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Beyond Decline Curves: Life-CycleReserves Appraisal Using an IntegratedWork-Flow Process for Tight Gas Sands

Unconventional Reservoirs Workshop

20-Aug-2009

J.A. RushingAnadarko Petroleum Corp.

A.D. PeregoAnadarko Petroleum Corp.

K.E. NewshamApache Corp.

J.T. ComiskyApache Corp.

T.A. BlasingameTexas A&M University

Previously Presented @ SPE ATCE 2007 SPE109836

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Methods of Reserves Estimates• Arps decline curve method

• Calculating original volumetric gas-in-place and applying a recovery factor to estimate reserves.

• Conventional material balance models to estimate OGIP and applying a recovery factor to estimate reserves

• History match well and/or field production with a reservoir simulator, and estimate future production and reserves with the calibrated model.

Arps Methodology & Assumptions

– Plot gas production rate against time & history match existing production using Arps models

– Extrapolate history-matched trend into future and estimate reserves using economic cutoffs

• Assumptions Implicit in Using Arps Equations– Extrapolation of best-fit curve through existing data is accurate

model for future trends

– There will be no significant changes in current operating conditions that might affect trend extrapolation

– Well is producing against constant bottom hole flowing pressure

– Well is producing from unchanging drainage area, i.e., the well is in boundary-dominated flow

• Methodology for Estimating Gas Reserves• b-exponent of 1.3• Reservoir abandonment pressure

of 2000 psi • Effective decline rate of 58%• EUR estimate is 2.08 Bcsf

Estimating Arps Decline Curve Parameters

( ) bi

i

tbDqtq /11

)(+

= Di is the initial decline rate, qi is the gas flow rate, and b is the Arps decline curve constant or exponent.

tDitD

i i

ieq

eqtq −==)( The exponential decline equation can be derived from

Equation (1) with a b-exponent of zero

1)

2)

( )tDqtq

i

i

+=

1)(3) The harmonic decline is the special case of Equation

(1) when the b-exponent equals one

4) The hyperbolic decline which can be derived from Equation (1) when b is between 0 and 1.0( ) b

i

i

tbDqtq /11

)(+

=

• The value of b determines the degree of curvature of the semilog decline, ranging from a straight line with b=0 to increasing curvature as b increases.

• Values of b greater than one reflected transient or transitional rather than true boundary-dominated flow.

Problem Statement

• Reserves in tight gas sands typically evaluated using Arps decline curve technique

• Reservoir properties preclude accurate reserve assessments using only decline curve analysis

• Errors most likely during early field development period before onset of boundary-dominated flow

Paper Objectives

• Develop reserves appraisal work-flow process to reduce reserve estimate errors in tight gas sands

• Work-flow process model should:

– Allow continuous but reasonable reserve adjustments over entire field development life cycle

– Prevent unrealistic (either too low or too high) reserve bookings during any field development phase

– Be applicable during early development phases when reserve estimate errors are most likely and are largest

Work-Flow Process Model Overview

• Model Attributes– Captures characteristic tight gas sand flow and storage

properties

– Incorporates comprehensive data acquisition and evaluation programs

– Integrates static and dynamic data types (i.e., engineering, geological, and petrophysical) at all reservoir scales

• Model Hypothesis– Complement rather than replace traditional decline curve

analysis with deterministic evaluation program

– Reduce reserve estimate uncertainties and errors with integrated work-flow process model

Reserves

TraditionalDecline Curve

Analysis

Quantification

VolumetricGIP

(Static)

ContactedGIP

(Dynamic)

