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The influence of wettability and carbon dioxide injection on
hydrocarbon recovery
Saif Al SayariMartin J. Blunt
• Objective• The influence of wettability on
– Electrical resistivity– NMR– Pc– Kr
• Pore scale modelling
• Efficacy of CO2 injection for hydrocarbon recovery– Tertiary HC gas injection– Tertiary WAG injection
– Tertiary CO2 Injection
Outline
• Evaluate the influence of wettability
• Compare the results with numerical predictions using pore-scale modelling where the pore space has been imaged using micro-CT scanning.
• Assess CO2 injection in carbonate oil fields.
Objectives
• Sandpack– Porosity ~ 34%– Permeability ~ 35 Darcy
• Sandstone – Fontainebleau– Porosity ~ 9 %– Permeability ~ 140 mD
• Carbonate – Middle East– Porosity ~ 28 %– Permeability ~ 7 mD
Conventional core analysis
MICP
Distribution Functions vs Log Pore Throat Size
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0.001 0.01 0.1 1 10 100
Log Pore Throat Radius (Microns)
Dis
trib
uti
on F
un
ctio
ns
0
40
80
120
0.00 0.20 0.40 0.60 0.80 1.00Water saturation, Sw (frac.)
Cap
illar
y pr
essu
re, P
c (p
si)
• Mercury injection capillary pressure is employed:
• to describe the pore-size distribution
• to draw drainage capillary pressure that can be used to compare to other methods such as the porous plate method .
Carbonate SN 4
Knowledge of the wettability of a reservoir rock and its influence on petrophysical properties is a key factor for determining oil recovery mechanisms and making estimates of recovery efficiency.
We combine in one study the effects of wettability on multiphase flow parameters, looking at capillary pressure, relative permeability, electrical properties and NMR.
Influence of wettability
Wettability Influence: Electrical Resistivity
Water wet Oil-wet
n (drainage) 2.33 2.67
n (imb.) 2.39 2.72
n (forced imb.) 2.66 3.25
1
10
100
1000
0.01 0.10 1.00Water saturation, Sw (frac.)
Res
istiv
ity in
dex,
RI
Drainage (Oil-wet)
Series2
Imb. (Oil-wet)
Forced Imb. (Oil-wet)
Drainage (Water-wet)
Series2
Imb (Water-wet)
Forced Imb (Water-wet)
Carbonate SN 4 - 5
-120
-80
-40
0
40
80
120
0.00 0.20 0.40 0.60 0.80 1.00
Water saturation, Sw (frac.)
Cap
illa
ry p
ress
ure,
Pc
(psi
)
Sample No. 4
Sample No. 5
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0.001 0.01 0.1 1 10 100
Log Pore Throat Radius (Microns)
Dis
trib
utio
n F
unct
ions
Carbonate sample:Pc (Oil-wet vs. Water wet)Very similar samples (Pore throat distribution)
Wettability Influence: Capillary Press.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Water saturation, frac.
Rel
ativ
e p
erm
eab
ility
ISSM kro ISSM krw Inj.Face krw Inj.Face kro
Steady-state relative permeability for carbonate sample at water-wet condition. The sample is then aged in crude oil and elevated temperature and the relative perm. will be conducted again
Wettability Influence: Relative Perm.
Carbonate SN 1
Core Micro-CT Network
Rock Properties PorosityPermeabilityFormation FactorCapillary PressureRelative PermeabilityNMR Response
PorosityPermeabilityFormation FactorNMR Response
PorosityPermeabilityFormation FactorCapillary PressureRelative PermeabilityNMR Response
Relative Permeability, SPE84550 Capillary Pressure
Pore-scale modeling: - Complementary to SCAL, for the determination of single and multiphase flow properties. - Looking at trends where data is lacking, different rock types, wettability and three-phase flow
Laboratory – pore scale
Sand pack - LV60B
Sand pack - F42B
F42B
0.01
0.1
1
0 1000 2000 3000Time (ms)
Nor
mal
ized
Am
plitu
de
Experimental
Micro-CT
Network
F42B
0
0.1
0.2
0.3
0.4
10 100 1000 10000T2 (ms)
Fre
quen
cy
Experimental
Micro-CTNetwork
LV60A
0.01
0.1
1
0 1000 2000 3000Time (ms)
Nor
mal
ized
Am
plitu
de
Experimental
Micro-CT
Network
LV60A
0
0.1
0.2
0.3
0.4
10 100 1000 10000T2 (ms)
Fre
quen
cy
Experimental
Micro-CTNetwork
NMR – Results Sandpacks
Carbonate (2)
Comparison of the experimental capillary pressures of carbonate C22 with simulation results from a tuned Berea network.
