Advances in CO 2 EOR Reservoir Modelling 公开课第12课 CO 2 提高采收率数值模拟进展
Advances in CO2 EOR Reservoir Modelling
公开课第12课
CO2提高采收率数值模拟进展
Agenda
• Introduction to EOR Processes
• Design Steps of CO2 EOR
• Mechanism Important to Process
• Advances in Hybrid EOR Processes
• Practical Workflow & Case Studies
• Conclusions
Why EOR Processes?
Oil recoveries from primary and secondary recovery phases are generally in the range of 20–40% of OOIP
Little Creek Field
Why CO2 EOR?
Two major advantages: • Additional oil recovery
• CO2 storage to reduce emissions of CO2
Miscible or Immiscible CO2 EOR?
• Proven to be technically feasible in miscible andimmiscible modes
• Among 123 CO2-EOR projects in the United States, 114are miscible projects (koottungal, 2012; kuuskraa, 2012)
• Mainly on light to ultra-light oils (>28°API) with aviscosity of less than 3 centipoise
Design Steps of CO2 EOR
Data Management and Analyses
Screening
Experimental Studies
Detailed Studies
Project Feasibility
Field Pilot Implementation
Full Field Development
Reserves (e.g. OOIP)Petro-physical Properties Oil Price, etc.
Criteria (e.g. depth)Projected Recovery Requirements, etc.
Full PVT ExperimentsCore Flood TestsRecovery Mechanisms, etc.
Risks (Enviro. & Tech.)Comm. & Political factors, etc.
Simulation Model
Applicability,Potential, Economic
Performance Monitoring
Optimization using Simulation
What Does Reservoir Modelling Aim at?
Better Understanding of Reservoir Performance
Steps to Make a Representative Model?
STEP 1: Reliable data Input • Reservoir Parameters, PVT, etc.
STEP 2: History Matching• Production and pressure history data
STEP 3: Forecast• Different scenarios, optimum design, etc.
Most Important StepNeeds understanding of physics and important
mechanisms
Reliable and Capable Modelling Tool
CO2 EOR Mechanisms
• PVT, solubility, and swelling
• Miscibility mechanisms
• Asphaltene deposition
• Wettability Alteration
• Hysteresis
• IFT Effects
• Diffusion and Dispersion
Additional Process Mechanisms
• Matrix dissolution from CO2 injection
• Aqueous chemical equilibrium reactions
• Ion-exchange
• Mineralization: dissolution and precipitation
• Thermal effects
• CO2 leakage through caprock
What to Use?
• Advanced general equation-of-statecompositional simulator
• Simulates compositional effects ofreservoir fluid during primary andenhanced oil recovery processes
• Phase behaviour and reservoir fluidproperty program for PVT modellingand data matching
For modelling of:
• Gas condensates
• Tight/shale gas
• CO2 EOR
• WAG
• Chemical EOR
• CO2 Sequestration
• LSW flooding
• Polymer Flooding
• ASP flooding
• D
Sensitivity Analysis
• Better understanding of a simulation model• Identify important parameters
History Matching
• Calibrate simulation model with field data• Obtain multiple history-matched models
Optimization
• Improve NPV, Recovery, D• Reduce cost
Uncertainty Analysis
• Quantify uncertainty• Understand and reduce risk
What to Use?
PVT
• Fluid Characterization
‒ Compositional Analysis
‒ Recombination
• Lab Data Matching
→→→→ P, T, and composition variation
‒ CCE
‒ Differential liberation
‒ Separator test
‒ Swelling test
0.00
0.05
0.10
0.15
N2
C1
CO
2
C2
H2
S
C3
i-C
4
n-C
4
i-C
5
n-C
5
C6
C7
C8
C9
C1
0
C1
1
C1
2
C1
3
C1
4
C1
5
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6
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8
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9
C2
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C2
1
C2
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C2
3
C2
4
C2
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9
C3
0+
Mo
l%
Component
6000
7000
8000
9000
10000
11000
12000
13000
0 0.1 0.2 0.3 0.4 0.5
Psat
(kP
a)
CO2 Composition
ModelExp. Data
0
30
60
90
120
150
180
0 3000 6000 9000 12000 15000 18000
Gas-O
il R
ati
o (
sm
3/s
m3)
Pressure (kPa)
Model
Exp. Data
Define pseudo-comp.