FluidAcquisition

& Evaluation

Well LogAcquisition

& Evaluation

CoreAcquisition & Evaluation

StaticPressures

WellSurveillance& Monitoring

WellPerformance

Analysis

ReservoirSimulation

FlowingPressures

Work-Flow Process Diagram

Expected Gas Volumes Relationships

FieldDevelopment

Stage

Type ofFlow

Period

RelationshipsAmong Gas

Volumes

Early Transient Gp < CGIP << EUR < VGIP

Intermediate Transitional Gp < CGIP < EUR < VGIP

Late Boundary-Dominated

Gp < EUR < CGIP < VGIP

Abandonment Boundary-Dominated

Gp < EUR < CGIP < VGIP

Example Application of Work-FlowProcess Model

• Granite Wash of TX Panhandle

• 2000’+ Gross Interval

• Sand Geometry: fan - delta

• Mixed lithology and layered

• Porosity range: 0% - 15%

• Permeability: 0.0001 - 0.1 mD

• Pressure gradient ~ 0.47 psi/ft

• Multiple frac stages required

Application of Work-FlowProcess Model

Reserves Quantification StageTraditional Decline Curve Analysis

ReservesReserves

TraditionalTraditionalDecline CurveDecline Curve

AnalysisAnalysis

QuantificationQuantification

VolumetricVolumetricGIPGIP

(Static)(Static)

Valida

tion

Valida

tion

ContactedContactedGIPGIP

(Dynamic)(Dynamic)

Validation

Validation

FluidFluidAcquisitionAcquisition

& Evaluation& Evaluation

Well LogWell LogAcquisitionAcquisition


CoreCoreAcquisition Acquisition & Evaluation& Evaluation

StaticStaticPressuresPressures

WellWellSurveillanceSurveillance& Monitoring& Monitoring

WellWellPerformancePerformance

AnalysisAnalysis

ReservoirReservoirSimulationSimulation

FlowingFlowingPressuresPressures

ReservesReservesReservesReserves


AnalysisAnalysis



AnalysisAnalysis


AnalysisAnalysis



(Static)(Static)

Valida

tion

Valida

tion


(Static)(Static)


(Static)(Static)

Valida

tion

Valida

tion


(Dynamic)(Dynamic)

Validation

Validation


(Dynamic)(Dynamic)


(Dynamic)(Dynamic)

Validation

Validation





















AnalysisAnalysis






AnalysisAnalysis


AnalysisAnalysis

ReservoirReservoirSimulationSimulationReservoirReservoirSimulationSimulation

FlowingFlowingPressuresPressuresFlowingFlowing

PressuresPressures

Decline Curve Analysis; 300 & 700 Day

•b-exponent of 1.3

•Effective decline rate of 58%

•EUR estimate is 2.08 Bcsf

•Gp = 0.465 Bcsf gas, 15.5

Mbbl oil , and 27.1 Mbbl water.

300 day flow period

700 day flow period

•b-exponent of 1.0

•Effective decline rate of 38.8

•EUR estimate is 1.359 Bcsf

•Gp = 0.69 Bscf gas, 21.3

Mbbl oil, and 33.4 Mbbl

water

Abandonment pressure of 2000 psi


Reserves Validation Stage Computing Volumetric Gas-in-Place (VGIP)

ReservesReserves


AnalysisAnalysis



(Static)(Static)

Valida

tion

Valida

tion


(Dynamic)(Dynamic)

Validation

Validation









AnalysisAnalysis





AnalysisAnalysis



AnalysisAnalysis


AnalysisAnalysis



(Static)(Static)

Valida

tion

Valida

tion


(Static)(Static)


(Static)(Static)

Valida

tion

Valida

tion


(Dynamic)(Dynamic)

Validation

Validation


(Dynamic)(Dynamic)


(Dynamic)(Dynamic)

Validation

Validation





















AnalysisAnalysis






AnalysisAnalysis


AnalysisAnalysis



PressuresPressures

Key Data RequirementsBottom Hole Pressure Profile & Gradient Analysis

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,0000 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000

BHP of Bottom, psi

Dep

th (M

D),

ft

Slight Over Pressure Gradient ~ 0.474 psi/ft

Severe Over Pressure; Incremental Gradient ~ 3.1 psi/ft

Normal Pressure Gradient Based On Water Chemistry: 0.4179 to 0.4327 psi/ft with increasing depth due to

temperature changes

• Well and Reservoir Surveillance & Monitoring Program – Initial BHPs required to

compute VGIP

– Initial and subsequent BHPs required to monitor flow periods during field development and compute CGIP

• Core Acquisition Programs– Recommend core samples be taken early in

field development

– Also recommend conventional whole core rather than sidewall cores taken through complete vertical sections

– Use drilling fluids to minimize mud invasion and displacing connate water

Core, Fluid & Log Programs

Height Above Free Water - All Rock Types

1

10

100

1,000

10,000

100,000

0102030405060708090100

Hg Incremental Saturation, %

Hei

gh

t A

bo

ve

Fre

e W

ate

r, f

t.

