-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
Screening Technologies 3rd Annual Wyoming IOR/EOR Conference
V L A D I M I R A LV A R A D O
C H E M I C A L A N D P E T R O L E U M E N G I N E E R I N G
S E P T E M B E R 1 3 , 2 0 11
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
• Introduction
• Why run screening?
• Screening type
• Engineering (lookup tables)
• Data-driven (drawn from experience)
• Geological (ex: pay continuity)
• Multi-parameter projections
• Closing remarks
Outline
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
ValuesUncertaintiesDecisions
Objective
Function
EOR MethodNPV
Tax
CAPEX
OPEXReservoir
Properties
Oil
ProductionProduction
revenue
Oil Price
Water
Handling Costs
EOR MethodNPV
Tax
CAPEX
OPEXReservoir
Properties
Oil
ProductionProduction
revenue
Oil Price
Water
Handling Costs
CO2
Sequestration
EOR MethodNPV
Tax
CAPEX
OPEXReservoir
Properties
Oil
ProductionProduction
revenue
Oil Price
Water
Handling Costs
NPV
SAGD
Yes
No
High
Low
Base case
SF Yes
No
Yes
No
High
Low
Base case
High
Low
Base case NPVNPVISC
ValuesUncertaintiesDecisions
Objective
Function
EOR MethodNPV
Tax
CAPEX
OPEXReservoir
Properties
Oil
ProductionProduction
revenue
Oil Price
Water
Handling Costs
EOR MethodNPV
Tax
CAPEX
OPEXReservoir
Properties
Oil
ProductionProduction
revenue
Oil Price
Water
Handling Costs
CO2
Sequestration
EOR MethodNPV
Tax
CAPEX
OPEXReservoir
Properties
Oil
ProductionProduction
revenue
Oil Price
Water
Handling Costs
NPVNPV
SAGD
Yes
No
Yes
No
High
Low
Base case
High
Low
Base case
SF Yes
No
Yes
No
High
Low
Base case
High
Low
Base case NPVNPV
High
Low
Base case
High
Low
Base case NPVNPVNPVNPVISC
Conventional Economic
Evaluations
EOR Decision Making
Manrique et al., SPE 113269, 2008
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
Natural Depletion
Water Flooding
Water-Alternating-Gas (WAG)
Alkali-Surfactant-Polymer (ASP)
Gas Flooding
Miscible
Immiscible
Water-Alternating-Gas (WAG)
CO2 Sequestration
High Pressure Air Injection
Gas Injection Water Injection
WAG IGR by late Depressurization
Pressure Maint.
Steam Stimulation
Steamflooding
In-Situ Combustion
Steam-Assisted-Gravity-Drainage (SAGD)
Problem: Too many choices
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
• “Screening guides or criteria are among the first items
considered when a petroleum engineer evaluates a
candidate reservoir for enhanced oil recovery (EOR)”1
• “The choice of enhanced oil recovery processes is
based on technical and economic data”2
• “Sophisticated and complex numerical models are used
in industry to evaluate the suitability of a reservoir for
CO2 flooding,… Thus, these methods and models are
not suitable for a regional-scale, quick initial
assessment and screening of oil pools…with respect to
suitability…” 3
Screening
1Taber & Martin, SPE 12069, 1983 2Guerillot, SPE 17791, 1988 3Shaw & Bachu, JCPT, 2002
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
Prospective Simulations
Screening
Detailed Appraisal
Project Implementation
Stop
Stop
Stop
Goodyear & Gregory, SPE 28844, 1994
• Several methods for
feasibility
• Analytical or sector model
simulations => performance
prediction
• More data serve to build
detailed models and deal
with uncertainty
• A go-ahead is given (or not)
to deploy a development plan
and invest resources
Why run screening?
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E *Taber, Martin & Seright, SPEREE, 1997 (I)
Lookup tables (Yes or No, or Maybe)
EOR Method
Gravity (oAPI)
Viscosity (cp)
Comp. So (% PV)
Formation Type
Net Thick. (ft)
(md)
Depth (ft)
T (oF)
N2 & Flue Gas
> 35↗ 48↗
40↗ 75↗
Sandstone Carbonate
Thin unless Dipping
NC >6,000 NC
HC Gas > 23↗ 41↗
30↗ 80↗
Sandstone Carbonate
Thin unless Dipping
NC >4,000 NC
CO2 > 22↗ 36↗
20↗ 55↗
Sandstone Carbonate
Wide range NC >2,500 NC
Immisc. gases
> 12 35↗ 70↗
Sandstone Carbonate
NC if dipping and/or good Kv
NC >1,800 NC
• Similar tables are available for chemical and thermals methods.
