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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
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
& Evaluation& Evaluation
CoreCoreAcquisition Acquisition & Evaluation& Evaluation
StaticStaticPressuresPressures
WellWellSurveillanceSurveillance& Monitoring& Monitoring
WellWellPerformancePerformance
AnalysisAnalysis
ReservoirReservoirSimulationSimulation
FlowingFlowingPressuresPressures
ReservesReservesReservesReserves
TraditionalTraditionalDecline CurveDecline Curve
AnalysisAnalysis
QuantificationQuantification
TraditionalTraditionalDecline CurveDecline Curve
AnalysisAnalysis
TraditionalTraditionalDecline CurveDecline Curve
AnalysisAnalysis
QuantificationQuantification
VolumetricVolumetricGIPGIP
(Static)(Static)
Valida
tion
Valida
tion
VolumetricVolumetricGIPGIP
(Static)(Static)
VolumetricVolumetricGIPGIP
(Static)(Static)
Valida
tion
Valida
tion
ContactedContactedGIPGIP
(Dynamic)(Dynamic)
Validation
Validation
ContactedContactedGIPGIP
(Dynamic)(Dynamic)
ContactedContactedGIPGIP
(Dynamic)(Dynamic)
Validation
Validation
FluidFluidAcquisitionAcquisition
& Evaluation& Evaluation
Well LogWell LogAcquisitionAcquisition
& Evaluation& Evaluation
CoreCoreAcquisition Acquisition & Evaluation& Evaluation
StaticStaticPressuresPressures
FluidFluidAcquisitionAcquisition
& Evaluation& Evaluation
FluidFluidAcquisitionAcquisition
& Evaluation& Evaluation
Well LogWell LogAcquisitionAcquisition
& Evaluation& Evaluation
Well LogWell LogAcquisitionAcquisition
& Evaluation& Evaluation
CoreCoreAcquisition Acquisition & Evaluation& Evaluation
CoreCoreAcquisition Acquisition & Evaluation& Evaluation
StaticStaticPressuresPressures
StaticStaticPressuresPressures
WellWellSurveillanceSurveillance& Monitoring& Monitoring
WellWellPerformancePerformance
AnalysisAnalysis
ReservoirReservoirSimulationSimulation
FlowingFlowingPressuresPressures
WellWellSurveillanceSurveillance& Monitoring& Monitoring
WellWellSurveillanceSurveillance& Monitoring& Monitoring
WellWellPerformancePerformance
AnalysisAnalysis
WellWellPerformancePerformance
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
Application of Work-FlowProcess Model
Reserves Validation Stage Computing Volumetric Gas-in-Place (VGIP)
ReservesReserves
TraditionalTraditionalDecline CurveDecline Curve
AnalysisAnalysis
QuantificationQuantification
VolumetricVolumetricGIPGIP
(Static)(Static)
Valida
tion
Valida
tion
ContactedContactedGIPGIP
(Dynamic)(Dynamic)
Validation
Validation
FluidFluidAcquisitionAcquisition
& Evaluation& Evaluation
Well LogWell LogAcquisitionAcquisition
& Evaluation& Evaluation
CoreCoreAcquisition Acquisition & Evaluation& Evaluation
StaticStaticPressuresPressures
WellWellSurveillanceSurveillance& Monitoring& Monitoring
WellWellPerformancePerformance
AnalysisAnalysis
ReservoirReservoirSimulationSimulation
FlowingFlowingPressuresPressures
ReservesReservesReservesReserves
TraditionalTraditionalDecline CurveDecline Curve
AnalysisAnalysis
QuantificationQuantification
TraditionalTraditionalDecline CurveDecline Curve
AnalysisAnalysis
TraditionalTraditionalDecline CurveDecline Curve
AnalysisAnalysis
QuantificationQuantification
VolumetricVolumetricGIPGIP
(Static)(Static)
Valida
tion
Valida
tion
VolumetricVolumetricGIPGIP
(Static)(Static)
VolumetricVolumetricGIPGIP
(Static)(Static)
Valida
tion
Valida
tion
ContactedContactedGIPGIP