Miscibility Mechanisms
• Vaporizing, condensing, combined
• MMP and MME determination
• Methods‒ Cell to Cell ‒ Multiple Mixing Cell ‒ Semi-Analytical
Solubility in Water
• Direct Henry’s ConstantInput
• Correlations‒ Harvey’s Method
‒ Li-Nghiem’s Method
‒ Account for Salinity
0.000
0.005
0.010
0.015
0.020
0.025
0.000 0.005 0.010 0.015 0.020 0.025
Calc
ula
ted
CO
2 S
olu
bilit
y (
mo
le f
racti
on
)
Experimental CO2 Solubility (mole fraction)
Nighswander et al. (1989)
Kiepe et al. (2002)
Lucile et al. (2012)
Asphaltene Precipitation
Change in P, T, or Composition• Asphaltene/Wax Modelling Native Oil Solvent (CO2)
Precipitation
Flocculation
DepositionRe-Entrainment Pore Plugging
DepositionFlocculation
Pre
cip
itatio
n
Flocculation and Deposition
Plugging and Permeability Impairment
• Flocculation
‒ Aggregation into larger particles
‒ Suspended component
• Deposition
‒ Surface deposition, plugging deposition and re-entrainment
‒ Non-equilibrium Blockage
Blockage
• Resistance Factor Calculation‒ Power Law Model
‒ Kozeny-Carman Equation
‒ Solid Adsorption Model
• Permeability is divided by theresistance factor whilecalculating the phasetransmissibilities
k = k0 / rf
0
0.2
0.4
0.6
0.8
1
1.2
0 20 40 60 80
Pore Volumes Oil Injected
Pe
rme
ab
ilit
y R
ed
uc
tio
n (
k/k
0)
Experiment Model
Leontaritis et al. 1994, SPE 23810.
Wang 1988, SPE 37232
Wettability Alteration
• Wettability alteration− Asphaltene adsorption
− Geochemical interaction/ionexchange
• Capillary pressure andrelative permeability curveschange* KRINTRP
* INTCOMP
IFT Effect
• Relative permeability as a function of IFT
• At higher IFT, typical relative permeability curves
• Straight line relative permeabilitiesas the IFT is lowered
CO2 CO2
Nearly Miscible
Zone
Oil Bank
Additional Oil
Water Water
Hysteresis
A fluid (e.g. gas) moves into a pore:
1) Displaces fluid in pore(called drainage)
2) Sometimes displaced fluidmoves back into the pore(called imbibition)
3) A shift in the RelativePermeability during this can trapsome of the gas in the pore,making it immobile
Videos Courtesy Laboratório de Meios Porosos e Propriedades Termofísicas
Hysteresis
A fluid (e.g. gas) moves into a pore:
1) Displaces fluid in pore (called drainage)
2) Sometimes displaced fluid moves back into the pore (called imbibition)
3) A shift in the Relative Permeability during this can trap some of the gas in the pore, making it immobile
0
0.2
0.4
0.6
0.8
1
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
Re
lati
ve
Pe
rme
ab
ilit
y t
o G
as
Gas Saturation
Relative Permeability to Gas Changes Due to Hysteresis
Trapped due to Hysteresis
Diffusion and Dispersion
*D
D
*p D/du
Hydrostatic axis (σ’1= σ’2= σ’3)
σ’1, σ’2, σ’3 : Principle effective stresses
Cap
σ’1
σ’2
σ’3
Hydrostatic axis (σ’1= σ’2= σ’3)
σ’1, σ’2, σ’3 : Principle effective stresses
Cap
σ’1
σ’2
σ’3
Geomechanics
• Caprock integrity due to stress/strain relationships
• Different constitutive models
• Applications:
− Risk assessment in sequestration
− Deformation of geological structure due to fluid withdrawal/injection
− Geomechanical effects on coal-seams
− D
Geomechanics
Perkins and Johnston 1963
Advances in Hybrid EOR Processes
LSWI, Foam, etc.