• “Screening criteria are based on a combination of the reservoir and oil characteristics of successful projects plus our understanding of the optimum conditions needed for good oil displacement by the different EOR fluids”*
Expert: having, involving, or displaying special skill or knowledge derived from training or experience
http://www.merriam-webster.com/dictionary/experience
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
• Each triangle represents a comfort reference interval
• A second triangle is the reservoir interval for each variable
• The overlapping area yields an index (0,1); the closer to “1” the better
Comfort intervals (Ex: f)
Softening lookup tables
Alvarado, Thyne & Murrell, SPE 115940, 2008
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
Out[18]=
VARIABLE MINIMUM MOST LIKELY MAXIMUM INDEX
Depth 30 2515 5000 0.760022
Thickness 3 251.5 500 0.0117616
Pressure 10 250 500 0.380952
Permeability 100 2550 5000 0.496016
Viscosity 0.2 1.35 2.5 0.0636642
Temperature 0 100 200 0.35
TOTAL 0.343736
Fuzzy lookup tables
Alvarado, Thyne & Murrell, SPE 115940, 2008
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
Soft lookup tables can rank
Alvarado, Thyne & Murrell, SPE 115940, 2008
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
WY Test Cases
Alvarado, Thyne & Murrell, SPE 115940, 2008
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
Triangle U Field
0
5000
10000
15000
20000
25000
30000
Jan-
76
Jan-
80
Jan-
84
Jan-
88
Jan-
92
Jan-
96
Jan-
00
Jan-
04
Jan-
08
Jan-
12
Jan-
16
Jan-
20
Jan-
24
Jan-
28
Jan-
32
Jan-
36
Date
Oil r
ate
(B
bl/m
on
th)
-10
0
10
20
30
40
50
60
70
Wa
ter
Cu
t (%
)
Waterflooding
startedChemical treatment
started
WY Test Cases
• Can we use learned lessons?
• Critical conditions & parameters?
• Can we develop strategies for basins?
• Can we recommend objectively?
Alvarado, Thyne & Murrell, SPE 115940, 2008
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
Violations
0
10
20
30
40
50
60
70
Dep
th
Per
mea
bility
Thickn
ess
Tem
pera
ture
Oil visc
osity
Pre
ssur
e
Oil de
nsity
Aniso
tropy
(kv/kh
)
Clay co
nten
t
Salinity
Parameters
Fre
qu
en
cy
Waterflooding
Chemical Flooding
Results for Minnelusa
Alvarado, Thyne & Murrell, SPE 115940, 2008
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
0
10
20
30
40
0 0.2 0.4 0.6 0.8 1
Index
Fre
qu
en
cy
Waterflooding
Chemical Flooding
Results for Minnelusa
Alvarado, Thyne & Murrell, SPE 115940, 2008
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
15 SPE-78332
Expert Map: Polymer Floods CO2 Immisc.
CO2 Misc.
N2 Immisc.
N2 Misc.
Polymer
Steam
WAG CO2 Immisc.
WAG HC Immisc.
WAG CO2 Misc.
WAG HC Misc.