(Dynamic)(Dynamic)
Validation
Validation
ContactedContactedGIPGIP
(Dynamic)(Dynamic)
ContactedContactedGIPGIP
(Dynamic)(Dynamic)
Validation
Validation
FluidFluidAcquisitionAcquisition
& Evaluation& Evaluation
Well LogWell LogAcquisitionAcquisition
& Evaluation& Evaluation
CoreCoreAcquisition Acquisition & Evaluation& Evaluation
StaticStaticPressuresPressures
FluidFluidAcquisitionAcquisition
& Evaluation& Evaluation
FluidFluidAcquisitionAcquisition
& Evaluation& Evaluation
Well LogWell LogAcquisitionAcquisition
& Evaluation& Evaluation
Well LogWell LogAcquisitionAcquisition
& Evaluation& Evaluation
CoreCoreAcquisition Acquisition & Evaluation& Evaluation
CoreCoreAcquisition Acquisition & Evaluation& Evaluation
StaticStaticPressuresPressures
StaticStaticPressuresPressures
WellWellSurveillanceSurveillance& Monitoring& Monitoring
WellWellPerformancePerformance
AnalysisAnalysis
ReservoirReservoirSimulationSimulation
FlowingFlowingPressuresPressures
WellWellSurveillanceSurveillance& Monitoring& Monitoring
WellWellSurveillanceSurveillance& Monitoring& Monitoring
WellWellPerformancePerformance
AnalysisAnalysis
WellWellPerformancePerformance
AnalysisAnalysis
ReservoirReservoirSimulationSimulationReservoirReservoirSimulationSimulation
FlowingFlowingPressuresPressuresFlowingFlowing
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
Application of Work-FlowProcess Model
Reserves Validation Stage Computing Contacted Gas-in-Place (CGIP)
ReservesReserves
TraditionalTraditionalDecline CurveDecline Curve
AnalysisAnalysis
QuantificationQuantification
VolumetricVolumetricGIPGIP
(Static)(Static)
Valida
tion
Valida
tion
ContactedContactedGIPGIP
(Dynamic)(Dynamic)
Validation
Validation
FluidFluidAcquisitionAcquisition
& Evaluation& Evaluation
Well LogWell LogAcquisitionAcquisition
& Evaluation& Evaluation
CoreCoreAcquisition Acquisition & Evaluation& Evaluation
StaticStaticPressuresPressures
WellWellSurveillanceSurveillance& Monitoring& Monitoring
WellWellPerformancePerformance
AnalysisAnalysis
ReservoirReservoirSimulationSimulation
FlowingFlowingPressuresPressures
ReservesReservesReservesReserves
TraditionalTraditionalDecline CurveDecline Curve
AnalysisAnalysis
QuantificationQuantification
TraditionalTraditionalDecline CurveDecline Curve
AnalysisAnalysis
TraditionalTraditionalDecline CurveDecline Curve
AnalysisAnalysis
QuantificationQuantification
VolumetricVolumetricGIPGIP
(Static)(Static)
Valida
tion
Valida
tion
VolumetricVolumetricGIPGIP
(Static)(Static)
VolumetricVolumetricGIPGIP
(Static)(Static)
Valida
tion
Valida
tion
ContactedContactedGIPGIP
(Dynamic)(Dynamic)
Validation
Validation
ContactedContactedGIPGIP
(Dynamic)(Dynamic)
ContactedContactedGIPGIP
(Dynamic)(Dynamic)
Validation
Validation
FluidFluidAcquisitionAcquisition
& Evaluation& Evaluation
Well LogWell LogAcquisitionAcquisition
& Evaluation& Evaluation
CoreCoreAcquisition Acquisition & Evaluation& Evaluation
StaticStaticPressuresPressures
FluidFluidAcquisitionAcquisition
& Evaluation& Evaluation
FluidFluidAcquisitionAcquisition
& Evaluation& Evaluation
Well LogWell LogAcquisitionAcquisition
& Evaluation& Evaluation
Well LogWell LogAcquisitionAcquisition
& Evaluation& Evaluation
CoreCoreAcquisition Acquisition & Evaluation& Evaluation
CoreCoreAcquisition Acquisition & Evaluation& Evaluation
StaticStaticPressuresPressures
StaticStaticPressuresPressures