Atherton 1 - 68 12,671 ft.

Atherton 1 - 68 12,690 ft.

Atherton 1 - 68 12,776 ft.

Atherton 1 - 68 12,782.5 ft.

Atherton 1 - 68 12,813.5 ft.

Atherton 1 - 68 12,974 ft.

Atherton 1 - 68 12,980 ft.

Hydrostatic to Uniaxial Stress Response

0

10

20

30

40

50

60

70

80

90

100

800 1800 2800 3800 4800 5800 6800 7800

Net Confining Pressure (Net Effective Stress), psi

% O

f O

rig

inal

Per

mea

bili

ty @

800

psi

.

Sample 1 Uniaxial Sample 2 Uniaxial Sample 3 UniaxialSample 1 Hydrostatic Sample 2 Hydrostatic Sam[ple 3 HydrostaticSample 4 Uniaxial Sample 4 Hydrostatic Sample 5 UniaxialSample 5 Hydrostatic Sample 7 Uniaxial Sample 7 HydrostaticSample 8 Uniaxial Sample 8 Hydrostatic Initial Reservoir Conditions

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.00.20.40.60.81.0Gas Saturation, fraction

Re

lativ

e P

erm

ea

bili

ty,

fra

ctio

n

Krg Krw Krw Model Krg Model RT2 Krg RT2 Krw

Capillary Pressure

Stress Dependent P&P

Relative Permeability

Absolute PermeabilityKLINKENBERG AIR PERMEABILITY, md

y = 0.0133x + 0.0100R2 = 0.9951

0.000

0.010

0.020

0.030

0.00 0.10 0.20 0.30 0.40 0.50 0.60

1/mean ATM

Perm

eabil

ity to

Gas

, md

'

Log Profiles; Sw, φ , k

Storage and Flow Capacity AssumptionsH

ydro

carb

on-In

-Pla

ce

Hydrocarbon Porosity Volume

Reservoir Storage Capacity

Expe

cted

Ulti

mat

e R

ecov

ery

Hydrocarbon Porosity Volume

Traditional methods

attempt to correlate storage

capacity to EUR with little

success

Effective Permeability Thickness

Expe

cted

Ulti

mat

e R

ecov

ery

Reservoir Flow Capacity

Effective Permeability Thickness

Expe

cted

Ulti

mat

e R

ecov

ery

Advanced analysis method

correlates flow

capacity to EUR

)Rln( e

wg

fbhii

RB

HKeffPP

QP••

••=

−=

µ

α

gi

w

BS

ΦHAGIP )1(43560−

= ••••

Dynamically Calibrated Net Pay Thickness

Gas Flow Prediction

Spinner

• Integrate log-based Keff, then• Match log-based Keff to recorded PL gas in-flow, by• Altering net pay threshold criteria (e.g. φ, Sw, Keff)

Net Pay Layering Effects on VGIP

gBSwHAVGIP )1(43560 −

⋅⋅⋅= φ

• The reduction in gross to net ratios is a direct result of the loss of porosity and permeability by diagenesis and diminishes the connected or effective drainage area

• Well spacing is commonly used as the area for estimating initial VGIP (80 ac)

• VGIP was updated ~ 12.7 Bcsf by multiplying the net pay/gross interval ratio by the initial spacing

Nested Cutoffs: Vcl < 25% Phi > 6% Sw < 60%

Gross Interval

Gross Sand

Thickness

Net Porous Sand

ThicknessNet Pay

Thickness

Gross Reservoir to Gross Interval

Net Porous

Reservoir to Gross

Net Pay Reservoir to Gross Interval

Average Porosity

Average Water

Saturation

Average Effective

Peremability to Gas

Pore Pressure

ft ft ft ft v/v v/v mD psi116 17.052 6.5 2 0.147 0.056 0.017 0.138 0.341 0.001964 5946.804

