability inRevisions of Previous Estimates of Proved Oiland Gas Reserve QuantityInformation: An Update." Petroleum Accountingand Financial Management, Spring 1988.
Campbell, J.M. (ed.) 1970. Oil and Gas PropertyEvaluation and Reserve Estimates. SPE ReprintSeries, No.3.
---. 1986. "Nontechnical Distortions in theAnalysis and Management of Petroleum Investments." JCPT, Dec. 1986.
Capen, E.C. 1976. "The Difficulty of AssessingUncertainty." SPE Journal, Aug. 1976, pp. 843850; also in Megill, 1985.
Clark, I. 1979. Practical Geostatistics. AppliedScience Publishers, London, UK, p. 129.
Crovelli, R.A., and Balay, R.H. 1991. "A Microcomputer Program for Energy Assessment andAggregation Using the Triangular ProbabilityDistribution." Computers & Geosciences, Vol.17., No.2, pp. 197-225.
Davis, lC. 1986. Statistics and Data Analysis inGeology (2nd ed.). Wiley, New York, NY.
Drew, LJ. 1990. Oil and Gas Forecasting:Reflections ofa Petroleum Geologist.International Association for MathematicalGeology Studies in Geology, No.2, OxfordUniversity Press, Oxford, UK.
Drew, LJ., and Schuenemeyer, lH. 1993. "TheEvaluation and Use of Discovery Process Modelsat the US Geological Survey." AAPG Bulletin,Vol. 77, No.3, p. 467.
Garb, FA 1988. "Assessing Risk in EstimatingHydrocarbon Reserves and in EvaluatingHydrocarbon- Producing Properties." JPT, Jun.1988,pp.765-778.
Haun, J.D. (ed.) 1975. Methods ofEstimating theVolume ofUndiscovered Oil and Gas Resources.American Association of Petroleum Geologists,Studies in Geology No. I, p. 206.
Hohn, M.E. 1988. Geostatistics and PetroleumGeology. MacMillan, New York, NY, p. 264.
Houghton, J.C., Dolton, G.L., Mast, R.F., Masters,C.D., and Root. D.H. 1993. US GeologicalSurvey Estimation Procedure for AccumulationSize Distributions by Play." AAPG Bulletin, Vol.77, No.3, p. 454.
Isaaks, E.H., and Srivastava, R.M. 1989. AnIntroduction to Applied Geostatistics. OxfordUniversity Press, Oxford, UK, p. 561.
Kadane, J.B. 1990. "Comment: Codifying Chance."In: Mosteller, F., and Youtz, C., 1990.
Lee, PJ., and Wang, P.C.c. 1983. "ProbabilisticFormulation of a Method for the Evaluation ofPetroleum Resources." Jour. ofthe Int. Soc.forMath. Geol., Vol. 15, pp. 163-181.
---.1985. "Prediction of Oil or Gas Pool Sizeswhen Discovery Record is Available." Jour. ofthe Int. Soc.for Math. Geol., Vol. 17, pp. 95-113.
---. 1986. "Evaluations of Petroleum Resourcesfrom Pool Size Distributions." In: Rice, D. D.,1986.
Masters, C.D. 1993. "US Geological SurveyPetroleum Resource Assessment Procedures."AAPG Bulletin, Vol. 77, No.3, p. 452.
---. (ed.) 1984. Petroleum ResourceAssessment. International Union of GeologicalSciences, Publication No. 17.
279
McCray, A.W. 1975a. Petroleum Evaluations andEconomic Decisions. Prentice-Hall, Inc.,Englewood Cliffs, NJ, pp. 3-4.
---. 1975b. Petroleum Evaluations and EconomicDecisions. Prentice-Hall, Inc., Englewood Cliffs,NJ, p. 215.
---,. 1975c. Petroleum Evaluations and EconomicDecisions. Prentice-Hall, Inc., Englewood Cliffs,NJ,Ch.8.
---. 1975d. Petroleum Evaluations and EconomicDecisions. Prentice-Hall, Inc., Englewood Cliffs,NJ, Ch. 7.
Megill, R.E. 1984. An Introduction to Risk Analysis(2nd ed.). PennWell Publishing Co., Tulsa, OK.
---. 1985. Evaluating and Managing Risk: ACollection ofReadings. SciData Publishing,Tulsa, OK.
Miller, B.M. "Resource Appraisal Methods: Choiceand Outcome." In Rice, 1986.
Mosteller, F., and Youtz, C. 1990. "QuantifyingProbabilistic Expressions." Statistical Science,Vol. 5, No. I, pp. 1-34.
Newendorp, P. 1975a. Decision AnalysisforPetroleum Exploration. Petroleum PublishingCompany, Tulsa, OK, Ch. 6.
---. 1975b. Decision Analysis for PetroleumExploration. Petroleum Publishing Company,Tulsa, OK, Ch. 7 & 8.
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Podruski, J.A., Barclay, J.E., Hamblin, A.P., Lee, PJ.,Osadetz, K.G., Procter, R.M., and Taylor, G.C.1987. Conventional Oil Resources of WesternCanada. Part I: Resource Endowment. Geologi_cal Survey of Canada Paper 87-26, Minister ofSupply and Services Canada.
Rice, D.O. (ed.). 1986. Oil and Gas Assessment:Methods and Applications. American Associationof Petroleum Geologists, AAPG Studies inGeology #21.
Robinson, J.G. 1990. "Determination of Reserves andValues and Application of Risk." JCPT, Nov.1990 Supplement.
Rock, N.M.S. 1988. Numerical Geology. SpringerVerlag, New York, NY.
Root, D.H., and Attanasi, E.D. 1993. "Small Fields inthe National Oil and Gas Assessment." AAPGBulletin, Vol. 77, No.3, p. 485.
Root, D.H., and Mast, R.F. 1993. "Future Growth ofKnown Oil and Gas Fields." AAPG Bulletin, Vol.77, No.3, p. 479.
Sluijk, D., and Parker, J.R. 1986. "Comparison ofPredrilling Predictions with Postdrilling Outcomes, Using Shell's Prospect Appraisal System."In Rice, D.O. (ed.), 1986.
Spetzeler, C., and Stael von Holstein, C. 1975."Probability Encoding in Decision Analysis."Management Science, Vol. 22, No.3, Nov. 1975,pp.344-347.
Tversky, A., and Kahneman, D. 1985. "The Framingof Decisions and the Psychology of Choice." InMegill, R.E., 1985.
Chapter 23
THE REGULATORY ENVIRONMENT
23.1 INTRODUCTIONThis chapter describes the regulatory environment forthe petroleum industry in Canada. The regulatory activities, functions and objectives ofboth the provincialand the federal levels of government are described, aswell as the necessary legislationand organizationalstructures. The focus is on Alberta, which is Canada's largestproducer of oil and gas. The regulatory environment inthe other producing provinces would, in general, besimilar.
Governments are involved in a number of differentfunctions that have a direct influence on the development of oil and gas reserves:
• Resource inventories
• Mineral ownership
• Economic development policies
• Conservation control
• Development, operating, and environmentalregulation
• Domestic supply assurance
• Fiscal policies
• Business regulation
• International policies
The provincial governments have jurisdiction over allaspects of the petroleum industry within provincialborders, except for lands under federaljurisdiction, suchas Indian reservations and national parks. The federalgovernment has jurisdiction over all frontier lands,including the Yukon and Northwest Territories,Hudson's Bay, and most of Canada's offshore areas.The federal government signed accords with the governments of Newfoundland and Nova Scotia, givingthese provinces joint control with the federal government over offshore petroleum. The federal governmenthas jurisdiction over interprovincial and internationaltrade and commerce, which are ofmajor importance tothe petroleum industry.
Basic policy direction in all of the functions isestablished by political elements of government. Atthe provincial level these include the Legislature,the Premier and Cabinet, and the Minister ofEnergy; atthe federal level, the Parliament, the Prime Ministerand Cabinet, and the Minister of Energy, Mines andResources. The basic policies are embodied in the actsand regulations that are administered by specializedgovernment agencies.
In Alberta, the principal agencies are the EnergyResources Conservation Board (ERCB), the AlbertaDepartment of Energy, and the Alberta PetroleumMarketing Commission. The principal federal agenciesare the Department of Energy, Mines and Resources,the National Energy Board (NEB), and the Departmentof Indian and Northern Affairs. Under the accords withNewfoundland and Nova Scotia, management and regulation are carried out by the Canada-NewfoundlandOffshore Petroleum Board and the Canada-Nova ScotiaOffshore Petroleum Board, which have equal representation from the federal government and the particularprovince.
Reserves estimates are an important factor in manyregulatory functions and policies. The governmentsources of reserves estimates, how these are used, andtheir effect on reserves development are discussed inthis chapter.
23.2 RESOURCE ASSESSMENTSAssessments of petroleum resources and reserves areneeded by governments in order to carry out their functions relating to exploration, development, and the useof these resources.
Both the provincial and federal governments conducttheir own assessments of ultimate potential, recoverable reserves, and supply (rate ofproduction). Alberta'sassessment is done primarily by the ERCB, which carries out continuing detailed evaluation of reserves andperiodic assessments ofultimate potential. The AlbertaGeological Survey also does some assessments.
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The Geological Survey of Canada evaluates ultimatepotential for the federal government, and the NEB evaluates reserves and supply. These two agencies also workwith the Energy Sector of the Department of Energy,Mines and Resources in the Petroleum ResourcesAppraisal Panel.
Because reserves assessments are frequently quitesubjective and interpretive, and evolve as a result ofemerging technology and changing economic conditions, governments seek comparative estimates fromexternal sources. These sources include reserves assessments supporting gas removal and export licenceapplications, assessments by other organizations,and voluntary submissions by oil and gas companies.Governments are also very interested in reserves estimates for other jurisdictions (i.e., other provinces andother countries) with whom they compete for investment capital and for markets.
23.3 MINERAL OWNERSHIPThe majority of mineral rights in Canada are owned byeither the provincial or the federal Crown. The remainder are held privately by individuals or corporationswhose ownership originated from land and mineralrights granted a century or more ago to certain parties,notably the Canadian Pacific Railway Company andthe Hudson's Bay Company. The Province of Albertaowns about 80 per cent of the mineral rights within itsborders. The federal government is responsible for mineral rights in the territories (Yukon and NorthwestTerritories) and offshore (arctic, east coast, west coast,Hudson's Bay, and St. Lawrence), as well as in federallands and Indian Reserves within the provinces.Governments manage these mineral rights on behalf ofthe citizens.
The mineral rights are leased to private operators fordevelopment. Leasing is done by a competitive biddingprocess involving an initial acquisition cost (bonus), plusannual rental fees and royalties (share) on production.Decisions regarding initial acquisition costs usually takeinto account estimates of reserves under the tractsinvolved.
In Alberta, the Department ofEnergy is responsible formineral rights disposition, rentals and royalties underthe Mines and Minerals Act. The department relies oncompetitive bidding in the initial disposition of rights(Crown sales). Ifa well has not been drilled during theinitial term ofthe lease, under certain circumstances thelease may be extended if the lands are considered to becapable of economic production.
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Government's royalty interest can be taken in-kind (theactual oil or gas, rather than monetary proceeds of itssale), which results in direct involvement in marketingof the product. In Alberta, the marketing of Alberta'sroyalty oil is carried out by the Alberta PetroleumMarketing Commission (APMC), which has a mandateto ensure that the greatest possible benefits are securedfrom the sale of Alberta's oil and gas. Royalty on gasis not taken in-kind, but the APMC closely monitorsall gas sales from Alberta under the Natural GasMarketing Act. The APMC also represents Alberta atnational and international regulatory proceedings.
The Alberta government has an interest in acting tomaintain or increase petroleum product prices becauseof the direct royalty income and also because of theoverall economic development benefits. In the early1970s,the Alberta government brought about an increasein the price of its gas, which at that time was significantly underpriced on a heating value basis relative tooil. In the subsequent energy crisis, Alberta sought tohave the price of its oil and gas follow the rapidly escalating world prices.
Leasing of federal oil and gas rights is done underterms of the Canada Petroleum Resources Act. Rightsto explore are granted after competitive bidding basedon the proposed exploration expenditure during theinitial term of the licence. The Department of Indianand Northern Affairs has the responsibility of managing these rights in frontier lands north of the 60thparallel, and the Department of Energy, Mines andResources has responsibility south of the 60th, exceptfor the east-coast offshore accord areas, which areunder the Canada-Newfoundland and Canada-NovaScotia Offshore Petroleum Boards. The Department ofIndian and Northern Affairs assists in the managementofmineral rights in Indian Reserves.
The levels of royalties can affect whether a particularreserve is developed and becomes proven, or remainsin a less certain category of reserve. Royalty reductionor royalty holidays are commonly used to promote development of the petroleum industry or a particularsector of the industry. Similarly, the oil and gas pricelevels, which can be influenced to some extent by governments, significantly affect the rate of development.When prices are restrained, the rate slows; when pricesescalate, the rate increases.
23.4 ECONOMIC DEVELOPMENTPOLICIES
Most governments have an interest in overall economicdevelopment, and the governments usually concentrate
•
THE REGULATORY ENVIRONMENT
on the development of industries having a largepotential. Decisions regarding the promotion of petroleum industry development are based on estimates ofultimate potential, including assessment of conditionsnecessary for these to be economic viable reserves.
Petroleum development is very capital-intensive. Themethods used by governments to attract capital includethe following:
• Minimizing of royalty and taxation
• Subsidization
• Loan guarantees
• Equity participation by government
• Funding of infrastructure construction
Funding of research
• Assistance with market development
• Maintenance ofpetroleum product prices
Maintenance ofpolitical, business, fiscal, and socialstability
• Provision of business and technical information
• Publication of estimates of available resourcepotential
Industrial diversification and decentralization are twoother usual government objectives that are embodied inmany policies that affect oil industry development.
As an example of a government policy meant tostimulate the development ofthe Canadian oil industry,the National Oil Policy (196 I) reserved the Canadianmarket in Ontario and westward for Canadian oil ata time when cheap offshore supplies were available.An example of government financing support was theconstruction of the TransCanada gas pipeline (1957) tostimulate development of the then-fledgling gas industry and provide an alternative energy source to Ontario.Development of the Athabasca oil sands has beensupported in a variety of ways including equity participation, loan guarantees, reduced royalties and taxation,and the direct funding ofresearch and testing ofvariousrecovery methods.
When world petroleum prices were rapidly escalatingduring the 1970s, Alberta and the producing provincessought to have their petroleum prices follow worldlevels, but the federal government, reflecting theinterests ofthe consuming provinces, wanted to restrainthe rate of price increases to domestic consumers.Therefore, from 1975 to 1985, natural gas prices werecontrolled by agreements negotiated between thefederal government and the governments of the producing provinces. Oil prices were controlled in a similar
fashion. In 1985 the two levels ofgovernment agreed toderegulate and allow market-responsive pricing.
23.5 CONSERVATION CONTROLS
23.5.1 Field Development and ProductionConservation
Oil and gas reserves can be lost both in the reservoirand on the surface as a result of wasteful productionpractices. The governments of the producing provinceshave the following kinds of legislation to minimizewasteful practices:
• Limits on excessive gas production from oilreservoirs
• Requirements to implement enhanced recoveryschemes
• Production rate limits from wells or pools
• Requirements to gather and conserve solution gasproduced with oil
In Alberta, conservation requirements are stipulated inthe Oil and Gas Conservation Act and Regulations,which are administered by the ERCB. The applicationof specific measures to individual wells and pools frequently depends on the reserves estimates for those wellsand pools.
Conservation controls serve to increase proved reservesin developed pools, but can slow the development ofother projects that are competing for limited availablecapital. Regulation is necessary because the economicrate of return of a conservation project is sometimesless than for the same project without controls.
23.5.2 Consumer Demand ConservationParticularly during the energy crisis of the 1970s, alllevels of government were involved in programs toreduce the demand ofpetroleum products. Many ofthesewere in the form of advertising campaigns and incentive programs to reduce waste and increase efficiencyby the individual consumers. Development of alternative fuels was actively supported. In Alberta, the ERCBregulates manufacturing industries that use natural gas,and requires gas useage to be efficient.
23.6 DEVELOPMENT, OPERATING,AND ENVIRONMENTALREGULATIONS
The provincial and federal governments impose avariety of detailed regulations relating to the construction and operation of oil and gas production facilities.These regulations are aimed at achieving safe, orderly,efficient, and equitable development and operation of
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facilities, and minimizing their social and environmentalimpacts. Some of these regulations are specific to thepetroleum industry while others apply to all industries.
In Alberta, the regulations specific to the petroleumindustry include the following acts and the regulations pertaining to them: the Energy ResourcesConservation Act, the Oil and Gas Conservation Act,the Oil Sands Conservation Act, and the Pipelines Act.The regulations are administered by the ERCB and apply to all oil and gas wells, pipelines, and productionand processing facilities. The regulations cover suchaspects as demonstration of need, sites and routes, sizing and design, construction and operational practices,monitoring and reporting, and ultimate decommissioning offacilities. Applications for each individual facilityand operation must show that all regulations and standards will be met. The applications are also subject toscrutiny by the public, including affected landownersand residents, special interest groups, and competingoil companies. Public hearings are held when issues dictate or when the issues cannot be resolved by privatenegotiation. When all requirements and concerns havebeen met, approvals, permits and licences are issued.
Further specific approvals are required from otherprovincial government departments. Department ofEnvironment authorizations are required for pollutantemissions and waste disposal, watercourse crossings,and land surface disturbance and reclamation. Wherepublic lands are involved, land use authorizations mustbe obtained from the Department ofForestry, Lands andWildlife. Development permits must be obtained frommunicipal authorities. Generic provincial regulationsregarding worker and public safety, building and construction standards and codes, and industrial water usageapply to all industries including the oil industry.
The ERCB, the Alberta Department of Environment,and other provincial agencies do regular inspections andcompliance monitoring during the operating lives ofoiland gas facilities and operations.
In federal lands, similar functions are exercised underthe Oil and Gas Production and Conservation Act bythe NEB and the Offshore Petroleum Boards. The NEBis also responsible for regulation of pipelines thatcross provincial and international borders. The FederalEnvironmental Assessment and Review Process(EARP) applies to projects that are on federal lands,receive federal funding, require approvals from federaldepartments, or are undertaken directly by a federaldepartment. For hydrocarbon development projects
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DETERMINATION OF OILAND GASRESERVES
requiring NEB approval, the NEB coordinates the EARPreviews carried out by all the federal departments thatare involved.
Development regulations often result in increaseddevelopment costs for reserves. In particular, pollutionand environmental control requirements are becomingan increasingly significant factor in the cost ofpetroleum development and production.
23.7 DOMESTIC SUPPLY ASSURANCEThe provincial and federal governments both reviewproposals for removal or export ofcertain energy products from their jurisdictions, to ensure that domesticlong-term needs are provided for and that the export isin the best interests of their jurisdictions.
In Alberta, the removal of natural gas is subject to theGas Resources Preservation Act, which is administeredby the ERCB, and is subject to subsequent further approval by the provincial government. Alberta's currentremoval criteria requires that a IS-year supply bereserved for the core market within the province (principally residential and commercial consumers) in theform ofestablished reserves ("proven" plus a portion of"probable") before removals are permitted. The entireamount ofgas approved for removal must be in the formof established reserves and under the contractual control ofthe permit holder at the time the permit is issued.This requirement causes reserves to be moved from the"possible" category to "proven" and "probable." In theabsence of this criterion, the supply for the later stagesof some long-term supply contracts would likely relyon "possible" reserves. Gas removal from Alberta issubject to further approval by the Minister of Energyor the Provincial Cabinet, both of which considersuch matters as gas pricing and market practices,commitments, and destinations.
At the federal level, the National Energy Board isresponsible for deciding export applications. One of itscurrent criteria is that sufficient established reservesmustbe under contract to cover the volume licensed for export. In addition, gas purchasers in Canada are given anopportunity to formally complain about any proposedexport if they have been unable to obtain gas on termsand conditions similar to the proposed export.
The ability to control cross-border movement of gasallows some capability to control prices. Both Albertaand Canada acted to ensure higher prices for exportedoil and gas during the "energy crisis" ofthe 1970s whenprices were escalating worldwide.
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THE REGULATORY ENVIRONMENT
23.8 FISCAL POLICIESGovernments can vary taxation levels, apply specialtaxes, and grant tax incentives to achieve the objectivesof deficit or balanced budgets, and to stimulateeconomic growth (especially in localities, areas andregions of lagging economies) and industries ofspecific importance.
A number ofdifferent taxes are levied on the producingsector of the petroleum industry by municipal, provincial and federal governments. Municipal governmentslevy property taxes on petroleum facilities and realestate. Both the provincial and federal government levytax on all corporate income. In addition, the Albertagovernment collects a freehold mineral tax on all freehold mineral leases (mineral rights not held bygovernment), based on their production. The federal andprovincial governments both have the ability to applyspecial taxes to the petroleum industry.
The Alberta government grants a special royalty taxcredit of up to 2.5 million dollars annually, which is asignificant benefit to small petroleum companies.During the period 1972 to 1984, the Alberta government provided exploratory seismic and drillingincentives through drilling credits and royalty holidayprograms. These were designed to promote explorationfor new reserves and to maintain industry activity during periods of economic downturn. During this sameperiod, Alberta significantly increased its royalties onoil and gas.
The federal government offered tax incentives forfrontier exploration in the 1960s and 1970s. TheNational Energy Program brought in by the federal government in 1981 provided incentive payments forexploration and development expenditures (PetroleumIncentive Program) giving particular advantage to companies of predominantly Canadian ownership. TheNational Energy Program also significantly increasedfederal taxation of oil and gas production, particularlythrough the Petroleum and Gas Revenue Tax.
Fiscal policies affect the timing of reserves development. Governments within Canada and throughoutthe world are in competition to attract and retaininvestment capital. A high economic rent may causeexploration capital to move to other provinces or othercountries where the economic rent is lower. Petroleumindustry capital is quite mobile. Even small companiestend to look on a worldwide basis, and they can investaway from their home operating area by taking a minority working interest in a project sponsored by a largercompany.
23.9 BUSINESS REGULATIONSPrice- or fee-setting regulation is necessary wherenormal business competition is not present. This is thecase with many pipelines. For field gathering systemsand for gas processing plants in Alberta, a productionowner may apply to the ERCB to have these facilitiesdeclared to be "common" and then to the PublicUtilities Board to have useage fees set. Tolls and tariffson interprovincial transmission lines are under thejurisdiction of the National Energy Board. The pricesfor natural gas distributed to end-users by local utilitycompanies are subject to the approval by some type ofpublic utilities board in each of the provinces. Theseboards protect the interests of the consumer and ensurethat rates are justified.
Right-of-entry and land compensation legislation hasbeen established by the provinces so that mineral owners cannot be prevented by surface owners fromrecovering the minerals. In Alberta, this function iscarried out by the Surface Rights Board.
The provinces each have some type of securities andexchange commission that regulates corporate matters.Public corporations are required to publish annualfinancial statements listing, among other things, theassets of the corporation. Oil and gas reserves are theprimary assets of most petroleum companies. Consistency in the method of estimating the volume andvalue of these reserves is important.
The Federal Competition Act (FCA) protects andpromotes competitive processes, and is administeredby Consumer and Corporate Affairs Canada. The acthas both criminal and non-criminal provisions. Thelatter are prosecuted by the Attorney General ofCanada.Criminal offences include conspiracy, bid-rigging,price discrimination, predatory pricing, price maintenance,misleading advertising, and deceptivemarketingpractices.
Certain other activities and practices are subject toreview, but are not criminal matters. For example,companies proposing to merge must notify Consumerand Corporate Affairs Canada if the companies exceeda certain size of assets or gross revenues. If a proposedmerger is found to prevent or substantially lessencompetition, the merger may be conditioned orprohibited.
23.10 INTERNATIONAL POLICIESPetroleum is usually considered to be a strategiccommodity. Hence, countries try to protect themselvesfrom any serious supply disruptions that may result from
285
business, political, or natural events. Canada has a largeoil and gas potential and has followed the strategy ofdeveloping supply through the incentive ofallowing exports to the USA. Exploration and development offrontier areas could not proceed on the basis of thedomestic Canadian market alone.
Canada has exported oil and gas to the USA fordecades, and the US views Canada as a secure supplier.Currently, approximately one-third ofCanada's oil production goes to the USA. Oil is being exported to thewest and midwest regions of the USA at the same timeoffshore oil is imported into Quebec and the Maritimes,resulting in a near balance ofexports and imports. Morethan 40 percent ofCanada's gas production is exportedto various parts of the US including California, themidwest, and recently the northeast.
The producing provinces are usually more anxious toincrease exports than are the consuming provinces. Thefederal government has the challenge of balancing theinterests ofboth groups.
Canada's close political and economic ties to the USled to the Free Trade Agreement which came into effectin January 1989. For Canadian oil and gas producers,this agreement provides access to US markets free ofexport or import taxes or duties. Except in national defence emergencies, export restrictions may be appliedonly under limited circumstances and in a proportionate manner. Incentives for exploration and developmentare still allowed.
Recently, Canada, the USA, and Mexico negotiated theNorth American Free Trade Agreement (NAFTA) whichis scheduled to come into effect on January I, 1994.
286
~DETERMINATION OF OIL AND GAS RESERVES ......:,.:,.. : i
This agreement will allow for relatively free movementof oil and gas between these three countries and willallow the Canadian and US companies to participate insupply and services ofthe Mexican petroleum industrybut not ownership of Mexican oil and gas resources. '
The review of company take-overs and mergers byConsumer and Corporate Affairs Canada described inSection 23.9 applies even if foreign-owned companiesare involved.
Canada is signatory to the Agreement on anInternational Energy Program, along with the USA anda number of European countries. This group has a planfor distribution of available oil in a supply crisis.
In issues ofworldwide public concern, Canada seeks todo its part. Energy conservation was such an issue during the energy crisis of the '70s. Environmentalconcerns, including petroleum transport failures andatmospheric emissions, are issues at the current time.
In a similar vein, Canada feels obligated to providetechnical assistance to developing countries to developtheir petroleum industries. Canada and the producingprovinces provide expert advisers and trainers inresponse to specific requests and under on-going international aid programs. Government interfacing withmore developed countries is often in the form oftechnical exchanges and discussions about business andregulatory systems. Some countries seek assistance fromCanada specifically, not just because it has a high levelofexpertise and technological development, but becausethe country seeking aid wants to avoid a tie to the USA.
Both the federal and provincial governments are activein trade development initiatives in other countries.
s
Chapter 24
CRUDE OIL MARKETS
24.1 INTRODUCTIONThis chapter provides an overview of Canadian crudeoil markets, with particular focus on Alberta and otherwestem Canadian provinces. More detailed informationcan be found in the references cited in this chapter.
Despite the slump in activity since 1986, the Canadianoil industry is an important element of the domesticeconomy in terms of direct employment, total revenueand trade surplus. Crude oil satisfies nearly 40 percentof the total domestic energy demand. According to thePetroleum Communication Foundation (1992), the bulkof crude oil was used for various modes of transportation (65 percent), heating and electricity generation (25percent), and manufacture of oil-based products suchas asphalt, lubricants and various petrochemicals (10percent). In the global context, Canada is a mediumsize oil producer, supplying less than 3 percent ofworldproduction.
The history of the Canadian oil industry dates back to1947, when the discovery ofthe Leduc field triggered aresurgence of exploration activity in Alberta. Duringthe 1950s, the industry operated in a free market environment characterized by essentially no governmentregulation. The period of the laissez-faire approach towards the oil industry came to an end in 1961, when theNational Oil Policy divided Canadian markets along theOttawa Valley line. Markets to the east of the line wereto use cheaper imported crudes, while markets to thewest were to be supplied with domestic crudes.
The oil crisis in 1973-74 precipitated further marketregulation involving an oil price freeze, an exporttax, reductions in exploration write-offs and depletionallowances, and the establishment ofPetro-Canada as anational oil company. Market intervention reached itspeak in 1980 when, on the heels ofthe second oil crisis,the federal government introduced the National EnergyProgram (NEP), which provided for oil price controls,several new federal taxes, Canadian ownership targets,and incentives for fuel switching. This first federal
attempt to tax resources under provincial jurisdictionwas countered by very strong opposition from Alberta.
Election of the conservative government in 1984 andthe decline in oil prices paved the way for the WesternAccord between the federal government and the energyproducing provinces. The signing ofthe accord on JuneI, 1985 marked the dawn of crude oil deregulation andthe demise of both the NEP and 12 years of administered pricing. All NEP taxes were either phased out oreliminated, and oil price controls were lifted. Canadianproducers were free to compete in the internationalmarket place and reap the rewards ofunrestricted salesopportunities through the direct negotiation ofcontractswith refiners and marketers. In the process, Albertamodified its prorationing program, virtually returningcontrol ofproduction levels to producing companies.
In Canada, the term "conventional" crude oil usuallyrefers to light, medium and heavy crudes from the western Canadian sedimentary basin-the traditional sourcefor most Canadian production. The distinction amongthese three classes ofcrudes is based mainly on gravity,with specific gravity cutoff rates differing regionallyin the absence of one widely recognized internationalstandard.
For instance, the minimum gravity for light crude rangesfrom 28·API in Canada to 32·API in the US and 36·API overseas. Medium oil is defined by the WorldEnergy Conference as having gravity between 22· and31·API (Petroleum Communication Foundation, 1992).In Canada, generally no distinction is made betweenlight and medium oil. Heavy oil is typically defined ascrude with the API gravity between 12· and 28·API,although Alberta's Energy Resource ConservationBoard (ERCB) uses a lower maximum of25·API. SinceCanadian pipelines generally require oil to have a gravity ofat least 21·API, some of the heaviest grades mustbe blended with condensate or natural gas liquids to beshipped by pipeline.
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~DETERMINATION OF OIL ANDGAS RESERVES
Figure 24.2-1 Major Alberta Pipeline Systems
lnterprovlnclettoEastern Canada andU.S.
ContinentalToU.S. Rock MIn.States
• Calgary
Rainbow
InterprovinclalFrom Norman Wells
Great Lakes region of the US Midwest. In addition,IPL is linked to the Wascana system, which providesaccess south to the Rocky Mountain markets ofWyoming and Colorado. During 1992, average throughput on the IPL system was 1.45 million barrels per day,with deliveries split almost evenly between domesticand export markets.
~
TMPL extends over 1300 kilometres from Edmontonto delivery locations in the Vancouver area. The systemcan transport up to 190 thousand barrels per day ofcrudeoil, partially processed oil, and petroleum products fromAlberta. TMPL also receives small volumes of crudefrom northern B.C. via the West Coast Pipe Line connection at Kamloops. TMPL's marine terminal atWestridge, B.C. is capable of loading barges servingthe US West Coast and small tankers providing accessto Pacific Rim markets. TMPL also operates a laterallink from Sumas, B.C. to Anacortes, Washington, wherefour refineries are located. In 1992, the system delivered 161 thousand barrels per day to domestic locations
"Nonconventional crude" comprises synthetic andfrontier oil. "Synthetic" oil is heavy oil and oil sandsbitumen refined to make a product similar to high-quality light crude oil. "Frontier" oil includes resources offthe eastern coast or north of the 60th parallel inthe Arctic. Nonconventional crudes differ from conventional in that they are more difficult to recover andcannot be shipped to a refinery without processing orpreparation.
Geographically, oil production is heavily concentratedin the western Canadian sedimentary basin. In 1992,Alberta, which is by far the largest oil producing province, accounted for 8I percent ofthe 1.73million barrelsper day produced in Canada. Saskatchewan accountedfor another 13 percent and the remainder came fromBritish Columbia, Northwest Territories, Manitoba andOntario and Nova Scotia. Conventional light oil dominates the Canadian crude slate, representing halfoftotalproduction. The other half comprises heavy oil (29 percent), synthetic oil (13 percent) and pentanes (8 percent).
Historically, Canadian crude oil production hasbeen relatively stable since 1980, hovering closelyaround the 1992 level. Underlying this almost flat overall performance were divergent trends for conventionaland nonconventional crude oils, conventional declining at 5 percent per year (mainly light crude) andnonconventional increasing by more than half since1988.
24.2 TRANSPORTATION NETWORKCanadian crude reaches domestic and export marketsthrough a vast network of pipelines. In Alberta, acapillary-like system of gathering lines throughout theprovince collects and transports field crude productionto a smaller number of feeder pipelines. Trucking is amarginal mode of transportation and is used locally inareas where batteries are not connected to the gatheringlines. Most ofthe feeder pipelines conjoin at Edmonton(Figure 24.2-1) to serve the Alberta refining market andfurther link to two major interprovincial pipelinesystems: Interprovincial Pipe Line (IPL) and TransMountain Pipeline (TMPL). These and most otherCanadian pipelines are "common carriers", that is, public utilities for hire obligated by law to provide equitableand nondiscriminatory pipeline access to all interestedparties.