Air
Water Flooding
Cluster 1
Cluster 5
Cluster 2
Cluster 3
Cluster 6
Cluster 4
Method %
Air 41.38
Steam 27.59
CO2 Immisc. 10.34
Polymer 8.62
WAG CO2 Immisc. 5.17
Water Flooding 5.17
N2 Immisc. 1.72
Method %
CO2 Immisc. 22.58Air 12.90
Water Flooding 12.90
CO2 Misc. 9.68
Polymer 9.68WAG HC Immisc. 9.68
N2 Misc. 6.45
WAG HC Misc. 6.45
N2 Immisc. 3.23Steam 3.23
WAG CO2 Misc. 3.23
Method %
Water Flooding 29.17
CO2 Misc. 20.83
Polymer 18.75
N2 Immisc. 6.25
Steam 6.25WAG HC Misc. 6.25
CO2 Immisc. 4.17
WAG CO2 Misc. 4.17
N2 Misc. 2.08
WAG N2 Misc. 2.08
Method %Water Flooding 48.28
Polymer 25.29WAG CO2 Misc. 12.64
CO2 Misc. 10.34
N2 Immisc. 1.15WAG HC Misc. 1.15
Steam 1.15
Method %
Water Flooding 38.46
WAG CO2 Misc. 13.46
WAG HC Misc. 13.46
N2 Misc. 9.62
CO2 Misc. 7.69
N2 Immisc. 7.69
Polymer 5.77
Air 3.85
Method %N2 Misc. 42.86
N2 Immisc. 21.43
WAG N2 Misc. 14.29Water Flooding 14.29
WAG HC Misc. 7.14
Polymer floods in shallow and low
pressure reservoirs
Alvarado et al., SPE 78332, 2002
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
16
Geologic Screening Criteria LOW MODERATE HIGH
LATERAL HETEROGENEITY
LO
WM
OD
ERATE
HIG
H
VE
RT
ICA
LH
ET
ER
OG
EN
EIT
Y
Wave-dominated delta Barrier core Barrier shore face
Sand-rich strand plain
Delta-front mouth bars Proximal delta front
(accretionary) Tidal Deposits Mud-rich strand plain
Meander belts*
Fluvially dominated delta* Back Barrier*
Eolian Wave-modified delta(distal)
Shelf barriers
Alluvial Fans Fan Delta Lacustrine delta
Distal delta front
Braided stream
Tide-dominated delta
Basin-flooring turbiditesCoarse-grained meander belt Braid delta
Back barrier**
Fluvially dominated delta** Fine-grained meander belt**
Submarine fans**
* Single units **Stacked Systems
(1) / [1] (3) / [1]
[1] (6)
(7) / [2] (2) (2)
(3) / [2]
Tyler and Finley clastic heterogeneity matrix showing depositional systems of 24 successful (Blue) and 7 failed [Red] CO2 injection projects
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
1. Conventional screening (XY Plots)
2. Screening with analytical tools
3. Geological screening
4. Advanced screening
5. Inclusion of soft variables
6. Evaluate constraints (simulation)
7. Economic evaluation
A possible methodology
Conventional Screening
Geologic Screening
Advanced Screening
Evaluation of Soft Variables
Decision Analysis
Performance Prediction
Analytical Simulation Numerical Simulation
Economics
Stop
Decision Analysis Stop
Re-e
valu
ation c
ycle
Fie
ld C
ases T
ype I
Fie
ld C
ases T
ype II
Conventional Screening
Geologic Screening
Advanced Screening
Evaluation of Soft Variables
Decision Analysis
Performance Prediction
Analytical Simulation Numerical Simulation
Economics
Stop
Decision Analysis Stop
Re-e
valu
ation c
ycle
Conventional Screening
Geologic Screening
Advanced Screening
Evaluation of Soft Variables
Decision Analysis
Performance Prediction
Analytical Simulation Numerical Simulation
Economics
Stop
Decision Analysis Stop
Conventional Screening
Geologic Screening
Advanced Screening
Evaluation of Soft Variables
Decision Analysis
Performance Prediction
Analytical Simulation Numerical Simulation
Economics
Stop
Decision Analysis Stop
Re-e
valu
ation c
ycle
Fie
ld C
ases T
ype I
Fie
ld C
ases T
ype II
Fie
ld C
ases T
ype I
Fie
ld C
ases T
ype II
Manrique et al., SPEREE, 2009
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
CO2 Misc.
N2 Immisc.
N2 Misc.
Polymer
WAG-CO2 Misc.
WAG-HC Misc.
air
Water flooding
Field A - Case 1
Field A - Case 2
Field A - Case 3
Cluster 2-3
Method %
N2 Immiscible 50.0
Polymer 25.0
Water Flooding 25.0
Cluster 2-4
Method %
WAG-HC 38.5
N2 Miscible 23.1
Water Flooding 23.1
N2 Immiscible 15.4
Cluster 2-1
Method %
Water Flooding 47.6
WAG-CO2 Misc. 23.8
Air 9.5
CO2 Misc. 9.5
Polymer 9.5
Cluster 2-2
Method %
Water Flooding 42.9
CO2 Misc. 14.3
N2 Miscible 14.3
WAG-CO2 Misc. 14.3
WAG-HC 14.3
Binger
East Binger
Field “A” sensitivity cases
CO2 Misc.