Simulation Parameters
Diffusion Coefficient: 2.07x10-9m2/s (Vinegar, 1995)
Bulk Relaxivity: 3.1s (Vinegar, 1995)
Surface Relaxivity: 2.8μm/s
Number of walkers: 2,000,000
Pores: 12,349Throats: 26,146
Network: Tuned BereaCapillary Pressure (C22)
0
200
400
600
800
1000
0.0 0.2 0.4 0.6 0.8 1.0S w
Cap
illar
y P
ress
ure
(K
Pa)
Experimental
Tuned Network
C22
0.01
0.1
1
0 500 1000 1500 2000Time (ms)
Nor
mal
ized
Am
plit
ud
e
Experimental
SimulationC22
0
0.05
0.1
0.15
0.2
0.25
10 100 1000 10000T2 (ms)
Fre
quen
cy
Experimental
Simulation
NMR – Results Carbonats
Carbonate (3)
Comparison of the experimental capillary pressures of carbonate C32 with simulation results from a tuned Berea network.
Simulation Parameters
Diffusion Coefficient: 2.07x10-9m2/s (Vinegar, 1995)
Bulk Relaxivity: 3.1s (Vinegar, 1995)
Surface Relaxivity: 2.1μm/s
Number of walkers: 2,000,000
Pores: 12,349Throats: 26,146
Network: Tuned BereaCapillary Pressure (C32)
0
200
400
600
800
1000
0.0 0.2 0.4 0.6 0.8 1.0S w
Cap
illar
y P
ress
ure
(K
Pa)
Experimental
Tuned Network
C32
0.01
0.1
1
0 500 1000 1500 2000Time (ms)
Nor
mal
ized
Am
plit
ud
e
Experimental
Simulation
C32
0
0.1
0.2
0.3
0.4
0.5
10 100 1000 10000T2 (ms)
Fre
quen
cyExperimental
Simulation
NMR – Results Carbonats
Efficacy of CO2 injection
Reservoir condition core flooding test have commenced
using a composite core plug from a producing field from the
Middle East. Reservoir temp. ~ 250 oF and press. ~ 4000 psi
After flooding the sample with brine, vertical flooding sequence has been applied:
• Tertiary Gas flood.
• Tertiary Water Alternating Gas.
• Tertiary CO2 injection.
• Oil produced from waterflooding was 42%
0.00
0.10
0.20
0.30
0.40
0.50
0.0 0.5 1.0 1.5 2.0
Brine Injected (PV)
Oil
Rec
over
y, H
CP
V fr
ac.
Efficacy of CO2 injection
• Oil produced from gas flooding was 82%
0.40
0.50
0.60
0.70
0.80
0.90
1.00
2.0 2.5 3.0 3.5 4.0Gas Injected (PV)
Oil
Rec
ove
ry, H
CP
V f
rac.
Tertiary Gas injection
• Oil produced from WAG flooding was 80%
0.40
0.50
0.60
0.70
0.80
0.90
1.00
2.0 2.5 3.0 3.5 4.0
Brine-Gas Injected (PV)
Oil
Rec
over
y, H
CP
V fr
ac.
Tertiary WAG injection
• Oil produced from CO2 flooding was 96%
0.40
0.50
0.60
0.70
0.80
0.90
1.00
2.0 2.5 3.0 3.5 4.0
Gas Injected (PV)
Oil
Rec
over
y, H
CP
V fr
ac.
Injection of CO2 stopped
Tertiary CO2 injection
• Comparison between different tertiary flooding methods
0.00
0.20
0.40
0.60
0.80
1.00
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0
Brine-Gas Injected (PV)
Oil
Re
cove
ry, H
CP
V fra
c.
Secondary Brine Injection
Tertiary Gas
Tertiary WAG
Tertiary CO2
Efficacy of CO2 injection
The influence of wettability and carbon dioxide injection on
hydrocarbon recovery
Saif Al SayariMartin J. Blunt