CO2 + Low Salinity Water Flooding
LSW is attractive because:
• Operationally identical to conventional waterflooding
• No requirements for expensive chemicals
• Possible significant increase in recovery
LSW works in oil-wet reservoirs with clay
Main mechanism: wettability change from oil-wet to water-wet
CO2 LSWAG
CO2 WAG
- CO2 Miscibility
- Mobility Control (WAG)
- High Recovery Factor
- Delayed Production Problem
LSWI
- Wettability Alteration
- Higher Recovery w.r.t HSWI
- Lower Chemical Cost
- Environmental Impact
- Field Implementation
- Lower Recovery w.r.t Miscible Floods
CO2 LSWAG
- Synergy of Mechanisms
- CO2 Miscibility
- Mobility Control
- Wettability Alteration
- Geochemical Reaction with Inj CO2
- Ion Exchange
- Dissolution of Carbonate Minerals
- Higher Recovery w.r.t HSWI, LSWI, CO2 HSWAG, and pure CO2
- No Challenge of late Production
CO2 LSWAG in GEM
• EOS compositional simulator
• Full geochemistry model
− Aqueous reactions E.g. CO2(aq) + H2O = (H+) + (HCO3-)
− Ion exchange equilibria E.g. (Na+) + 0.5(Ca-X2) = 0.5(Ca++) + (Na-X)
− Mineral dissolution/precipitation reactions E.g. Calcite + (H+) = (Ca++) + (HCO3-)
• Interpolation between oil-wet andwater-wet relative permeability based onion exchange
• Models temperature effects on low salinity
Foam Assisted CO2 EOR
• Gas Mobility Control – Improve the sweep efficiency in by-
passed oil zones– Foam is used to change the mobility of
gas in the reservoir
• Gas Shut-Off – Foam around perforations reduce gas
mobility and production in wells located near the gas oil contact
Advances in Foam Modelling
• FMMOB: Foam Mobility
• F1: Surfactant Concentration
• F2: Oil Saturation
• F3 & F4: Capillary Number
• F5: Oil Composition
• F6: Salinity
• FDRY: Foam Dry Out
Modification of Relative Permeability Dependencies
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• Uses FM as interpolant
– FM = 0 Strong Foam
– FM = 1 No Foam
• Use FM as a multiplier to krg
Practical Workflow
Practical Work Flow
PVT Modelling
GEM 1D Model
Geological Modelling
Reservoir SimulationFlow, Wettability
Alteration, Miscibility, D
Sensitivity AnalysisHistory Matching
OptimizationUncertainty Assessment
CCE, Diff Liberation Separator, Swelling Test, D
Slim tube, Core-floods, D
Case Studies
Case Studies
Case 1: Field-scale inverted 5-spot pattern model• Application of workflow
Case 2: Field scale model • Primary and Secondary Recovery HM• WAG optimization• Evaluation of Mechanisms
Case 1: Field-Scale 5-spot Model
CCE Diff Lib
Separator
Fluid Model
Swelling testSaturated µ , ρ
FCM, Oil/CO2 Model
Slim Tube Test
Thermodynamic
Models (MCM)1D Model
Oil Recovery
Core Flood
1D ModelWAG
SS & HMRel Perm
0
20
40
60
80
100
0 0.2 0.4 0.6 0.8 1 1.2
Oil
Re
cov
ery
(%
)
PV Injected
GEM
SlimTube
0.96
0.97
0.98
0.99
1.00
1.01
1.02
5 10 15 20 25 30 35
RO
V
P (MPa)
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0 0.1 0.2 0.3 0.4 0.5
SF
Psa
t (M
Pa
)
CO2 Composition
Check MMP - Cell to Cell- Multiple Mixing- Semi-Analytical
Go