IPL operates the largest and most complex crude oilpipeline system in North America, stretching over 3700kilometres from Edmonton to Montreal (Figure24.2-2). It transports up to 35 different types of liquidhydrocarbons to refineries in eastern Canada and the
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s
CRUDE OILMARKETS
•SaintJohn(27000)
,
t-: ·· ...'b" ,',,' ~" ,.,.-
' .. ,,-JI
<::::;:::::> Come-By-Chance(15100)
"
Wood River • III
Loydminster ;,,(3700) :
Regina(7200)
•-MooseJaw
(2110)
BeaufortSea
Taylor " \(2860)'" ,. ,
Edmonton I
• .: (56300) •
Prince George':... r .....~1500)/ '\,
\},~.__ CalgaryVancouver- .. -(5180) .(22700)
•Legend
Refinery Locations (m3/d)
Rainbow Pipeline
--- Interprovincial PipelinePortland-Montreal Pipeline
TransMountain Pipeline
Proposed Pipeline
Loop/Capline/Chicap from Gulf Coast
Source: National Energy Board. 19918.
Figure 24.2-2 Maior Crude Oil Pipelines and Refining Areas
and another 41 thousand barrels per day to exportdestinations.
A smaller pipeline, the Rangeland, transports oil southfrom Edmonton into the Montana market. The line hasa capacity of approximately 90 thousand barrels perday and has recently operated at rates approaching thatcapacity.
The Portland-Montreal pipeline is the main oil importline that brings offshore crudes to the Montreal market.In 1992, the line delivered 166 thousand barrels perday of oil, equivalent to 67 percent of its maximum
capacity and over 90 percent of Montreal's oilrequirements. Marginal volumes of US and overseasgrades are also imported into Ontario via IPL's Lakeheadportion, which ties in at Chicago with two major USpipeline routes: the Capline/Chicap system fromLouisiana Gulf Coast and the Arco system from TexasGulf Coast via Cushing, Oklahoma.
Since the beginning of deregulation in 1985, pipelinecapacity constraints have had occasional impact onCanadian crude oil pricing and production. Prior toIPL's 1987 expansion, insufficient capacity of the system necessitated diversions of Canadian crude to lower
289
valued markets and even to the shut-in of wellheadproduction. More recently, in March 1991, a leak onLakehead's Line 9 restricted the throughput and causedpersistent prorationing of the nominated volumes.Apportionment continued through 1991 and early 1992,as the capacity was restricted to 80 percent by an orderfrom the US Department of Transport and, additionally, by line closures during hydrostatic tests.
In the face of these unprecedented high levels ofapportionment, producers and shippers attempted toprotect their access to IPL capacity by over-estimatingcrude supply. That practice led to even higher levels ofapportionment. which, in tum, resulted in inequitablepipeline and market access. By mid- 1991, the forecasting and nomination systems used to schedule feederpipelines and IPL broke down. Subsequently, an industry working group was formed to address the problem.The group developed modified procedures designed toeliminate overnominations through stricter monitoringof batteryproduction and penalties for inflated forecasts.These procedures came into effect in March of 1992,reducing IPL apportionment only temporarily.
Among other developments, IPL's extension fromSarnia to Montreal was re-opened in July of 1992, afterbeing mothballed for one year. The initiative came froma group of Alberta producers and marketers who decided to move 20 to 30 thousand barrels per day ofheavycrudeto Montreal. Around the same time, the Bow RiverPipeline completed construction of a 55-mile pipelineacross the US border, to ease access from the southernAlberta fields to the Billings market. This pipeline expansion was triggered by the addition of a heavy crudecoker at Conoco's Billings refinery. The current capacity is around 24 thousand barrels per day, but can beexpanded to about 42 thousand barrels per day.
With the exception ofa few privately owned feeder linesthat are not common carriers, Canadian pipelines areregulated by a host of government agencies. Pipelinescrossing the US or provincial boundaries, such as IPLand TMPL, come under the jurisdiction ofthe NEB. Asan independent federal regulatory tribunal, the NEB isresponsible for the issuance of export licences for oil,natural gas and electricity; the certification ofinterprovincial and international pipelines and powerlines; and the setting of pipeline tolls and tariffs(National Energy Board, 199Ib). Pipelines functioningwithin provincial boundaries are generally underprovincial jurisdiction. For example, the constructionand operation of the province's feeder pipelines areregulatedby Alberta's ERCB and Public Utilities Board.
290
DETERMINATION OFOIL AND GAS RESERVES
Setting tolls and tariffs is a key component ofregulation and is intended to protect public interestagainst monopolistic or discriminatory practices ofpipeline companies. That protection is aimed at establishing"just" and "reasonable" tolls, which "under substantiallysimilar circumstances are charged equally to all persons"(National Energy Board Act, 1985). The main standardof reasonable tolls is the cost of service, meaning necessary cost, reasonably or prudently incurred, inclUdingthe cost of capital. This involves consideration of thecapital structure of a pipeline company and its operating costs and of the necessity to attract capital through afair rate of return. The ancillary rules of cost-causalityand user-pay imply that costs should be assigned directly to specific classes of service or customers orgeographic areas, and that the users bear financial responsibility for the costs caused by the delivery of theirparticular commodity.
24.3 MAJOR MARKETSCrude oil must be refined to the various forms ofpetroleum products before it can be utilized by the endusers. Thus, the refineries are essentially the only directrecipients ofcrude oil and, as such, determine the market for it. The refinery requirements are in tum drivenby the level of inventories and sales ofpetroleum products to the consumers. The main product categoriesinclude motor gasoline, middle distillates, heavy fueloil, and petrochemical feedstock. Seasonal nature ofdemand for these products dictates seasonal variationsin refinery modes of operation and the optimal composition offeedstock crudes.
During the 1980s, Canadian refiners faced volatilefeedstock costs, reduced oil demand, changing productspecifications and demand slate. The industry respondedthrough rationalization, which included plant closuresand refinery upgradings. As a result, eleven refinerieswere closed and two reduced in size. Over the past fewyears, Canada's refining capacity has stabilized at around1.9 million barrels per day, down from 2.3 million barrels per day in 1980. In the process, the Canadian refiningindustry has become highly competitive and capitalintensive, resulting in the gradual erosion of the profitmargins. In 1992, the refinery utilization rate droppedto 80 percent, down from 85 percent in 1990, as sluggish demand forced refiners to trim their crude runs(Energy, Mines and Resources Canada, 1993).
Traditionally, Canadian refining centres west ofMontreal have been supplied exclusively with westernCanadian crude oil, while those east of Montreal have
--------------------_.",.,
CRUDE OIL MARKETS
relied heavily on water-borne imports of mostly lightcrude from offshore sources. The reliance of Atlanticrefineries on imports has increased steadily, reachingalmost 100percent in the past few years. Montreal refiners have obtained their feedstock crude from bothdomesticand overseassourcesbut, most recently,haveincreasingly favoured cheaper overseas crudes fromtheNorthSea,WestAfricaand LatinAmerica. Overall,Canada has been a net oil exporter, with the surplus ofmainly heavy crudes declining gradually through thelate 1980s, before increasing to 190 thousand barrelsper day in 1991 and 289 thousand barrels per day in1992on the heels of sluggish domestic demand.
The bulk of Canadian refining capacity is located inOntario and the prairie provinces (Figure 24.2-2).Consequently, these two regions are the largest domestic markets for Canadianoil, with the receiptsreaching26 and 21 percent of total 1992production respectively. British Columbia consumed another 9 percent ofCanadian crude in 1992 (mostly from Alberta), whiledeliveriesto Quebecand the Atlanticprovincesconstituted a mere0.3 percent (Energy,Mines and ResourcesCanada, 1993). The remaining 44 percent of Canadiancrude was destined for exports. The US Midwest wastheprimaryexportmarketfor Canadiancrude,accounting for approximately three-quartersof all exports. TheUS Rocky Mountain and the US East Coast acceptedthe bulk of the remaining export barrels.
In 1992, Canadian crude oil exports were split almostevenlybetweenlightandheavycrudes.However, heavyoilproducerswere substantially more dependent on foreign marketsthan light oil producers.Heavyoil exportsamounted to three-quarters of total supply, while thecomparable figure for lightoil was only38percent. Thisstrong dependence on export markets for heavy oil iscaused by limited demand from Canadian refineries,which are designed to run predominantly light crudes.
Although a large number of northern tier Americanrefiners useCanadian heavycrudes,overhalfof the totalexports is purchased by three large refiners: Koch atMinneapolis, and two Chicago refineries owned byMobil andAmoco (Table24.3-1). Sincelate 1980s, theseand other refineries (including Newgrade at Regina)have gone throughdebottlenecking, which has resultedin increased demand for Canadian heavy crudes. Thisgrowthhas been partially offsetby the shutdown of theSarnia-Montreal line, and a switch by the Uno-Ven(Union) refinery in Chicago to Venezuelan feedstock,following a 50 percent acquisition of the refinery byPetroleosde VenezuelaSA (PDVSA).
Canadian crude is sold to the end-users directly by theproducers, or throughthe AlbertaPetroleumMarketingCommission (APMC) and several commercial marketing entities. The APMC is a provincial crowncorporationand the largestmarketerof Canadian crudeoil, supplying it to a wide base of refiners throughoutCanada and the northern tier of the United States. Asagent for the Alberta Crown, the APMC is responsiblefor gatheringand marketingcrude oil royalty taken inkind from provincial Crown leases. It also marketsAlberta's 16.74percent equity share in Syncrude, andofferscontractmarketingservices to Alberta producers(AlbertaPetroleum MarketingCommission, 1992).
TheUSRockyMountain regionisoneof fivegeographical districts, delineated in 1950 by the PetroleumAdministration for Defense (PAD) for the purpose ofadministration, and is often referred to as PADD IV. Inrecentyears,PADDIVhas offeredthe highest netbacksforAlbertacrude, butrelatively limiteddemand. Bycontrast, the US Midwest (PADD II) and Ontario marketshavebeenthe mainrecipientsof Albertacrude, togetheraccounting for overhalf of Albertaproduction. The USEastCoast(PADD I)andparticularly theUSWest Coast(PADD V) have been the marginal markets, both interms of relativevolumes and netbacks.
Closure of the Sarnia-Montreal extension in mid-1991andIPL's persistentcapacityconstraints sincethenhaveled to the development of oil surplus in the traditionalmarkets for Canadiancrudes.This encouraged Albertaproducers to pursue opportunities in nontraditionalmarkets in order to stabilize prices and avoid shut-in.Consequently, increased volumes of light crude weremoved to Wyoming, the US West Coast and thePacificRimcountries. For example, in its annual reportthe Alberta Petroleum Marketing Commission (1992)reported selling 900 thousand barrels of light royaltycrude to the Chinese PetroleumCorporation in Taiwanduring the fourth quarter of 1991.
24.4 NORTH AMERICAN PRICINGDeregulation coincided withaneraof substantially lowerworldoil prices in the aftermathofthe 1986price crash.AverageOECDI importprices have fallen from an average of over US $26 per barrel in 1985 to US $14 perbarrel in 1986, and fluctuated in a US $15-20 range inrecentyears. TheOPEC' "basket"price-another globalindicatorrepresenting the average price for a basket of
'Organization forEconomic Co-operation andDevelopment.
'Organization of Petroleum Exporting Countries.
291
•
seven OPEC crudes and one Mexican crude-movedin tandem with OECD import prices.
In North America, prices of West Texas Intermediate(WTI) crude have followed the world trend, falling fromover US $30 in late 1985 to below US $12 in the summer of 1986, and fluctuating between US $15 and 23through the summer of 1990 (Figure 24.4-1). In late1990, WTI prices briefly soared over US $40 (on a dailybasis), the highest level since 1982, on the heels of theMiddle East tensions. Since March of 1991, WTI priceshave exhibited remarkable stability, hovering in a narrow range around US $20. WTI enjoyed price premiumsagainst major international crudes, particularly againstheavier and more sour grades. These premiums havemore than doubled since 1987, reflecting falling WTIoutput, US pipeline and refining bottlenecks, widersweet/sour differentials and higher tanker rates.
Table 24.3-1 Importers of Canadian Heavy Crude
DETERMINATION OFOIL ANDGAS RESERVES
Since the establishment of the New York MercantileExchange (NYMEX), WTI has been the benchmark forNorth American and overseas light crudes. WTI is thedeliverable grade ofcrude oil specified in the NYMEXfutures contra~t. WTI prices are quoted at Cushing,Oklahoma, which IS the mam gathenng terminus forpipelines shipping US domestic crudes north toChicago and other Midwest refining centers.
With Chicago constituting the key export market forCanadian crude, WTI is also the benchmark forCanadian light sweet oil. Since 1986, Canadian refinerpostings have tracked WTI spot prices very closely. TheFOB parity value for Alberta crude ofequivalent quality has been based on WTI price at Chicago, netted backto Edmonton. In 1992, this value fluctuated around thetransportation cost differential of US $0.85 per barrelbelow WTI (Figure 24.4-2), modified occasionallyby "market discounts" reflecting local pipeline and
Company Location Rated Capacity (bed x 103) Canadian Heavy Crude
Crude Coking Cracking Asphalt Usage in 1991(bed x 103)
Indiana Amoco Whiting 350.0 28.0 145.0 45.0 62.1Laketon Laketon 8.3 - - 3.5 5.4
Illinois Clark Wood River 57.0 14.5 26.0 - . 0.0Mobil Joliet 180.0 38.0 98.0 - 84.8Uno-Yen Lemont 177.0 27.9 58.0 3.6 8.1
Michigan Marathan Detroit 70 - 27.0 18.0 4.0
Minnesota Koch Rosemount 218.5 58.0 55.0 35.0 157.6Ashland St. Paul 67.1 - 23.0 14.0 3.4
Montana Cenex Laure 40.4 - 12.0 10.0 14.8Conoco Billings 49.5 14.0 19.0 6.5 0.0·Exxon Billings 42.0 7.7 25.9 11.0 10.0MontanaRefining Great Falls 7.0 - 2.4 1.2 2.3
Ohio BP Toledo 120.7 15.0 90.0 7.0 1.0Ashland Canton 66.0 - 25.0 12.0 2.3
Washington US Oil Tacoma 32.8 - - 8.0 2.7
Wisconsin Murphy Supedor 32.0 - 11.0 13.5 5.6
Source: Scott, 1992.• Coker startup in 1992.
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s
CRUDE OIL MARKETS
refining constraints. That price relationship is expectedto hold in the near future, as the positive impact of thephase-out of US import duties will be offset by risingIPL pipeline tariffs.
Unlike sweet crude prices, the Canadian postings forsour and heavy grades have not consistently tracked theirUS and international benchmarks. Canadian prices forheavier grades have typically been lower and morevolatile due to the limited Canadian market, seasonality of demand, aggressive competition from Mexicanand Venezuelan heavy grades, and lower desirability ofheavy feedstock. In 1991, the situation was further exacerbated by increased Canadian production of heavycrudes.
Lower prices for heavy crudes reflect their inferiorphysical characteristics as compared to light crudes.
J93JaB JaB a so J91 J92
Trading Month Averages
0,00+---+---<----+---+-->---+--_-JaB J87
Source:Reuters.
10.00 -------------------------. --_ •. ------------ ••. -------- •• --_ ••••
30.00 ---------------. ---- .-------------------.-- - --_ ••• -------- •• __•••••• --
US$Jbbl40.00 ._----
Figure 24.4-1 NYMEX WTI Prices at Cushing
CHICAGOWTI + $US 0.52
$US 1.26$US 0.07$US 1.33
Tariff & lossCarrying costTotal
$US 0.02$US 0.02
$US 0.04
$US 0.48$US 0.04$US 0.52
Tariff & lossCarrying costTotal
U.S. importfeeCustom user fee
U.S. import fees
1.19175.94%5.00%
$US 1.22$US 0.06$US 1.28
Tariff & lossCarrying costTotal
Price used in pipeline lossand carrying cost calculations
$US 21.74/bbl
Exchange rateCanadian interestrateU.S. interestrate(Prime rate =1%)
Source: Alberta Petroleum Marketing Commission, 1992.
Figure 24.4-2 Alberta Crude Oil Pricing, Chicago Market (July 1992)
293
.
Heavy crudes yield significantly higher volumes ofheavy components at the standard distillation cuts.Heavy components can be used either to produce lowpriced heavy oil products (i.e., residual fuel oil orasphalt) or run through sophisticated catalytic. orthermal conversion units to obtain lighter products (i.e.,gasoline or jet fuel). Since lighter products fetch higherprices, but are also more expensive to produce fromheavy crudes, the refiners' choice ofthe feedstock crudesis determined by relative product values and operatingcosts.
The refinery coking differentials between light andheavy crudes, which represent the difference in "grossproduct worth" net ofoperating costs, constitute a floorfor light/heavy crude price differentials. When the existing heavy oil conversion capacity is fully utilized andthe demand for heavy products is limited, processing ofincremental heavy oil requires installation of new conversion units. The refiners will consider such aninvestment ifthey can expect to recover associated coststhrough low prices ofheavy oil feedstock. This threshold differential is more difficult to pinpoint as it iscontingent on the type of conversion unit and location.The National Energy Board (I991c) estimates that theadditional cost of upgrading ranges from US $6 perbarrel for existing US refineries to US $10 per barrelfor a stand-alone upgrader in Alberta.
In summary, the price differentials for light and heavycrudes are driven primarily by the supply of heavycrudes, the demand for heavy products, and the economics of converting these crudes to lighter products.The demand for heavy products is related to economicactivity, weather patterns, environmental regulations,competition from natural gas, and technologicalprogress. These differentials are also affected by changesin world crude slates, available conversion capacity(planned vs. required), and transportation logistics.
The refinery posted prices are typically set for heavyoil blends rather than for pure heavy crudes, which often require diluent to be shipped through the pipelines.Differentials against the reference light crude forCanadian heavy oil blends such as Bow River orLloydminster have typically been around US $5-6per barrel. These differentials widened to US $9 perbarrel in early 1991, due to such factors as increasedsupply of domestic heavy crudes, the closure of theSarnia-Montreal pipeline, warm winter weather, andnatural gas substitution. By the summer of 1992, thedifferentials narrowed close to the typical levels, as aresult of incremental demand by the newly constructed
294
'-'DETERMINATION OF OIL AND GASRESERVES "".".. c>
Lloydminster upgrader and the new coker at Conoco'sBillings refinery.
24.5 PRICE RISK MANAGEMENTWith the deregulation and commoditization ofcrude oilin Canada, the producers have been exposed to international price volatility, thus creating the need tominimize price risks through the use of various instru_ments that spread the risk over a large number ofmarketparticipants. The reduction ofthe price risk over a specific period of time is commonly referred to as hedging.The main hedging instruments include energy futures,options, and swaps.
24.5.1 FuturesFutures are developed from forward contracts, that is,individually negotiated contracts for the future deliveryof commodities. The uniqueness of each forward contract, limited transferability, and the lack ofa third-partyguarantee of performance led to the creation of futurescontracts. A "futures" contract is an agreement to buyor sell a standard quantity and quality ofa specific commodity at a fixed price, time and place, under the rulesof a recognized exchange, guaranteed by a third partyknown as a clearing house (Arshi, 1992). The energyfutures were established on the NYMEX in 1978. Thesewere followed by the gasoline futures in 1981, crude oilfutures in 1983 and propane futures in 1987. At present,NYMEX futures are the main short-term risk management vehicle for oil prices, with more than 30 millioncontracts traded annually.
Each NYMEX crude oil futures contract represents anobligation to deliver one thousand barrels ofWTI crudeat Cushing on a specified future date. A company wishing to protect its cash flow can use the futures to pre-sella specified portion of its annual production by taking ashort position on NYMEX. The company can sell futures contracts ifprices rise above target levels or whenprices are expected to decline. If, subsequent to sellin.gthese contracts, the prices fall, lower prices from physical sales are offset by profits from the futures "paper"trade. Alternatively, if prices rise, futures losses areoffset by higher prices from physical sales.
The NYMEX contract owes its popularity to relativelyhigh liquidity (the highest number of contracts traded)and transparency (prices are broadly disseminated to theindustry and quoted in the press). For these reasons, theNYMEX contract is the most accepted by the buyersand sellers as the benchmark for North American andinternational oil transactions. In particular, close correlation ofCanadian oil prices with NYMEX futures prices
____________________A
CRUDE OIL MARKETS
makes the futures contract an excel1enthedging vehiclefor Canadian producers. WTI futures contract prices areavailable on a real time basis up to 36 months out andprovide participants with the opportunity to lock in oilprices any time during the trading hours.
24.5.2 OptionsFutures protect against unfavourable price movementsat the expense oflost opportunity to benefit from favourable price movements. Crude oil options expand therange of hedging strategies by offering limited quantifiable risk and the potential to gain from favourable pricemovements as wel1. The first NYMEX option contractwas launched in November 1986 for crude oil futures,fol1owed in June 1987 by an option on heating oilfutures. These powerful financial instruments complement the energy futures and greatly enhance liquidityand trading opportunities at futures and optionsmarkets.
A "put option" buyer pays a premium for the right tosel1 at a specific price for a specific period oftime. Therefore, a put option strategy can provide a guaranteed pricefloor. A "call option" gives the holder the right to purchase a futures contract at a specified price during thelife of the option which, in effect, provides a guaranteed price ceiling. The simplest hedging strategy is topurchase put options to be exercised if WTI futuresprices fal1 below a predetermined strike price. This strategy establishes a guaranteed floor price withoutsacrificing potential upward price gains. A more sophisticated strategy cal1ed a "fence option" involvesestablishing both a floor and a ceiling price.
24.5.3 Swaps"Swaps" are over-the-counter financial transactions thatallow producers and consumers to transfer price risk toa financial intermediary. Liquidity problems associatedwith the purchase or sale offutures contracts in the moredistant months have led to the development ofthese socal1edoil price swaps. The intermediary can either holdthe unbalanced risk portion, match the position to anopposite counterpart, or use futures and options tobalance the risk. The provider of swaps offers customtailored price insurance in a variety of crudes andproducts, with guaranteed maximum or minimum prices,according to the need, and protection from othermarket uncertainties.
Oil swaps took off in 1988 when oil prices were fallingand oil producers wanted a guaranteed revenue. Theswaps market is now wel1-developed with brokeragecompanies and banks providing forward pricing in
crude oil for terms of up to ten years. Although mosttransactions are limited to less than two years. The volume ofswap market is difficult to estimate due to closecompetition and the secrecy of swap business.
24.6 OUTLOOK AND CHALLENGESCanada has a large resource base and enhanced accessto the world's largest energy-consuming market, but theindustry is facing chal1enges from deteriorating geology and rising production costs. There are strongindications that conventional oil production from themature western Canadian basin may be in an irreversible decline. Hence, future supplies will have to comeincreasingly from nonconventional sources or imports.
As a result, it is expected that the quality of crude andthe regional distribution of supply will shift dramatical1y. Heavy oil will increase its share at the expense oflight oil, while conventional supplies from westernCanada will be increasingly replaced by nonconventional supplies of synthetic and frontier oil. Basedon the latest projections by the National Energy Board(1991c), synthetic oil is expected to account for 18 percent of Canadian production by year 2000, while crudeoil from the East Coast offshore (mainly Hibernia) isexpected to provide about 12 percent. Consequently,the share of western Canadian conventional light oil intotal supply may fal1 from over three-quarters in 1991to only one-third by year 2010.
Growing supplies of heavy oil will require equivalentgrowth in easily accessible markets, posing seriouschal1enges for Alberta producers in the areas of transportation (reduced pipeline space, increased demand fordiluent), marketing and refining (limited upgrading facilities and environmental concerns). There is someopportunity to increase sales to the established majorexport markets. New capacity could also be added inthese markets, but this would require substantial up-frontinvestment. Optimization ofcurrent available capacity,fol1owed by conversion of current light refining capacity to handle heavy crudes, seems to offer the lower costsolution to expected heavy oil refining bottlenecks.Some additional "grass roots" upgraders may also berequired early in the next decade.
The outlook for world oil prices is rather bleak. Thereis growing consensus that future world capacity additions will be more than sufficient to satisfy the world'ssluggish demand for oil, which will be increasinglyconstrained by environmental regulations. As a consequence, real oil prices are general1y expected to showlittle, if any, growth over the next decade. Low oil prices
295
-
will have a detrimental impact on the size ofestablishedreserves, as well as on future production and industrycash flows.
To survive in the continued soft price environment,Canadian producers will be hard-pressed to minimizeproduction costs by employing leading edge technology and focusing on narrower areas of expertise. Aswell, vast amounts of capital will be required both upstream and downstream to meet increasingly stringentenvironmental standards. Marketing efforts will likelycontinue to be frustrated by growing refining and pipeline constraints, while governments will be faced withshrinking attainable economic rents and growingpressure to soften their crude oil royalty terms.
ReferencesAlberta Petroleum Marketing Commission. 1992.
Annual Report (1991). Calgary, AB, p. 8.
Arshi, A.A. 1992. "Energy Swaps as Profit MotiveInstruments in Oil Markets". OPEC Review,Summer 1992, pp. 201-212.
Energy, Mines and Resources Canada. 1993. TheCanadian Oil Market. Vol. IX, No.1. Ministerof Supply and Services Canada (1993), ISSN0829-3732, p. II.
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DETERMINATION OFOIL AND GASRESERVES
National Energy Board. 1991a. Canadian Energy.Supply and Demand 1990-2010. Minister ofSupply and Services Canada, Calgary, AB, June1991, Cat. No. NE 23-15/199IE, ISBN 0-66218956-6, p. 232.
---. 1991b. Annual Report. Minister of Supplyand Services Canada (1992), Cat. No. NE 11991E, ISBN 0-662-19372-5.
---. 1991c. Canadian Energy. Supply andDemand 1990-2010. Minister ofSupply and Services Canada (1991), Cat. No. NE23-15/1991E, ISBN 0-662-18956-6, p. 228.
National Energy Board Act. R.S. 1985. c.N-?, Cat.No. YX76-N7/1992, ISBN 0-662-58945-9, PartIV, par. 62, p. 37.
Petroleum Communication Foundation. 1992. "CrudeOil." The Backgrounder Series, Calgary, AB.
Scott, G.R. 1992. "Canadian Heavy Oil andBitumen-Some New and Old Ideas." Paperpresented at AOSTRA-Heavy Oil Assoc.conference, Calgary, AB, Jun. 1992.
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Chapter 25
NATURAL GAS MARKETS
25.1 INTRODUCTIONSince the deregulation of gas markets in 1986, a veryrapid evolution has occurred in the marketing, transportation, and government regulation ofnatural gas. Theenvironment ofgas markets has developed from that ofa virtual monopoly held by a very small number ofaggregators into a large spectrum of sales opportunitiesfor producers falling into three general categories:direct purchases, aggregator purchases, and hedging opportunities such as storage purchases and participationin futures markets.
Similarly the role of reserves estimates has changedconsiderably. No longer do the reserves provide the soleunderpinning ofa contractual arrangement between thebuyer and the seller; reserves are now frequently onlyone of the supply characteristics providing the buyerwith assurance that his requirements will be met.
Production forecasting is the synthesis of all of thefactors and variables that drive the producer activitiesof exploring, developing, and selling natural gas.
The market factors that affect production forecastingwill be defined and discussed in this chapter by reviewing the Canadian and US market environment duringthe following periods: (I) the pre-deregulation era,before November, 1986 in Canada and before themid-1980s in the United States, (2) the current era, and(3) the (expected) future. Demand forces exerted byvarious types of markets and buyers will be describedfollowed by a discussion of production forecasting.
25.2 THE MARKET ENVIRONMENT25.2.1 Review of Pre-Deregulation EraMarket demand forces had a very strong, but somewhatindirect, role during the years prior to deregulation. Gaswas purchased from producers by a small number ofaggregators in the United States and Canada, and theseaggregators were usually affiliates of pipeline companies or utilities. The aggregators pooled the producers'volumes and then resold them to utilities and local
distribution companies (LDCs), who in turn suppliedthe core and noncore markets. "Core markets" aredefined for purposes of this discussion as "the group ofconsumers who have no ability to use alternativeenergy sources, primarily use gas for space heating, andhave a high security requirement." In addition, theaggregators performed all of the intermediate steps between producer purchase and burner tip includingtransporting the gas from gas plant to end user and obtaining governmental regulatory approvals (such asAlberta Energy Resources Conservation Board (ERCB)removal permits, National Energy Board (NEB) exportlicences, and US import authorizations). Most importantly, the aggregator provided the contractual link thatjoined producer and end user. This contractual linkcoupled with the regulatory permits provided securityof supply for the end user and for the exporting andimporting geographical regions.
The producer was given the assurance that the takelevels and prices under his purchase contract would bemaintained, often through some sort of "take-or-pay"or "take-or-release" mechanism. The end user was provided with assurances as to security of supply throughthe reserves pool that the aggregator had under contract.The exporting provincial and federal governments wereprovided with assurances ofsupply security through thesurplus test mechanisms.
This arrangement worked well enough considering theoverall philosophy of the end users and regulators atthe time who regarded the gas reserves of westernCanada and the United States as a finite resource, limited entirely by the technology then currently available.The issue of supply security was paramount and wasmet entirely by the known reserves inventory. Accordingly, producers' contracts with aggregators wereusually long term and had a daily contract quantity basedon a 15 to 20 year reserve life. The end user did not dealdirectly with the producer, but the aggregator's purchaseand sales contracts and regulatory mechanisms acted asa buffer that filtered market signals. This regulatory
297
•
mechanism has now been viewed as partiallyresponsible for creating the large productive capacitysurpluses during the last two decades, otherwise knownas the infamous "gas bubble."
This era came to an end with the following changes toregulatory approvals:
Canada
I. NEB amendments to export licences in 1984, whichallowed US purchasers to negotiate prices subjectto the Toronto City Gate Price as a floor
2. The federal - provincial agreement on "Natural GasMarkets and Prices" ofMarch, 1985, which droppedprice tests in favour of a price monitoring mechanism
United States
1. The enactment of the Natural Gas Policy Act(NGPA) of 1978, which commenced a phaseddecontrol of wellhead gas prices
2. Various amendments by the US Federal EnergyRegulatory Commission (FERC) to the Natural GasAct (NGA) in the form ofFERC orders. The intention of these orders was as follows:
• To ensure that producing states would regulatethe physical production of gas and controlintrastate marketing matters
• To protect overall public interest where gas production transportation sales to end users involvestwo or more states
• To establish a framework for contract demandconversions by merchant pipelines and for thecreation ofgas inventory charges that would ultimately allow customers to purchase gas in areliable and competitive fashion from as manysuppliers as they wished
The more important FERC orders that furthered theprocess were as follows:
• May, 1984. FERC Order 380, which outlawedthe collection ofminimum commodity bills, leaving LDCs free to reduce their minimum purchaseobligations from the merchant interstate pipelines.
• October, 1985. FERC Order 436, which introduced a voluntary open access program allowingLDCs to convert their service from sales to transportation, but ignored any resulting take-or-payimplications.
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DETERMINATION OF OIL AND GASRESERVES
• June, 1986. FERC Order 451, which adminis_tratively commenced deregulation ofinterstate gasas defined in the NGPA.
• December, 1986. FERC Opinion 256, whichaddressed the problem of different pipeline ratecalculations utilized by US and Canadian pipelines. Most Canadian pipelines use the "full fixedvariable" rate design whereby all fixed costsnamely, operating, maintenance, depreciation'debt costs, income taxes, and return on equity areincluded in the demand charge, and variable costsare included in the commodity charge. Most USpipelines utilize the "modified fixed variable" rate .design whereby income taxes and the retum onequity are included in the commodity chargerather than in the demand charge. This FERCopinion attempted to solve this problem by disallowing the pass-through of Canadian pipelinecharges except for the ''prebuild'' portions of theAlaska Natural Gas Transmission System (i.e., theFoothills Pipeline System).
• August, 1987. FERC Order 500, whichaddressed the take-or-pay implications in pipeline company-producer contracts that wereunresolved in FERC Order 436. Open accesspipelines were ordered to offer volumetric takeor-pay credits to shippers on their pipelines. Theentire gas producing and transmission industryhad to absorb the large take-or-pay liabilitieswhich had been incurred from 1987 onwards asmarket forces forced the process ofreforming gaspurchase contracts.
• 1991. Proposed Mega-NOPR (Notice ofProposed Rulemaking), which forces mandatoryunbundling on all pipeline companies, thusrequiring them to offer transportation, storage,and balancing services on an individual basis toshippers.
• 1992. FERC Order 636A, which implementsthe unbundling process by specifying the stepspipelines can go through to offer transportation,storage or merchant services to customers as wellas offering rights on upstream pipelines.