N2 Immisc.
N2 Misc.
Polymer
WAG-CO2 Misc.
WAG-HC Misc.
air
Water flooding
Field A - Case 1
Field A - Case 2
Field A - Case 3
Cluster 2-3
Method %
N2 Immiscible 50.0
Polymer 25.0
Water Flooding 25.0
Cluster 2-4
Method %
WAG-HC 38.5
N2 Miscible 23.1
Water Flooding 23.1
N2 Immiscible 15.4
Cluster 2-1
Method %
Water Flooding 47.6
WAG-CO2 Misc. 23.8
Air 9.5
CO2 Misc. 9.5
Polymer 9.5
Cluster 2-2
Method %
Water Flooding 42.9
CO2 Misc. 14.3
N2 Miscible 14.3
WAG-CO2 Misc. 14.3
WAG-HC 14.3
Binger
East Binger
Field “A” sensitivity cases
A. Light-Oil Dolomitic Reservoir
Manrique et al., SPEREE, 2009
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
0
5
10
15
20
25
30
35
40
45
50
0 20 40 60 80 100
% Pore Volume Injected
Reco
very
facto
r, %
CMG-75
CMG-150
CMG-300
Prize-75
Prize-150
Prize-300
Screening Criteria
c1 c2
cn
...
cn-1
Analytic
Numeric
Simulation
Analytical vs. Numerical
0
20000
40000
60000
80000
100000
120000
140000
160000
180000
0.0 0.5 1.0 1.5 2.0 2.5 3.0
Time, year
Cu
mu
lati
ve
Oil
Pro
du
cti
on
, m
3
SAGD NP=21m
SAGD NP=10m
STEAM NP=21m
STEAM NP=10m
IN-SITU NP=21m
IN-SITU NP=10m
ValuesUncertaintiesDecisions
Objective
Function
EOR MethodNPV
Tax
CAPEX
OPEXReservoir
Properties
Oil
ProductionProduction
revenue
Oil Price
Water
Handling Costs
EOR MethodNPV
Tax
CAPEX
OPEXReservoir
Properties
Oil
ProductionProduction
revenue
Oil Price
Water
Handling Costs
CO2
Sequestration
EOR MethodNPV
Tax
CAPEX
OPEXReservoir
Properties
Oil
ProductionProduction
revenue
Oil Price
Water
Handling Costs
NPV
SAGD
Yes
No
High
Low
Base case
SF Yes
No
Yes
No
High
Low
Base case
High
Low
Base case NPVNPVISC
ValuesUncertaintiesDecisions
Objective
Function
EOR MethodNPV
Tax
CAPEX
OPEXReservoir
Properties
Oil
ProductionProduction
revenue
Oil Price
Water
Handling Costs
EOR MethodNPV
Tax
CAPEX
OPEXReservoir
Properties
Oil
ProductionProduction
revenue
Oil Price
Water
Handling Costs
CO2
Sequestration
EOR MethodNPV
Tax
CAPEX
OPEXReservoir
Properties
Oil
ProductionProduction
revenue
Oil Price
Water
Handling Costs
NPVNPV
SAGD
Yes
No
Yes
No
High
Low
Base case
High
Low
Base case
SF Yes
No
Yes
No
High
Low
Base case
High
Low
Base case NPVNPV
High
Low
Base case
High
Low
Base case NPVNPVNPVNPVISC
CO2 Immisc.
N2 Immisc.
Polymer
Steam
Air
Water Flooding
WAG CO2 Immisc.
ASP
SAGD (Canada)
Avg. Grosmont Carbonate
Peace River, Shell
Cold Lake, IOL
Primrose, CNRL
Ikiztepe (Heavy Oil Carbonate)
Qarn Alam (Heavy Oil Carbonate)
Issaran (Heavy Oil Carbonate)
Cluster 5-1
Cluster 5-3
Cluster 5-4
Cluster 5-2
Cluster 5-6
Cluster 5-5
Method %
CO2 Immisc. 33.33
Air 22.22
WAGCO2 Immisc. 22.22
Water Flooding 11.11
Polymer 11.11
Method %
Air
35.71
Steam
28.57
CO2 Immisc.
