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