25.2.2 Review of Current EraDeregulation in Canada commenced officially onNovember 1, 1986, and pent-up market forces wereunleashed that caused structural changes to supply contracts, markets, transportation, and governmentregulatory requirements. The most obvious change
---------------------
NATURALGAS MARKETS
occurred with prices: export prices from Canada wereno longer set by the federal govermnent, but rather reflected competitive market forces. The customers andproducers were now to be closely linked, without theartificial buffers that blurred market forces.
Deregulation has progressed at different rates in theareas of marketing, supply, and transportation and in adifferent fashion in the US as compared to Canada.
United States Deregulation
Deregulation in the US is occurring at a somewhatuneven pace. The end users themselves have adoptedderegulation fairly quickly; for several years variousend-users have purchased volumes directly fromproducers. However, transportation deregulation hasbeen much slower than in Canada, and a number of USpipelines still retain their merchant function while anumber of others are not yet open-access carriers. Thisappears largely due to the industry responses to FERCOrders 380 and 436, which gave LDCs and shippersoptions as to purchases and transportation.
Another significant factor is, ofcourse, that Canada hasonly one interprovincial carrier, TransCanada Pipelines,whereas a large number of pipelines exist in the US.One of the more significant events taking place in theUS during 1991 was the California Public UtilitiesCommission's (Cpuq move to dismantle the PacificGas and Electric (PG&E) monopoly in northernCalifornia. This is an example of an individual statecommission overturning freely negotiated contracts between two parties: PG&E with its affiliated purchasingarm Alberta and Southern, on the one hand, and theAlberta producer group on the other. It appears that thisaction is being taken by the CPUC in order to expeditethe transition of Pacific Gas Transmission (PGT) to acompetitive open access carrier.
The same process is occurring with other US pipelines;however, the process was much more disruptive in thecase of PGT due to the unique northern California gassystem, where a large dedicated Alberta supply isconnected to a single pipeline owned by an end userwith a complete sales and distribution monopoly.
Historically the US domestic supply-demand balancehas reflected more ofa market approach than in Canadawhere a mandatory surplus test created an artificialsupply-demand ratio. The current US reserves-toproduction ratio, RIP, is approximately 8 to 10; theCanadian equivalent RIP is approximately 15 to 20.Approximately 40 to 60 percent of US sales volumesand approximately 20 to 40 percent of Canadian sales
volumesarepurchased through short-termcontracts (lessthan one year). Thus a significant number of sales arrangements are not based on traditional reserve-basedcontracts; instead, term, interruptible or deliverabilitytypes of contracts may be used. This reserves-toproduction philosophy, coupled with the clear relianceby end-userson short-term"spot market" price contracts,demonstrates the deregulated nature of the end-usersegment of the industry. However, a significant number of merchant pipelines are not yet deregulated. Thepace of this deregulation will be a function of theimplementation speed of the Mega-NOPR and theprogress of individual states-the most visible beingCalifornia-towards full deregulation. This will not bea straightforward process; literally thousands of LDCmerchant contracts will be ultimately replaced with thefollowing:
• Direct LDC-producer sales contracts
• LDC or producer transportation service contracts
• LDC or balancing service contracts
• Combinations of all of these
Canadian Deregulation
The market environment in Canada is significantlydifferent than in the US. Intraprovincial transportationis virtually fully open access from a contractual sense.The same is true of interprovincial pipelines; however,there is less physical access due to the fact that only onepipeline services markets east ofthe Alberta border, anda small number of pipeline systems carry volumes intothe US market areas. Domestic markets, with the exception of some restrictions on core markets, are fullyopen to all producers, but there is limited access due tothe magnitude ofthe long-term purchase contracts currently in place between the LDCs and their suppliers.
A further restriction on open access is political: Albertahas not yet developed a policy ofallowing producers todirectly sell to eastern Canadian core markets on termsof less than 10 years. The intention is to maintain security of supply and prevent further erosion ofthe historiccore sales arrangements by only allowing long-termcontracted supplies to sell to the eastern Canadian coremarket. However, the net effect has been market displacement via the acquisition of direct short-termpurchase supplies from Saskatchewan (and to a certainextent from B.C.) by eastern Canadian end users.
The mix of markets now available covers a fullspectrum ranging from short-term with no reservesdedication, to long-term underpinned by corporate warranty (with or without reserves dedication). The trend
299
towards shorter term sales and faster pool depletionshas caused Canada's RIP to steadily decline during thelast decade from approximately 25 to just below 20. Thisphenomenon will likely continue during the 1990s,approaching a stable value in the range of 8 to 10 bythe tum of the century.
Many events currently underway will ultimately playarole in determining the market demand forces discussed.These events need to be viewed in the context of thepreceding discussions.
I. US storage continues to mask the true daily supplydemand relationships. The actual US deliverabilitycapability is still difficult to determine'.
2. Canada and US statistics show sizeable replacements ofproduction during the last 3 to 4 years, inspite of dropping prices and oversupply signals.
3. The phenomenon of "overmarketing," i.e.,producers being very aggressive in marketing hasled to:
• NOVA excess receipt capacity
• Over-subscription of NOVA export capacity
4. Supply distortions such as the US subsidy of coalseam gas development result in producer netbackscurrently higher than current spot prices for naturalgas.
5. Futures markets monthly closing prices arecorrelating consistently with actual monthly spotprices.
6. The political and regulatory "out of sync"phenomenon; the Alberta government is stillproceeding slowly to establish a core marketdefinition with Ontario.
7. Producer price expectations vs. marketplace priceexpectations. Very recently cogeneration projectshave been proposed with fixed-price, 20-yearcontracts, i.e., no formulae, no "openers."
8. The FERC Mega-NOPR and subsequent implementation orders are an attempt to complete the fullderegulation of gas from wellhead to burner tip byforcing pipelines to completely unbundle their salesand transportation services.
9. The "prorationing experiment" being tested by thestates ofTexas and Oklahoma is an attempt to forcegas supply and demand into a closer balance. Thisis an interesting attempt at re-introducing government regulation at the same time as the efforttowards complete deregulation is still continuing.
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DETERMINATION OFOIL AND GAS RESERVES
25.2.3 Preview of Future EraThe current era in Canada and the US appears to be atransition phase. The role ofthe traditional marketers ischanging rapidly; market types are becoming lessdefinable; and producers are reacting in different waysto this changing environment.
It is expected that the next era of gas markets willcommence when the following occur:
• Canadian core markets can purchase supplies fromany source under freely negotiated terms, as opposedto terms set by regulatory bodies.
• US pipelines become mostly open access carrierswhich allow capacity brokering.
• Sufficient export pipelines are constructed out ofAlberta to reduce the excess deliverability inside theprovince.
• Buyers and sellers in the US and Canada can effectgas sales arrangements, and pipeline systems can provide transportation arrangements on a com-mercialbasis only without regulatory impediments.
An equilibrium phase may then be in place, to theextent that any market can be accessed by any source ofsupply, subject only to "ordinary" economic supplydemand relationships.
As a result of the experience of the last three decades,the remaining reserves in Canada and the US may beviewed as an inventory that is continuously beingreplaced rather than as afixed entity.
25.3 MARKET MECHANISMS ANDMARKET FORCES
This section discusses market forces in the context ofa North American reserves base dependent only uponeconomics.
25.3.1 Market Types and MarketMechanisms
Markets are generally of two types: core and noncore.Various Canadian provinces and US states have yet toestablish formal definitions for core markets althoughthey have been attempting to do so for several years.The definition of core markets developed in Section25.2.1 will be used throughout this discussion.
Market mechanisms are illustrated in Figure 25.3-1,which illustrates the basic steps that a producer must gothrough to place gas onstream to an ex-Alberta market.The following are the fundamental requirements:
1. Establish reserve deliverability; in other words,define the volume to be sold.
______________________1
NATURAL GASMARKETS
Short-Alberta-ERCB
Producer NOVA Term Ex-Alberta Pipeline Eastern
(Alberta) Pipeline (Less thanRemoval
ICanadian
Permit Market2 Years)Ex-cana~ Pipeline
(Federal) US DOEUSNEB Short-Term f-- Short-Term Import f-
Export Licence AuthorizationMarket
Long-Term
Ex-AlbertaPipeline
,,Consuming Eastern,,
, Province Canadian,Import Review Market,,
required
L NEBFERC
US DOE ReviewLong-Term Import US
Export Licence Authorization If facilities Market
Ex-Canada Pipeline
Basic RequirementsI. Transportation in Alberta2. ERCB Removal Permit3. Transportation Ex-Alberta4. NEB Export Licence5. DOE Import Authorization6. FERC Review7. US Transportation8. Markets
Figure 25.3-1 Commercial and Regulatory Mechanisms for Ex-Alberta Markets
2. Identify a market and negotiate a purchase contract.
3. Procure transportation in Alberta to move the gasfrom the production point to the Alberta border.
4. Obtain an ERCB removal permit, either short-term(less than 2 years) or long-term, which requires ademonstration of reserves, market details, transportation arrangements, and an analysis ofthe socialand economic impact on the province.
5. Obtain transportation outside of Alberta, either toeastern Canada or to the United States.
6. Obtainan NEB export licence,either short-term(lessthan 2 years) or long-term, which requires demonstrationofmarkets, transportationarrangements,andreserves and an assessment ofthe impact (optional)on the effect on Canadian energy markets of thisexport plus an estimate ofproject revenues.
7. Obtain Department of Energy (DOE) importauthorization, either short-term (2 years or less) or
long-term, which requires identification of themarket and specifics of the sales contract.
8. Obtain FERC approval if interstate transportationfacilities are required.
The foregoing very briefly outlines the mechanicsinvolved in selling volumes to an ex-Alberta market.The degree ofcomplexity of regulatory approval applications, will obviously be a function of the size of themarket and the amount, if any, of new transportationfacilities required in Canada or the US.
The marketing options are illustrated in Figure 25.3-2,which shows some of the options available to a producer. Most important from a reserves point of view isthe degree to which liabilities are passed through to theproducer and whether the liability is satisfied by reservesdedication alone or whether a corporate guarantee mustbe made as to supply make-up should a shortfall occur.
The manner in which reserves and markets are linkedis shown in the simple examples of Figure 25.3-3. In
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DETERMINATION OF OIL AND GAS RESERVES
Aggregator End-User
Pro· Residential• Takes titleducer • Commercial
I • Pooled supply & markets· Industrial· Market swings levelled out· Electrical utilities· Regulatory permits• Cogenerators• Transportation· May hold transportation
MarketsBroker / Agent
ucer • Pass-through titleCore or noncoreI · Obtains permits in
producer's name may hold
· Mayor may not hold transportation
transportion
Prod
Figure 25.3-2 GasMarketing Options
Figure 25.3-3a, the reserves of an individual producer(or producers) provide the underpinning or supplysecurity to the customer either directly or throughan aggregator, broker or agent. This supply securitymechanism can be one of two main types: a reservesunderpinning or a financial warranty. The reserves comfort is based upon the pooling procedure ofan aggregatoror, if long-term (greater than 2 years in Alberta's case)export licences are required, then the appropriateregulatory bodies will be "inserted." The effect of aregulatory "screen" in the sales arrangement is toprovide a second security blanket for the customer.Regardless of the particular mechanism in place, theproducer's reserves still provide the overall supplyassurances.
In Figure 25.3-3b, the customer is provided not with areserves base for security but rather with a financialguarantee on the part of the supplier to pay for replacement volumes in the event of a supply failure. In thiscase, the assumption is that sufficient gas supplies areavailable and the question ofobtaining replacement volumes is simply a matter ofpaying for them. Therefore,provided that there is overall comfort as to the reservesstock, and total daily delivery capability, there is noapparent need for a direct connection between theproducer's reserves and the customer.
By choosing a more direct contractual link to the enduser, the producer has done several things:
• Established more direct control over the value ofhisreserves.
• Reduced the "aggregated pool" effect, i.e., theindividual producer's particular reserve entity willnot be rolled into a pool where it would share in thetake level and price characteristics of a basket ofmarkets which the aggregator has. Thus the specificreserve entity will enjoy a unique price-and/or-takelevel market.
• Placed a portion of his assets, either from a reservesvalue or other financial asset point of view, at riskfor the market. Failure to deliver either on a daily orcontract term basis will make a producer liable anddirectly impact the producer's financial situation.
Thus the upside of direct marketing vis-a-vis take leveland price must be balanced off against the downside,namely, corporate warranty costs and demand c~arge
payments to pipelines, all of which impact negatIvelyon the value of the producer's reserves.
25.3.2 Market Demand ForcesThe foregoing discussion has laid the groundwork for adiscussion of market demand forces and their specificeffect on reserves and reserves value. From a globalperspective, the North American reserves-marketconnection takes on a "chicken and egg" charactenstIc(as indicated also in the diagram that follows):
302
_____________________c.
NATURAL GASMARKETS
(a) Reserves Underpinning
Individual Volumes Directly Dedicated Customer
Producer Reserves or via Broker or Agent(Individual
or Pool)
Producer Volumes AggregatorVolumes Customer
ReservesPooled (Individual
Reserves or Pool)
AggregatorProducer Volumes Volumes Regulatory Volumes Customer
ReservesPooled Body (Individual
Reserves Licences, Permits or Pool)
(b) Deliverability Warranty or Corporate Warranty Underpinning
ProducerDeliverability Warranty
Customer(Payment For Replacement Deliveries)
Figure 25.3-3 Reserves Connection to Markets
• The market actions establish the value of the reserves,and affect exploration, development, and acquisitions.
• The reserves characteristics provide the qualityassurances that will support a high quality (meaninghigh price) contract.
• The size of the reserves stock pushes on the market,creating the forces that re-establish the value of thereserves.
~ Price and Price Trends :-II Demand and Demand Trends I
Producer Actions Market Actions
- Technology ~- Cost rationalization
Reserves Stock and'----- Delivery Capability
Commencing with Canadian deregulation in 1986, andcontinuing with the issuance ofkey FERC orders from1984 onwards, the market forces have triggered a seriesof continuous downward revisions to asset valuesthroughout North America. This overall loss of value
has not been quantified here, but amounts to a sizeabledollar figure.
It is reasonable to assume that reserves in remotegeographical locations, such as Canada's arctic regions,have likely been discounted severely during the last5 years. This loss in value translates directly into areal loss of proven reserves. In other words, reservesformerly classified as potential and probable and anyquantities ofproven reserves burdened with a high development cost have been removed from the reservesstock.
During this same period of time, however, significantcost reductions and technological improvements in exploration and development have resulted in new reservesadditions and reserves appreciation to existing pools;these have mitigated and perhaps even outweighedthe discounting effect ofdecreasing market prices. Thenet effect has been a virtual replacement of gas production each year in the United States (which is evidencedby the static RiP ratio during the 1980s), and replacement of a significant fraction of Canadian productioneach year during the 1980s. Therefore, the quantum ofthe ultimate stock of North America's remaining proven
303
!...
plus probable plus possible reserves acts as an overalldampener.
This apparently endless supply reduces the quality andhence the degree offorce that an individual producer orgroup ofproducers can exert on the market, resulting instronger market forces and forcing the seesaw in themarket's favour.
25.3.3 Production ForecastingProduction forecasting is the act of reconciling theexpected market demand environment with the expectedsupply environment. The market demand scenario hasalready been developed in this chapter on the assumption that the North American gas supply base is largeenough to be considered unlimited. Thus productionforecasting, from a global point ofview, appears to be areasonably simple task. One need only assimilate andaccurately forecast the interactive effects of all of theregulatory and political market demand phenomenadescribed in this chapter, and then match productioncapability to this complex model!
A simplistic total North American production forecastwould be based upon the following:
• An established forecast ofrequirements and expectedmarket price
• An estimate of established reserves and productivecapability
• An estimate of supply costs
• An estimate of future finding rates-perhaps bestderived by statistical analysis ofdrilling activity, discovery rates per well, drilling costs-all modified bygas market prices
It follows that a supply-demand curve can then bedrawn as the intersection ofconsumer gas demand withsupply capability.
A more sophisticated forecasting model would incorporate such variables as:
• Pipeline restrictions
• Political decisions or government edicts that setprices, production rates, or fuel substitution
• Complex demand forecasts for each type of gas user
• Individual forecasts for major pools or producingregions
Regardless of the degree of sophistication of theproduction forecast mode, simplifying assumptions mustbe made regarding price, consumer demand, and
304
"".,""'""osOL '"'"",,::-;III'overall producing sector responses to changes idemand and price. n
Developing a production forecast on an individual_producer-of-individual-field basis is somewhat morestraightforward. A producer would have to consider thefollowing variables in developing a production forecast:
I. Gas purchase contract conditions
• Price expectations
• Take level expectations
• Daily volume nomination levels and modifica_tions to this level (i.e., restoration ofvolume levelspreviously reduced by deliverability testing)
• Some expectation ofthe purchaser's performancein view of all of the global market demand andregulatory items
2. Existing field conditions
• Reserve and deliverability information
• Drilling, completion, and well tie-in costs
• Operating costs
3. Undeveloped field conditions
• Capital and operating cost expectations
4. Producer corporate objections
• Financial health and corporate economic guidelines
• Type of reserves available to produce, e.g., rawland, which requires "full cycle" costs, includingland; geophysical drilling, including risk; andsurface facilities costs or acquired reserves, whichmay have been purchased at a discount from thefull cycle costs and thus may be connected atrelatively less cost
The field forecast can then be prepared by matchingindividual well or field physical capability and marketdemand with corporate economic criteria. The producercan then use this forecast to make the appropriate drilling and other capital expenditure decisions.
25.4 THE ROLE OF RESERVESThe foregoing discussion ofmarket forces and production forecasting has provided at least a "thumbnail"sketch of the process. It is worth noting what has happened to the role ofreserves since deregulation. Reservesare one of the cornerstones, directly or implied, of asales contract between a buyer and a seller. Any user ofgas must have some degree of assurance as to supplycontinuity. Reserves can take on different roles in themarketplace, as follows:
c
NATURALGAS MARKETS
Negotiating Tool. A large reserves stock owned by aproducer or controlled by a broker or aggregator carriesa significant weight in sales contract negotiations.
Supply Indicator. A buyer would naturally beinterested in the seller's reserves supply, but the absolute size of the reserve base may be ofless importancethan the seller's replacement ability.
Security. An adequate reserves supply, or adequateassurance of replacement ability, provides support forfinancing the construction offacilities such as pipelinesand end user equipment.
Reserves-to-Production Ratio Yardstick. Thereserves-to-production ratio, RIP, of a seller providesan indication of efficiency, longevity, and marketingstrength as well as perhaps relative financial health. TheRIP ratio for a region or country gives a picture ofoverall security of supply, as well as an indication ofemerging trends such as oversupply or undersupplyproblems.
An understanding by buyers of the RIP for producersand aggregators or brokers and countries as a whole iscrucial to establishing sound contractual arrangements.A buyer's needs for supply security need to fit
a producer's needs for economic turnover of hisinventory ofreserves. Currently, most producers have aneed to sell reserves at approximately a 7 to 12 yearturnover rate, or a I :3000 to I :4500 RIP ratio.
Sellers, on the other hand, can have a need for 20 oreven 30 years of dedicated reserves. Thus, sales arrangements need to satisfy both these needs.
25.5 CONCLUSIONSMarket demand forces are obviously the very basis forthe gas industry; markets are simply the demand for thecommodity the gas producers are trying to sell. Thedemand forces are not necessarily in balance, from aclassical textbook supply-demand law consideration,with either the customers' or the producers' needs.
Production forecasting is becoming an increasinglydifficult task. A forecaster needs to consider all of thefollowing: regulatory and political uncertainties, merchant pipeline deregulation, government jurisdictionaldisputes over market deregulation, market price uncertainties, and changing relationships between findingcosts, technology, and producers' corporate objectives.The complexities of the physical characteristics of thereservoir may be ultimately less difficult to forecast thanthe market factors.
305
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Chapter 26
USES OF RESERVES EVALUATIONS
26.1 INTRODUCTIONThe estimates of reserves and forecasts ofproductionfrom those reserves are widely used within the oil andgas industry and by organizations working withthe industry. The users fall into two well-definedgroups: the first uses only the volumes resulting fromthe process (Section 26.2); the second uses the valuesderived from the cash flows generated from the forecasts ofproduction and other variables (Section 26.3).The development of various economic yardsticks isexplained in Section 26.4.
26.2 USERS OF RESERVES VOLUMESAND PRODUCTION FORECASTS
A wide range of users requires only estimates ofreserves and forecasts of production to operate theirbusinesses and make their decisions. The users withthis requirement would include the following:
Producers, who use the forecasts of production andlife of facilities to size the equipment put in placeto produce the reserves and to deliver them to theirmarket
Pipeline companies, who require estimates of bothcurrent and potential reserves, together with forecastsof current and potential maximum future production,to decide whether new or extended pipelines could bejustified and, if so, the sizes needed
Governments, who need information on reserves andproduction to implement and modify legislation andpolicy on resource development and security ofenergy supply
Gas marketers, who need to know how much gasthey have under contract and the physical limits onthe way in which their contracted gas can be produced
26.2.1 ProducersProducers ofoil and gas must have realistic estimatesof recoverable reserves and forecasts ofproduction toplan the development of hydrocarbon discoveries.
306
The sizing of equipment, from the diameter of the welldrilled to the size of the plant required to process theproduction stream, and everything in between, dependsupon the level of reserves and the resulting production.It is important that the estimates be as realistic as possible, as over-enthusiastic estimates result in unneededcapacity and expense, while low estimates result inbottlenecks that limit production and are costly to overcome. It is important to use reserves estimates based ondetailed engineeering studies.
26.2.2 TransportersCompanies (either producing or pipeline) that transportoil and gas to their final markets need to know both thecurrent level of reserves and the production their facilities will handle, and also the ultimate reserves andproduction their facilities may be required to move.
Pipeline companies need reserves and production datanot only for their own planning and development, butalso for supporting government applications to build newpipelines or expand existing ones.
The building ofpipelines requires government approvalto prevent their unnecessary proliferation and, as a consequence, their tariffs are set by the government indollars, recognizing their operating costs, the recoveryofcapital, and a return on any unrecovered capital costs.Projectionsoffuture tariffs require forecasts ofproduction to estimate the amount ofproductthat will be movedthrough the facilities; from this, charges per unit ofproduct moved can be predicted. Pipelines that are under- orover-sized may result from inadequate estimates ofcurrent and future reserves and production.
26.2.3 GovernmentsGovernments must have detailed knowledge of thecurrently developed resource base and also the ultimateresource that is available for development in order toplan the best legislation and policies for resourcedevelopments.
s
USES OF RESERVES EVALUATIONS
A knowledge of both present and future reserves isnecessary for the best resource development legislationand policies, and also for the development oflong-rangeenergy policy. Identifying sources of supply to meetfuture demands is dependent upon realistic forecasts ofcurrent and potential reserves.
26.2.4 Gas MarketersBrokers of natural gas must know with the greatestprecision possible the reserves they have under contractand the changing rate at which the reserves can be produced, so that they can match these reserves with themarkets they are servicing.
Marketers also need estimates ofreserves and forecastsofproduction for government approvals ofexports fromthe producing provinces and also of exports to othercountries.
The use ofunrealistic estimates of reserves can lead toeither excessive reserves with no markets or a shortageof supply, so that markets are lost.
26.2.5 Other UsersMany other groups benefit from estimates of hydrocarbon volumes, including stockholders, the investmentcommunity in general, and consumer groups.
26.3 DEVELOPING VALUES FROMRESERVES ESTIMATES
The cash flows that result from estimating reserves andforecasting production, prices, royalties, costs, and taxesare discounted to provide a range ofnet present values.This provides a very powerful tool for investment decisions, whether they are internal capital investmentdecisions regarding land, drilling, or production facilities; decisions to buy or sell producing properties;decisions to acquire or merge with other corporations;or decisions to lend money using future production asthe security.
If realistic discounted forecasts offuture cash flows arenot included in the information on which investmentdecisions are made, the investments are not likely to beintelligent or successful. The Canadian oil and gas industry runs on discounted dollars. This situation is notunique to the Canadian oil and gas industry. It mustalways be remembered that the estimation of reservesshould never be considered as the end of the evaluationprocess. Unless the resulting economics are understood,reserves may be incorrectly estimated, and the risks anduncertainties may not be fully understood. The resultmay be reserves that are incorrectly classified as proved,probable or possible.
In corporate investment decision-making, the mostcommon internal investment decisions involve the drilling ofdevelopment wells and the building ofproductionfacilities. While risk may exist with these investments,it is usually not addressed explicitly, but the minimumvalue used to accept or reject an opportunity is set to besufficiently conservative to allow for the risk. In thisway, the targeted rate of return can be achieved on acorporate basis.
26.3.1 Profitability IndicesThe following are some ofthe profitability indices usedin Canada (but certainly not the only ones):
• Payout period
• Return on investment
• Rate of return
• Discounted return on investment
• Net present value
The use and limitations of each index are described inthe following subsections.
Payout Period
Payout period is the time required to recover theinvestment in a project. It can be calculated on a discounted or undiscounted basis. In some cases discountedpayouts are used in the evaluations.
It is important to note that payout is measured from thetime ofthe first significant investment, not from the timeat which production starts. Payout period is usually oneof the indices used in the selection of investment opportunities. A commonly used index is a payout periodthat is a maximum of3 years for a development project(where there is some risk) orno more than 4 to 4Y2 yearsfor fully developed producing properties (where the riskis considered to be minimal). The choice of payoutperiod, however, varies from investor to investor.
Ifthe payout period for a development project is greaterthan 3 years, it should not necessarily cause the projectto be rejected, but should be a warning that the projectmust be better than average to overcome the longerperiod required to recover the investment.
A useful rule of thumb is that projects with payoutperiods ofgreater than 3 years should not represent morethan 10 percent, or at a maximum 20 percent, of thetotal investment budget in anyone year. The companyhas to be able to stay in business until payout iscomplete.
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DETERMINATION OF OIL AND GAS RESERVES
~I'~, I
,
Ibecomes the rate of return at which the cash flow mustbe discounted to give a present worth value ofzero.
This index takes the time value of money into account,but suffers from two serious deficiencies. First, the ratesof return can be very high (in the order of 30 to 70 percent) with the result that little weight is given to anycash flow after 10 years. This causes projects with highcash flows in the short term to appear to be more desirable and may cause long-life projects to appear to beless desirable, with the result that the wrong investmentdecisions may be made.
Second, each project has a different ROR, so thatdifferent weights (discounted values) are given to dollars earned at the same time in the future. Projects beingcompared also have different lives so it becomes a problem to decide ifa project with a ROR of 50 percent anda IS-year life is better or worse than a project with aROR of 40 percent and a 25-year life. Assumptions onre-investment can be made for the project with the shorter life to try to solve the problem; however, a bettermeasure of the relative desirability of investment opportunities is to calculate the discounted return oninvestment (DROl), as described in the next subsection,in which a constant discount rate is used.
The ROR is a good and commonly used hurdle forculling projects that are to be rejected from those thatare acceptable. In Canada, the minimum RORnormallyrequired would be in the range of 15 to 20 percent, using the after-tax cash flow, the most common minimumbeing 18 percent after taxes. The rate ofreturn requiredis a function of the cost of capital and the overall riskinvolved in investing in oil and gas.
Discounted Return on Investment
The discounted return on investment (DROl) is definedas the present worth value ofthe future income using anexternally- derived discount rate, divided by theinvestment, or:
present worthDROI= .
mvestment
This index is also known by many names including thediscounted profit-to-investment ratio (DPR), the presentworth ratio (PWR), and capital productivity index (CPI).
The discount rate that should be used is whatever themarketplace is using to determine the value of oiland gas assets. This rate is currently in the order of 12to 15 percent, applied to the after-tax cash flow stream;however, the rate will change as the following change:
Only those investments required prior to payout areincluded in the calculation of payout period. It isusually calculated using the before-tax cash flow.
Return on Investment
Return on investment (ROI) is also known as theundiscounted profit-to-investment ratio. It is simplydefined as the undiscounted net revenue (also called cashflow) divided by the initial investment. It has the serious disadvantage of ignoring the time value of money,but is still used by some in selecting suitable investments. It can draw attention to projects with short livesor unusual cash flow profiles if it yields a value that isnot in keeping with the other indices calculated.
The ROI may be calculated for a project requiringinvestment on either a gross basis (the investment is notincluded in the cash flow) or a net basis (the investmentis included in the cash flow). The normal procedure isto calculate the net ROI, but the gross ROI will be exactly 1.0 more than the net ROJ. A hurdle of $4.00 per$1.00 invested (ROI =4.0) is often used for the net ROI,but this may vary between companies. A net ROI ofless than 3.0 should raise questions about the desirability of an investment project.
The reason that the ROI is not recommended as a limiting index is that the cash flow profiles for oil industryinvestments usually vary significantly over their lives;consequently, the relationships between cash flow ineach year vary widely. In industries where the annualcash flow relationships from various projects remainrelatively constant, the time value of money may bedownplayed. This is not the case in the oil industry.
The ROI can be calculated using the gross cash flow(without deducting the investment), or the net cash flow(after deducting the investment), or the total investmentrequired, or only the initial investment, but there is noone "correct" way. The important thing is to calculateall ROIs in a particular company in the same way.
Rate of Return
In recent years, rate of return has been one of the morewidely used profitability indices and has been called bymany different names, including internal rate of return,internal yield, discounted rate ofreturn, discounted cashflow rate ofreturn, profitability index, and marginal efficiency ofcapital. In this chapter, the term rate ofreturn(ROR) will be used, and it is defined as the rate at whichthe future cash flow must be discounted to give a presentworth value that is equal to the investment. If the investment is included in the cash flow, then the definition
308
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USES OFRESERVES EVALUATIONS
the cost of capital, the perception of risk in forecastingprices, and the supply of and demand for properties.
The DROI is a very powerful index for the ranking ofinvestment opportunities. If the current marketplacederived discount rate is used, then the value of thenumerator in the DROI ratio represents the market valueof the investment being considered. The denominatoris the investment required to generate this value.Consequently, the index is the number of dollars ofasset value to be added per dollar of investment.
The DROI overcomes the problems inherent in the RORas a ranking tool since the same discount rate is used forall projects, and the discount rate is realistic.
If the investment is included in the cash flow stream(from which the value in the numerator is derived), thena value of zero indicates a rate of return equal to thatused to discount the cash flow. Any positive value indicates a rate ofreturn greater than the discount rate used.Conversely, a negative value indicates a rate of returnthat is less than the discount rate used and does notnecessarily indicate a loss.
Sometimes, the DROI is increased by \.0 ("DROI plus1.0") to calculate the index when the investment hasbeen included in the cash flow stream. In this way, theinvestment is removed from the cash flow stream, whichin effect is adding an amount equal to the denominator(the investment) to the numerator (the value). It is measuring the value of the asset after the investment hasbeen made as a function ofthe investment required. The"DROI plus 1.0" index is the multiplier to be applied tothe investment to give the value of the asset expected tobe developed as a result of the investment.
Ifthe "DROI plus \.0" index is used, then a result of \.0means that $\.00 ofvalue is being added for each $\.00spent. Ifthe value is greater than 1.0, then an asset withmore value than the investment being made is expected.Because there is some risk with most investments in theoil business, a DROI that is considerably greater thanzero ("DROI plus \.0" considerably greater than \.0)would usually be required before an investment wouldrank above other investment opportunities. Capitalavailabillity certainly sets the minimum DROI, but theusual range would be from \.0 to 3.0 (2.0 to 4.0 for"DROI plus \.0"). A low risk opportunity, such as thepurchase of producing reserves, would usually have aDROI of \.0, if the investment is not included in thenumerator; that is, the value ofthe asset acquired is equalto the investment.
The value in the numerator is the asset value and,therefore, all future investments must be included in thecash flow; however, there is some argument as towhether the investments used in the denominator shouldbe only those required to start the project or the total ofthe investments (suitably discounted) required duringits life. The DROI is used as a ranking tool and is usedto select projects for inclusion in the current budget and,for this reason, it can be argued that only the funds to bebudgeted to the star! of production should be used inthe denominator. Ifthis is correct, then the use ofall theinvestments (discounted, ofcourse) in the denominatorcould cause the rejection ofdesirable projects. This couldbe a serious problem with the use of the DROI.
It should be remembered that the DROI is the value ofthe asset added divided by the cost required to add thatasset. If the "DROI plus \.0" is used, then none of theinvestment in the denominator is included in the numerator, if only the investment to the start ofproductionis used as the divisor.
Net Present Value
The present value equation compares income and costsat time zero. Net present value (NPV) is equal to thepresent value calculated at a selected discount rateminus the investment.