14.29
Polymer
7.14
Water Flooding
7.14
ASP
7.14
Method %
CO2 Immisc. 33.33
N2 Immisc. 16.67
WAG CO2 Immisc. 16.67
Polymer 16.67
ASP 16.67
Method %
Air 70
Steam 30
Method %
Air 52.94
Steam 47.06
Method %
Steam 37.5
Air 25
Polymer 25
12.5Water Flooding
Reservoir “B”
Burnt Lake
Foster
Creek
CO2 Immisc.
N2 Immisc.
Polymer
Steam
Air
Water Flooding
WAG CO2 Immisc.
ASP
SAGD (Canada)
Avg. Grosmont Carbonate
Peace River, Shell
Cold Lake, IOL
Primrose, CNRL
Ikiztepe (Heavy Oil Carbonate)
Qarn Alam (Heavy Oil Carbonate)
Issaran (Heavy Oil Carbonate)
Cluster 5-1
Cluster 5-3
Cluster 5-4
Cluster 5-2
Cluster 5-6
Cluster 5-5
Method %
CO2 Immisc. 33.33
Air 22.22
WAGCO2 Immisc. 22.22
Water Flooding 11.11
Polymer 11.11
Method %
Air
35.71
Steam
28.57
CO2 Immisc.
14.29
Polymer
7.14
Water Flooding
7.14
ASP
7.14
Method %
CO2 Immisc. 33.33
N2 Immisc. 16.67
WAG CO2 Immisc. 16.67
Polymer 16.67
ASP 16.67
Method %
Air 70
Steam 30
Method %
Air 52.94
Steam 47.06
Method %
Steam 37.5
Air 25
Polymer 25
12.5Water Flooding
Reservoir “B”
Burnt Lake
Foster
Creek
CO2 Immisc.
N2 Immisc.
Polymer
Steam
Air
Water Flooding
WAG CO2 Immisc.
ASP
SAGD (Canada)
Avg. Grosmont Carbonate
Peace River, Shell
Cold Lake, IOL
Primrose, CNRL
Ikiztepe (Heavy Oil Carbonate)
Qarn Alam (Heavy Oil Carbonate)
Issaran (Heavy Oil Carbonate)
Cluster 5-1
Cluster 5-3
Cluster 5-4
Cluster 5-2
Cluster 5-6
Cluster 5-5
Method %
CO2 Immisc. 33.33
Air 22.22
WAGCO2 Immisc. 22.22
Water Flooding 11.11
Polymer 11.11
Method %
Air
35.71
Steam
28.57
CO2 Immisc.
14.29
Polymer
7.14
Water Flooding
7.14
ASP
7.14
Method %
CO2 Immisc. 33.33
N2 Immisc. 16.67
WAG CO2 Immisc. 16.67
Polymer 16.67
ASP 16.67
Method %
Air 70
Steam 30
Method %
Air 52.94
Steam 47.06
Method %
Steam 37.5
Air 25
Polymer 25
12.5Water Flooding
Reservoir “B”
Burnt Lake
Foster
Creek
CO2 Immisc.
N2 Immisc.
Polymer
Steam
Air
Water Flooding
WAG CO2 Immisc.
ASP
SAGD (Canada)
Avg. Grosmont Carbonate
Peace River, Shell
Cold Lake, IOL
Primrose, CNRL
Ikiztepe (Heavy Oil Carbonate)
Qarn Alam (Heavy Oil Carbonate)
Issaran (Heavy Oil Carbonate)
Cluster 5-1
Cluster 5-3
Cluster 5-4
Cluster 5-2
Cluster 5-6
Cluster 5-5
Method %
CO2 Immisc. 33.33
Air 22.22
WAGCO2 Immisc. 22.22
Water Flooding 11.11
Polymer 11.11
Method %
Air
35.71
Steam
28.57
CO2 Immisc.