al
Sim
ula
tor
Da
ta
Case 1: Field-Scale 5-spot Model
Geological data, maps, etc
Base Case
Primary Production
Data
Prod & Press HM
Forecast
Optimization
TT1
Time (Date)
Oil R
ate
SC
(b
bl/d
ay)
1970 1975 1980 1985 19900
1,000
2,000
3,000
4,000SIMULATION OIL RATEHISTORICAL OIL RATE
Go
al
Sim
ula
tor
Da
ta
GAS_CYCLE_TIME
WATER_CYCLE_TIME
GAS_CYCLE_TIME
WATER_CYCLE_TIME
GAS_CYCLE_TIME*WATER_CYCLE_TIME
NUM_CYCLE
TT1
Time (Date)
Wate
r C
ut
SC
- %
1970 1975 1980 1985 19900
20
40
60
80SIMULATION WATER CUT %HISTORICAL WATER CUT %
Case 2: Field Scale Model
Original Oil in Place (OOIP):684.6 million barrels
• Start with 7 years of primary production (1983-1990)
• Followed by 18 years of water-flooding (1990-2008)
• Water-flooding followed by CO2 WAG process from 2008-2035
Cu
mu
lati
ve
Oil
Pro
du
cti
on
(m
illi
on
s m
3)
40
30
20
10
0
Time01/01/1983 23/06/1988 14/12/1993 06/06/1999 26/11/2004 19/05/2010
Case 2: Multiple-Stage History Match
Needed to match• Bottom-hole
pressures
• Cumulative oil production
− Per well
− Entire field
• From 1983 - 2008
Initial History Match (Primary)
Secondary History Match (Water-Flood)
CO2 EORPrediction
100 200 300 4000 500
Simulator Run Number
Net-
Pre
sen
t V
alu
e (
Mil
lio
ns $
)
700
775
850
925
1000
Base Solution, $750 Million
Optimized Solution, $975 Million
Case 2: Optimization of WAG Process
Optimized NPV
– Base NPV• $750 Million
– Optimized NPV• $975 Million
– Slug sizes
– Injection pressures
– Producer water-cut& GOR controls
Case 2: Physics Included
EOS phase behaviour
• Correctly accounts for phase changes of oil and CO2
FCM and MCM determinations
• Viscosity alteration
Solubility of CO2 in the aqueous phase
• Viscosity and density alterations of aqueous phase
Case 2: Additional Considerations
HysteresisNative Oil Solvent (CO2)
Precipitation
Flocculation
DepositionRe-Entrainment Pore Plugging
0
0.2
0.4
0.6
0.8
1
10000 12000 14000 16000 18000
So
lid
Pre
cip
itati
on
(w
eig
ht
%)
Pressure (psia)
3%5%
Asphaltene Deposition
GEM
– Geochemical EOS compositional simulator for CO2 storage in saline aquifers
Modelling of CO2 solubility and brine properties
– Solubility trapping
Relative permeability hysteresis
– Residual gas trapping
Aqueous chemical equilibrium reactions and mineral dissolution and precipitation kinetics
– CO2 mineralization
Geo-mechanics to model the cap rock integrity based on stress/strain relationships
Capabilities for Carbon Management
Conclusions• CMG accurately models CO2 related processes and mechanisms
• PVT modelling and data matching (WinProp)
• GEM multiphase multicomponent EOS thermal flow simulator
− CO2 Flooding, WAG, Foam, Polymer, ASP, LSWI, D
− Low Salinity + Miscible + Foam + ASP
− GEM is only commercial simulator that models combination of processes
• Full geochemistry model (aqueous reactions, ion-exchange, mineraldissolution, D)
• Geomechanics Module
• Sensitivity study, history matching, optimization, uncertainty analysis(CMOST)
• No other simulator/package can do all of this!