Using Cash Flow Forecasts in InvestmentDecision-Making
When the value of an investment opportunity is beingdetermined, sunk costs are never taken into account. Ifthey are, the wrong investment decision may be made.An example ofthis would be the decision to complete awell uphole when the lower target is found to be dry.The well may have cost $1,000,000 to drill, but thecompletion of an uphole zone for $100,000 would addan asset worth $200,000. Ifthe sunk costs are included,a request to spend $1,I00,000 for a $200,000 asset wouldbe rejected. The correct request would be for $100,000to develop the $200,000 asset. At the end of the day, ifthe $100,000 is approved, the net out-of-pocket costwould be $900,000 ($1,000,000 plus $100,000 less$200,000), but if the additional $100,000 is not spentthen the cost would be $1,000,000.
Sunk costs cannot be recovered so they are neverincluded. Only future revenue and costs should beincluded in the basis for an investment decision.
An interesting down-side check on an investmentopportunity is to use trial and error to determine, usingconstant prices and costs, the minimum product price
309
that will yield an acceptable rate of return, usually 10percent after taxes, because ofthe use ofconstant pricesand costs. This test will give an indication of the sensitivity ofa project to price variations. If a project cannottolerate much reduction in price, it may be too risky topursue.
Most cash flow forecasts used to justify an investmentopportunity consider the incremental effect that the newproject will have on the total corporation. For this reason, only those incremental costs and revenues that resultfrom the project are included in the cash flow forecast.
General and administrative expenses (G&A) usually willnot increase as a result of the addition of the incremental charges created by a new project (such as a well orgas plant) and, therefore, no G&A costs are included.However, if the incremental charge being consideredwill result in increased or even decreased G&A charges,then these charges should be included in the cash flowforecasts.
There is an argument that some G&A should beincluded, ifnot in the first year, certainly after that time.While the current wells (excluding the incremental increase being contemplated) will meet the current G&A,the new project will be charged with its share in thefuture. Of course, those entities currently meeting theG&A cost will disappear with time and only the newinvestments will be available to meet the G&A. Thispoint should be considered, as ignoring future G&Acosts could present a more optimistic basis for a newincremental investment than is really justified.
It is important to note that charges for depreciation,depletion and amortization (DD&A), which are includedin financial statements, are noncash items and are, therefore, not included in the cash flow forecast. DD&A isan accounting means of charging the revenue streamwith a share of the capital required to generate the revenue stream. Any capital costs are included in the cashflow forecast in full at the time at which they areincurred.
26.3.2 Incremental EconomicsThis section does not refer to the incremental nature ofmost investment opportunities analyzed from a corporate perspective, but deals with the method that shouldbe used to evaluate an additional investment that mayenhance the performance of an existing project. Forinstance, a waterflood will increase the recovery froman existing pool as the result of additional investmentin injection wells and water-injection facilities.
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DETERMINAnON OF OIL AND GASRESERVES
How should the incremental effect of the additi I. bd ined? onainvestment e etermine .
The procedure is simple. A forecast of cash flow'd e h . if . ISprepare lor t e project 1 no mvestment is made (pri-
mary case). A cash flow forecast is then prepared fothe project ifthe investment is made (waterflood case)fwith the investment being included in the cash flow fore~
cast. In the next step, the cash flow for the primary caseis subtracted from the cash flow for the waterflood case.The resulting incremental cash flow provides the basisfor making the investment decision. Because the investment is included in the incremental cash flow forecast,the rate of' return is the discount rate which gives apresent worth value of zero.
Incremental investment opportunities often yield highrates of return.
The incremental annual cash flow determined bysubtracting one cash flow from the other will usually benegative for some of the life ofthe incremental project.This does not mean that the project is losing money andshould be discontinued, but that the upgraded project,after the investment, has lower cash flows in later yearsthan would have been the case had the incrementalinvestment not been made.
26.3.3 Acceleration ProjectsAn acceleration project is one in which an investmentis made, not to get any additional revenue, but merelyto get the same, or even a reduced, cash flow sooner:then on a discounted cash flow basis, the investmenthas the potential to earn a rate of return.
The big problem is that true acceleration projectsusually have at least two rates ofreturn. The investmentmade only brings the cash flow ahead. It does not addany extra cash flow and, in fact, the cash flow may beless through lower prices and higher costs. Coupledwith the'Tnvestment, this will result in a negativeundiscounted cash flow for the incremental acceleration investment. The investment required for theacceleration project is evaluated in the same way as anyincremental investment; the cash flow forecast for theproject without the investment is subtracted from thecash flow for the project if the investment is made.
As the discount rate is increased, the present worth valuegoes from negative to positive. Experience has shownthat this usually occurs at discount rates of 5 to IS percent. As the discount rate is further increased, the presentworth value continues to increase (the opposite of thenormal effect of discounting) until the discount rategenerally gets to the range of35 to 50 percent, at which
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USES OF RESERVES EVALUATIONS
point the present worth value begins to decline. Itreturns to zero at a discount rate usually in the order of100 to 300 percent. These general ranges do not applyto all projects.
By definition, the rate of return is the discount raterequired to give a present worth value of zero, whichoccurs usually between 5 and 15 percent and between100 and 300 percent; that is, there are two rates of return. Which is the "correct" rate ofreturn? Well, no onehas answered that question yet. One appears to be toolow and the other too high.
The only practical way to check an acceleration projectappears to be to determine its sensitivity to price reductions. Ifa small reduction in price results in no positivevalues for the discounted cash flow, then the projectmay not be worthwhile.
The problem is to make sure that an acceleration projectis recognized as such by the people making the analysisand the investment decision. If a present worth value ata selected discount rate is used as the ranking index (suchas a DROI at a 15 percent discount rate), an acceleration project might not qualify, but if a higher discountrate is used, the DROI would increase and the projectcould become acceptable. For this reason, all projects(whether acceleration or not) should have a profile ofpresent worth values calculated for a range of discountrates (usually from 0 to 50 percent), so that multiplerates of return and increasing present worth values withincreasing discount rates can be recognized.
Most acceleration projects are masked by the inclusionof additional cash flow with the accelerated cash flow;in fact, most incremental projects include an element ofacceleration. A waterflood project includes increasedrates of production (that is, acceleration) as well asadditional recovery of reserves,The most common acceleration project in Canada is onein which infill wells are drilled. Such an opportunitycould be a true acceleration project if it only results ingetting the same reserves sooner with the increased wellcount. Normally, there is also an increase in the reservesto be recovered and this will mask the acceleration aspects of the project. The main thing to remember is thatthe new wells will affect the production performanceand reserves to be recovered from the existing wells.For this reason, the economics of the new infill wellsshould never be looked at on a stand-alone basis. Theproject should be evaluated by looking at the performance ofthe total project without any infill drilling andsubtracting that cash flow from the cash flow that will
result from the total project when the infill wells aredrilled. This incremental cash flow is the way in whichthe investment should be analyzed.
26.4 USES OF THE VALUES DERIVEDFROM RESERVES ESTIMATES
26.4.1 Valuing Oil and Gas CompaniesThe assets ofan oil company consist of its inventory ofreserves of oil, gas and related products and its landholdings. The balance sheet of an oil company recordsthe value of the reserves and lands as the price paid toacquire or develop those assets. However, the price paidto develop reserves or purchase unexplored lands isunlikely to be an indication of their current value.
To overcome this problem, the value carried under"Property, Plant and Equipment" on the asset side ofthe balance sheet should be replaced with the going concern value of the remaining reserves and lands.Goingconcern value (GCV) is the value assigned to anasset that is already owned and that will be kept for future exploitation. It is not the value to be expected iftheasset is sold directly.
The determination of the GCV of reserves would bebased on a projection of future cash flow, using estimates of reserves and forecasts of production, costs,prices and royalties for each separate interest. These cashflows would then be summed and an after-tax calculation made, using not only future investments to protectincome from taxes, but also any unused tax pools heldby the company such as:
• Canadian exploration expense (CEE)
• Canadian development expense (CDE)
• Canadian oil and gas property expense (COGPE)
• Tangibles subject to capital cost allowance (CCA)
Any prepayments to be repaid in the future, and allabandonment and reclamation costs, would also be included in the cash flow forecasts. The after-tax cash flowdiscounted at an acceptable rate, currently between 12and 15 percent, would give the value to replace the remaining undepreciated investment carried under"Property, Plant and Equipment."
All future taxes and costs are included in the cash flowforecast, as well as any repayments of prepaymentsreceived, so the amounts carried as "Deferred Taxes,""Site Restoration Costs" and "Deferred Revenues" onthe liability side ofthe balance sheet should be removed.
The value of any unexplored lands would then bedetermined and added to the value of the reserves. No
311
where MV market value ($)GCV = going concern value ($)F = multiplier
In Alberta, where the current total tax rate is 44.34percent, the multipliers would be:
1.2711 for a 12 percent discount rate
1.2349 for a 15 percent discount rate
With the value of the COGPE adding 23 to 27 percentto the value of the reserves (or lands), it is too big to beignored. Similarly, if a COGPE is not created becausethe corporation, not the resource property, is purchased,a value that includes the COGPE will be far too high.These distinctions must be understood if the correctvalues are to be assigned.
The seller of properties that create a COGPE for thebuyer is required to take the total proceeds of the sale(not just the gain in value) into income for the purposeof calculating the taxable income in the year in whichthe sale occurs, and it is income that is not eligible forthe resource allowance; however, up to 100 percent ofany unused Canadian development expense or COGPEbalances may be used to offset the proceeds ofthe sale,in addition to 100 percent ofany unused CEE balances.Often a seller ofproperties will buy properties with approximately the same value before or in the same year asthe sale. Ip this way, he has a COGPE balance that hecan use to render the sale a tax-free event.
A complicating factor in the determination of MV isthe fact that part of the price paid is classified as theprice of the tangible assets (generally, the productionfacilities) acquired with the resource properties. Thesetangible assets can usually be written off at the rate of12.5 percent of the value in the year of acquisition andat 25 percent ofthe declining balance each yearthereafter. Some tangible assets are written off at other rates.The multiplier for this higher write-offrate would be inthe order of 1.32 to 1.38 for discount rates ofl5 and 12percent. The fraction of the total price considered to be
value would be assigned separately to the productionfacilities, such as gas plants and treating facilities, asthe value of these facilities is included in the value assigned to the reserves. The only time that a facilitywouldbe valued separately would be when the interest in thefacility is not the same as the interest in the reservesbeing processed through it.
The sum of all the assets less all the liabilities wouldthen give the GCV of the corporation. The value pershare would be this value divided by the number ofshares outstanding. This would be the basis used to makean offer to acquire an oil and gas company.
26.4.2 Sale of Resource PropertiesThe Canadian definition of resource properties forincome tax purposes includes oil and gas reserves (andthe wells to produce them) and unexplored lands. Thedirect purchase of resource properties (but not the purchase of the shares of a company that owns resourceproperties) creates a tax advantage for the buyer in theform of the Canadian oil and gas property expense(COGPE). This is equal to the price paid and may bewritten offat the rate of 10 percent ofthe declining balance each year against all taxable income from anysource.
The creation of the COGPE by the act of buying theresource property means that a buyer is acquiring twoincome streams, one from the production and sale ofthe oil or gas, and the other from the tax savings generated by the write-off of the COGPE. Because of thecompetitive nature of the marketplace, the buyer mustbe prepared to pay the full value ofboth the reserves (orpotential reserves in the case of unexplored lands) andthe COGPE, ifhe expects to acquire the property. Thisvalue would be described as the market value (MV) ofthe asset.
A term often used isfair market value (FMV) which isdefined as the price that a willing buyer would pay to awilling seller, ifneither is under any compulsion to buyor sell and both are competent and have reasonableknowledge ofthe facts. Because all of these limitationsare seldom met, the term market value (MY), rather thanfair market value, has been used.
The value of the COGPE is a function of the value ofthe reserves (or lands) and the write-off rate, tax rateand discount rate. Equation (I) gives the multiplier, F,to be applied to the value of the reserves (or lands) todetermine the value of both income streams (using midperiod discounting):
312
F= I
1-(WRxTR)x (I +i)'"'WR+i
where WR fractional write-off rateTR = fractional tax rate
= fractional discount rate
Thus MV GCVxF
0)
(2)
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USES OFRESERVES EVALUATIONS
for the purchase of tangible assets is negotiated by thebuyer and the seller, but the fraction must be reasonableto be acceptable to the taxman.
Because of the different tax consequences of a directpurchase and a purchase of a company owning oil andgas assets, it is not recommended that GCV and MV bedetermined from before-tax cash flows. The MV for oilreserves in Alberta is generally found to be equal to abefore-tax cash flow discounted at 20 percent (this isthe same value that would normally be determined bydiscounting the after-tax cash flow at 12 percent). InSaskatchewan, a cash flow before taxes from an oil property would have to be discounted at 25 to 30 percent,depending on whether the Crown royalty is new or old,to give a 12 percent after-tax rate of return. Similarly,the cash flow before taxes for gas properties in bothAlberta and Saskatchewan should be discounted at 18percent to give a value equal to the after-tax cash flowdiscounted at 12 percent.
If GCVs are to be based on before-tax cash flows, thediscount rate would range from 22 to 34 percent, depending on the province and royalty classification. It isdangerous to ignore taxes when determining the valuesof Canadian resource properties.
26.4.3 Evaluation of Unexplored Landsand Exploration Wells
The procedure for estimating the value of interests heldin unexplored lands by oil and gas companies starts bydetermining the value of discoveries of oil or gas reserves that could be made on each spread oflands. Afterthis value is determined, the probability of success isdetermined. Then, the cost of failure is estimated; theprobability of failure is equal to one minus the probability of success. The difference between the productof the value and probability of success and the productof the cost and probability of failure gives the riskweighted value, or expected monetary value (EMV) ofthe land on which oil or gas may be found. It must always be recognized that the prices at which lands thatare close to those being evaluated have traded may differ greatly from the value determined using thisprocedure because of variations in the geologicalprospects under the lands.
The value of success would be determined in the sameway that reserves are valued. The size of the reservesthat can be expected to be discovered would be estimated, the production forecast, and an after-tax cashflow forecast prepared and discounted as previouslydescribed. The cost of failure would be the cost ofa dry
hole, after taking into account the value of anytax advantages resulting from the expenditure.
The values of unproved properties are based on aftertax values and costs. Consequently, the value ofany taxadvantages to be gained by exploring for and developing reserves in the future is either included in the valuesassigned to the lands presently held or will be includedin the prices paid for lands that are acquired in the future. If the values assigned to the reserves ofa companyare based on the assumption that future investments inexploration and development will eliminate any tax payments on income from the production of the reserves,then the value of these future tax advantages will havebeen taken twice.
When unexplored lands are purchased, the price paidnot only represents the risk-weighted value these landsare expected to contribute, but also includes the valueof the COGPE created by the acquisition. Consequently, iflands already held are being evaluated, their valuewill be equal to the price currently set in the marketplace less the value of the COGPE, which can bedetermined using the formula set out in Section 26.4.2on the sale of resource properties. If the price paid inAlberta is $100 per acre, it would represent $78.70 forthe land and $21.30 for the COGPE if a 12 percent discount rate were used. These values would change to$81.00 and $19.00, respectively, with a 15 percentdiscount rate.
Exploratory wells would be evaluated in the samemanner. The value and probability ofsuccess would bedetermined and the cost offailure, after taxes, estimated.Then, the EMV would be calculated as the differencebetween the product ofthe value and probability ofsuccess and the product ofthe cost and probability offailure(i.e., one minus the probability of success), The EMVis the risk-weighted contribution the exploration wellcould be expected to make to the assets of the corporation, in excess ofthe investment required. If the exerciseis repeated frequently .and the probabilities of successare assessed realistically, then the sum of all the EMVsfor a year should be the level ofvalue ofthe assets addedby exploration in the year, in excess of the investmentrequired.
A possible index for ranking exploration wells wouldbe to divide the EMV by the after-tax dry hole cost.This is similar to the DROI (Section 26.3.1) and iscommonly referred to as the profit/risk capital ratio.
Another index that can be used for project ranking, theprofitability index (P/I), is calculated by dividing theEMV by the maximum capital exposure (present worth
313
c
value of total capital, after taxes), which indicates theexpected net dollar value to be received for eachafter-tax dollar of capital expended.
26.4.4 Lending and BorrowingFinancial institutions are permitted by law to take apledge of reserves and assignment of production proceeds as security for funds advancedto the productionowner.
The following discussion effectively assumes thata termloan is made available for a particular reserve. (In thecase of a company with diverse production interests,annual principal payments may not be required.)
To assess the maximum loan that can be secured byproduction, the lender may look at a series of values todeterminethe amountof the loan.A lendermay requirethe production offered as security to come from morethan one well, each of which has a productionhistory.Forecasts of reserves, production, and cash flow, usually supplementedby an independent engineer's report,are used by the lender.
The loan life is normally limited to no more than theperiodrequiredto recoverhalf thereserves (thereserveshalf-life), with the loan amount as a percentage of thediscountedvalue of production.
Loans secured by productionwould normallybe basedon reserveshalf-life witha maximum termthat is establishedby the lendingpolicyof the financial institutions.Reasons for including the reserves half-life are (I) toensure that when the loan is repaid, the property willstill have sufficient value that the borrower will lookafter it while repaying the loan, and (2) to ensure thatthe loan will still be repaid if the reserves estimate isnot accurate. If there is little value left when the loan isrepaid, the lender cannot expect the borrower to havemuch interest in the property.
When the amount and the term of the loan have beendetermined, the annual minimumprincipaland interestpayments are determined under different repaymentoptionsandpossiblyunderdifferent priceforecasts. Dueto the risk of changes in legislationand tax, anyAlbertaroyalty tax credit is calculatedseparately.
The price to be expected from a distressed sale of theproperties may be estimatedby the lender in a numberof ways. It may range from using 80 percent of theafter-tax cash flow discounted at 15 percent, with theCOGPEadded in, to taking 50 percentof thebefore-taxcash flow discounted at 15 percent. Whatever methodis used, the end result is a reasonably consistent
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DETERMINATION OFOIL AND GAS RESERVES
estimate of the price to be received under distr dditi essecon itions.
Lenders may ignore income taxes in determin'I di I" I mgen mg irmtsun ess the companyis fully taxablea dI . f i n aarge portion 0 Itstotal cash flow is being dedicated tloanrepayments. Underthese circumstances, the tax ~ligations of the company will be forecast, recogniz~ngthat all interestpayments would reduce the taxable i _come. It is realistic to assume that only the cash flo:after taxes would be available to repay principal.
Theactualloan size is negotiatedbetweentheborrowerand the lender, using the foregoing calculations as aguide.
26.4.5 Auditing EvaluationsFor manyyears,the industryhas attempted to introduceauditing techniques as the basis for an independentevaluatorto offeran opinionofthe reservesdeterminedinternally by a company. In the auditing of financialstatements, procedures are established and thencheckedto see if they are being followed by reviewing randomand material samples of the various financial transactions. If the samplesshowthat the procedures arebeingfollowed, then the financial statements, after adjustments, are considered to reflect the finances of thecompany.
The lack of the development of an equivalent systemfor reserves reportssuggests that theauditing proceduresused for financial accounts may not be applicable toreserves reports. Procedurescancertainlybe establishedand checked,but because of the need for interpretationofthe data in the estimationof reserves,the checking ofa sample could lead to an erroneous conclusion concerningthe accuracyofthe reservesestimates. It wouldbe very easy for a comparisonof a sampleto lead to theconclusion that the reserves should be half or doublethose determined by the companybecauseeachevaluator could interpret the available data differently.Of course, it would also be possible to agree afterreviewing a sample, but disagree significantly afterreviewing the total reserve base.
Because of this problem of interpretation leading todifferent answers using the same data by differentengineers who are both knowledgeable and objective,it is common for external evaluators, when asked toofferan objectiveopinionofthe reservesof a company,to independently evaluate the reserveswhich represent70 to 80 percent of the total reserves (or value) of thecompany. This would normally require 20 to 30percent of the properties in which the company has
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USES OFRESERVES EVALUATIONS
interests to be evaluated. The ratio of external tointernal reserves determined for the 70 to 80 percent ofthe reserves is then applied to the internal total to givethe order ofmagnitude ofreserves that the auditor wouldexpect to determine if he carried out a complete, independent evaluation. The anticipated difference shouldnot be more than plus or minus 10 percent, with a desired difference of less than plus or minus 5 percent.These are the differences that can be expected as theresult of interpretation by different evaluators. Differences in the total of greater than 10 percent wouldnormally require review and explanation.
No two evaluators will agree on the reserves for all ofthe properties ofa company, but the differences will behigher for some properties and lower for others so thatthe sum of all the estimates by each evaluator will usually be within the 10 percent range suggested. Twoevaluators will seldom estimate the same reserves for agiven property. The best opinion that can be expectedfrom an audit is that any differences would be within anacceptable range.
Attempts are still being made for external evaluators touse samples to develop an opinion ofthe "correctness"of the reserves estimates by company staff. This doesnot appear to have a statistically sound basis for drawing such a conclusion due to the need for datainterpretation.
It is a reality that no one can accurately predict thereserves that will be recovered from a well until it hasbeen abandoned. This lack ofprecision appears to limitthe use of audits based on small samples to arrive ata soundly based opinion of the accuracy of reservesestimates.
26.4.6 Securities ReportingThe agencies regulating public companies in both theUS and Canada require annual reporting ofreserves andmay require additional information on the future cashflows expected from those reserves. The US agency isthe Securities and Exchange Commission (SEC), andthe most important agency in Canada is the OntarioSecurities Commission (OSC), which regulates theToronto Stock Exchange on which a number ofCanadian companies are listed.
US Securities and Exchange Commission
The SEC requires companies listed on a US stockexchange to submit annual reports that include a reconciliation of the changes in the net (after royalties)remaining proved reserves of the company. Thisinformation is reported on SEC Form 10K and includes
the opening and closing net proved reserves volumes,together with an analysis of the change broken into thefollowing:
• Revisions
• Discoveries and extensions
• Purchases
• Sales
Production
Net proved developed reserves are also to be disclosed.
Form 10K also requires disclosure of the discountedfuture net cash flows, which are based on a forecast ofproduction from the proved reserves with constant pricesand constant costs and after deducting income taxes,using any remaining tax pools and all future investmentsrequired to produce the proved reserves. The discountrate used is 10 percent.
A quarterly report is also submitted to the SEC on Form10Q, but this report does not require reserves to be disclosed or the basis for the ceiling test, even though oneis required in the preparation ofthe financial statementsreported in Fonn IOQ.
Recently, the SEC has agreed to accept the disclosuremade to the Canadian equivalent ofthe SEC (generally,the OSC), instead ofFonn 10K, for companies listed inboth Canada and the US. The Canadian disclosure doesnot include a discounted cash flow; however, reconciliation to US accounting principles, including the ceilingtest, will be required at least to the end of 1993.
In a prospectus issued by an oil and gas company listedon a US exchange, net remaining proved reserves at adate generally within 12 months ofthe date of the prospectus must be included. Any material changes inreserves since their determination must be disclosed. Adiscounted cash flow, using constant prices and costs,after taxes, and at a discount rate of 10 percent, must beincluded.
The reserves reported in the prospectus must besupported by a detailed report on the determination ofthose reserves. The SEC does not require an independent reserve report; however, in practice, except for themajor companies, underwriters usually insist on anindependent report.
Ontario Securities Commission
The OSC requires an annual report in which the gross(before royalties) remaining proved reserves must beincluded. It includes the opening and closing balancesand a reconciliation that breaks the change in reserves
315
into the same five categories used for the report to theSEC.
A prospectus for an oil and gas company listed on theOSC must include a statement ofgross remaining provedand probable reserves at a date generally within 12months of the date of issue of the prospectus. Materialchanges in reserves, since their determination, must bedisclosed. The OSC also requires a discounted cash flow,after taxes, using constant prices and costs and a discount rate of 10 percent. A cash flow, after taxes, usingescalated prices and costs and higher discount rates mayalso be included, at the choice of the issuer.
The reserves reported in the prospectus must besupported by a detailed report on the determination ofthose reserves. The report must be prepared by a registered professional engineer, or a registered professionalgeologist, who is independent of the issuer of the prospectus, but in-house reports may be acceptable fromlarge, well-established companies at the discretion ofthe OSC.
26.4.7 Accounting RequirementsAccountants use reserve estimations and subsequentevaluations in preparing financial reports and audits. Themain uses of evaluations by accountants are for thepurposes of ceiling tests and depletion calculations.
Ceiling Tests
Two methods ofreporting the costs ofexploring for anddeveloping oil and gas reserves are available to corporations: "full-cost" accounting and "successfulefforts" accounting. In full-cost accounting, all costs associated with exploration and development arecapitalized and written off over the life of all the reserves in each country. With successful-effortsaccounting, only those investments in exploration anddevelopment that are successful in finding reserves arecapitalized and written off over the life of the reserveson a property-by-property basis; all costs ofunsuccessful wells are expensed in the year in which they occur.
Full-Cost Accounting
Full-cost accounting, presents a less conservative, butperhaps more accurate, picture of the financial resultsof a company. It is justified by the argument that allinvestments, both successful and unsuccessful, lead tothe development of the company's total "inventory" ofoil and gas reserves.
The users of full-cost accounting could experience a runof bad luck that results in costs which are greater than
316
~I:""" ':
DETERMINATION OF OIL AND GASRESERVES . .
the value of the reserves added or are even greater ththe total net income to be earned by producing the ::serves. To ensure that the balance sheet does tinclude highly overstated values for the company'sn~1and gas reserves, a "ceiling test" must be performedquarterly for US registered companies and at leastannually for Canadian registered companies. This testdetermines the maximum value that can be carriedfor the net cost of reserves under "Property, Plant andEquipment" on the balance sheet and, ifthe actual valuecarried is in excess of the ceiling test value, then theactual value must be written down to the ceiling testvalue. This is a one-way street, so that ifthe ceiling testvalue is greater, there is no change to the value carried.
In Canada, a company using full-cost accounting issubject to a ceiling test with a value based on a cashflow forecast prepared from the forecasts ofproductionfrom the proved reserves, using constant prices and costs.The company's estimated future interest and administrative costs and income taxes are deducted. Incometaxes take into account the remaining tax pools and anyfuture investments. The resulting undiscounted cashflow is then compared with the value of the net cost ofthe reserves carried on the balance sheet (less deferredincome taxes) and, ifthe cash flow is lower, then a writedown to the lower amount must be made. This ceilingtest is a cost-recovery test, as it limits the valueof the reserves on the balance sheet to no more thanthe net estimated cash flow to be recovered from theproduction of those reserves.
The constant price used may be either the price at theend of the reporting period or the average price for theperiod.
In the US, the ceiling test is a value comparison test forcompanies using full-cost accounting. The ceiling testvalue for a full-cost company is determined by takingthe estimates of proved reserves and forecasts of production for the company and preparing a cash flowforecast using constant prices and costs. This cash flow,after taxes, is then discounted at 10 percent per annumand, ifthe value carried for the net costs of the reserveson the balance sheet (less deferred income taxes) ismorethan this present worth value, a write-down to this valuemust be made.
It is a rough estimate of the value of the reserves, andthis constant price and cost-based cash flow, discountedat 10percent, must be reported in the annual report submitted to the SEC. The 10 percent discount rate usedrecognizes that inflation is not included in the cash flowforecast because constant prices and constant costs are
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USES OFRESERVES EVALUATIONS
used. The price used is that in effect on the last day ofthe reporting period.
The volatility of oil and gas prices over the last fiveyears has resulted in significant write-downs, especiallyin the US where the price to be used must be the priceon the last day of the reporting period and the ceilingtest must be applied quarterly. A very low price at theend ofone period can cause an extreme write-down thatcan never be recovered even if prices bounce back infuture quarters.
Successful-Efforts Accounting
Canadian and US companies using successful effortsaccounting are subject to a ceiling test, but the constantprice, constant cost cash flow used is not discounted orreduced by any interest, administrative, or income taxcosts.
In both Canada and the US, unproven properties areincluded in the ceiling test value. The value included isthe cost, reduced by any impairment of value due toeither exploration on the lands or to declines in marketvalues.
Depletion Calculations
Accountants also employ estimates of proved reservesas the most commonly used method of amortizingor writing off the cost of capital investments.This "depletion" calculation divides the remainingundepleted or undepreciated capital costs by the remaining reserves to determine a depletion rate. These netcapital costs are depleted (that is, reduced) by the product of the production during the depletion period andthe depletion rate. In this way, all the capital costs arewritten offby the time the last production is received.
To calculate the depletion rate and charge, all thereserves and production must be converted to the sameunits, usually barrels of oil equivalent (BOE), whichmust be based on either heating values (6 x 103 cf perBOE) or relative selling prices. Having determined therate per BOE, then the rate per barrel of oil and perthousand cubic feet of gas can be back-calculated.
The depletion charge is calculated at the end of theperiod, using the remaining net investment, and beforethe current period charge for depletion and remainingproved reserves plus production for the period are calculated.Depletion is usually calculated on a quarterlybasis,and the annual charge is the sum of the quarters. Thedepletion calculation must be updated whenever thereis a material change to the rate, as a result of either newinvestment or changes in reserves quantities.
26.4.8 Establishing Finding andReplacement Costs
One of the important uses of estimates of reserves is indetermining the average cost of replacing reserves. Itmust be determined whether the exploration and development expenditures are adding reserves for a cost thatis less than or equal to their value. Ifthe cost ofreservesadditions is in excess of their value, then the companywill not be making a rate of return that is equal to orgreater than the discount rate used to determine value.
The finding cost that is often calculated as a measure ofexploration success is determined by dividing the exploration costs by the proved reserves discovered. Acalculation that only includes exploration costs gives acompletely useless (and possibly misleading) result asdiscovered reserves are of no use until they are fullydeveloped. The cost ofa fully developed unit of reservesranges from 1.3 to 3.0 times the cost of finding the reserves. For this reason, a low finding cost could lead tothe mistaken conclusion that the exploration programwas successful even though the fully developed cost wasin excess of the value of the reserves added. The opposite is also true, where high exploration costs mightindicate an apparent lack of success, but low development costs, in fact, develop reserves with a cost that isless than their value.
Only replacement costs give a useful measure ofsuccess. They are calculated by dividing the totalof all exploration and development costs (including allplants and production facilities) by the proved reservesadded. The reserves other than oil would be convertedto barrels of oil equivalent (BOE) to make this calculation. This conversion is discussed in Section 26.4.9.Replacement costs are calculated on before-tax costs,but values are based on after-tax calculations. Using amix of tax write-offs for an average program of exploration and development, the after-tax cost ofreplacementwould be in the order of 65 percent of the before-taxcost for a company that can use all the tax write-offs.The current average going concern values of oil andgas reserves in Alberta are approximately $7.00 perbarrel and $0.35 per thousand cubic feet. This meansthat the before-tax replacement cost ofreserves must beless than $10.00 per barrel and $0.55 per thousandcubic feet if a rate of return of 12percent is to be earned,after taxes. In recent years, only 60 percent of thecompaniesdevelopingreserves in Canada have been able.to add reserves at costs that are this low.
Proved reserves may be added before all the costs ofdevelopment have been incurred or may be added after
317
7
the investments are made, such as with enhancedrecovery schemes. Because costs and reserves additionsmay be out of synchronization, it is preferable to calculate replacement costs on a three- to five-year rollingaverage.
Studies have shown that annual replacement costs for acompany can range from $4.00 per barrel one year to$280.00 per barrel the next year, while on a five-yearrolling average, the costs are $10.00 per barrel, whichmeans that the company is earning an acceptable rate ofreturn. If replacement costs are higher than values foran extended period, it is an indication that serious financial problems will probably develop for the companysome time in the future.
The average values set out in the foregoing discussionmay not be applicable to reserves added by particularcompanies; consequently, the actual value ofthe reservesadded by a company should be determined in detail forcomparison with the replacement cost.
26.4.9 Estimating Barrels of OilEquivalent
From time to time, it becomes necessary to divide costsamong reserves of oil, gas and related products, or toreport reserves ofoil, gas and related products asa common unit. This is done by converting reserves that arenot oil to barrels of oil equivalent (BOE).
Often the reason for the conversion is not understoodand, therefore, the conversion is made incorrectly.Conversions to BOE are. usually made for one of thefollowing reasons:
1. To calculate the depletion charges used to write offthe investment in reserves
2. To report reserves volumes using a common unit
3. To calculate the replacement cost per unit ofreservesadded
4. To calculate the acquisition cost per unit ofreservespurchased
The conversion for the first reason must use eitherheating value (6 x 103 cf per BOE) or relative sellingprices, as established by accounting principles. Each ofthe other three reasons is for the purpose of making avalue comparison and, therefore, conversions based onthe relative values of the reserves to be converted compared to the value of oil reserves should be used, ifpossible. Energy equivalence should not be used forthe purpose ofvalue conversion, as energy equivalenceis only of significance at the burner tip. It costsapproximately five times as much to move a unit of
318
DETERMINATION OF OIL AND GASRESERVES
energy as gas from the well.head to the burner tip as itcosts to move the same unit of energy as oil. Conse_quently, the value at the wellhead (or in the ground) isin no way related to energy content.