14.29
Polymer
7.14
Water Flooding
7.14
ASP
7.14
Method %
CO2 Immisc. 33.33
N2 Immisc. 16.67
WAG CO2 Immisc. 16.67
Polymer 16.67
ASP 16.67
Method %
Air 70
Steam 30
Method %
Air 52.94
Steam 47.06
Method %
Steam 37.5
Air 25
Polymer 25
12.5Water Flooding
Reservoir “B”
Burnt Lake
Foster
Creek
0
0.2
0.4
0.6
0.8
1
Porosity (%) (16-45)
Permeability (mD) (5-10500)
Depth (ft) (200-6800)
API Gravity (5.8-35)
Oil Viscosity (cp) (0.4-6000000)
Temperature (F) (10-280)
Primrose Gueheng Karamay 9-5 - 9-9McKittrick Karamay 6 Elk PointIron River Frog Lake MorganYorba Linda Maguerite Lake AthabascaPeace River Area Saner Ranch Cat CanyonKern River Tangleflags East Wolf Lake/Primrose/Burnt LakeFoster Creek Lean LindberghCaribou Lake Charlotte Lake Gregoire (Athabasca)Pikes Peak Cold Lake San Miguel-4Reservoir "A" Lost Hills Sec. 30 Schoonebeeck
0
0.2
0.4
0.6
0.8
1
Porosity (%) (16-45)
Permeability (mD) (5-10500)
Depth (ft) (200-6800)
API Gravity (5.8-35)
Oil Viscosity (cp) (0.4-6000000)
Temperature (F) (10-280)
Primrose Gueheng Karamay 9-5 - 9-9McKittrick Karamay 6 Elk PointIron River Frog Lake MorganYorba Linda Maguerite Lake AthabascaPeace River Area Saner Ranch Cat CanyonKern River Tangleflags East Wolf Lake/Primrose/Burnt LakeFoster Creek Lean LindberghCaribou Lake Charlotte Lake Gregoire (Athabasca)Pikes Peak Cold Lake San Miguel-4Reservoir "A" Lost Hills Sec. 30 Schoonebeeck
LOW MODERATE HIGH
LO
W
Wave-dominated delta
Barrier core
Barrier shore face
Sand-rich strand plain
Delta-front mouth bars
Proximal delta front
(accretionary)
Tidal Deposits
Mud-rich strand plain
Meander belts*
Fluvially dominated delta*
Back Barrier*
MO
DER
ATE
Eolian
Wave modified delta (distal)
Shelf barriers
Alluvial Fans
Fan Delta
Lacustrine delta
Distal delta front
Braided stream
Tide-dominated delta
HIG
H
Basin-flooring turbiditesCoarse-grained meander belt
Braid delta
Back barrier**
Fluvially dominated delta**
Fine-grained meander belt**
Submarine fans**
* Single units **Stacked Systems
LATERAL HETEROGENEITY
VE
RT
ICA
L H
ET
ER
OG
EN
EIT
Y
(9) / [1] (9) / [2]
(9) (83) / [14] (52) / [4]
(19) / [1] (2) (4)
LOW MODERATE HIGH
LO
W
Wave-dominated delta
Barrier core
Barrier shore face
Sand-rich strand plain
Delta-front mouth bars
Proximal delta front
(accretionary)
Tidal Deposits
Mud-rich strand plain
Meander belts*
Fluvially dominated delta*
Back Barrier*
MO
DER
ATE
Eolian
Wave modified delta (distal)
Shelf barriers
Alluvial Fans
Fan Delta
Lacustrine delta
Distal delta front
Braided stream
Tide-dominated delta
HIG
H
Basin-flooring turbiditesCoarse-grained meander belt
Braid delta
Back barrier**
Fluvially dominated delta**
Fine-grained meander belt**
Submarine fans**
* Single units **Stacked Systems
LATERAL HETEROGENEITY
VE
RT
ICA
L H
ET
ER
OG
EN
EIT
Y
(9) / [1] (9) / [2]
(9) (83) / [14] (52) / [4]
(19) / [1] (2) (4)
(9) / [1] (9) / [2]
(9) (83) / [14] (52) / [4]
(19) / [1] (2) (4)
Decision and Risk Analysis and EE
B. Canadian Oil Sand
Manrique et al., SPEREE, 2009
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
• Comparison of basic geologic
properties.
• DP coefficient from log and
core data to estimate the
impact on steam chamber
development.
• Lateral and vertical
heterogeneity indexes for
feasibility of SAGD well pairs in
the same units, vertical
separation and length.