WellWellSurveillanceSurveillance& Monitoring& Monitoring
WellWellPerformancePerformance
AnalysisAnalysis
ReservoirReservoirSimulationSimulation
FlowingFlowingPressuresPressures
WellWellSurveillanceSurveillance& Monitoring& Monitoring
WellWellSurveillanceSurveillance& Monitoring& Monitoring
WellWellPerformancePerformance
AnalysisAnalysis
WellWellPerformancePerformance
AnalysisAnalysis
ReservoirReservoirSimulationSimulationReservoirReservoirSimulationSimulation
FlowingFlowingPressuresPressuresFlowingFlowing
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
•CGIP = 1.215 Bscf
•Contacted area = 7.31
acres
Agarwal-Gardner
Flowing P/ZComputing Contacted
GIP
Rate Transient Analysis; CGIP, k, Fh
300 Day Flow Period
•CGIP = 1.038 Bscf
•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
Application of Work-FlowProcess Model
Reserves Validation Stage Reservoir Simulation; Estimation of Drainage
Area &EUR
ReservesReserves
TraditionalTraditionalDecline CurveDecline Curve
AnalysisAnalysis
QuantificationQuantification
VolumetricVolumetricGIPGIP
(Static)(Static)
Valida
tion
Valida
tion
ContactedContactedGIPGIP
(Dynamic)(Dynamic)
Validation
Validation
FluidFluidAcquisitionAcquisition
& Evaluation& Evaluation
Well LogWell LogAcquisitionAcquisition
& Evaluation& Evaluation
CoreCoreAcquisition Acquisition & Evaluation& Evaluation
StaticStaticPressuresPressures
WellWellSurveillanceSurveillance& Monitoring& Monitoring
WellWellPerformancePerformance
AnalysisAnalysis
ReservoirReservoirSimulationSimulation
FlowingFlowingPressuresPressures
ReservesReservesReservesReserves
TraditionalTraditionalDecline CurveDecline Curve
AnalysisAnalysis
QuantificationQuantification
TraditionalTraditionalDecline CurveDecline Curve
AnalysisAnalysis
TraditionalTraditionalDecline CurveDecline Curve
AnalysisAnalysis
QuantificationQuantification
VolumetricVolumetricGIPGIP
(Static)(Static)
Valida
tion
Valida
tion
VolumetricVolumetricGIPGIP
(Static)(Static)
VolumetricVolumetricGIPGIP
(Static)(Static)
Valida
tion
Valida
tion
ContactedContactedGIPGIP
(Dynamic)(Dynamic)
Validation
Validation
ContactedContactedGIPGIP
(Dynamic)(Dynamic)
ContactedContactedGIPGIP
(Dynamic)(Dynamic)
Validation
Validation
FluidFluidAcquisitionAcquisition
& Evaluation& Evaluation
Well LogWell LogAcquisitionAcquisition
& Evaluation& Evaluation
CoreCoreAcquisition Acquisition & Evaluation& Evaluation
StaticStaticPressuresPressures
FluidFluidAcquisitionAcquisition
& Evaluation& Evaluation
FluidFluidAcquisitionAcquisition
& Evaluation& Evaluation
Well LogWell LogAcquisitionAcquisition
& Evaluation& Evaluation
Well LogWell LogAcquisitionAcquisition
& Evaluation& Evaluation
CoreCoreAcquisition Acquisition & Evaluation& Evaluation
CoreCoreAcquisition Acquisition & Evaluation& Evaluation
StaticStaticPressuresPressures
StaticStaticPressuresPressures
WellWellSurveillanceSurveillance& Monitoring& Monitoring
WellWellPerformancePerformance
AnalysisAnalysis
ReservoirReservoirSimulationSimulation
FlowingFlowingPressuresPressures
WellWellSurveillanceSurveillance& Monitoring& Monitoring
WellWellSurveillanceSurveillance& Monitoring& Monitoring
WellWellPerformancePerformance
AnalysisAnalysis
WellWellPerformancePerformance
AnalysisAnalysis
ReservoirReservoirSimulationSimulationReservoirReservoirSimulationSimulation
FlowingFlowingPressuresPressuresFlowingFlowing
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