The energy equivalent often (but incorrectly) used is6 x 103 cf per BOE, but it actually ranges from about5.8 x 103 cf per BOE for light oil to approximately6.3 x 103 cfper ~OE for hea~ oil. The.use of energycontent as the basis for conversion can give misleadingresults which, in turn, could lead to wrong decisionsabout success and value. It is recommended thatthis BOE never be used for the purpose of valueconversion.
Because most conversions to BOE are for the purposeofvalue comparison, the values of oil and gas reservesshould be used to calculate the conversion ratio.Currently, "average" values for fully developed reserves of oil and gas in Alberta are in the order of $7.00per barrel and $0.35 per thousand cubic feet. Thisgives a conversion ratio of 20 x 103 cf per BOE. Theequivalent barrel of oil is a barrel oflight oil.
The value-based conversion rates have varied as shownin Table 26.4-1 over the last eight years for "average"reserves. No company owns average reserves, so thatthe conversion rate for a particular company could behigher or lower, depending on the actual reserves owned.
Table 26.4-1 Conversion Rates
Year BOE(103 cf/stb)
1984 201985 171986 171987 181988 16
~1989 141990 161991 20
Price is not the most desirable basis for determiningconversion to BOE, as the cost of producing energy inthe form ofgas is usually different per dollar of incomethan the cost of producing oil. Therefore, value, whichis the difference between price and cost, will usuallyyield conversion rates that are different from those basedsolely on price. If values are available, they are to bepreferred; however, values are not generally availablefor related plant products and, therefore, price providesthe only useful way to convert reserves of ethane,propane, butanes, pentanes plus and sulphur to BOE.
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Conversion Factors
USES OF RESERVES EVALUAnONS
Example
Reserves ofcrude oil, gas and related products as shownin the following table were purchased several years agofor $197.8 million.
Reserves Purchases
ProductWellhead
PriceConversion to BOEValue-Equivalence(Crude Oil PriceIProduct Price)
What did this price represent in the way of value perunit of reserves? At the time, the conversion of gas toBOE on a value-equivalence basis was 14 x 103 cf ofgas for each barrel of oil. No value data was availablefor the related gas products, so the wellhead price hadto be used to determine the conversion ratios. At thetime, the prices shown in the table ofconversion factorswere in effect.
Using these conversion factors, with the conversionfactor of 14 x 103 cfper BOE for gas and the reservesset out earlier, the total reserves in barrels of oil
Company InterestGross Reserves
(before deducting royalties)
equivalent were calculated. These are shown in thefollowing table.
By using the BOE at 23,966,233 barrels and thepurchase price at $197.8 million, the value paid per BOEwas $8.25 per BOE. The purchase price can be allocated to each product to determine the respective valueper unit of reserves. The table on the next page showsthe value per unit of reserves.
The assignment of value is extremely sensitive to theconversion ofother products to BOE. Ifthe price equivalence for gas had been used instead of the valueequivalence to convert to BOE, the conversion factorwould have been 12 x 103 cf per BOE and the pricepaid for the crude oil reserves would be reduced from$8.25 per barrel to $7.65 per barrel, but the price paidfor the gas reserves would be increased from $0.59 to$0.64 per thousand cubic feet.
Product
Crude oilNaturalgasEthanePropaneButanesPentanesplusSulphur
8,200,000165,400740,000610,000370,000670,000670,000
bblX 10' cf
bblbblbblbbl
It
CrudeoilEthanePropaneButanesPentanes plusSulphur
$19.70/bbl7.00/bbl7.50/bbl
11.50/bbl19.50/bbl75.00/1t
2.812.631.711.010.26
Total Reserves in Barrels of Oil Equivalent
(1) (2) Barrels of OilProduct Company Conversion Equivalent
Interest toBOE (BOE)Reserves Col (1) + Col (2)
Crude oil 8,200,000 bbl 1.00 8,200,000Naturalgas 165,400,000 x 10' cf 14.00x 10' ef/BOE 11,814,286Ethane 740,000 bbl 2.81 bbl/BOE 263,345Propane 610,000 bbl 2.63 bbl/BOE 231,939Butanes 370,000 bbl 1.71 bbllBOE 216,374Pentanes plus 670,000 bbl 1.01 bbl/BOE 663,366Sulphur 670,000 It 0.26 It/BOE 2,576,923
Total 23,966,233
319
iM
DETERMINATION OF OIL ANDGAS RESERVES
Value per Unit of Reserves
Product ROE Purchase Company ValuePrice Interest Per Unit
of Reserves Reserves
Crudeoil 8,200,000 $67,676,885 8,200,000 bbl 8.25/bblNatural gas 11,814,286 97,506,595 165,499,000 x 10' cf 0.59/10' cfEthane 263,345 2,173,460 740,000bbl 2.94/bblPropane 231,939 1,914,257 610,000bbl 3.14/bblButanes 216,374 1,785,795 370,000bbl 4.83/bblPentanes plus 663,366 5,474,944 670,000bbl 8.17/bblSulphur 2,576,923 21,268,064 670,000It 31.74/lt
Total 23,966,233 $197,800,000
il'1
Although it has no relevance except at the burner tip,the energy equivalence is used from time to time to convert reserves of gas to BOE. The equivalence used isusually 6 x 10' cfper BOE. Ifthis had been used in thiscase, the price paid for the oil reserves would bereduced from $8.25 per barrel to $5.00 per barrel, butthe price paid for the gas reserves would be increasedfrom $0.59 to $0.83 per thousand cubic feet. This isquite an unrealistic assignment of the price paid to thedifferent reserves.
If the values for related products were included withthe value of the natural gas, then the value of the gasand related products at $130,123, 115 ($197,800,000 lessthe value of oil at $67,676,885) divided by the naturalgas reserves of 165,400,000 x I OJ cfwould yield a unitvalue of$0.79 per thousand cubic feet.
These values are market values, not going concernvalues, as the value ofthe COGPE created by the directpurchase was included in the price paid.
It is easy to understand why reserves quoted in BOEthat are calculated using a conversion of 6 x 10J cfperBOE would vastly overstate the apparent reserves ofthe company, when the conversion should have beenbased on a conversion rate of 20 x 10J cf per BOE.Reserves are usually used as a proxy for value and theuse of a 6 to I conversion ratio, instead of a 20 to Iconversion ratio, will yield gas reserves in BOE that aremore than three times what they should be.
Conversions to BOE are really being made to barrels oflight oil equivalent. Because reserves of medium and
320
heavy oil have values which may be only 25 percent (orless) of the value of a barrel of light oil, it is perhapstime for the industry to break out oil reserves into light,medium and heavy categories, or convert medium andheavy oil reserves to "barrels oflight oil equivalent," asa better indication of the real value of the inventory ofoil and gas reserves.
26.4.10 Estimating Net-Back CalculationsA calculation used from time to time takes the pricereceived for a unit ofproduction at a particular time anddeducts from it all production costs, royalties, and taxesto give the net-back to the producer from each barrel orthousand cubic feet. This net-back calculation is a dangerous way to identify value or to determine the effectof changes in price, costs, royalties or taxes.
A net-back calculation only looks at the situation at onetime and ignores anything that may occur at some othertime. It is also difficult, if not impossible, to make realistic tax calculations because the write-off of tax poolsis not a function of a unit of production. Net-backcalculations ignore changes in the future in productionrates, royalties and operating costs and also ignore anycapital costs.
A net-back calculation merely looks at the revenue perunit of production at a particular time and some of thecosts at that time. For this reason, the results can bemanipulated to give the answer being sought. It is a poormeasure of what is likely to happen over a period oftime and, consequently, is not recommended as a usefulbasis for making investment decisions.
BIOGRAPHIES OF AUTHORS
Complete namesof technical societies are given in the Acronyms.
Dr. Roberto Aguilera- B.Sc., Petroleum Engineering, Universidad de
America, Bogota, Colombia; M.Eng. and Ph.D.,Colorado School of Mines, Golden, CO
- Currently, President, Servipetrol Ltd.
- Authorof Naturally FracturedReservoirs andco-author of The Technology ofArtificialLiflMethods and Horizontal Wells, and papers intechnical journals
- International lectureron naturallyfracturedreservoirs
- Memberof AAPG, ACIPET, APEGGA, CWLS,Petroleum Society of CIM, SPE, SPWLA; pastDirectorof Petroleum Society, Calgary Section
Dr. Soheil Asgarpour- B.Sc., Mechanical Engineering, Tehran
University, Tehran, Iran; Ph.D., Rice University,Houston, TX
- Currently, Technical Leader of Northern Albertaand BritishColumbia Group, Gulf CanadaResources Limited
- Authorof over 35 technicalpapers on heattransfer, solarenergy, reservoirengineering,enhanced oil recovery, production engineering,and risk analysis
- Memberof APEGGA, Petroleum Society ofCIM, PNA, SPE;National DirectorofPetroleum Societyof CIM since 1990; Chairmanof Editorial Board of JCPT 1991-1993
BarryR. Ashton- B.Sc., Chemical Engineering, University of
Alberta, Edmonton, AB
- Currently, SeniorPartner, Ashton JenkinsandAssociates Ltd., which specializes in reservoirstudies and reserve evaluations
- Experience includes Chairman of ReserveEvaluation Committee of Encor Inc. as part ofthe $1 billionproperty rationalization agreementreached between Encor, Amoco Canada,andMaligne Resources in 1992
- Member of APEGGA, SPE, PetroleumSocietyofCIM
Dr. Anthony D. Au- Ph.D.,ComputerScience,University of Utah,
Salt LakeCity, UT- Currently, Vice-President, Servipetrol Ltd._ Specialties include fractured reservoirs and
reservoir simulation- Co-author of over 20 technicalpapers on
reservoir simulation technology- Memberof APEGGA, PetroleumSocietyof
CIM, SPE; Directorof PetroleumSocietyof CIM
C. BrentAustin- B.E.,Mining Engineering, Technical University
of Nova Scotia, Halifax, NS- Currently, Advisor, Petrophysics, PanCanadian
Petroleum Limited_ Experience includes international consulting in
areasofformation evaluation and economicanalysis
- Memberof APEGGA, CanadianInstituteof Management, Petroleum Society of CIM,SPWLA
321
l
N. Guy Berndtsson
· B.Sc., Chemical Engineering, University ofAlberta, Edmonton, AB
• Currently, Board Member, Energy ResourcesConservation Board
- Experience includes formation evaluation and oiland gas reserves determination
· Co-author and presenter of technical papers oncrude oil reserves, enhanced recovery techniquesand economics, water and waste disposal wells,and well servicing
• Member of APEGGA, Petroleum Society ofCIM, Technical Advisory Committee for thePetroleum Recovery Institute
Robin G. Bertram
- B.Sc., Petroleum Engineering, University ofAlberta, Edmonton, AB
· Currently, Operations Engineer, TalismanEnergy Inc.
• Experience includes formation evaluation, oiland gas reserves determination, and projectmanagement
- Member ofAPEGGA, Petroleum Society ofCIM, SPE
Janusz Bielecki
• Masters Degrees in Energy Economics,University of Calgary, Calgary, AB, andInternational Law, University of Warsaw, Poland
· Currently, evaluator of supply costs and theimpact of new technologies (i.e., horizontaldrilling) on petroleum reserves and supply,National Energy Board
Experience in economic evaluation, marketanalysis, price and supply forecasting, energyregulation and strategic planning
- Member of International Association of EnergyEconomists
322
'''-1DETERMINAnON OFOILANDGASRESERVES I
Keith M. Braaten
· B.Sc., Mechanical Engineering(Distinction), University of Saskatchewan,Saskatoon, SK
· Currently, Technical Consultant and PartnerColes Gilbert Associates Ltd. '
• Specialties include reservoir engineering andeconomic studies of secondary and tertiaryenhanced oil recovery schemes, fracturedreservoirs, gas cycling schemes, heavy oilreservoirs, and shallow gas reserves
• Member ofAPEGGA, Petroleum Society ofCIM, SPE
Keith D. Brown
· B. Chern. Eng., Technical University ofNovaScotia, Halifax, NS
• Currently, Manager, Oil and Gas Evaluations,Royal Bank of Canada, directing the technicalevaluation of the bank's energy portfolio
• Experience includes gas processing, construction,and economic evaluations
· Member of APEGGA
Mike J. Brusset
• B.Sc., Geological Engineering, University ofOklahoma, Norman, OK
• Currently, President, Brusset Consultants Ltd.
• Specialties include formation evaluation, oil andgas reservoir performance studies, and economicevaluations of oil and gas reserves
· Lecturer for 13 years on economic evaluationsin petroleum exploration and engineering atU ofC
• Member ofAPEGGA, Petroleum Society of CIM
s
- B.Sc., Geology, University of Alberta,Edmonton, AB
- Currently, Executive Vice-President, SprouleAssociates Limited
- Specialties include geological interpretation ofoil and gas reservoirs, reserves estimates, andanalysis of exploration prospects based onassessmant of geological risk and economicevaluation
- Co-author of papers and course notes onsubsurface mapping of oil and gas reservoirs,potential oil and gas resources, economicevaluation and risk analysis of Canadian oil andgasproperties
- Member ofAPEGGA, CSPG, Petroleum SocietyofCIM
Graham R. Campbell
- B.Sc., Physics, University of Waterloo,Waterloo, ON; M.Sc., University of BritishColumbia, Vancouver, BC
- Currently, Director-General, Energy Resources,National Energy Board, responsible for assessment of Canada's oil and gas supply, monitoringof upstream industry activity and new resourceextraction technologies, and regulation ofgeological and geophysical activities in the north
- Member of AAPG, APEGGA
Noel A. Cleland
- B.E. (Honours), Mining Engineering, Universityof Sydney, Australia
- Currently, Senior Engineering Consultant andDirector, Sproule Associates Limited
- Author ofpapers on petroleum economics andthe Canadian petroleum industry and lecturer onpetroleum economics at U. of C.
- Member of APEGGA, Austro-Asian Institute ofMining and Metallurgy, Petroleum Society ofCIM, SPEE; Past President of APEGGA
- Recipient ofFrank Spragins Award fromAPEGGA in 1990, and Petroleum Society'sDistinguished Service Award in 1984; CIMDistinguished Lecturer in 1974
- B.Sc., Mineral Engineering (Petroleum) andMBA, University of Alberta, Edmonton, AB
- Currently, Director, Natural Gas BusinessCentre, Shell Canada Limited, responsible fornatural gas marketing and business developmentactivity
- Experience includes technical and managerialpositions in petroleum engineering, as well asassignments in economics and corporatestrategies
- Member of APEGGA, Petroleum Society ofCIM, SPE
G.J. (Gerry) DeSorcy
- B.Sc., Petroleum Engineering, University ofAlberta, Edmonton, AB
- Currently, Energy Consultant
- Formerly, first Chairman of Alberta NaturalResources Conservation Board, and previously,Manager of Gas Department, Board Member,and Chairman, Alberta Energy ResourcesConservation Board
- Member of APEGGA, Petroleum Society of CIM
John Drury
- B.A., Honours Science, University of Toronto,Toronto, ON
- Currently, independent consultant and technicalconsultant to the Ontario Securities Commission
- Experience includes mining geology and theregulatory industry
- Member of APEO, CSEG, GAC; Life Member ofCIM
Dr. David C. Elliott
- B.Sc. and Ph.D., Geology, University ofBirmingham, U.K.; B.Math., University ofWaterloo, Waterloo, ON
- Currently, Consultant, Geosgil Consulting
- Experience includes oil and gas field develop-ment in Canada and overseas; statistical,geostatistical and mathematical applications
- Member of AAPG, APEGGA, CSPG, GeologicalSociety (UK), IAMG, Petroleum Society of CIM
323
Robert V. Etcheverry
- B.Sc., Mechanical Engineering, University ofSaskatchewan, Saskatoon, SK
- Currently, General Manager, Production andEngineering, CN Exploration Inc.
- Experience includes technical, research, supervisory, and managerial positions in the oil andgas industry in Canada and the US
- Member of Petroleum Society ofCIM, PNA,SPE; Director, Calgary Section, PetroleumSociety of CIM
Merlin B. Field
- B.Sc., Petroleum Engineering, OklahomaUniversity, Norman, OK
- Currently, Consulting Reservoir Engineer
- Specialties include petroleum propertyoptimization, project evaluations, numericalsimulation, computer applications, andenhanced recovery
- Member of APEGGA, SPE
RonM. Fish
- B.Sc., Geological Engineering, University ofManitoba, Winnipeg, MB
- Currently, Reservoir Engineering Advisor, NewPool Development Group, Imperial Oil Limited,Resources Division
- Experience includes reservoir engineering,production engineering, development, operations,research and oil sands
- Member of APEGGA
J.D. (Joe) Giegerich
- B.Sc., Mining Engineering, University of BritishColumbia, Vancouver, BC
- Currently, retired from Chevron CanadaResources
- Experience includes drilling, production, andreservoir engineering, and estimating hydrocarbon reserves
- Member of APEGGA, Petroleum Society ofCIM; past Chairman, Edmonton Section andtwo-term Director, Petroleum Society of CIM
324
Mam Chand Gupta
B.Sc. and M:Sc., Physical Chemistry, Universityof Agra, India; D.LC., all Technology andM.Sc., Petroleum Reservoir Engineering,Imperial College, University of London, LondonUK '
- Currently, President and Consultant, GMInternational Oil and Gas ConsultingCorporation
- Experience includes supervisory, advisory andtechnical positions in reserves determinationformation evaluation, oil and gas well testing, oiland gas field development, enhanced oil and gasrecovery studies, economic evaluation, oil andgas property evaluation
Instructor of drilling and production engineeringcourses at SAlT and U. of C.
Co-author of one technical paper
- Member of APEGGA, Petroleum Society of CIM
Dave Hemphill
- B.Sc., Mining Engineering, University ofAlberta, Edmonton, AB
- Currently, Petroleum Engineering, Shell CanadaLimited
- Experience includes uranium mining industry,development geology, oil and gas reservesdefinition, and field development optirriization
- Member of APEGGA, CSPG, SPE
John M. Hewitt
- M.A., Mechanical Science, Queens' College,Cambridge University, UK
Currently, Consulting Partner, Martin Petroleum& Associates
Experience includes oil and gas property andcompany evaluations, reserves determination,reservoir engineering and enhanced recoverystudies, royalty and regulatory problems, government presentations, and acquisition analysis
- Member of APEGGA
--------------------------d
BIOGRAPHIES OFAUTHORS
William E. (Bill) Kerr
- B.Sc. (Honors), Petroleum Engineering,University of Wyoming, Laramie, WY
Currently, Operations Manager, Joss Energy
Experience includes production, operations,drilling, reservoir, evaluations, and enhancedrecovery
- Member ofAPEGGA, Petroleum Society ofCIM, SPE
Harold R. Keushnig
- B.Sc., Chemical Engineering, University ofAlberta, Edmonton, AB
- Currently, Manager, Gas Department, AlbertaEnergy Resources Conservation Board, responsible for well spacing, reservoir recovery andrecovery estimation, conservation, processing,and removal of gas from the province
Member of APEGGA, CGPA, CanadianPotential Gas Committee, Petroleum Society ofCIM
Gobi Kular
- B.Sc., Petroleum Engineering, University ofMontana, Missoula, MT; course work towardM.Sc., University of Calgary, Calgary, AB
- Currently, President, Advanced PetroleumTechnologies
- Experience includes international consulting onmajor reservoir studies in Canada, North Africaand the Middle East
- Author and presenter of several technical paperson pressure transient well-test design and analysis, fracture design, project monitoring, andenhanced oil recovery
- Member ofAPEGGA, Petroleum Society ofCIM, SPE
Craig F. Lamb
- B.Sc. and M.Sc., Geology, University ofManitoba, Winnipeg, MB; M.B.A., University ofCalgary, Calgary, AB
- Currently, President of Lonach Consulting Ltd.
- Specialities include core analysis, fracturedreservoir studies, design of technical trainingprograms, and geoscience management
- Author ofnine publications
- Member of AAPG, APEGGA, CSPG, PetroleumSociety of CIM, SCA
R.V. (Bob) Lang
- B.Sc., Chemical Engineering, University ofAlberta, Edmonton, AB
- Currently, independent petroleum consultant
- Specialties include reserves determination andreserves reporting
- Member ofAPEGGA, Petroleum Society ofCIM, SPE
- Recipient of two merit awards from CPA, oneservice award from AGA
Dana B. Laustsen
- B.Sc. (Distinction), Mechanical Engineering,University of Calgary, Calgary, AB
- Currently, Consultant and Director, Coles GilbertAssociates Ltd.
- Specialties include economic analyses andreservoir engineering studies of waterfloodoptimization, miscible flood performance, gasstorage, and tight gas deliverability models
- Member of APEGGA, Petroleum Society of CIM
William V. Mandolidis
- B. Applied Science and Chemical Engineering,University of Toronto, Toronto, ON
- Currently, Coordinator, Corporate Planning andBusiness Development, Saskatchewan Oil andGas Corp.
- Experience includes surface and subsurfacepetroleum engineering, reserves evaluation andreporting, economic and business analysis, andcorporate strategy development
- Member of APEGGA, Petroleum Society of CIM
325
Michael E. McCormack
- B.Sc., Chemical Engineering, University ofCalgary, Calgary, AB
- Currently, Founder and Consultant, FracticalSolutions Inc.
- Specialties include the application of fractalmathematics and computer solutions to petroleum engineering problems, fluid dynamics,heat transfer, well design, and surface facilitiesoptimization
- Author and presenter of several papers on wellengineering
Member of APEGGA, Petroleum Society ofCIM, SPE
Raymond A. Mireault
- B.Sc., Agricultural Engineering, University ofManitoba, Winnipeg, MB
· Currently, Senior Engineer, Southern BusinessUnit, Reserves Additions Team, Gulf CanadaResources Limited
• Experience includes conventional oil and gasexploration, development and production, coalbed methane, horizontal drilling, and super sourgas
· Member ofAPEGGA, CSEG, CSPG, PetroleumSociety of CIM
Margaret Nielsen
- B.sc., Mechanical Engineering, University ofAlberta, Edmonton, AB
· Currently, Business Planning and Performance,Petro-Canada
· Experience includes evaluating and developinggas, oil and heavy oil reserves under primaryrecovery, waterfloods, cycling schemes, misciblefloods, and fire floods.
· Member of APEGGA
326
David C. Poon
- M.Sc., Chemical Engineering, University ofCalgary, Calgary, AB
· Currently, Engineering Consultant, D.C. PoonConsulting Inc.
· Specialities include geostatistics, reservoirsimulation, well testing, and horizontal wells
• International lecturer on enhanced oil recovery,thermal well testing, and water management
- Member of APEGGA, CHOA, CSChE,Petroleum Society of CIM, SPE
- Recipient ofbest paper award in 1990 fromPetroleum Society of CIM
Dr. Ross A. Purvis
· B.Sc., University of Oklahoma, Norman, OK;M.Sc., University ofWyoming, Laramie, WY;Ph.D., University of Alberta, Edmonton, AB
- Currently, Manager, Oil Department, EnergyResources Conservation Board
- Experience includes production engineering andthe development of technical software for phasebehavior, petrophysics, decline curve, and otherreservoir engineering applications, and teaching
- Member of APEGGA, Petroleum Society ofCIM, SPE
Tim J. Reimer
· B.Sc., Chemical Engineering, University ofCalgary, Calgary, AB
- Currently, Manager, Gas Contracts and Supply,Pan Alberta Gas Ltd.
· Experience includes gas plant design andoperations, joint interest, economic evaluations,exploitation and development.
- Member of APEGGA, CGPA, Petroleum SocietyofCIM,PNA
W.D. (Bill) Robertson_ B.Comm., University of Alberta, Edmonton, AB
_ Currently, Co-Chairman and Partner, Oil and GasIndustry Specialist Group, Price Waterhouse
· Specialty is oil and gas accounting
- Member of Petroleum Society of CIM; pastDirector and Officer, Petroleum Accountants'Society; Council Member, Institute of CharteredAccountants of Alberta
------------------_.~
BIOGRAPHIES OFAUTHORS
J. Glenn Robinson
- B.Sc. (Honours), Civil Engineering, Queen'sUniversity, Kingston, ON
- Currently, President, Sproule Associates Limited
- Experience includes exploitation engineering,production geology, petrophysical engineering,reservoir engineering, mathematical reservoirsimulation, economic evaluations, and riskanalysis
- Lecturer on evaluation and risk analysis ofCanadian oil and gas properties
- Member of APEGGA, CWLS, Petroleum Societyof CIM, SPE, SPEE, SPWLA
Darlene A. Sheldon
- M.Sc., Statistics and M.Eng., ChemicalEngineering, University of Calgary, Calgary, AB
- Currently, Manager, Strategic Action Planning,Petro-Canada
- Experience includes reservoir engineering, oiland gas development and evaluations,information systems, economics, and assetrationalization
- Author ofthree technical papers
Member of AWES, Petroleum Society of CIM,SPE
Dr. Phillip M. Sigmund
- B.A.Sc., Chemical Engineering, University ofWaterloo, Waterloo, ON; Ph.D., ChemicalEngineering, University of Texas, Austin, TX
- Currently, designing specialty oil extractionprocesses and building associated researchequipment
- Experience includes contract research andconsulting projects related to improved reservoirmanagement and fluid extraction processes
- Author of several technical papers
- Member of AIChE, APEGGA, PetroleumSociety of CIM
Dr. Ashok K. Singhal
- Ph.D., Petroleum Engineering, University ofCalifornia, Berkley, CA
- Currently, Group Leader, Gas Flooding,Petroleum Recovery Institute, Calgary, AB
- Experience includes horizontal well applications,enhanced oil recovery, and reservoir engineering
- Member ofAPEGGA, Petroleum Society ofCIM, SPE
David W. Turt
- B. App. Sc., Civil Engineering, University ofToronto, Toronto, ON .
- Currently, Vice-President, Engineering, Oil andGas Department, Bank of Montreal, responsiblefor assessment of large domestic and international oil and gas project loan packages
- Member of APEGGA, Petroleum Society ofCIM, SPE, SPEE
George A. Warne
- B.Sc., Electrical Engineering, University ofAlberta, Edmonton, AB
- Currently, Energy Resource Consultant andSecretary-Treasurer of the Canadian Associationof the World Petroleum Congresses
- Experience includes energy resource regulationand management, and reservoir engineering
- Lecturer on energy resource regulation andmanagement
- Member of APEGGA, Petroleum Society ofCIM, SPE
Andy Warren
- B.Sc., Civil Engineering, Queen's University,Kingston, ON
Currently, Assistant Manager of Engineering,Oil Department, Alberta Energy ResourcesConservation Board
- Experience includes tight gas, shallow gas, smallgas pools, oil pool reserves, well testing, andpool depletion strategies
- Member of APEGGA, Petroleum Society ofCIM,SPE
327
d
----------------1
ACRONYMS
Acronyms for technical terms used in the monograph are listed first, followed by the acronyms for technical journalsand societies, then for universities and colleges, and last, for countries, provinces and states.
AACRT adjusted attributed Canadian royalties and EARP Environmental Assessment and Reviewtaxes Process
ACRI attributed Canadian royalty income EMV expected monetary value
ADP average daily production EOR enhanced oil recovery
AMP .Alberta market price FCA Federal Competition Act (US)
APMC Alberta Petroleum Marketing Commission FDC compensated formation density
AOF absolute open flow FERC Federal Energy Regulatory Commission
AOS Alberta oil sands (US)
AARTC adjusted Alberta royalty tax credit FOB freight on board
BHT bottom-hole temperature FVF formation volume factor
BOE barrels of oil equivalent G&A general and administrative (costs)
BTR break-through ratio GCA gas cost allowance
CAL caliper GCV going concern value
CCA capital cost allowance GOR gas-oil ratio
CDE Canadian development expense GORR gross overriding royalty
CEC cation exchange capacity GPSA Gas Processors Suppliers Association
CEDOE Canadian exploration and development GR gamma ray (API)
overhead expense GSC Geological Survey of Canada
CEE Canadian exploration expense GSP gas select price
CDF cumulative distribution function HClP hydrocarbon in place
CGR condensate-gas ratio HPV hydrocarbon pore volume
CGL conglomerate 1FT interfacial tension
CNL compensated neutron log lLd deep induction resistivity
COGPE Canadian oil and gas property expense lLm medium induction resistivity
CPI capital productivity index IMPES Implicit Pressure Explicit Saturation
CPM Critical path method Method
CPUC California Public Utilities Commission IPL Interprovincial Pipe Line
CSU cyber service unit IRR internal rate of return
DD&A depreciation, depletion and amortization K.B kelly bushing
DNPBI discounted net profit before investment LDC local distribution company
DOE Department of Energy (US) LGR liquid-gas ratio
DPHI density porosity LPG liquefied petroleum gas
DPR discounted profit-to-investment ratio MCM multiple-contact miscibility
DROI discounted return on investment MMP minimum miscibility pressure
DST drillstem test MV market value
329
t
,.1DETERMINATION OFOILANDGASRESERVES
reserves-to-production ratio
a carbonate unit on the Kelly-Snyder fieldin Texas
Securities and Exchange Commission(US)
spherically focused laterolog
specific gravity
sidewall neutron porosity
spontaneous potential
Trans Mountain Pipeline
take-or-pay (gas)
true vertical depth
township
United States Bureau of Mines
viscous gravity ratio
weighted average cost of capital
water alternating gas injection
water-air ratio
wire line formation test
water-gas ratio
water-oil ratio
West Texas Intermediate
API
AWES
CHOA
CIM
APEO
AlME
Technical Journals, Societies, and Institutions
AAPG American Association of PetroleumGologists
ACIPET Association of Colombian PetroleumEngineers
American Gas Association
American Institute of ChemicalEngineering
American Institute of MechanicalEngineering
APEGGA Association of Professional Engineers,Geologists and Geophysicists of Alberta
Association of Professional Engineers ofOntario
American Petroleum Institute
Association of Women in Engineering andScience
Canadian Heavy Oil Association
Canadian Institute of Mining, Metallurgyand Petroleum
AGA
AIChE
SEC
SFL
SG
SNP
SP
TMPL
TOP
TVD
TWP
USBM
VGR
WACC
WAG
WAR
WFT
WGR
WOR
WTI
RIP
SACROC
North American Free Trade Agreement
National Energy Program
natural gas liquids
Natural Gas Policy Act (US)
nuclear magnetic log
Notice of Proposed Rulemaking
net overriding royalty
an Alberta corporation
neutron porosity
net present value
New York Mercantile Exchange
Organization for Economic Co-operationand Development
original gas in place
original oil in place
Organization of Petroleum ExportingCountries
a consortium of companies
Ontario Securities Commission
Petroleum Administration for Defense(US)
Petroleum Administration for DefenseDistrict (US)
Program Evaluation and ReviewTechnique
probability distribution function
Petroleos de Venezuela S.A.
Pacific Gas and Electric
petroleum and gas revenue tax
Pacific Gas Transmission
profitability index
pore volume
pressure-volume-temperature
present worth ratio
pressure composition diagram
rising bubble apparatus
recovery factor
repeat formation tester
range
return on investment
resource profits
PADD
PDVSA
PG&E
PGRT
PGT
PII
PV
PVT
PWR
P-X
RBA
RF
RFTRGE
ROI
RP
OSLO
OSC
PAD
OGIP
OOIP
OPEC
NAFTA
NEP
NGL
NGPA
NML
NOPR
NORR
NOVA
NPHI
NPV
NYMEX
OECD
PERT
330
----------------------~
ACRONYMS
CSChE
CGPA
CSPG
CSEG
CWLS
GAC
GPSA
IAMG
IHRDC
JCPT
JPT
O&GJ
OGCI
PNA
SCA
SPE
SPEE
SPEJ
SPWLA
Canadian Society of ChemicalEngineering
Canadian Gas Processors Association
Canadian Society of Petroleum Geologists
Canadian Society of ExplorationGeophysicists
Canadian Well Logging Society
Geological Association of Canada
Gas Processors Suppliers Association
International Association forMathematical Geology
International Human ResourceDevelopment Corporation
Journal of Canadian PetroleumTechnology
Journal of Petroleum Technology
Oil and Gas Journal
Oil and Gas Consultants International
Petroleum Joint Venture Association
Society of Core Analysts
Society of Petroleum Engineers
Society of Petroleum EvaluationEngineers
Society of Petroleum Engineers Journal
Society of Professional Well Log Analysts
Universities and Colleges
U of A University of Alberta
U of C University of Calgary
SAlT Southern Alberta Institute of Technology
Countries, Canadian Provinces, American StatesAB Alberta
AZ Arizona
CA California
CO Colorado
MB Manitoba
MT Montana
SK Saskatchewan
NS Nova Scotia
OK Oklahoma
ON Ontario
TX Texas
UK United Kingdom
US, USA United States of America
WY Wyoming
331
t
---------------------------a
GLOSSARY
Acidizing. A method ofwell stimulation using acid (toincrease productivity); conducted mostly incarbonates.