LOW MODERATE HIGH
LO
WM
OD
ERATE
HIG
H
LATERAL HETEROGENEITY
VE
RT
ICA
L H
ET
ER
OG
EN
EIT
Y
LOW MODERATE HIGH
LO
WM
OD
ERATE
HIG
H
LATERAL HETEROGENEITY
VE
RT
ICA
L H
ET
ER
OG
EN
EIT
Y
LOW MODERATE HIGH
LO
WM
OD
ERATE
HIG
H
LATERAL HETEROGENEITY
VE
RT
ICA
L H
ET
ER
OG
EN
EIT
Y
LOW MODERATE HIGH
LO
WM
OD
ERATE
HIG
H
LATERAL HETEROGENEITY
VE
RT
ICA
L H
ET
ER
OG
EN
EIT
Y
LOW MODERATE HIGH
LO
WM
OD
ERATE
HIG
H
LATERAL HETEROGENEITY
VE
RT
ICA
L H
ET
ER
OG
EN
EIT
Y
LOW MODERATE HIGH
LO
WM
OD
ERATE
HIG
H
LATERAL HETEROGENEITY
VE
RT
ICA
L H
ET
ER
OG
EN
EIT
Y
B. Canadian Oil Sand
Manrique et al., SPEREE, 2009
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
• Cells (120 m x 800 m)
indicates potential SAGD
well pairs locations.
• Cumulative oil and CSOR
can be estimated from
correlations for different
net pays with and w/o top
gas and bottom water.
• As expected, RF
decreases and CSOR
increases with thickness
and presence of top gas
and bottom water.
Discarded for SAGD
B. Canadian Oil Sand
Manrique et al., SPEREE, 2009
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
Ongoing efforts at EORI-PETE (UW)
• Selection of adequate clustering algorithms to data-mine EORI database and others
• Reservoir type identification
• Incorporation of reservoir, fluids and geologic data into clustering methods
• Per-basin analysis of historical data
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
Screening: Variables used
• 3-7 variables (median) were considered: depth, permeability, thickness, temperature, viscosity, pressure, salinity. Example:
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
Gran
ularity
As one goes from top to bottom by fixing a horizontal line at certain levels, the number of clusters can be identified. The numbers at the bottom represent the individual reservoirs in the database
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
Projections One way of visually looking at the data is projections. Here is an example of 7 parameters projected on 3 Principal Component (PCA). Colors identify clusters.
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
Projections A more familiar look can be seen from the 2D projection
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
Projections (analogs)
The cluster structure can be used to find analogs
The lines joining “+”
with points identify
the connection
between 3 “new”
reservoirs with their
analog cases.
Minimum distance
was used to find the
analogs
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
Closing remarks
• Screening is not a one-step process and does not replace reservoir studies, but helps to assist decisions
• Several screening methods should be considered, especially when different data types are used
• Data-mining approaches alleviate expert opinions’ biases and can lead to the concept of “reservoir type”
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
BACKUP SLIDES SPEREE
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
C. Steam flooding project
• Decreasing well spacing increases the recovery factor
• Steam quality > 0.6 is required for significant increments in recovery factor – this is a critical design variable
0
10
20
30
40
50
0 50 100 150 200 250 300
Well Spacing (m)R
eco
very
Facto
r, %
SQ=1.0
SQ=0.8
SQ=0.6
SQ=0.4
SQ=0.2
SQ=0.0
0
10
20
30
40
50
60
0 20 40 60 80 100
% Pore Volume Injected
Rec
ove
ry F
ac
tor,
%
Well Spacing = 75mWell Spacing = 150 mWell Spacing = 225 mWell Spacing = 300 mWell Spacing = 75mWell Spacing = 150 mWell Spacing = 225 mWell Spacing = 300 m
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
C. Steam flooding project
• Performance predictions from simulations indicated improvement in oil recovery for smaller well spacing
• However, economics dictates an optimal well spacing below which no economic gain can be obtained
$0
$400
$800
$1,200
$1,600
$2,000
0 100 200 300 400
Well Spacing, (m)
Net
Pre
sen
t V
alu
e
PVI=70%, Oil Price = $90
PVI=70%, Oil Price = $60
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
5000 100005000 10000
• Decision problem is well spacing for a steam flooding
• Framing is for optimal recovery/production
• Building petrophysical models was not feasible
C. Steam flooding project
Manrique et al., SPEREE, 2009
-
E N H A N C E D O I L R E C O V E R Y I N S T I T U T E
Screening: Variables used
• Parameters values were rescaled (normalized)
• Once processed, the data were partitioned and clustered
• Dendograms were produced as a way to see the structure of the data and analyzed granularity of the dataset