Studies of Foam for EOR and CO storage: Liquid Injectivity

Studies of Foam for EOR and CO2 storage:

Liquid Injectivity3, the Effect of Oil on Foam2, and

Generation In-situ in Heterogeneous Formations1

Delft University of Technology

1Swej Y. Shah [email protected]

2Jinyu Tang [email protected]

3Jiakun Gong [email protected]

4William Rossen [email protected]

2

INTRODUCTION TO FOAM IN POROUS MEDIA

Foams are a distribution of discontinuous gas bubbles in a continuous liquid phase.

Gas mobility reduction, conformance improvement in displacement processes. Enhanced oil recovery (EOR).

Shallow aquifer remediation - (D)NAPL removal.

CO2 storage.

Subsurface applications

1Fried, A.N., 19612Marsden, 19862Kovscek and Radke, 19943Rossen, W.R., 19964Hirasaki, G.J. et. al., SPE J., 19975Alcorn, Z.P. et. al., 20186Rognmo, A. et. al. 2018

3

N2 vs CO2 FOAM

Some considerations before extending conclusions from N2-foam to CO2-foam:

CO2-water systems have lower interfacial tension

CO2 foam can be easier to generate

Lower pressure gradient required to sustain propagation

Different rates of gas diffusion.

CO2 solubility in water is much higher than N2.

Different behaviour in the presence of oil.









5

BACKGROUND

Liquid Injectivity in Surfactant-Alternating-Gas Foam

Enhanced Oil Recovery

Injectivity is a key economic factor of a foam EOR process

Gas injectivity in SAG process is good

Liquid injectivity is often very poor in a SAG process

What controls liquid injectivity? How to model it?

[email protected]

6

EXPERIMENTAL DESIGN

Surfactant

Solution

Back-Pressure

Regulator

CT Scan

Effluent

Flask

Quizix Pump

N2

dP2

6.9 cm

4.2 cm

dPt Pout

P1

N2Mass Flow

Controller

[email protected]

7

EXPERIMENTAL DESIGN

Surfactant

Solution

Back-Pressure

Regulator

CT Scan

Effluent

Flask

Quizix Pump

N2

dP2

6.9 cm

4.2 cm

dPt Pout

P1

N2Mass Flow

Controller

Field core is used for all experiments

Focus on middle section

Free of entrance and capillary-end effects

0 2 4 6 80.1

0.2

0.3

0.4

0.5 Case A

Case B

Case C

Wa

ter

sa

tura

tio

n [

-]

Distance from inlet [cm]

Region studied (Section 2)

[email protected]

Liquid injection directly after

steady-state foam

9

LIQUID INJECTION DIRECTLY AFTER STEADY-STATE FOAM

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0 5 10 15 20 25 300

100

200

300

400

Pre

ssu

re g

rad

ien

t [b

ar/

m]

Total pore volumes liquid injected [-]

a

c

b

d

e

fg

1

0

0.8

0.6

0.4

0.2

Sw

Liquid injectivity directly following foam is

poor

Pressure gradient evolves over three

stages

Liquid enters with relatively high

mobility

Liquid penetrates foam in a finger

Displacement or dissolution of gas

trapped within a finger into

unsaturated injected liquid

Gong, J. et. al., EAGE IOR, 2019

How would gas-slug injection affect

subsequent liquid injectivity?

11

PROLONGED PERIOD OF GAS INJECTION

[email protected], J. et. al., EAGE IOR, 2019

Foam collapses or greatly weakens

when a sufficient volume of gas is

injected.

0 100 200 300 400 500 600 7000

50

100

150

200

250

300

0 100 200 300 400 500 600 7000.0

0.1

0.2

0.3

0.4

c

b

Pre

ss

ure

gra

die

nt

[ba

r/m

]

Total pore volumes gas injected [-]

afoam

34 PV

174 PV

211 PV

340 PV

397 PV

461 PV

539 PV

639 PV

1

0

0.8

0.6

0.4

0.2

Sw

1.8 cm

3.0 cm

4.2 cm

5.4 cm

Wa

ter

sa

tura

tio

n [

-]


0 100 200 300 400 500 600 7000

50

100

150

200

250

300

0 100 200 300 400 500 600 7000.0

0.1

0.2

0.3

0.4

c

b

Pre

ss

ure

gra

die

nt

[ba

r/m

]


afoam

34 PV

174 PV

211 PV

340 PV

397 PV

461 PV

539 PV

639 PV

1

0

0.8

0.6

0.4

0.2

Sw

1.8 cm

3.0 cm

4.2 cm

5.4 cm

Wa

ter

sa

tura

tio

n [

-]


Foam weakens

Foam collapses

The collapsed-foam region moves

as a front from the inlet to the

outlet as more gas is injected.