Acoustic log. A measurement ofthe interval transit timeof compressional seismic waves in rocks near thewellbore of a liquid-filled borehole; used chieflyfor estimating porosity and lithology; also referredto as sonic log.
Analogous fields. Fields having similar properties thatare at a more advanced stage of development orproduction history than the field of specific interest, and that may provide concepts or patterns toassist in the interpretation ofmore limited data.
Anhydrite. A granular, white or light-colored evaporite mineral (CaSO.), often found together with rocksalt.
Annulus. The space around the tubing in a wellbore,the outer wall of which may be the wall of eitherthe borehole or the casing.
Aquifer. A stratum or zone below the surface of theearth capable ofproducing water.
Arithmetic mean. The average obtained by dividingthe sum of a distribution by the number of itsaddends.
Asphaltene. Any ofthe dark solid constituents ofcrudeoils and other bitumens that are soluble in carbondisulphide but insoluble in paraffin naphthas.
Beta model. A numerical simulator used to model blackoil systems; also referred to as black oil model.
Bias. A systematic deviation from the actual valueor distribution; a combination of two effects:displacement bias and variability bias.
Bitumen. Refer to Crude bitumen.
Black oil. Refers to a system in which the volume offluid is primarily a function of reservoir pressureand constant temperature. A system that is not ablack oil system includes compositional variables.
Black oil model. Refer to Beta model.
Bomb. A thick-walled container, usually steel, used tohold samples of oil or gas under pressure.
Bottom-hole pressure. The pressure in a well at a pointopposite the producing formation as recorded by abottom-hole pressure recorder.
Bottom-hole temperature. The temperature in a wellat a point opposite the producing formation.
Bottom water. Sand layers at the bottom of a forma. tion which contain mobile water that appreciablyaffects reservoir performance; water in strataunderlying an oil- or gas-bearing formation.
Bourdon tube. A mechanical pressure-measuringinstrument employing as its sensing element acurved or twisted metal tube, flattened in crosssection and closed.
Bubble point. In a solution oftwo or more components,the pressure at which the first bubbles of gasappear; same as saturation pressure.
Bulk deusity. Density of the combined pore volumeand rock volume; measured, for example, by adensity log.
Bulk volume. Total volume of a formation includingthe pore volume and the rock volume.
Butanes. In addition to its normal scientific meaning ofC.H IO (a mixture of two gaseous paraffins, normalbutane and isobutane), a mixture mainly ofbutanesthat ordinarily may contain some propane orpentanes.
Capillarity. The effect of surface attraction forcesamong oil, gas, water, and rock in retaining fluidsaturations within the pore structure of a porousmedium. Refer to Capillary pressure.
Capillary pressure. A force per unit area resultingfrom surface forces at the interface between twoimmiscible fluids.
Carbonates. Sedimentary rocks primarily composedof calcium carbonate (limestone) or calciummagnesiumcarbonate (dolomite), which form manypetroleum reservoirs.
Carbon dioxide flooding. A recovery processin which carbon dioxide is injected into an oilreservoir to improve recovery.
333
...
• Heavy:
• Medium:
less than 870 kg/m' (greaterthan 31.1 0 API)
870 to 920 kg/m'' (31.1 to 22.3°API)
920 to 1000 kg/rrr' (22.3 to 10°API)
• Extra-heavy: greater than 1000 kg/rrr' (less than10° API)
Heavy or extra-heavy crude oils, as defined bythe density ranges given, but with viscositiesgreater than 10 000 ml'a-s measured at originaltemperature in the reservoir and atmosphericpressure, on a gas-free basis, would generally beclassified as crude bitumen.
Conventional natural gas. Natural gas that occursin a normal, porous, permeable reservoir rock andthat, at a particular time, can be technically andeconomically produced using normal productionpractices.
Cricondentherm. Maximum temperature at which twophases (for example, liquid and vapour) can exist.
Critical gas saturation. Saturation at which free gas ina reservoir becomes mobile.
Critical pressure. The pressure required to condensea gas at the critical temperature, above whichregardless ofpressure, the gas cannot be liquefied:
Critical temperature. That temperature above whicha substance can exist only in the gaseous state, nomatter what pressure is exerted.
Crude bitumen. A naturally occurring viscousmixture consisting mainly of pentanes and heavierhydrocarbons. Its viscosity is greater than 10 000ml'a-s measured at original temperature in thereservoir and atmospheric pressure, on a gas-freebasis. Crude bitumen may contain sulphur and othernonhydrocarbon compounds and in its naturalviscous state is not normally recoverable at acommercial rate through a well.
Crude oil. A mixture, consisting mainly of pentanesand heavier hydrocarbons, that exists in the liquidphase inreservoirs and remains liquid at atmosphericpressure and temperature. Crude oil may containsmall amounts ofsulphur and other nonhydrocarboncompounds, but does not include liquids obtainedfrom the processing ofnatural gas. Classes ofcrudeoil are often reported on the basis ofdensity, sometimes with different meanings. Acceptable rangesare as follows:
• Light:
Cementation. The process of precipitation or growthofa binding material around grains or fragments ofrock.
Chase gas. Gas used to displace another phase in anenhanced recovery process.
Chemical flooding. A recovery process in whichchemicals added to water are injected into an oilreservoir to improve recovery.
Choke. An orifice installed in a line to restrict the flowand control the rate ofproduction.
Clastics. Sedimentary rocks composed offragments of. pre-existing rocks; sandstone is a clastic rock.
Clay lattice. A three-dimensional pattern of clay partsin space.
Compaction. A decrease in volume of sediments as aresult ofcompressive stress, usually resulting fromcontinued depositional loading by accumulation ofoverlying sediments.
Compressibility. The rate ofchange in volume of rockand fluids with decrease in pressure. Compressibility is a major contributor to recovery efficiency anda cornerstone of reservoir performance.
Condensate. A mixture of pentanes and heavierhydrocarbons recovered as a liquid from field separators, scrubbers or other gathering facilities, orat the inlet of a processing plant before the gas isprocessed.
Conductivity. A property of an electrical conductordefined as the electrical current per unit area dividedby the voltage drop per unit length.
Conformance efficiency. The fraction of totalreservoir volume that is contacted by injected fluidas a result of discontinuities in the reservoir; alsoreferred to as continuity factor.
Conglomerate. A sedimentary rock composed ofcoarse-grained rock fragments, pebbles or cobblescemented together in a fine-grained matrix.
Coning. A cone of gas or water that forms in thereservoir due to pressure drawdown at theperforations.
Connate water. The original water ofdeposition trappedin the interstices of the reservoir rock.
Conventional crude oil. Crude oil that, at a particulartime, can be technically and economically producedthrough a well using normal production practicesand without altering the natural viscous state oftheoil.
334
________________________1
GLOSSARY
D' Arcy's Law. The basic law of fluid flow througha porous medium that expresses how easily a fluidof a certain viscosity flows through a rock under apressure gradient.
Decision tree. A graphical summary of the possibleoutcomes and probabilities of the events thatcomprise a project.
Density. The ratio of the mass of an object to itsvolume.
Density log. A radioactivity log for open-hole surveying that responds to variations in the specific gravityof formations; an excellent porosity-measuringdevice, especially for shaly sands. It is a contact log(i.e., a detector held against the wall of the hole).The tool emits neutrons and then measures the secondary gamma radiation that is scattered back tothe detector.
Depositional environment. The conditions underwhichsediments were laid down.
Differential liberation. The liberation of gas from oilas pressure is reduced wherein the evolved gas isseparated from its associated oil; usually the physical model related to transport ofoil and gas throughthe formation during the majority of the primarydepletion life.
Dip. The angle at which a stratum is inclined from thehorizontal.
Discounted cash flow. Future cash converted to presentconditions using an appropriate discount rate.
Displacement bias. A shift of the whole frequencydistribution curve to higher or lower values.
Displacement efficiency. The fraction of initial oilsaturation that is displaceable by a given injectionfluid.
Displacement process. The process by which oil isdisplaced by water, gas, or another fluid.
Disposal well. A well used for the disposal of saltwater. The water is pumped into a subsurface formation sealed offfrom other formations by imperviousstrata of rock.
Dolomite (CaMg(COJ)2)' A common rock-forming
mineral.
Dolomitization. The process whereby limestone isaltered to dolomite by the substitution of magnesium carbonate for a portion ofthe original calciumcarbonate.
Drillstem test. The procedure used to gather data on aformation to determine its potential productivitybefore installing casing in a well. In the drillstemtesting tool are a packer, valves or ports that maybe opened and closed from the surface, a samplechamber and a pressure-recording device. The toolis lowered in the wellbore on a string of drill pipeand the packer set, isolating the formation to betested from the formations above and below andsupporting the fluid column above the packer. Aport on the tool is opened to allow the trapped pressure below the packer to bleed off into the drill pipe,gradually exposing the formation to atroosphericpressure and allowing the well to produce to thesurface, where the well fluids may be sampled andinspected. From a record ofthe pressure readings, anumberoffacts about the formationmay be inferred.
Efflux. Quantities of hydrocarbons, water or otherfluids that leave a reservoir or zone of interest viapermeable formation boundaries.
Electrical conductivity. Used for estimating reservoirproperties; reciprocal ofelectrical resistivity. Referto Conductivity.
Electrical resistivity. The reciprocal of electricalconductivity; used for estimating properties suchas water saturation and fracture porosity. It isone of the most useful measurements in boreholegeophysics.
Enhanced oil recovery. Refer to Recoveryenhanced.
Established reserves. Those reserves recoverableunder current technology and present and anticipated economic conditions, specifically proved bydrilling, testing or production, plus that judgementportion of contiguous recoverable reserves that isinterpreted, from geological, geophysical or similar information, to exist with reasonable certainty.This is a term that has been used historically inCanada, particularly by regulatory agencies, andtypically comprises proved reserves plus one-halfprobable reserves.
Ethane. In addition to its normal scientific meaningof C2H6 (a colourless, odourless gas of the alkaneseries), a mixture mainly of ethane that maycontain some methane or propane.
Evaporite. Deposits ofmineral salts from sea water orsalt lakes due to evaporation of the water.
Expectation. The mean of all possible outcomes of anevent.
335
..
Facies. Part of a bed of sedimentary rock of similardepositional environment, composition, appearanceand properties.
Fault. A break in subsurface strata. Often strata on oneside of the fault line have been displaced (upward,downward, or laterally) relative to their originalposition.
Fault plane. A surface along which faulting hasoccurred.
Filtrate. A fluid that has been passed through a filter.
Fines migration. The dislocation and movement of fineparticles within a reservoir. Fines migration cancause damage or impair permeability by blockingpore throats.
Flash liberation. The liberation of gas from oil aspressure is reduced wherein the evolved gas remainsin contact with the liquid phase.
Flow test. A test of the ability ofa well to produce fluids usually at a constant rate.
Fluid saturation. The fraction of the pore volumeoccupied by fluid.
Fluid viscosity. Internal friction of a fluid, causedby molecular interactions, that makes it resist atendency to flow.
Fold. A flexure of rock strata into arches and troughs,produced by earth movements.
Formation heterogeneity. Variation both laterallyand vertically of properties such as porosity,permeability, and formation thickness.
Formation imaging. Logs that generate images (or"pictures") of the borehole from various sourcesincluding sonic and resistivity devices.
Formation pressure. The pressure in a formation at adefined depth.
Formation temperature. The temperature at a givenpoint within a formation. Temperature usuallyincreases with depth. .
Formation volume. The volume of fluid, at formationpressure and temperature, that results in one barrelof stock tank oil.
Fractional flow. Phase flow rate as a fraction of totalflow rate.
Fracturing. A stimulation to increase productivity thatresults in the formation ofa fracture in the wellborearea; conducted mostly in clastics.
336
DETERMINATION OF OIL AND GAS RESERVES
Free-water I~vel. The level or depth at which capillarypressure IS equal to zero and which, in rocks ofvari_able pore structure, is the only truly level referencline between hydrocarbons and water. e
Friable. Describes a substance that is easily rubbed,.crumbled, or pulverized into powder.
Gamma ray detector. A device that is capableof sensing and measuring the amount of gammaparticles emitted by certain radioactive substances.
Gas. Refer to Natural gas.
Gas chromatography. The process of separatingconstituents of a mixture by permitting a solutionof the mixture to flow through a column ofadsorbent on which the different substances arc selectivelyseparated into distinct bands or spots.
Gas compressibility factor. A factor used to correctthe Ideal Gas Law (pv = nRT) to actual measurements.
Gas-oil ratio. The ratio of gllll in solulion to the 011volume in which it is dissolved, u.ually expretledin cubic feet of gas per barrel of liquid It 101.325kPa (14.65 psia) and 15.6'C (60·F).
Genetic sand unit. Formation consisling ofsand. fromthe same origin.
Geostatistlcs. A specific statistical technique (based onthe statistics of regionalized variables) that uses theposition as well as the magnitude of a parameter;classical statistics' docs not generally use position,Other spatial statistics methods also exist.
Gravity drainage. The movement of oil in a reservoirtoward a wellbore resulting from the force ofgravity.
Gravity override. Preferential movement of one fluidover another due to density differences.
Gross pay. The gross economically productive thickness of a formation containing hydrocarbons.
Gross swept volume. The reservoir rock volume thatis swept by injected fluid.
Heterogeneity. A lack ofuniformity in formation properties such as permeability, porosity and thickness.
Homogeneity. Uniformity ofreservoir properties in alldirections.
Horizontal sweep efficiency. The areal fraction of apattern contacted by the injected fluid; also referredto as areal sweep efficiency.
---------------------
GLOSSARY
Horizontal waterflood scheme. The injection ofwaterin a pattern ofwells with oil production from wellscompleted between injectors.
Hybrid sand unit. A formation with sands fromdifferent origins.
Hydrate. A hydrocarbon and water compound thatforms under reduced pressure and temperature ingathering, compression, and transmission facilitiesfor gas; flakes ofhydrate resemble snow or ice andimpede fluid flow.
Hydrocarbon pore volume. The pore volume in areservoir containing hydrocarbons; the product ofhydrocarbon-filled thickness, porosity, and hydrocarbon saturation usually expressed for a unit area.May be represented on a contour map as a type ofvolumetric map.
Hydrodynamic flow. The motion and action of waterand other liquids in the subsurface.
Hydrodynamic trap. An oil or gas reservoir trappedby surrounding water movement; usually leads totilted water-oil contacts.
Hydrodynamics. The study of the motion of a fluidand of the interactions of the fluid with its boundaries, especially in the incompressible ideal(frictionless) case.
Hydrostatic head. The pressure exerted by a body ofwater at rest.
Hysteresis. A change in process path in successiveexperimental tests.
Ideal Gas Law. The volume occupied by an ideal gasdepends only upon temperature, pressure, and thenumber of molecules (moles) present (pv = nRT).
Imbibition. The increase in saturation of the wettingphase in a porous medium with time.
Improved recovery. Refer to Recoveryimproved.
Influx. Quantities of hydrocarbons, water or otherfluids that enter a reservoir or a designated portionofa reservoir through permeable formation boundanes.
Initial reserves. A term often used to refer to reservesprior to deduction of any production. Alternatively,initial reserves can be described as the sum ofremainingreserves and cumulativeproductionat thetime of the estimate.
Initial volumes in place. The gross volume ofcrudeoil, natural gas and related substances estimated,at a particular time, to be initially contained in areservoir before any volume has been producedand without regard for the extent to which suchvolumes will be recovered.
Injection. The pumping of fluids into the reservoir viawellbores, for wellbore conditioning or stimulationor for improved recovery operations.
In situ recovery. A term that is used, when referringto oil sands, for the process of recovering crudebitumen from oil sands other than by surfacemmmg.
Intercalation. Insertion of a bed or stratum of onematerial between layers of another material.
Interfacial tension. The force per unit length existingat the interface between two immiscible fluids.
Irreducible water saturation. The minimum watersaturation that can be obtained in a reservoir undernormal operations.
Isochrone. A line on a chart connecting all pointshaving the same time of occurrence of particularphenomena or of a particular value of a quantity.
Isolating packers. Devices used for isolating aninterval in a well.
Isopach map. A geological map of subsurface stratashowing contours of the thickness of a given formation underlying an area; one type of volumetricmap.
Isotherm. A line connecting points of equaltemperature.
Isothermal. Having constant temperature; at constanttemperature.
J function. A dimensionless grouping of the physicalproperties of a rock and its saturating fluids proposed by Leverett.
Kerogen. A solid bituminous substance occurring incertain shales that decomposes to oil and naturalgas when heated.
Klinkenberg. Mathematical correction oflaboratory airpermeability measurements (made on formationmaterial) intoequivalent liquid permeability values,necessitated by gas slippage in pores.
Laterolog. A resistivity measuring device usingelectrodes in which a current is forced through theformation in a sheet ofpredetermined thickness, sothat the measurement involves a limited verticalextent.
337
.
Liquefied petroleum gases. A term commonly usedto refer to hydrocarbon mixtures consisting predominantly of propane and butanes. In Canada,ethane is also frequently included.
Lithification. The conversion of unconsolidateddeposits into solid rock by compaction and cementing together of the individual rock grains.
Lithology. The description ofthe physical character ofa rock as determined by eye or with a low-powermagnifier; based on color, structures, mineralogiccomponents, and grain size.
Mandrel. A cylindrical bar, spindle, or shaft aroundwhich other parts are arranged or attached, or thatfits inside a cylinder or tube.
Marketable natural gas. Natural gas that meetsspecifications for its end use, whether it occursnaturally or results from the processing of rawnatural gas. Field and plant fuel and losses areexcluded, excepting those related to downstream reprocessing plants. The heating value ofmarketablenatural gas may vary considerably, depending uponits composition, and therefore quantities are usually expressed not only in volumes,but also in termsof energy content.
Material balance method. An engineering method ofdefining project performance wherein expansion ofin situ rock and fluids is related to influx-efflux andproduction-injection streams; may be arranged todeterminefluids in place or productionperformance.
Matrix. The continuous, fine-grained material in whichlarge grains of a sediment or sedimentary rock areembedded.
Mean. The most commonly used measure of centraltendency; the average value of repeated trials. Themean represents the most probable value of anestimate of reserve volume or value.
Median. A measure of central tendency; the middlevalue or the arithmetic mean of the two middlevalues of a list of numbers, for a list containing anodd or even number of members, respectively.Geometrically, the value that divides a histogramor frequency distribution into two parts of equalarea; also the 50 percent probability level on acumulative distribution function or expectationcurve.
338
DETERMINATION OFOIL AND GASRESERVES
Methane. In addition to its normal scientific meaning of CH. (a light, odourless, colourless gaseoushydrocarbon), a mixture mainly of methane thatordinarily may contain some ethane, nitrogenhelium or carbon dioxide. •
Miscibility. The tendency or capacity of two or moreliquids to form a uniform blend, that is, to dissolvein each other; degrees are total miscibility, partialmiscibility, and immiscibility.
Miscible flooding. A recovery process inwhich a fluid(a "solvent") that is capable of dissolving into thecrude oil it contacts is injected into an oil reservoirto improve recovery.
Micellar flooding. The addition of surfactants toinjected water to reduce interfacial tension.
Micro-fractures. Fractures not easily seen bythe naked eye; might be seen in thin sections. Theyusually feed macro-fractures.
Microlog. A wellbore resistivity log recorded withelectrodes mounted at short distances from eachother in the face ofa rubber-padded microresistivitysonde and with different depths of investigation.Comparison of the two curves identifies mudcakewhich indirectly identifies the presence of permeable formation.
Microporosity. Porosity that is visible only at highmagnification and that is generally not effective.
Mobility. The ratio ofthe permeability ofa given phaseto the viscosity of that phase. Phase mobility is anindication of how easily that phase moves in thereservoir.
Mobility ratio. The ratio of the mobility of thedisplacing phase behind the flood front to thedisplaced phase ahead of the flood front.
Mode. A measure of central tendency; the mostcommonly occurring value of a set ofnumbers.
Mole. An amount of substance of a system whichcontains as many elementary units as there areatoms of carbon in 0.012 kilogram of the purenuclide carbon-12; the elementary unit must bespecified and may be an atom, a molecule, an ion,an electron, a photon, or even a specified group ofsuch units.
Morphology. The observation of the form oflands.
ii\f.",~,~ ,".
GLOSSARY
Mudcake. The residue that forms on the wall of theborehole as the drilling mud loses filtrate intoporous and permeable formations; also called wellcake or filter cake.
Mud-gas log. The recording of information derivedfrom examination and analysis offonnation cuttingsmade by the bit and mud circulated out of the hole.A portion of the mud is diverted through a gasdetecting device and examined under ultravioletlight to detect the presence of oil or gas. Oftencarried out in a portable laboratory set up at the well.
Natural fracture. A discontinuity in rock caused bydiastrophism, deep erosion of the overburden, orvolume shrinkage. Examples would include shalesthat lose water, the cooling of igneous rock, and thedesiccation of sedimentary rock.
Natural gas. A mixture of lighter hydrocarbons thatexist either in the gaseous phase or in solution incrude oil in reservoirs but are gaseous at atmosphericconditions. Natural gas may contain sulphur or othernonhydrocarbon compounds.
Natural gas liquids. Those hydrocarbon componentsthat can be recovered from natural gas as liquidsincluding, but not limited to, ethane, propane,butanes, pentanes plus, condensate, and small quantities of nonhydrocarbons.
Net present value. The value obtained when all cashflow streams, including the investment, arediscounted to the present and totalled.
Neutron log. A radioactive device that emits highenergy neutrons and records a curve which respondsprimarily to the amount of hydrogen in the formation. Thus, in clean formation where the pores arefilled with water or oil, the neutron log measuresthe amount of liquid-filled porosity.
Nonconventional crude oil. Crude oil that is notclassified as conventional crude oil. An examplewould be kerogen contained in oil shale deposits.Bitumen is also generally included in the nonconventional crude oil category as a matter ofpractice, although some wells may produce atcommercial rates without steam injection. Alsoreferred to as unconventional crude oil.
Nonconventional natural gas. Natural gas that is notclassified as conventional natural gas. An examplewould be coal-bed methane. Also referred to asunconventional natural gas.
Nuclear magnetism inject log. A tool that uses a pulsednuclear magnetic resonance analyzed to determinefluid content, total and free fluid porosity, andpermeability.
Oil sands. Deposits of sand or sandstone or othersedimentary rocks that contain crude bitumen.
Oolite. A spherical to ellipsoidal body, 0.25 to 2.00 mmin diameter, which mayor may not have a nucleus,and has concentric or radial structure or both; usually calcareous, but may be hematitic or of othercomposition.
Pentanes plus. A mixture mainly of pentanes andheavier hydrocarbons, which ordinarily may contain some butanes, and which is obtained from theprocessing of raw gas condensate or crude oil.
Permeameter. A device for measuring permeability bymeasuring the flow offluid through a sample acrosswhich there is a pressure drop.
Petroleum. A naturally occurring mixture consistingpredominantly of hydrocarbons in the gaseous,liquid or solid phase.
Petroleum reservoir (pool). A porous and penneable underground rock formation that contains anatural accumulation ofcrude oil or natural gas andrelated substances, or combinations ofthem, that isconfined by impermeable rock or water barriers, andthat is individual and separate from other reservoirs.
Phase behaviour. The equilibrium relationshipsbetween water, liquid hydrocarbons, and dissolvedor free gas, either in reservoirs or as separatedaboveground in gas-oil production facilities.
Polymer flooding. The addition ofpolymers to injectedwater to improve mobility ratios and increase oilrecovery.
Pore volume. The pores in a rock considered collectively; the product of porous thickness timesporosity. May be represented on a contour map, atype of volumetric map.
Porosimetry. The measurement of the porosity ofreservoir rocks.
Porosity. The volume of the pore space expressed as apercentage of the total volume of the rock mass.
Pressure depletion. Pressure decline in a reservoir dueto oil or gas production.
Pressure transient analysis. The estimation ofreservoirproperties from measurements offlow, buildup anddrawdown pressures.
339
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Primary recovery. Refer to Recovery - primary.
Production tests. Tests conducted to determine theproductivity of a given reservoir.
Propane. In addition to its normal scientific meaningof C,H. (a heavy, colourless hydrocarbon of theparaffin series), a mixture mainly of propane thatordinarily may contain some ethane or butanes.
Pseudo-critical and pseudo-reduced properties(temperature and pressure). Properties of purehydrocarbons are often the same when expressed interms oftheir reduced properties. The same reducedstate relationships often apply to multicomponentsystems if "pseudo" critical temperatures and pressures are used rather than the true critical propertiesof the systems. The ratios of the temperature andpressure of interest to the pseudo-critical temperature and pressure are called the pseudo-reducedtemperature and pressure respectively.
Pulsed neutron log. A special cased-hole logging toolthat uses radioactivity reaction time to obtain measurements ofwater saturation, residual oil saturation,and fluid contents in the formation outside the casing of an oil well.
PVT data. Information describing the physicalinter-relationship ofpressure, volume, and temperature of reservoir fluids and various production andinjection streams.
Pyrobitumen. Any of various dark-colored, relativelyhard, nonvolatile hydrocarbon substances oftenassociated with mineral matter, which decomposeupon heating to yield bitumens.
Pyrolysis. The breaking apart of complex moleculesinto simpler units by the use ofheat, as in obtaininggasoline from heavy oil.
Raw natural gas. Natural gas as it is produced fromthe reservoir prior to processing. It is gaseous at theconditions under which its volume is measured orestimated and may include varying amounts ofheavier hydrocarbons (that may liquefy at atmospheric conditions) and water vapour. May alsocontain sulphur and other nonhydrocarbon compounds. Raw natural gas is generally not suitablefor end use.
Recovery - enhanced. A term that, in Canada, isequivalent to improved recovery.
340
DETERMINATION OFOILANDGASRESERVES
Recovery - improved. The extraction of addif ald '1 Ion
cru e 01 , natural gas and related substances fr. hr h omreservoirs t oug a production process other th
nat~ral depletion. Includes both secondary a:tertiary recovery processes such as pressure maintenance, cycling, waterflooding, thermal methods~he~ic~1 flo?ding, and the use of miscible andimmiscihls displacement fluids.
Recovery - primary. The extraction of crude oilnatural gas and related substances from reservoirsutilizing only the natural energy available in thereservoirs.
Recovery - secondary. A term frequently used todescribe the extraction of additional crude oilnatural gas and related substances from reservoirsthrough pressure maintenance schemes such aswaterflooding or gas injection.
Recovery - tertiary. A term frequently used todescribe the extraction of additional crude oil.natural gas and related substances from reservoirsusing recovery methods other than natural depletion or pressure maintenance. A tertiary proeClllcanbe implemented without a precedinll prinwy orsecondary recovery scheme.
Remaining reserves. Initial reserves less cumulativeproduction at the time of the estimate.
Reservoir. Refer to Petroleum reservoir.
Reservoir continuity. No interruption of a reservoirby faults, facies changes. or any other type ofheterogeneity.
Residual 011 saturation. Following a recovery process,the oil saturation at which oil will no longer flow ina normal immiscible water-oil system.
Resin. Any of a class of solid or semisolid organicproducts of natural or synthetic origin with nodefinite melting point, generally ofhigh molecularweight; most resins are polymers.
Resistivity. The electrical resistance offered to thepassage of current; the inverse of conductivity.
Resistivity log. The measurement of subsurfaceelectrical resistivity accomplished either by sending current into the formation and measuring theease of electrical flow or by inducing an electricalcurrent into the formation and measuring how largeit is.
Risk. The probability ofloss or failure.
GLOSSARY
Salt dome intrusive. A subsurface mound or dome ofsalt.
Sandwich loss. The volume of oil remaining unsweptat the top of a reservoir after water flooding or atthe bottom of the reservoir after gas or miscibleflooding.
Saturation. Refer to FluidSaturation.
Saturated oil. Oil that contains all the gas that iscapable of dissolving given the compositions ofthat oil and gas at the particular temperature andpressure.
Saturation pressure. Also known as bubble-pointpressure; the pressure at which the first bubble ofgas comes out of solution.
Secondary recovery. Refer to Recoverysecondary.
Seismic. The measurement of the response to energywaves travelling through rock layers. The energywaves may be created by earthquakes, explosivesor by dropping or vibrating a heavy weight. Someenergy is reflected whenever the waves cross aninterface ofrock layers ofdistinctly different properties. Measurements can be made at the surface oftravel time, which may be related to depth, and waveamplitude variations, which may relate to changesin rock properties (porosity, etc.).
Separator. An oilfield vessel or series of vessels inwhich pressure is reduced so that the dissolved gasassociated with reservoir oil is flashed off or removed as a separate phase. Also known as gasseparator, oilfield separator, oil-gas separator, andoil separator.
Shrinkage. The decrease in volume of a liquid phasecaused by the release of solution gas or by thethermal contraction of the liquid; the reciprocal offormation volume factor.
Shrinkage factor. The reciprocal of the formationvolume factor expressed as barrels ofstock tank oilper barrel of reservoir oil.
Solution gas. Natural gas that is dissolved in crudeoil in the reservoir at original reservoir conditionsand that is normally produced with the crude oil;also known as dissolved gas.
Solvent flooding. Refer to Miscible flooding.
Sonde. A logging tool assembly, especially the devicein the logging assembly, that senses and transmitsformation data.
Sonic log. A device that measures the time required fora sound wave to travel through a definite length offormation. Refer to Acoustic log.
Sour gas. Natural gas that contains corrosive, sulphurbearing compounds such as hydrogen sulphide,sulphur dioxide, and mercaptans.
Specific gravity. The ratio of the density of a materialto the density of some standard material, suchas water at a specified temperature, 4'C or 60'F or(for gases) air at standard conditions ofpressure andtemperature.
Spontaneous potential. A recording of the differencebetween the electrical potential of a movable electrode in the borehole and the electrical potential ofa fixed surface electrode.
Stock tank cubic metre. One cubic metre of oil atstandard temperature and atmospheric pressure.
Static gradient. Pressure measured in a wellbore atvarious depths while a well is shut in.
Stratification. A structure produced by deposition ofsediments in beds or layers (strata), laminae, lenses,wedges, and other essentially tabular units.
Stratigraphic trap. A type of reservoir capable ofholding oil or gas, in which the trap is formed by achange in the characteristics of the formationwhich could be loss ofporosity and permeability ora break in its continuity.
Stringer. A narrow vein or irregular filament ofmineral traversing a rock mass of differentmaterials.
Structure map. A map showing contour lines drawnthrough points ofequal elevation on a stratum, keybed, or horizon, in order to depict the attitude oftherocks.
Structural trap. A type ofreservoir containing oil and!or gas, formed by deformation of the earth's crustthat seals off the oil and gas accumulation in thereservoir, forminga trap. Anticlines, salt domes, andfaulting of different kinds form structural traps.
Sulphur. As used in the petroleum industry, theelemental sulphur recovered by conversion ofhydrogen sulphide and other sulphur compoundsextracted from crude oil, natural gas or crudebitumen.
Surface loss. The quantity of natural gas removedat field processing plants as a result ofthe recoveryof liquids and related products and the removal ofnonhydrocarbon compounds, plus the gas used forfuel; also referred to as shrinkage.
341
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Surfactant. A soluble compound that reduces thesurface tension of liquids, or reduces interfacialtension between two liquids or a liquid and a solid.
Sweep efficiency. The volume swept by a displacingfluid divided by the total volume being flooded.
Sweet gas. A petroleum natural gas containing nocorrosive components, such as hydrogen sulphide,sulphur dioxide, and mercaptans.
Synthetic crude oil. A mixture of hydrocarbonsderived by upgrading crude bitumen from oil sands,and kerogen from oil shales or other substancessuch as coal. May contain sulphur or other nonhydrocarbon compounds and has many similaritiesto crude oil.
Tertiary recovery. Refer to Recovery - tertiary.
Thermal conductivity. The heat flow across a surfaceper unit area per unit time, divided by the negativeof the rate of change of temperature with distancein a direction perpendicular to the surface.
Tilts. Blocks that have received a marked tilt in regionsof block faulting. Regional tilts occur on the margins ofbasins of subsidence in the earth's crust.
Tool resolution. The precision of a tool to investigate agiven property.
Transition zone. The interval directly above the freewater level in a reservoir where capillary effectsresult in significant changes in water and hydrocarbon saturations in response to pore structurevariations and elevation.
Transmissibility. The ability of a reservoir to conductfluids spatially in response to pressure differentials.Depends upon permeability and formation flow geometry. Production potential depends heavily uponreservoir transmissibility.