116.5 92.035 36.5 21.5 0.79 0.313 0.185 0.104 0.4 0.002478 6001.906579.5 45.7125 24.5 21.5 0.575 0.308 0.27 0.096 0.311 0.006914 6048.3585224 189.504 96.5 70.5 0.846 0.431 0.315 0.088 0.458 0.002111 6120.288

506.5 396.083 157.75 107 0.782 0.311 0.211 0.089 0.418 0.003047 6293.4165537.5 389.6875 23 22 0.725 0.043 0.041 0.067 0.472 0.003213 6540.8445

1580 1130.074 344.75 244.5 0.715 0.218 0.155 0.089 0.42 0.003073 6158.603


Reserves Validation Stage Computing Contacted Gas-in-Place (CGIP)

ReservesReserves


AnalysisAnalysis



(Static)(Static)

Valida

tion

Valida

tion


(Dynamic)(Dynamic)

Validation

Validation









AnalysisAnalysis





AnalysisAnalysis



AnalysisAnalysis


AnalysisAnalysis



(Static)(Static)

Valida

tion

Valida

tion


(Static)(Static)


(Static)(Static)

Valida

tion

Valida

tion


(Dynamic)(Dynamic)

Validation

Validation


(Dynamic)(Dynamic)


(Dynamic)(Dynamic)

Validation

Validation





















AnalysisAnalysis






AnalysisAnalysis


AnalysisAnalysis



PressuresPressures

Flowing Material Balance Analysis

300 Day Flow Period

•CGIP = 1.042 Bscf

•Contacted area = 6.27 acres

300 day flow period

700 day flow period 700 Day Flow Period


•Contacted area = 7.31

acres

Agarwal-Gardner

Flowing P/ZComputing Contacted

GIP

Rate Transient Analysis; CGIP, k, Fh

300 Day Flow Period


•Contacted area = 6.25 ac

•Keff = 0.0043 mD

•Fh = 147 ‘

700 Day Flow Period

•CGIP = 1.2 Bscf

•Contacted area = 7.25 ac

•Keff = 0.004 mD

•Fh = 158 ‘

300 day flow period

700 day flow period

Rate Transient Analysis Summary

• CGIP increases by 20%

• Contacted area also increases

• Fracture half length increases

• The core-log model effective permeability of 0.0031 mD is very close to the average decline type-curve solution of 0.0029 mD.

300 Day Flow Period: Analysis Type CGIP Area Permeability

Frac Half Length

Bscf acres mD ftBlasingame - Fracture 1.04 6.25 0.0043 147.134Agarwal-Gardner - Fracture 1.03 6.2 0.002 293.305Transient: Finite Conductivity 1.05 6.33 0.0027 262.505NPI: Fracture 1.05 6.33 0.0022 296.211Flowing Material Balance 1.04 6.27

Averages 1.042 6.276 0.0028 249.78875

700 Day Flow Period: Analysis Type CGIP Area Permeability

Frac Half Length

Bscf acres mD ftBlasingame - Fracture 1.2 7.25 0.004 158.556Agarwal-Gardner - Fracture 1.21 7.31 0.0019 318.427Transient: Finite Conductivity 1.22 7.32 0.0039 282.365NPI: Fracture 1.21 7.25 0.0021 317.138Flowing Material Balance 1.22 7.31

Averages 1.212 7.288 0.002975 269.1215


Reserves Validation Stage Reservoir Simulation; Estimation of Drainage

Area &EUR

ReservesReserves


AnalysisAnalysis



(Static)(Static)

Valida

tion

Valida

tion


(Dynamic)(Dynamic)

Validation

Validation









AnalysisAnalysis





AnalysisAnalysis



AnalysisAnalysis


AnalysisAnalysis



(Static)(Static)

Valida

tion

Valida

tion


(Static)(Static)


(Static)(Static)

Valida

tion

Valida

tion


(Dynamic)(Dynamic)

Validation

Validation


(Dynamic)(Dynamic)


(Dynamic)(Dynamic)

Validation

Validation





















AnalysisAnalysis






AnalysisAnalysis


AnalysisAnalysis



PressuresPressures

Reservoir Simulation Workflow

I. Input core-log-based intrinsic reservoir layer properties into RTA

II. Fracture dimensions, conductivity and effective permeability from Rate Transient Analysis

Net Av Phi Av Sw Av EKg Pore Pressure Ari psi

2 0.138 0.341 0.001964 5946.80421.5 0.104 0.4 0.002478 6001.906521.5 0.096 0.311 0.006914 6048.358570.5 0.088 0.458 0.002111 6120.288107 0.089 0.418 0.003047 6293.416522 0.067 0.472 0.003213 6540.8445

All Layers 244.5 0.089 0.42 0.003073 6158.603

III. Numerical reservoir simulation where the drainage area is controlling variable. All other inputs have been constrained from the core-log and rate transient analysis.