Trap. A mass ofporous, permeable rock that is sealedon top and down both flanks by nonporous, impermeable rock that prevents the free migration ofhydrocarbons and concentrates them in a limitedspace.
Uncertainty. The spectrum ofpossible outcomes ofanevaluation.
Unconformity. Lack of continuity in depositionbetween rock strata in contact with one anothercorresponding to a gap in the stratigraphic record;the surface of contact between rock beds in whichthere is a discontinuity in the ages of the rocks.
342
DETERMINATION OFOILAND GASRESERVES
Unconsolidated sand. A sand formation in who hindividual grains are not cemented together. I/~unconsolidated sandstone produces oil or git will produce sand ifnot controlled or correcte~'
Undersaturated oil. Oil that is capable of absorbinhan is nresenr l gmore gas t an IS present in the reservoir. Under-
saturated ~i~ typically displays relatively lowcompressibility and hence a rapid pressure declinewith production.
Undersaturated oil reservoir. A reservoir that is abovethe bubble-point pressure.
Ultimate potential recovery. A term sometimes usedto refer to an estimate at a particular time of theinitial reserves that will have become developed inan area by the time all exploratory and developmentactivity has ceased, having regard for the geological prospects of the area, the known technology,and the anticipated economic conditions. It includescumulative production; remaining proved, probableand possible reserves; and future additions to reserves through extensions and revisions to existingpools and the discovery of new pools. It may alsobe described as initial reserves plus those other resources that may be recoverable in the future.
Unitization. A term denoting the joint operation ofseparately owned producing leases in a pool orreservoir.
Upgrading. The process ofconverting crude bitumenor heavy crude oil into synthetic crude oil.
Utilization rate. In an enhanced oil recovery process,the amount of gas or fluid injected per incrementaloil recovered.
Variability bias. An alteration in the shape of afrequency distribution curve.
Vertical sweep efficiency. The vertical fraction ofreservoir swept by injected fluid.
Vertical waterflood scheme. The injection ofwater atwells completed at the bottom of the formation; oilproduction is from wells completed at the top oftheformation.
Vesicle. A cavity in lava formed by entrapment ofa gasbubble during solidification.
Viscous fingering. Faster advance ofa displacing phaseas compared to the displaced phase due to anunfavorable mobility ratio.
GLOSSARY
Volumetric estimation. An estimate of hydrocarbonor water volume based on a combination of volumetric maps and other data which in total mustaccount for the reservoir area, thickness, porosity,and hydrocarbon and water saturation.
Volumetric mapping. A contour map of a parameteror combination of parameters that relate toreservoir volume.
Voidage. The reservoir volume of hydrocarbons andwater removed from the formation via wellboresduring a term ofproducing operations.
Voidage replacement. The volume at reservoirconditions of fluids injected into a producing poolto offset fluid withdrawals during depletion.
Voidage replacement ratio. The quotient of voidagereplacement divided by reservoir voidage.
Vugs. Pore spaces that are larger than would be expectedfrom the normal fitting together of the grains thatcompose the rock framework. Vugs are often formedduring dolomitization.
Water channelling. Preferential movement of watertowards a wellbore due to unfavourable mobilityratio and pressure drawdown at the wellbore or dueto the presence of higher permeability streaks.
Waterflooding. An improved recovery process in whichwater is injected into a reservoir to increase oilrecovery.
Water injector. A well in which water has beeninjected into an underground stratum to increasereservoir pressure.
Water saturation. Portion of the pore volumeoccupied by water. .
Weighted-mean. The number obtained by multiplyingeach value of x by the probability (or probabilitydensity) ofx and then summing (orintegrating) overthe range ofx.
Well density. The intensity of drilling in a given area.
Wetting phase. The liquid phase (oil, gas or water) that"wets" reservoir rock.
Wire line. A rope composed of steel wires twisted intostrands that are in turn twisted around a central coreof hemp or other fiber to create a rope of greatstrength and considerable flexibility; used asdrilling, coring, servicing, and winch lines.
343
BIBLIOGRAPHY
The following are additional recommended references that have not been cited in the text.
Determination of In-Place ResourcesAlexander, L.G. "Theory and Practice ofthe Closed
ChamberDrillstemTest Method." 51st AnnualSPE Fall Technical Conference,New Orleans,LA, SPE Paper No. 6024, 1976.
AmericanPetroleum Institute. "SamplingPetroleumReservoir Fluids." API RP 44, Washington, DC,1966.
Amyx,1.W.,Bass, D.M., and Whiting,R.L.Petroleum Reservoir Engineering. McGraw-Hill,New York, NY, 1960.
Archer,1.S."Reservoir Volumetrics and RecoveryFactors." In Developments in PetroleumEngineering, Elsevier SciencePublishingCo.,NewYork,NY,1985.
Bankhead, C.C., Jr. Processingof Geological andEngineeringData in Multipay Fields forEvaluation. Trans., AIME, Reprint Series#3,1970.
Bujnowicz, R. "PVT Data Generation, ReportingandGeneral Use." 39th Annual Tech. Meeting,Petroleum SocietyofCIM, Calgary,AB, PaperNo. 88-39-66, 1988.
Calhoun,1.e., Jr. Fundamentals ofReservoirEngineering. Universityof OklahomaPress,Norman, OK, 1947.
Campbell, J.M., and Holander, D.P. "The Effect ofPore Configuration,Pressure and Temperature onRock Resistivity." Paper presented at 7th AnnualSPWLALogging Symposium, May 1966.
Celbuliak, N., Hamp, T., Mayder, A., Shaw,1., andVokey, G. "Coring for Connate Water Saturation- UtikumaKeg River Sandstone." JCPT, Nov.1990.
Core Laboratories. "Applications of Core Data inIntegratedReservoir DescriptionandExploitation." Version 1.2, Calgary,AB, 1990.
Craft, B.C., and Hawkins, M.F. Petroleum ReservoirEngineering. Prentice-Hall, Inc., New York, NY,1959.
Dullien,F.A.L.Porous Media Fluid Transport andPore Structure. Academic Press, New York, NY,1979.
Enderlin, M.B., Hansen, D.K.T., and Hoyt, B.R.''The Role of Rock Volumes in Log to CoreIntegration." Paper presented at CWLS 12thFormation Evaluation Symposium, Calgary, AB,Sep. 1989.
EnergyResourcesConservationBoard. Gas WellTesting Theory and Practice. Guide G-3,Calgary,AB, 1979.
---. Pressure and Deliverability Testing Oil andGas Wells. Guide G-40, Calgary, AB, 1990.
Fatt, 1. "Effect of Overburdenand Reservoir Pressureon Electrical Logging Formation Factor." AAPGBulletin, Vol. 41, No. II, 1957.
Gatlin, C. Petroleum Engineering - Drilling and WellCompletions. Prentice-Hall, Inc., EnglewoodCliffs,NJ, 1969.
Hensel, W.M. Jr., Honarpour,M.M., Sprunt, E.S., andYork, C.E. "Compilationof Electrical ResistivityMeasurements Performed by Twenty-FiveLaboratories." The Log Analyst, Jan.-Feb. 1988.
Hitchon, B. "Geothermal Gradients,Hydrodynamicsand Hydrocarbon Occurrences,Alberta, Canada."AAPG Bull., Vol. 68. 1984.
International Human Resource DevelopmentCorp.VideoLibrary for Exploration & ProductionSpecialists: Cranquist, C. "Reserves Estimation,"PE508; Fowler, P.T., Hepburn, J.R., and Morrill,D.C. "Subsurface Mapping," GLZ02; Bradley,M.E., and Anstey, H.A. "Seismic Contouring,"GP502; Boston, MA.
James, S.C. "A Rapid Accurate Unsteady StateKlinkenberg Permeameter."SPEJ, No. 12, 1972.
Keelan, D.K. "A Critical Review of Core AnalysisTechniques." Paper presented at 22nd AnnualTechnicalMeeting ofPetroleum SocietyofCIM,Banff,AB, Jun. 1971.
345
Link, P.K. Basic Petroleum Geology. OGCIPublications, Tulsa, OK, 1982.
Maier, L.F. "Recent Developments in theInterpretation and Application of DST Data."JPT, Nov. 1962.
Majorowicz, J.A., Jones, F.W., and Jessop, A.M."Preliminary Geothermics ofthe SedimentaryBasins in the Yukon and Northwest TerritoriesEstimates from Petroleum Bottom-holeTemperature Data." Bull. ofCan. Pet. Geol., Vol.36,1988.
Majorowicz, J.A., Jones, F.W., Lam, H.L. and Jessop,A.M. "The Variability of Heat Flow BothRegional and With Depth in Southern Alberta,Canada: Effect of Groundwater Flow?"Tectonophysics, Vol. 106, 1984.
Mitchell-Tapping, H.J. "Porosity and PermeabilityRelationship to Cleaning Effectiveness in WholeCore Analyses." Log Analyst, May-Jun. 1982.
Murphy, R.P., and Owens, W.W. "The Use of SpecialCoring and Logging Procedures for DefiningReservoir Residual Oil Saturations." JPT, 1973.
Ruth, D.W., and Kenny, J. "The Unsteady State GasPermeameter." 38th Annual Technical Meeting,Petroleum Society of CIM, Calgary, AB, Paper87-38-52, Jun. 1987.
Scheidegger, A.E. The Physics ofFlow ThroughPorous Media (3rd ed.). University of Toronto,Toronto, ON, 1960.
Schlumberger. "Roundtable: Strategies for Thin-BedFormation Evaluation." Oilfield Review, Jul.1991.
Scholle, P.A., Bebout, D.G., and Moore, C.H. (ed.)."Carbonate Depositional Environments." AAPG,Memoir 33, 1983.
Schowalter, T.T. "Mechanics of SecondaryHydrocarbon Migration and Entrapment." AAPGBulletin, Vol. 63, No.5, May 1979.
Scientific Software. Reservoir Engineering Manual.NTIS PB - 247-806. 1975.
Walker, R.G. (ed.). "Facies Models." GeoscienceCanada. Reprint Series I, 1979.
Worthington, P.F. "Effective Integration of Core andLog Data." SCA Conference, Paper No. 9102,1991.
346
DETERMINATION OF Oil AND GASRESERVES
Carbon Dioxide Flooding
Holm, L.W. "CO, Flooding: Its Time Has Come."JPT, Dec. 1982.
Klins, M.A. Carbon Dioxide Flooding - BasicMechanisms and Project Design. InternationalHuman Resource Development Corporation,Boston, MA, 1984.
Mungan, N. "Carbon Dioxide Flooding _Fundamentals." JCPT, Jan. - Mar., 1981.
---. "Carbon Dioxide Flooding - Applications."JCPT, Nov. - Dec. 1982.
Stalkup, F.1. "Carbon Dioxide Miscible Flooding:Past, Present, and Outlook for the Future." JPT,Aug. 1978.
Crude Oil MarketsCanadian Petroleum Association. 1991 Statistical
Handbook. Calgary, AB, 1992.
Energy Resources Conservation Board. AlbertaEnergy Resource Industries. Monthly Statistics,Calgary, AB.
---. Selected Statistics and Forecasts. Calgary,AB,1991.
Petroleum Monitoring Agency Canada. CanadianPetroleum Industry. 1991 Monitoring Report.Minister of Supply and Services Canada, Cat. No.M2722/1991-2E, ISBN 0-662-19847-6, 1992.
Statistics Canada. The Crude Petroleum and NaturalGas Industry. Minister of Industry, Science andTechnology, Cat. No.26-213 Annual, ISSN0068-7103,1992.
Hydrocarbon Miscible FloodingBlackwell, R.J., Wall, T., Rayna, J.R., Lindley, D.C.,
and Anderson, J.R. "Recovery of Oil byDisplacement with Water Solvent Mixtures."Trans., AIME, Vol. 21,1960.
Brigham, W.E., Reed, P.W., and Dew, J.N."Experiments on Mixing During MiscibleDisplacement in Porous Media." Trans., AIME,Vol. 222; SPEJ, Mar. 1961.
Claridge, E.L. "Prediction ofRecovery in UnstableMiscible Flooding." SPEJ, Apr. 1972.
---. "Design of Graded Viscosity Banksfor Enhanced Recovery Processes." Ph. D.Dissertation, University of Houston, Houston,TX, Jul. 1979.
q
r
BIBLIOGRAPHY
Craig, F.E. Jr. "A Laboratory Study of GravitySegregation in Frontal Drives." Trans., AIME.Vol. 210,1957.
Gardner, A.a., Jr., Peaceman, D.W. and Pozzi, A.L.Jr. "Numerical Calculation of MultipleDimensional Miscible Displacement by theMethod of Characteristics." SPEJ, Mar. 1964.
Koval, E.J. "A Method for Predicting thePerformance of Unstable Miscible Displacementin Heterogeneous Media." Trans., AIME, Vol.228; SPEJ, Jun. 1963.
Peaceman, D.W., and Rachford, H.H., Jr. "NumericalCalculation of Multi-dimensional MiscibleDisplacement." Trans., AIME, Vol. 225; SPEJ,Dec. 1962.
Pozzi, A.C., and Blackwell, R.J. "Design ofLaboratory Models for Study of MiscibleDisplacement." SPEJ, Mar. 1963.
Shelton, J.L. and Yarborough, L. "Multiple PhaseBehaviour in Porous Media During CO, or RichGas Flooding." JPT, Sep. 1977.
Thermal StimulationEdmunds, N.R. "An Analytical Model of the Steam
Drag Affecting Oil Sands." Paper presented at the34th Annual CIM Technical Meeting, Banff, AB,May 1983.
347
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Abdassah,D., 234, 235Abramowitz, M., t93, 196Adamache, I., 179, 180Adams, R.H., 188, 196Agbi, B., 227, 235Aguilera, R. 214, 220Aitcheson, 1,107,119,232,235AlbertaEnergy,257-259, 265Alberta Petroleum Marketing Commission,
291,293,296Alexander, L.G., 345Ali, S.M., 190, 196Amaefule, J.O., 48, 52American Petroleum Institute, 53, 54, 55,
64,78,80,237,249,345Amyx, J.W., 96, 100,345Anderson,J.H., 179, 180Anderson,J.R., 346Anderson,W.G., 161, 169Archer,J.S., 345Archie,G.E., 66, 74Aronofsky,lS., 167-169Arps, J,J., 224, 225, 235, 238, 249Arshi, A.A., 294, 296Asgarpour, S.S., 177-180,206,213Attanasi,E.D., 279, 280Au, A.D.K.,215, 220Aziz, K., 92, 95,187,188, t92, 197,214,
215,220
Babu, D.K.,207, 212Balay,R.H., 277, 279Bankhead, C.C., Jr., 345Barclay,J.E., 232, 236, 243, 246, 250, 278,
280Bass, D.M., 96, 100,345Bebout, D.G., 346Beeler, P.F., 179, 180Behie,A., 215, 220Belvins,T.R., 188, 190, 197, 198Belyea, H.R., 188, 197Bennett, F.. 179, 180Bielecki,1, 205, 209, 212Bilozer, D.E., 179, 180Bird, K.I., 279Blackwell,R.I., 235, 236, 346, 347Bloy, G., 179,180Boberg,T.C., 188, 197Bobrowski, F.P., 96, 100Bodily, S.E., 108, 119Bokhari,S.W., 179, 181Bournazel, C., 139, 144Bousaid, 1., 195, 198
AUTHOR INDEX
Bowers, B., 205, 209,212Boyd, W.E., 153Bozac, P.G., 176, 181Brigham, W.E.,346British Columbia Ministry of Energy, Mines
andPetroleum Resources, 257.265Broomhall,R.W., 179, 181Brown,J.A.C., 107, 119,232,235Brown, S.L., 188, 199Bruskotter, J.F. 152, 153Buckles,R.S., 102,105, 188, 197Bujnowicz, R., 345Burger,D.H., 179,181Burns, lA., 188, 197Bursell, C.G., 190, 197Buskirk,D.L., t79, 180Butler,R.M., t88, 189,191, 194, 197,207,
208,212Butler,S., 179, t80
Calhoun,i.c, Jr., 345Campbell,A.D., 271, 279Campbell,J.M., 268, 278, 279, 345Canadian Petroleum Association, 346CanadianWell Logging Society,79, 80Cao, S., 85Capen,E.C., 108, It9, 274, 279Card, C., t78, 180Cardwell, W.T., 188, 197Carter, R.D., 125, 127, 138, 144, 153, 164,
169,170,176,181,185Celbuliak,N., 345Chaney, P.E., 139, 144Chaperon.L, 207, 212Chapman,D.S., 82, 83, 85Chase,C.A., 214, 220, 221Chen, S.M., 178, 180ChevronCanadaResources, 94, 96, 97Chierici, G.L., 139, t44Chin, T., 96, 100Chinna, H., 190, 198Christian,L.D., 153Christie, D.S., 212, 213Christie,J.A., 243, 246, 249Chu, C., 190, 197Ciucci, G.M., 139, 144Claridge,E.L., 176, 180,346Clark, I., 275, 279Clark, N.I., 145, 153Closmann,P.J., 188, 190, 199Coats, K.H., 188, 198,214,217,220Collins, R.E., 168, 169ComputalogGearhartLtd.,49, 52
Conn, R.F., 243, 246, 249Cook, A.B., 96, 100Coonibie, D., 188-190, 198Cooper, H.E., 176, 181CoreLaboratories, 345Cornelius,A.J., 139, 144Cornell, D., 146, 153Cornish, R.G., 179, 182Craft, B.C., 97, '100, 125, 127, 147, 153,
345Craig, F.E., Jr., 347Craig, F.F., 138, 144, 155-161, 164, 169,
176,180,185Crawford, P.B., 168, 169, 188, 197Crawly, A., 177, 180Crichlow, H.B., 214, 220Cronquist, C., 83, 85Crovelli, R.A., 277, 279Curran, R., 255, 265
Dalton, R.L., 214, 221Danielsen, C.L., 153Dardaganian, S.G., 161, 169Davis, J.C., 275, 279Davis, M.I., 228, 236Davis, R., 179, 180Dawson,A.G., 179, 180de Swaan, A., 167, 169Deans, H.A., 175, 181Deeds, C.T., 188, 190, 199Deming, D., 82, 83, 85Dempsey,J.R., 217, 220Denbina, E.S., 188, 197Derocco, M., 188, 189, 198Des Brisay, e.L., 139, 144Dew, J.N., 346Dietz, D.N., 138, 140, 144Dillabough,lA., 189, 197Dolton, G.L., 279Dore, T.L., 195, 198Doscher,T.M., 188, 197Dranchuk,P.M., 92, 95Drew, L.J., 268, 278, 279Duerkson,J.H., 188, 189, 198Dugdale, P.I., 194, 197Duggan, J.O., 148, 153Dullien, F.A.L., 345Durrant,A.I., 187, 197Dyes, A.B., 168, 170, 176, 181, 185Dykstra, H., 188, 197
Edmunds,N.R., 347Elenbass,r.a., 146, 153Elfrink, E.B., 137, 144
349
Ellis, H.E., 137, 144Enderlin, M.B., 345Energy Resources Conservation Board, 82,
85,102,105,152,153,161,170,237,240,241,249,253,345,346
Energy, MinesandResources Canada, 290,291,296
Enger, S.R., 179, 181Erikson, R.A., 176, 181, 185Ershagi, 1.,234, 235Espiritu, R., 208, 212
Fabes, L., 194, 197Farouq Ali, S.M., 187, 188, 197Farquharson, R.G., 194, 197Fatt, 1.,345 'Fetkovich, MJ., 230, 235Flach, P.O., 209, 212, 213Fang, O.K., 179, 181Fontanilla, J.P., 187, 197Freeborn, R., 207, 212Frydl, P.M., 179, 180
Garb, FA, 266, 269, 277, 279Gardner, A.a., Jr., 347GasProcessors Suppliers Association, 91,
95,151,153Gates, C.F., 194, 197Gatlin, C., 345Geffen, T.M., 185Gentry, R.W., 224, 225, 227, 235Geoghegan, J.G., 179, 180Geotechnical Resources Ltd., 56, 64Gilman, J.R., 215, 221Gontijo, J.E., 188, 192, 197Goodrich, J.H., 152, 153Gould, T.L., 160, 170Griffith, J.D., 179, 181Guerrero, E.T., 150, 153,238,249
Habermann, B., 176, 181Hamblin, A.P., 232, 236, 243, 246, 250,
278,280Hamp, T., 345Hamilton, J.M., 62, 64Hankinson, R.W., 92, 95Hanna, M., 194, 198Hanson, O.K.T., 345Haun, J.D., 278, 279Havlena, D., 126. 127Hawkins, M.F., 97,100,125,127,147,
153,345Henderson, J.H., 217,220Henley, D., 138, 144Hensel, W.M., Jr., 345Henson, W.L., 139, 144Hermanrud, C., 85Herring, T.R., 207, 212Heseldin, G.M., 68, 74Heyse1, M., 208, 212Higgins, R.V., 164, 170
350
Hitchon, B., 345Hahn, M.E., 275, 279Holander, D.P., 345Holm, L.W., 204, 346Honarpour, M.M., 345Home, A.L., 179, 181Home, J.S., 195, 198Homer, D.R., 87, 90Houghton, J.e., 279Howe, G.R., 176, 181Hoyt, B.P., 345Hurst, W., 125, 127, 138, 144Hutchinson, C.A., 124, 127Hutchinson, T.S. 138, 144
International Human ResourceDevelopment Corp., 345
Isaaks, E.H., 275, 279Ivory, J., 188, 189, 198
Jack, H.H., 215, 221Jackson, D.D., 179, 180James, S.G., 345Jeanson, B., 139, 144Jenkins, G.R., 194, 196, 198Jenkins, M.K., 176, 181Jessop, A.M., 346Johnson, W.M., 188, 198Jones, F.W., 82-85, 346Joshi, S.D., 206-209, 212Jung, K.D., 194, 197
Kadane, K.B., 274, 279Kahneman, D., 266, 280Katz, D.L., 96, 100, 146, 153Kazemi, H., 215, 221Keefer, D.L., 108, 119Keelan, D.K., 48, 52, 345Kemp, C.E., 138, 144, 168, 170Kennedy,P., 179, 180Kenny, J., 346Kersey, D.G., 48, 52Khallad, A., 188, 194, 197, 199Khan, A.M., 188, 196Khan, A.R.• 138, 144Kimbler, O.K., 176, 181Kirkpatrick, J.W., 194, 196, 198Klins, M.A., 204, 346Kobayashi, R., 146, 153Koval, EJ., 176, 181,347Krukowski, J.V., 261, 265Kuhme, A., 179, 180Kular, G. 188-190, 198Kuo, M.C.T., 139, 144, 161, 170,208,212Kyte,J.R., 167,170
Lai, F.S.Y., 179, 181Lake, J.W., 214, 221La1, F.S., 179, 182Lam, H.L., 82-85, 346Langenheim, R.W., 191, 198
DETERMINATION OF OIL AND GAS RESERVES
Lantz, R.B., 188, 197Laurie, R.A., 179, 180
Lee, P.J., 232, 236, 243, 246, 250, 278, 279280 '
Leighton, AJ., 164, 170Lerche, I., 85Leverett, M.C., 69, 74Lewis, D., 179, 180Lindley, D.C., 346Link, P.K., 346La, H.Y., 188, 191, 194, 197, 198Loder, W.R., 179, 180Lohec, R.E., 234, 236Long, D.R., 228,236Longstaff, WJ., 178, 182,214,221Lowe, K., 188-190, 198Lusztig, P.A., 264, 265
Ma, T.D., 179, 181MacDonald, A.J., 207, 212Mahaffey, J.L., 176, 181Maier, L.F., 346Mainland, G.G., 188, 198Majoros,S., 175, 181Majorowicz, J.A., 82, 83, 85, 346Mallimes, R.M., 179, 181Marschall, D.M., 48, 52Marshal, D., 138, 144Martinsen, R., 207, 212Marx, J.W., 191, 198Masse, L., 167-169Mast, R.F., 279, 280Masters, C., 278, 279Mathews, C.W., 176, 181Mattax, c.c., 167, 170,214,215,221Mayder, A., 345McCord, D.R., 96, 100McCray, AW., 266, 274-278, 280McCrossan, R.G., 239, 249Mcintyre, FJ., 171, 180, 181McKibbon, J.H., 126, 127, 194, 196, 198McNab, G.S., 188, 191, 194, 197Mead, N.H., 224, 235Megill, R.E., 275, 278, 280Mehra, R.K., 194, 198Meisingset, K.K., 85Meldau, R.F., 190, 196, 198Merrick, RJ., 153Metwally, M., 194, 198Miller, B.M., 278, 280Miller, C., 257, 265Mitchel-Tapping, HJ., 346Mollins, L.D., 137, 144Moore, C.H., 346Moore, D.W., 185Morse, RA, 185Mosteller, F., 274, 280Mukherjee, D., 180, 181Mungan, N., 204, 346Murphy, R.P., 346
AUTHORINDEX
Muskat, M., 137, 139, 144Mutalik, P., 206, 207, 213Myhill, N.A., 190, 191, 198
Nagel, R.G., 179, 181Natanson, S.G., 167-169National Energy Board, 289, 290, 294-296National Energy Board Act, 290, 296Newendorp, P., 266, 274-278, 280Ng, M.C., 227, 235Nieman, R.E., 179, 181Noble, M.D., 139, 144Nolen, J.S., 214, 221
Odeh, A.S., 126, 127,207,212Oglesby, KD.,,188, 198Okazawa, T., 176, 179, 181Olynyk, J., 178, 180Osadetz, KG., 232, 236, 243, 246, 250,
278,280Owens, W.W., 138, 144,346O'Dell, S., 257, 265
PanCanadian Petroleum Ltd., 59, 60, 68, 70Papatzcos, P., 207, 212Papst, W., 178, 180Parker, J.R., 278, 280Parson, R.L., 188, 197Patel, R.S., 179, 181Patzek, T.W., 189, 198Paxman, D.S., 126, 127Pearse, J., 257, 265Peggs, J.K., 179, 181Perry, G.E., 152, 153Petroleum Communication Foundation,
287,296Petroleum Monitoring AgencyCanada, 346Phillips, K.A., 92, 95Pirson, S.J., 137, 144, 185Pittman, G.M., 190, 197Pizzi, G., 139, 144Ploeg,J.F., 188, 189, 198Podruski, J.A., 232, 236, 243, 246, 250,
278,280Poettman,F.H., 146, 153Poon, D.C., 207, 212Pope, J.A., 178, 180Porter, KE., 212, 213Pow, M., 179, 180Powell, J.D., 48,52Pozzi, A.L., 347Prats, M.A., 188, 189, 193, 197, 198Pritchard, D.W.L., 179, 181Procter, R.M., 232, 236, 243, 246, 250, 278,
280Province of Alberta, 257, 258, 265Pursley, S.A., 188, 198Purvis, R.A., 92, 95, 229, 231, 236
Rachford, H.H., Jr., 347Railroad Commission of Texas, 152, 153
Ramey, H.J., 188, 199Rawlins, E.L., 151, 153Rayna, J.R., 346Reed, P.W., 346Reinbold, E.W., 179, 181Reisz, M.R., 211, 212Renke, S.M., 179, 181Rice, D.D., 278, 280Rice, T.D., 139, 144Richardson, J.G., 235, 236Roberts, T.G., 137, 144Robertson, S., 228, 236Robinson, D.B., 92, 95Robinson, J.G., 266, 280Rock, N.M.S., 275, 280Roebuck, LF., 185Rogers, E.E., 188, 198Romney, G.A., 194, 196, 198Root, D.H., 279, 280Root, P.J., 214, 221Rotter, M.B., 188, 197Rubin, 8., 215, 220Russell, B., 207, 208, 213Russell, D.G., 152, 153Ruth, D.W., 346Rutherford, W.M., 176, 181
Saizew, H., 194, 197Sander, P.R., 189, 190, 198Sanderlin,J.L., 185Sarern, A.M.S., 160, 170Saskatchewan Energy and Mines, 257, 265Scheidegger, A.E., 346Schellhardt, M.A., 151, 153Schilthuis, R.J., 125, 127, 137, 138, 144Schlumberger of Canada, 44, 52Schlumberger, 64, 67, 72, 74, 346Schoemaker, R.P., 225, 226, 235Schoeppel, R.I., 165, 170Scholle, P.A., 346Schowalter, T.T., 346Schuenemeyer, J.H., 279Schwab, B., 264, 265Scientific Software, 346Scott, G.C., 212, 213Scott, G.R., 292, 296Scott, K., 188, 189, 198See,D.L., 179, 181Sepehrnoori, K., 214, 221Seto, A.C., 176, 181Settari, A., 214, 215, 220Shaw, J., 345Shell Development Company, 51, 52, 71, 74Shepherd, D.W., 188, 198Shelton, J.L., 347Shipley, R.G., 188, 198Shreve, D.R., 185, 186Silberberg, LH., 138, 144Singhal, A.K., 178, 180,206,213Skjaeveland, S.M., 207, 212
Slider, H.C., 158, 160, 170, 226, 236Sluijk, D., 278, 280Smith, L.B., 195, 198Smith, L.R., 152, 153Smith, O.J.E., 215, 221Smits, L.J.M., 72, 74Sobocinski, D.P., 139, 144Sorensen, L.E., 179, 181Spencer, G.B., 96,100Spetzeler, c.,269, 280Springer, S.J., 178, 180,206,209,213Sprinkle, T.L., 153Sprunt, E.S., 345Srivastava, R.M., 275, 279Stael von Holstein, c., 269, 280Stalkup, F.L, 175, 181,204,346Standing, M.B., 92, 93, 95, 96, 100Statistics Canada. 346Stegeimeier, G.L., 190, 191, 198Stegun, LA., 193, 196Stewart, J.M., 62, 64Stiff, H.A., 79, 80Stiles, W.E., 186Stoian, E., 247, 250Stokes, D.D., 190, 198Stone, H,L., 176, 181,216,221Suffridge, F.E., 189, 196Suprunowicz, R., 208, 212Surface, R.A., 194, 197
Tarvydas, R., 257, 265Taylor, o.c, 232, 236, 243, 246, 250, 278,
280Taylor, H.G., 179, 182Telford, A.S., 247, 250Thambynayagam, C., 187, 197Thele, K.J., 214, 221Thomas, H.K., 92, 95Thornton, R.W., 194, 197Tiffin, D.L., 178, 181Todd, M.R., 177, 178, 180, 182,214,220,
221Towson, D., 186, 199Tracy, G.W., 125, 127, 137, 144Trimble, A.E., 190, 197Tsang, P.W., 179, 181Tversky, A., 266, 280
University of Calgary and CanadianPetroleum Tax Society, 262, 265
Valencia, L.E., 48, 52Van Dijk, c., 190, 199Van Everdingen, A. F., 125, 127Van Regan, N., 179, 180Vary, J.A., 146, 153Vinsome, P.K.W., 215, 220Vogel, J.V., 190, 191, 199Vokey, G., 345
Wahl, W.L., 137, 144
351
Walker, R,G" 346Wall, T., 346Wang, P.C.C., 278, 279Warren, A., 248, 250Warren, I.E., 107, 116, 119,214,221Wattenburger, R.A., 207, 208, 213Waxman, M.H., 72, 74,188,190,199Weinaug, C.F., 146, 153Weinmeister, M., 42, 43Welch, L.W., 185, 186
Welge, H,J., 138, 140, 144, 185, 186Whiting, R.L., 96, 100, 345Wichert, E., 92, 95Willhite, G.P., ISS, 158, 170, 187, 199Williams, R.L., 188, 199Witte, M.D., 164, 169Wong, A., 194, 196, 198Wong, F.Y., 179, 181Wong, T., 178, 180
Wood, K.N., 179, 182Woodford, R.B., 179, 182Worthington, P.F., 346Wuckoff, R.D., 139, 144
Yang, W., 207, 208, 213Yarborough, L., 152, 153,347York, C.E., 345Youngren, G.K., 214, 221Youtz, c, 274, 280
c
abandonment, 264abandonmentpressure, 148, 247absolute minimum/maximum value
approach, 107absolnteopen flow test, 77absolutepermeability, 216acceleration project, 310accounting
full-cost, 316successful-efforts, 317
accounting requirements, 316acoustic log, 57acquisition
of data, 46, 55, 96acquisition of data, 35actual value, 268additives, 189adjustedattributedCanadianroyalties
and taxes, 260age, 258aggregators, 297Albertaagencies, 281Albertaroyalty tax credit, 260allocationfactors, 223analogous
fields, 36pool, 249pools, 163reservoir, 22
analogous reservoirs, 17analogy, 132, 244
geologic, 278analysis
compositional, 77. 80decline, 132, 136, 137, 139, 162Homer, 88of data, 36, 82, 96pressure transient, 36PVT, 77statistical, 107volumetric, 158Warren's probability, 107
analyticalmethods, 137, 138, 140, 156performance predictions, 164transient type curves, 230water influx models, 124
apparatusDean Stark, 65, 66risingbubble, 174
SUBJECT INDEX
approachabsolute minimum/maximum
value, 107single-value, 106
aquifers, 124Archie equation, 66, 69area-weighted average, 90areal extent, 112areal sweep efficiencies, 167-168areal yield methods, 278arithmeticaverage, 90arithmeticmethod, 8asphaltenes in carbon dioxide
flooding, 203associated gas, 29, 145associated gas reserves, 150assumptions, 120
constant reservoir volume, 121constant temperature, 121material balance, 121pressure equilibrium, 121reliableproduction data, 121representative PVTdata, 121
attributedCanadianroyaltyincome, 259auditing evaluations, 314average
Albertamarketprice, 257area-weighted, 90arithmetic, 90porosity, 216recovery factors, 240reservoir pressure, 89volume-weighted, 90
backpressure testing, 152balancesheet, 263barrelsof oil equivalent, 318bestestimate, 11bias, 268
central, 269cognitive, 271displacement, 269motivational, 269variability, 269
bitumen, 46, 72, 103, 187black oil
simulation, 177simulators, 214
borehole environments, 49borrowing, 314bottom water, 190
bottom-holepressure, 49temperature, 49, 81
bottom-water drive, 239break-through
carbon dioxide flooding, 203ratio, 177
bubblepoint, 97Butler model, 194by-product. See related product.
calculationof initial solution gas in place, 29of oil in place, 28
calendar-day ratedefinition of, 223
calipermethod, 57call option, 295Canadian
crude oil exports, 291development expense, 261exploration anddevelopment overhead
expense, 263exploration expense, 261oil andgas property expense, 261refining, 290
capillaryeffects, 37capillarypressure, 27, 67
data, 216capital cost allowance, 263capital costs, 256carbon dioxide
availability and cost, 202flooding, 200, 202
carbonateplugging in carbon dioxide
flooding, 203pools, 242
carried interest, 254cash flow, 253, 255causesof failure
in situcombustion process, 196ceiling tests, 316central tendency, 240characteristics
flow, 75hydrocarbon, 131of naturalgas, 145reservoir, 131
chasegas slug size, 178chemicalmethod, 65-66
353
classificationempirical, 273of cumulative production, 7of miscible hydrocarbon reserves,of reserves, 4of resources, 4
clastic pools, 242clay
Dual Water Model, 72presence of, 72swelling, 54
closed-chamberdrillstemtests, 75combination
drive, 134, 135, 140of forward combustion and
waterflooding, 195combined
methods, 278thermal drive, 195
combustion processenriched air, 195in situ, 194
commoditypricing, 253compaction drive, 134company
grossremaining reserves. 7netremaining reserves, 7
compositionalanalysis, 77, 80simulator, 177, 214
compressibilityfactor, 28fornatural gases. 93
computermapping, 42computer simulation
Monte Carlo, 107, 206computer solutions, 127conditions
in situ, 63confidence level. 9conformance efficiency, 160, 163conical steam zone model, 191coningand cresting, 207connate water saturation, 65conservation controls, 283Conservation of Mass
Law of, 149Conservation of Matter
Law of, 120constant
reservoir volume. 121temperature, 121
constant andvariable rate test, 77contacts
fluid, 48tilted oil-water, 38
conventional crude oil, 287core, 45, 47. 50
analysis. 55markets, 297oil-base, 102
354
permeabilityfrom, 101porosity data. 58porosity from. 101
179 saturations from, 102coring
oil-base, 65correlation of log and coreporosity, 62corrosion
in carbon dioxide flooding, 203costs
capital, 256facility operating, 256field, 256finding, 317general andadministrative, 256intangible, 263operating. 256replacement, 317sunk. 309tangible, 263well abandonment. 256
Craig-Geffen-Morse Method, 164cresting
coning and, 207loss, 207
cross-contouring, 39cross-plot
neutron-density. 58Crown
interest, 254royalty, 7-8
crude oilconventional, 287density of conventional, 241exports
Canadian, 291light, 287markets, 253, 287nonconventional, 288oxidation of, 195prices, 255production, 288royalty, 258
cumulative production. 7curve
relative frequency, 30curves
analyticaltransient type, 230empiricaldepletiontype, 230
cutcurvesdefinition of, 223
cutoffvalues, 28cutoffs
permeability, 46porosity, 45
cutoffs, 102cyclic steam stimulation, 187cycling
of gas condensate reservoirs, 152
DETERMINATION OF OIL AND GASRESERVES
daily rates, 222D' Arcy's Law, 53data
acquisition of. 35, 46analysis of, 36, 58, 82capillary pressure. 216coreporosity, 58interpretation of, 48pressure buildup, 86productionand well, 216-217PVT, 120quality of, 85reliability of, 31, 63, 101, 121,
136, 157, 237rock compressibility, 216seismic, 35source of, 31, 81
data acquisition. 58database, 57, 168, 237
Energy Resources ConservationBoard, 58
Dean Starkapparatus, 56, 65, 66technique, 65
decision matrices, 276decision trees, 277decline
analysis, 136, 137, 139, 162exponential, 20, 225-226harmonic, 20, 229hyperbolic, 226-229
declinecurveanalysis, 18, 132definition of, 223methods for a group of wells, 231methods for a single well, 224source of data for, 222
deficiencies, 308definingnet pay, 45degree of uncertainty, 266Delphi Method, 274, 278density
log, 57of conventional crude oil. 241
depletioncalculations, 317immature, 157mechanism, 206
depletionstrategy, 131planning, 132purpose, 131
depositional environments, 36, 242deregulation, 291, 298
Canadian, 299United States, 299
deterministicprocedure, 8, J(}-II, 30developed
nonproducing reserves, 6producing reserves, 6reserves, 6
•
167-168167, 201167-168
SUBJECT INDEX
dew-point reservoirs, 146diagenesis, 37diagram
multi-contact ternary, 174P-X, 173ternary, 173
Dietz Method, 138, 140differentialliberation, 97
process, 97test, 79
dimensionless solutions, 230dippingfaults, 39discount
rate, 264discounted
netprofit before investmentdistribution, 116
return on investment, 308discovered resources, 5displacement
efficiency, 167, 175, 201process, 154
domestic needs, 284drainagevolume, ·72drawdowntest, 77drilling
incentives, 285rotary, 75
drillstemtest, 75, 104closed-chamber, 75open-hole, 72
drivebottom-water, 239combination, 134, 135, 140combinedthermal, 195compaction, 134dissolvedgas, 201edge water, 239expansion, 239gas cap, 134, 140, 239gravitysegregation, 238solutiongas, 133, 207, 238steam, 195water, 134, 137
drivemechanism, 147natural, 247
drive mechanismsnatural, 238primary, 238
dry gas, 152reservoirs, 145
Dual Water Model, 72dual-porosity formulation, 214dynamic implicitmethod, 215
earneddepletion, 263economic
development, 282evaluations, 119limit, 142
sensitivity cases, 8uncertainty, 266
economic conditions, 8economically recoverable reserves, 253economics, 206edge water drive, 239effect
Forcheimer, 53K1inkenberg, 53
effectivenet pay, 102permeability, 53porous zone, 102porous zones, 103
efficienciesareal sweep,displacement,vertical sweep,
efficiencyareal sweep, 202conformance, 160, 163displacement, 175, 201recovery, 203vertical sweep, 202volumetric sweep, 177, 202
electricalconductivity, 27method, 65-66
electromagnetic heating, 196empiricalclassification, 273empiricaldepletion type curves, 230energy equivalence, 9energyequivalent, 318Energy Resources Conservation
Board, 58, 281coreand cuttings storage, 58reserve database, 237
engineering uncertainty, 266enhanced
gas recovery, 153oil recovery, 131, 171oil recovery simulators, 214
enriched aircombustion process, 195environment
regulatory, 253environments
borehole, 49depositional, 36, 242
equationArchie, 66, 69material balance, 17, 120, 122of state, 178volumetric, 108, 158, 175WylieTime-Average, 58
equivalentbarrelsof oil, 318energy, 318gas, 9oil, 9
errorsin logs andcoreanalysis, 64in material balance method, 123sources of, 123, 268
estimatebest, 11single, 11single-value, 107volumetric, 106
estimated value, 268estimates
materialbalance, 30refinement of volumetric, 43uses of resource, 31volumetric 27
estimation of uncertainties, 178evaluation
of explorationwells, 313of undeveloped lands, 278of unexploredlands, 313
evaluators, 11, 31, 34, 315expansion drive, 239expectation, 266experimental methods
miscibility, 173exponential decline, 20, 225-226exports
to the USA, 286extraction, 201
facilityoperating costs, 256sizing, 142
factoraverage recovery, 240compressibility, 28formation, 66formation volume, 28, 105, 122gas compressibility, 28, 91, 105gas deviation, 91, 113gas formation volume, 91, 94oil formation volume, 96oil recovery, 239recovery, 17, 31, 168, 210shrinkage, 96
failurecyclic steam stimulation andsteam flood
process, 190, 196fair market value, 312faults
dipping, 39FederalCompetition Act, 285federalgovernment, 281fence option, 295field
costs, 256examples, 188
fieldperformanceof miscible floods, 179
financial statements, 263
355
finding costs, 317finesmigration, 53finite-difference method, 215first-contact miscible process, 172fiscal policies, 285flash liberation process, 97flash liberation test, 79flood
oil saturation atthestart of, 160flooding
carbon dioxide, 200, 202hydrocarbon miscible, 171micellar, 154, 168polyroer, 154, 168
floodshorizontal, 162horizontal miscible, 172vertical miscible, 171
flowcharacteristics, 75distribution, 206regimes, 72tests, 36, 46, 70
fluidcontacts, 48expansion, 133interface, 37invasion, 247properties, 216saturation, 27
fluid expansion,gas pools, 247
Forcheimer effect, 53forecasting
gas de1iverability, 151models, 191reserves and production, 132reservoir performance, 219
formationfactor, 66fluid saturation, 216heterogeneity, 50resistivity index, 67thin, 190volumefactor, 28, 105volume factors, 122water resistivities, 79, 103
forward combustion andwaterfloodingcombination of, 195
fractional flow, 155fracturepermeability, 63fractured reservoirs, 63fractures, 55FreeTrade Agreement, 286freehold
interest, 254royalty, 7-8, 260
frontaldisplacement model, 191frontieroil, 288fully implicitmethod, 215
356
futureinitial volumes in place, 5unrecoverable volumes, 5
future initial reserves, 5futures, 294-295
gasanalyses, 78associated, 29, 145compressibility factor, 28, 91, 105cost allowance, 258cresting, 208deliverability forecasting, 151deviation factor, 91, 113dry, 145, 152equivalent, 9expansion method, 57flow rate, 151formation volume factor, 91, 94marketers, 306, 307new, 257nonassociated, 29, 145old, 257permeabilities, 53permeability, 53prices, 255recovery, 147reserves, 148reservoirs, 123samples, 78saturation, 113secondary recovery of, 153solution, 28, 145sour, 92, 145sweet, 145wet, 145
gas cap, 124, 145, 190drive, 134, 140, 239secondary, 145
gas drivedissolved, 201
gas in placecalculation of initial solution, 29
gas in place, 113gas-oilcontact, 38gas-oil interface, 37gas-water injection
alternate, 202gas-water interface, 37gauge
electronic, 86mechanical, 86
general and administrativecosts, 256geochemical material balance
methods, 278geologicanalogy, 278geological
mapping, 39model, 177period, 243
DETERMINATION OFOILAND GASRESERVES
play, 243uncertainty, 266
Geological Surveyof Canada, 282geophysical log method, 65glaze, 101going concern value, 311government agencies, 32governments, 306
federal, 281" provincial, 281
gravity, 258, 287gravity override, 195gravity segregation drive, 238grid
block orientation, 166block sizing, 166design, 217
grossoverridingroyalty, 254pay, 44remaining reserves, 7reservoir, 44swept volume, 160
half-lifereserves, 314
harmonicdecline, 20, 229heavy oil, 187, 287heterogeneous reservoir, 209Higgins-Leighton Method, 164historical performance, 278historymatch, 166history matching, 219history-matched simulation, 22horizontal floods schemes, 162horizontalmisciblefloods, 172horizontal sweep efficiency, 159horizontal waterflood schemes, 156, 159horizontalwells, 205
critical rates for, 207performance projection, 206producibility, 206uses of, 205yield from, 205
Horner analysis, 88HumbleMethod, 137hydrocarbon
characteristics, 131miscible flooding, 171pore volume maps, 39
hydrocarbonsin place, 28, 118presence of, 14
hydrodynamic flowtrapping, 38hydrodynamics, 84hyperbolicdecline, 226-229
Ideal Gas Law, 28, 91imbibition, 167immature depletion, 157
a
SUBJECT INDEX
immisciblecarbon dioxide flooding, 200gas injection, 183
Implicit Pressure Explicit SaturationMethod, 215
in situ combustion process, 194in situ conditions, 63income tax, 261incremental economics, 310industry databases, 57, 168, 237initial
reserves, 5solution gas in place, 29volumes in place, 5
injectionalternate gas-water, 202rates, 189
injection schemesdispersed gas, 183, 185external, 183, 185
injectivitylack of, 190
intangible costs, 263interest
carried, 254Crown, 254expense, 256freehold, 254net profits, 255overriding royalty, 254production payment, 254royalty, 254working, 254
interfacefluid, 37gas-oil, 37gas-water, 37oil-water, 37, 39
interfacial tension, 69, 154reduction in. 201
interference test, 77internal rate of return, 264International EnergyProgram, 286inventory. 7isnpach maps, 13, 38
J function, 69
Klinkenberg effect, 53
laboratory analysisof fluidproperties, 96
landcompensation, 285LatinHypercube Method, 277Law
D'Arcy's, 53IdealGas, 28, 91of Conservationof Mass, 149of Conservation of Malter, 120
leasing, 282lending, 314
lessor royalty. 7light crude, 287liquidpermeability, 53liquids
naturalgas, 22, 29lithology, 242log
acoustic, 57density, 57neutron, 57resistivity, 63
log analysis, 57logs, 46
petrophysical well, 16resistivity, 69wireline, 45
losssandwich, 161
low productivityallowance, 257
mapping, 38computer, 42geological, 39volumetric, 35
mapshydrocarbon pore volume, 39isopach, 13, 38mechanically contoured, 39porosity-thickness, 38structure, 38thermal gradient, 81
marketdemand forces, 297, 302mechanisms, 300value, 312
marketing options, 301markets, 290
core, 297, 300crudeoil, 287crudeoil, 253naturalgas, 297naturalgas, 253noncore, 300noncore, 300typesof, 300
Marshal Method, 138Marxand Langenheim model, 191material halance, 35, 105, 126,136,
139, 140assumptions, 121determination of hydrocarbons
in place, 120equation, 17, 120, 122estimates, 30method, 17, 149
materialbalance equationspecial cases of, 122
material halance method, 121, 123mathematicalfunctions, 215marrix permeability, 63maturewaterflood, 158
maximum royalty, 257mean, 11mechanisms
recovery, 188median, 11medium oil, 287MercuryArchimedes Method, 57Method
Craig-Geffen-Morse, 164Delphi, 274, 278Dietz, 138, 140Higgins-Leighton, 164Humble, 137Latin Hypercube, 277Marshal, 138Mercury Archimedes, 57ModifiedHurst, 138MonteCarlo, 11, 30, 212Musknt, 137Pirson, 137Robertsand Ellis, 137Schilthuis, 138Tracy or Tamer, 137VVarren, 107, 118VVedge, 138VVelge, 140
method. Seeprocedure.arithmetic, 8caliper, 57chemical, 65-66dynamic implicit, 215electrical, 65-66finite-difference, 215fully implicit, 215gas expansion, 57geophysical log, 65historical performance, 278implicit pressure explicit
saturation, 215material balance, 17, 121, 123, 149reservoir simulation, 22semi-implicit, 215statistical, 9, 231-233straight-line, 126, 127, 136summation-of-fluids, 57volumerric, 12, 148, 163, 175,
205, 209methods
analytical, 137areal yield, 278combined, 278experimental, 173geochemical materialbalance, 278of achieving miscibility, 172of analysis, 275theoretical, 234-235volumetric yield, 278waterflood prediction, 165
micellar flooding, 154, 168mineral rights
357
ownershipof, 254, 282subsurface, 254
mineral tax, 260minimumroyalty, 257miscibility
methodsof achieving, 172vapourizing multiple-contact, 173
miscible floodingcarbon dioxide, 200residual oil saturation after, 175
miscible floodsareal sweep efficiency for
horizontal, 175field performanceof, 179vertical sweep efficiency for
horizontal, 176miscibleprocess
first-contact, 172multiple-contact, 172
mobility ratio, 154, 175mode, 11, 240model
Butler, 194conical steam zone, 191dimensions, 166frontal displacement, 191geological, 177Marx andLangenheim, 191Myhill and Stegeimeier, 193phases, 166sensitivityanalysis, 218steamoverlay, 191uncertainty, 268Vogel, 194
models!D, 2172D areal, 2172D radial, 2172D vertical, 2173D, 218forecasting, 191
Modified Hurst Method, 138Monte Carlo
computersimulation, 30,107, 206,212, 277
multi-wellpools, 13multiple-contact miscible process, 172Muskat Method, 137Myhill and Stegeimeiermodel, 193
National Energy Board, 281natural depletion mechanisms, 131, 133natural drive mechanisms, 238, 247natural gas, 28
characteristics of, 145liquids, 22, 29, 151, 255markets, 253, 297royalty, 257
naturally fracturedreservoirs, 167
358
fracture system, 214matrix system, 214
near-misciblecarbon dioxide flooding, 200
negotiatingtool, 305net
overridingroyalty, 254pay, 44, 103, 112
effective, 102presentvalue, 264, 309profits interest, 255reservoir, 44
net-back calculation, 320neutron log, 57neutron-density cross-plot, 58new gas, 257new oil, 258New York Mercantile Exchange, 292nonassociatedgas, 29, 145nonassociated gas reserves, 148nonconventional crude, 288North American Free Trade
Agreement, 286numericalsimulation, 132, 137, 166NYMEX, 292, 294
oilage, 258equivalent, 9formation volume factor, 96frontier, 288heavy, 287medium, 287new, 258old, 258quality, 141rate, 206recovery factors, 239samples, 79synthetic, 288third tier, 258viscosity, 141
oil inplacecalculationof, 28
oil recoveryfactors affecting, 140primary, 237
oil sandsdeposits, 189royalty, 260
oil saturationat the start of flood, 160
oil-basecores, 102coring, 65
oil-steamratio, 193oil-water interface, 37, 39oil-wet, 74old gas, 257old oil, 258
DETERMINATION OFOILANDGASRESERVES
Ontario Securities Commission. 315open-holedrillstemtest, 72open-hole wireline tools, 86operated-dayrate
definition of, 223operating costs, 256Operator, 259options, 295
call, 295fence, 295put, 295
over-pressured reservoirs, 148overhead fee, 256overriding
royalty, 7-8royalty interest, 254
ownershipmineral rights, 254of reserves. 7
oxidation of crude, 195
P-X diagram, 173par price, 258parameter uncertainty. 268parameters
reservoir, 16pay
defining net, 45gross, 44net, 44
payout period, 307pentanesplus royalty, 258performance prediction 184
analytical, 164performance prediction, 183permeability, 27, 53, 72
absolute, 216effective, 53fracture, 63from core, 53gas, 53horizontal, 101liquid, 53low, 190matrix, 63relative, 53, 54, 216specific, 53
permeability cutoffs, 46permeability from cores, 101permeameter. 54petrophysicalwell logs, 16phase
behaviour, 148, 201diagrams, 146
pipelinecompanies, 306gas reserves, 150major interprovincial systems, 288
pipelinesfeeder, 288
c
SUBJECTINDEX
PirsonMethod, 137politicaluncertainty, 266polymer flooding, 154, 168pool
area, 12discovery, 157parameter, 112size, 240
pooling, 255pools
analogous, 163carbonate, 242clastic, 242multi-well, 13single-well, 12
porevolume compressibility tests, 63porosity, 27, 48, 55, 72, 113, 159
average, 216correlation of log andcore, 62cutoffs, 45from cores, 101fromwell logs, 103low, 190primary, 37, 55secondary, 55
porosity-thickness maps, 38porpoising, 210possible
developedreserves, 6reserves, 5, 17, 179undeveloped reserves, 6
post-injection startup, 158post-waterflood response, 158presence of hydrocarbons, 14pressure, 75, 113
abandonment, 148average reservoir, 89bottom-hole, 49buildup data, 86buildup test, 77capillary, 67equilibrium, 121gradients, 86pseudo-critical, 91-92recorders, 75, 86reservoir, 86, 104stabilizedbottom-hole, 86threshold, 67transient analysis, 36
pressure-depth plots, 37,38pressure-volume test, 79price
average Albertamarket, 257select, 257wellhead, 255
pricedifferentialsfor light and heavy crude, 294
price risk, 294prices
crude oil, 255gas, 255
outlook for world oil, 295pricing, 291primary
depletion, 131drive mechanisms, 238oil recovery, 237porosity, 37, 55
probabilisticprocedure, 8, 11, 30simulation, 277
probability, 11, 17analysis, 166degree of, 10increase, 11
probabledeveloped reserves, 5reserves, 5, 17, 180undeveloped reserves, 5
procedure. See method.deterministic, 8, 10-11, 30probabilistic, 8, II, 30stochastic, 11
processdifferential liberation, 97displacement, 154enriched air combustion, 195flash liberation, 97steam flood, 189thermalwave, 195variations, 195
processesin situcombustion, 194thermalrecovery, 187
processing fees, 255producers, 306production
cumulative, 7data, 216forecasting, 132, 304paymentinterest, 254rate, 140revenue, 255royalty, 260tests, 75, 104
production performance chartsdefinition of, 223
production ratescarbon dioxideflooding, 203
productivity allowance, 257products
related, 29profitability indices, 307properties
reservoir rock, 101rock and fluid, 27
proved reserves, 17, 180provincial governments, 281pseudo-critical
pressure, 91properties, 91-92temperature, 91
put option, 295PVT
analysis, 77data, 120samples, 79
pyrobitumen, 72, 103
quantitative estimation, 274
ranges, 108rate of return, 308rate-cumulative graphs, 223rate-timegraphs, 223ratio
break-through, 177mobility, 154, 175oil-steam, 193viscous-gravity, 176
ratio curvesdefinition of, 223
ratioyardstickreserves-to-production, 305
recombination sampling, 77recover, 189recoverable gas, 148recovery
carbon dioxide floodingefficiency, 203estimates, 135factor, 17, 31, 168, 210
carbon dioxide flooding, 203distributions, 249for large pools, 238statistics, 237
mechanisms, 188, 195parameters, 247secondary, 171tertiary, 154, 171
refinement of volumetric estimates, 43refineries, 290refining
Canadian, 290regulations, 283,284regulatory approvals
changes to, 298regulatory constraints, 143regulatory environment, 253related products, 22-23,29, 151relative frequency curve, 30relative permeability, 53, 54, 216
measurement of, 54reliability of data, 31, 63, 101, 121,
136, 157, 237reliability of results, 162, 163, 164, 166remaining
proveddevelopedreserves. 5proved reserves, 5provedundeveloped reserves. 5reserves, 5
replacement costs, 317reserve
359
distribution, 116gas losses, 150parameters, 211
reserves, 3, 253associated gas, 150company grossremaining, 7companynet remaining, 7confldencelevelo~ 9determinations,
steps involvedin, 211developed, 6developed nonproducing, 6developed producing, 6economically recoverable, 253forecasting, 132from improved recovery projects, 22future initial, 5gas, 148grossremaining, 7half-life, 314initial, 5nonassociated gas, 148ownership, 7
company gross remainingreserves, 7
pipelinegas, 150possible,S, 17possible developed, 6possible undeveloped, 6probable,S, 17probabledeveloped, 5probable undeveloped, 5proved, 17remaining, 5remaining proved. 5remaining proved developed, 5remaining proved undeveloped, 5risk-weighting of estimates, 8role of, 304solutiongas, 150sulphur, 23undeveloped, 6users ofvolumes, 306uses of estimates, 311uses of evaluations, 253working interest share of, 7
reserves-to-production ratio, 305reservoir
analogous, 22area and volume, 35characteristics. 131continuity, 37deep, 190expansion terms, 122fluidsamples, 104fluids, 77forecasts of performance, 220geometry, 141, 216gross, 44heterogeneities, 141
360
heterogeneity, 63, 74limits, 39modelgrid design, 217model initialization, 218net, 44parameters, 16, 247performance charts
definition of, 223performance forecasting, 219poor, 190pressure, 86, 104quality, 238rock properties, 101saturated oil, 123shallow, 190simulation, 137, 140simulation datarequirements, 216simulation method, 22simulators, 214single-phase gas, 146temperature, 81, 104two-phase, 146undersaturated, 80undersaturated oil, 122, 133voidage terms, 121volume, 27
reservoirsanalogous, 17cycling of gas condensate. 152dew-point, 146dry gas, 145fractured, 63gas, 123naturally fractured, 167, 214over-pressured, 148retrograde gas condensate, 146
residualgas saturation, 148oil saturation, 161, 175
resistivitiesformation water, 79, 103
resistivity logs, 63, 69resource
allowance, 261assessments, 281properties, 312royalty, 260uses of estimates, 31
resources, 3, 4, 253discovered, 5undiscovered, 5
resultsreliability of, 162, 163, 164, 166
retrograde gas condensate reservoirs, 146return on investment, 308revenue, 255
production, 255right-of-entry, 285risingbubbleapparatus, 174risk, 266
DETERMINATION OFOIL ANDGASRESERVES
risk premium, 264risk-weighting of reserves estimates
aggregation, 8Robertsand Ellis Method, 137rock compressibility, 63
data, 216rock properties, 216rotary drilling, 75royalties
levelsof, 282royalty
Crown, 7-8crude oil, 258factor, 259freehold, 7-8, 260gross overriding, 254intent, 259interest, 254lessor, 7maximum, 257minimum, 257naturalgas, 257net ovetriding, 254oil sands, 260overriding, 7-8pentanes plus, 258production, 260rate, 259resource, 260sulphur, 258tax deduction, 259
rugosity, 49
sales, 7samples
oil, 79PVT, 79reservoir fluid, 104surface, 79surface crude oil, 79water, 78
sampling, 77subsurface, 77surface recombination, 78
sandwicheffect, 135sandwichloss, 161, 207saturatedoil reservoir, 123saturation, 65
connate water, 65formation fluid, 216gas, 113residualoil, 161,175water, 69
saturations from cores, 102schemes
dispersedgas injection, 183, 185external injection, 183, 185horizontalwaterllood, 156, 159vertical waterllood, 156, 161, 163
SchilthuisMethod, 138
•
SUBJECT INDEX
screening and feasibility studies, 174screening guidelines, 188secondary
gas cap, 145porosity, 55recovery, 171recovery of gas, 153
securities commissions, 8securities reporting, 315security, 305seismic
3-D, 36data, 35
selectprice, 257,258semi-implicit method, 215sensitivity cases, 8separator tests, 79shale, 190
content. 63presenceof, 72
shalysand interpretation process, 73shrinkage factor, 96shut-in period, 104simulation
blackoil, 177history-matched, 22Monte Carlo, 277numerical, 137, 166probabilistic, 277reservoir, 137, 140studies, 177
simulatorsblackoil, 214compositional, 214enhanced oil recovery. 214reservoir, 214types of, 178
singleestimate, 11single-phase gas reservoir, 146single-value
approach, 106estimate, 107
single-well pools, 12siterestoration and reclamation, 256slimtube test, 174slug size
chasegas, 178solvent, 178
slug sizing, 202solution gas, 28, 145
drive, 133, 207, 238reserves, 150
solventslug size, 178sour gas, 92, 145sourceof data, 31, 81sources of errors, 64, 123, 268sparecapacity, 256specific permeability, 53stabilized bottom-hole pressure, 86stand-off, 207
standardconditions, 30Standing Committee on Reserves
Definitions, 3, 10startup
post-injection, 158state
steady, 54, 125unsteady, 54, 125
statementof changes in cashposition, 263of income, 263
statistical analysis, 107statistical method, 9, 231-233statistical techniques, 58statistics
recovery factor, 237steadystate, 54, 125steady-state conditions, 206steam
distillation, 195drive, 195floodprocess, 189overlaymodel, 191
steam confinementlackof, 190
steam stimulationfollowed by wet combustion, 195
Stiffdiagram, 79stochastic evaluation, 275stochastic procedure, 11stocktank cubicmetre, 96straight-line method, 126, 127, 136stratigraphic traps, 39structure maps, 38subjective estimate, 274subsurface sampling, 77successorrules, 263sulphur, 23, 29, 151
royalty, 258summation-of-fluids method, 57sunkcosts, 309superposition theorem, 125supplemental calculations
aquifers, 124gas caps, 124water influx, 124
supplyindicator, 305surface crude oil samples, 79surface recombination sampling, 78surface samples, 79surfactants, 189sweepefficiency, 162
areal, 202horizontal, 159total, 159vertical, 160,202volumetric, 202
sweet gas, 145swelling, 201synthetic oil, 288
tangible costs, 263tariffs, 285, 290tax credit, 285taxation levels, 285technical assistance, 286technical uncertainty, 266techniques
statistical, 58temperature, 113
bottom-hole, 49, 81pseudo-critical, 91reservoir, 81, 104
temperature gradient, 82, 85ternary diagram, 173
multi-contact, 174tertiaryrecovery, 154, 171test
absolute open flow, 77constant andvariable rate, 77differential liberation, 79drawdown, 77drillstem, 75, 104flash liberation, 79interference, 77pressure buildup, 77pressure-volume, 79production, 75, 104separator, 79slim tube, 174vapourization, 79
testingbackpressure, 152
theoretical methods, 234,235thermal
conductivity, 84cracking, 195efficiency term, 193expansion, 195gradient maps, 81recovery processes, 187wave process, 195
third tier oil, 258threshold pressure, 67tiltedoil-water contacts, 38timestep sizing, 166tolls, 285, 290tool resolution, 63topgas, 256-257Tracy orTamerMethod, 137transition zones, 48trap, 37trapping
hydrodynamic flow, 38
trapsstratigraphic, 39
two-phase reservoir, 146type-curve matching, 230
uncertainties, 206, 212estimation of, 178
361
-I
DETERMINATION OF OILAND GASRESERVES
2Q
uncertainty, 10, 30, 253, 266causesof, 268degreeof, 266economic, 266engineering, 266estimation of, 273geological, 266magnitude of, 271model, 268parameter, 268political, 266technical, 266use of, 271
undersaturated oil reservoir, 80, 122, 133undevelopedreserves, 6undiscovered
hydrocarbon volumes, 278resources, 5
unitization, 255unrecoverablevolumes, 5
currently uneconomic volumes, 5residual unrecoverablevolumes, 5
unsteadystate, 54, 125unswept volumes, 161US Securities and Exchange
Commission, 315useage fees, 285uses of resource estimates, 31
valuing oil and gas companies, 311vapourization, 201
test, 79vapourizing multiple-contact
miscibility, 173vertical
miscible floods, 171resolution, 64sweepefficiencies, 167-168sweep efficiency, 160waterflood schemes, 156, 161, 163
viscosity. 79oil, 141reduction, 195, 20 I
viscous-gravity ratio, 176Vogelmodel, 194volume
drainage, 72
362
gross swept, 160volume-weighted average, 90volumes
currently uneconomic, 5future unrecoverable, 5residual unrecoverable, 5unrecoverable, 5unswept, 161
volumes in placefuture initial, 5initial, 5
volumetricanalysis, 158calculation, 28eqnation, 108, 158, 175estimate, 106estimates, 27mapping, 35method, 12, 148, 163, 175, 205, 209sweepefficiency, 177, 202yield methods, 278
vugs, 55
WarrenMethod, 107, 118theory, 107nse of, 118
water, 190analyses, 79channelling, 209drive, 134, 137influx, 121, 124samples, 78saturation, 48, 69saturations from well logs, 103
water-wet, 74waterflood
horizontalschemes, 156mature, 158prediction methods, 165reserves drainedfrom, 208verticalschemes, 156, 163
waterflooding, 154combination of forward combustion
and, 195wedge zones, 39weightedaverage costof capital, 264weighted-mean, 240
WelgeMethod, 138, 140well
abandonment costs, 256conditioning, 78data, 216horizontal, 205patterns, 188, 195-196porosity from logs, 103spacing, 142, 152, 196test analysis, 70testing, 48tests, 222water saturations from logs, 103
wellhead price, 255wet combustion
steamstimulation followed by, 195wet gas, 145wettability, 69, 74, 102wireline logs, 45wireline tools
open-hole, 86working capital, 257working interest, 254working interest share, 7Wylie Time-Average Equation, 58
zonestransition, 48
-II
I