I

II

III

Stiles 1-3

100

1,000

10,000

0 50 100 150 200 250 300

Time, Days

Gas

Rat

e, M

SCFP

D .

(100,000)

100,000

300,000

500,000

700,000

900,000

1,100,000

1,300,000

1,500,000

Cum

Gas

, MSC

F

'Gas Rate' Simulated 20 Acre Gas Rate Simulated 8 Acre Gas RateCum Gas Simulated 20 Acre Cum Gas, Mscfpd Simulated 8 Acre Cum Gas, Mscfpd

Reservoir Simulation; 300 - 10000 Day• 8 acre drainage area is the best

match

• < 80 acre well spacing

• > than the contacted area observed at the 300 (1.04 ac) and 700 (1.21 ac) day RTA analysis

• EUR = 1.06 Bscf at day 10000100

1,000

10,000

0 50 100 150 200 250 300

Time, Days

Gas

Rat

e, M

SCFP

D .

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

Cum

Gas

, MSC

F

'Gas Rate' Simulated 20 Acre Gas Rate Simulated 8 Acre Gas RateCum Gas Simulated 20 Acre Cum Gas, Mscfpd Simulated 8 Acre Cum Gas, Mscfpd

20 Acre

8 Acre

100

1,000

10,000

0 100 200 300 400 500 600 700 800 900 1000

Time, Days

Gas

Rat

e, M

SCFP

D .

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000C

um G

as, M

SCF

'Gas Rate' Simulated 8 Acre Gas Rate Cum Gas Simulated 8 Acre Cum Gas, Mscfpd

10

100

1,000

10,000

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

Time, Days

Gas

Rat

e, M

SCFP

D .

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

Cum

Gas

, MSC

F

'Gas Rate' Simulated Gas Rate Cum Gas Simulated Cum Gas, Mscfpd

Reservoir Simulation Summary

Flow PeriodDrainage

Area1Produced Gas, Gp

Contacted Gas-In-

Place, CGIP

2 Expected Ultimate

Recovery,EUR

3 Volumetric Gas-In-Place,

VGIPDays acres Bscf Bscf Bscf Bscf

0 80 0 12.754300 12 0.465 1.04 1.06 1.913700 8 0.69 1.21 1.06 1.294

10000 8 1.06 1.21 1.06 1.2941 Drainage area would not normally change. Down scaling of area is indicative of uncertainty in the knowledge of geology and the impact of pore disconnection due to diagensis on effective drainage area.2 EUR estimated from 10000 day numeric reservoir simulation3 VGIP is decreasing due to decreases in estimated drainage area.

Flow Period, Days Fluid RelationshipsType of Flow

PeriodStage of

Production300 Gp < CGIP << EUR < VGIP Transient Early

700 Gp < EUR < CGIP < VGIPBoundary-Dominated Late

10000 Gp = EUR < CGIP < VGIPBoundary-Dominated Abandonment

Summary & Conclusions

• Developed reserves appraisal work-flow process specifically for tight gas sands

• Work-flow process

– Designed specifically to incorporate tight gas sand production characteristics

– Intended to complement rather than replace traditional decline curve analysis

– Integrates both static and dynamic data with appropriate evaluation techniques

Summary & Conclusions(continued)

• Work-flow is adaptive process that allows continuous but reasonable reserve adjustments over entire reservoir life cycle

• Process is most beneficial during early field development stages before boundary-dominated flow conditions have been reached and when reserve evaluation errors most likely

Thank You

beyond decline curves: life -cycle reserves appraisal ... · pdf filebeyond decline curves:...

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