12

LIQUID FOLLOWS PROLONGED PERIOD OF GAS INJECTION


0 100 200 300 400 500 600 7000

50

100

150

200

250

300

0 100 200 300 400 500 600 7000.0

0.1

0.2

0.3

0.4

c

b

Pre

ss

ure

gra

die

nt

[ba

r/m

]


afoam

34 PV

174 PV

211 PV

340 PV

397 PV

461 PV

539 PV

639 PV

1

0

0.8

0.6

0.4

0.2

Sw

1.8 cm

3.0 cm

4.2 cm

5.4 cm

Wa

ter

sa

tura

tio

n [

-]


Foam collapses or greatly weakens after a prolonged period of gas

injection, leaving less trapped gas

Subsequent liquid injection is much easier than following full-strength foam

Liquid sweeps the entire cross section

without fingering

13

LIQUID FOLLOWS PROLONGED PERIOD OF GAS INJECTION

If the gas slug in a SAG process is equivalent to the pore volume to a

radius of 20 m from the well (far less than a pattern pore volume), at the

end of injection of the gas slug ...

region out to 20 cm has seen

10,000 PV gas injection

In radial flow, radius out to 3 m

represents half the pressure drop

in a region of radius 100 m

Translate to radial flow

14

LIQUID FOLLOWS A SMALLER GAS SLUG


Gas-slug size: 250 PV

0 100 200 300 400 500 600 7000

50

100

150

200

250

300

0 100 200 300 400 500 600 7000.0

0.1

0.2

0.3

0.4

c

b

Pre

ss

ure

gra

die

nt

[ba

r/m

]


afoam

34 PV

174 PV

211 PV

340 PV

397 PV

461 PV

539 PV

639 PV

1

0

0.8

0.6

0.4

0.2

Sw

1.8 cm

3.0 cm

4.2 cm

5.4 cm

Wa

ter

sa

tura

tio

n [

-]


Foam collapses or greatly weakens to this position

15



At the end of gas

injection, core is

occupied by the

collapsed-foam bank

and the weakened-

foam bank

OutletInlet

c

b

12 PV6.3 PV2.5 PV0.46 PV0.37 PV

3 cm1.2 cm

gas-end

a

gas-end 0.37 PV 0.46 PV 2.5 PV 6.3 PV 12 PV

front

collpased-foam bank weakened-foam bank 1

0

0.8

0.6

0.4

0.2

Sw

1.2 cm

3 cm

16



In the collapsed-foam

region, liquid first

flushes the entire cross

section, then forms

preferential paths

OutletInlet

c

b

12 PV6.3 PV2.5 PV0.46 PV0.37 PV

3 cm1.2 cm

gas-end

a


front


0

0.8

0.6

0.4

0.2

Sw

1.2 cm

3 cm

17



In the weakened-

foam region, liquid

fingers through foam

as in liquid injection

directly following

foam

OutletInlet

c

b

12 PV6.3 PV2.5 PV0.46 PV0.37 PV

3 cm1.2 cm

gas-end

a


front


0

0.8

0.6

0.4

0.2

Sw

1.2 cm

3 cm

Bank-propagation model

19

BANKS IN A SAG PROCESS

[email protected], J. et. al., SPE J., 2019

Gas-injection period Liquid-injection period

Foam bank

Collapsed-foambank

Injection Well

Flow Flow

Liquid-fingering bank

Gas-dissolution bank

Foam bank

Collapsed-foambank

Injection Well

Flow Flow

20

BANK-PROPAGATION MODEL


Gas-injection period:

∆𝑝𝑡 = ∆𝑝𝐹 + ∆𝑝𝐹𝐶𝐺

total pressure difference

foam bank

collapsed-foam bank

Foam bank

Collapsed-foambank

Injection Well

Flow Flow



Foam bank

Collapsed-foambank

Injection Well

Flow Flow Key parameters:

Dimensionless propagation velocity

Total mobility of each bank

21

BANK-PROPAGATION MODEL


Liquid-injection period:

∆𝑝𝑡 = ∆𝑝𝐹𝐶𝐿 + ∆𝑝𝐺𝐷 + ∆𝑝𝐿𝐹 + ∆𝑝𝐹

collapsed-foam bank

gas-dissolution bank

liquid-fingering bank

Foam bank

Collapsed-foambank

Injection Well

Flow Flow



Foam bank

Collapsed-foambank

Injection Well

Flow Flow

foam bank

Solve Darcy’s Law in each bank


Linear-flow model gives reasonable fit tolab data. Especially Section 4.

In Sections 2 and 3, foam collapse takesa somewhat shorter time in experimentthan in model.

WHY? Drying out and collapse of foam reflects

interplay of pressure gradient, capillaryeffects, evaporation.

Not all of these effects scale-up simply.

0 100 200 300 4000

20

40

60 Linear-flow model - S2

Linear-flow model - S3


Experiment - S2

Experiment - S3

Experiment - S4

Pre

ssu

re g

rad

ien

t [b

ar/

m]


S4S3S2

Experiment

Linear-flow model

LINEAR-FLOW FIT FOR GAS INJECTIVITY


Liquid injection follows 135 TPV gas Liquid injection follows 245 TPV gas

0 5 10 15 200

20

40

60

80




Experiment - S2

Experiment - S3

Experiment - S4

Pre

ssu

re g

rad

ien

t [b

ar/

m]


S4

S3

S2

0 5 10 15 200

20

40

60

80




Experiment - S2

Experiment - S3

Experiment - S4

Pre

ssu

re g

rad

ien

t [b

ar/

m]


Linear-flow model gives reasonable fit to lab data

LINEAR-FLOW FIT FOR LIQUID INJECTIVITY

Can conventional foam simulators

represent our experimental

findings?

[email protected]

GAS INJECTIVITY

PEACEMAN EQUATION VS. BANK-PROPAGATION MODEL

0 5 10 15 201

10

100

1000

10000 1 G-PV gas injection - Peaceman equation

10 G-PV gas injection - Peaceman equation


1 G-PV gas injection - Radial-flow model



Dim

en

sio

nle

ss p

res

su

re d

rop

[-]

Grid-block pore volumes gas injected [-]

Peaceman equation,Parameters fit to foam scan


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GAS INJECTIVITY


0 5 10 15 201

10

100

1000







Dim

en

sio

nle

ss p

res

su

re d

rop

[-]



Peaceman equation based simulation overestimates pressure peak by 70 times.


[email protected]

GAS INJECTIVITY


0 5 10 15 201

10

100

1000







Dim

en

sio

nle

ss p

res

su

re d

rop

[-]



Peaceman equation based simulation overestimates pressure rise by 40 times at a later stage.


[email protected]

LIQUID INJECTIVITY


In radial-flow calculations based on lab data, larger gas slugs increase injectivity of liquid slugs.

Small effects of gas slug on subsequent liquid slug in Peaceman equation.

The more gas is injected before liquid, the bigger error the simulation would give.

0 1 2 3 4 51

10

100

1000

10000 Liquid follows 1 GPV gas - Peaceman

Liquid follows 10 GPV gas - Peaceman

Liquid follows 20 GPV gas - Peaceman

Liquid follows 1 GPV gas - Radial-flow



Dim

en

sio

nle

ss p

ressu

re d

rop

[-]

Grid-block pore volumes liquid injected [-]

Peaceman equation


More gas was injected

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EXPLANATION

Example: 1 GPV liquid follows 10-GPV gas slug

20 m Conventional simulator

Collapsed-foam region mobility: 150 md/cPGas-dissolution region mobility: 66 md/cPLiquid-fingering region mobility: 0.85 md/cP

9 m

16 m

20 m

Grid-block water saturation: ~0.45Grid-block mobility: 0.75 md/cPDimensionless pressure rise: 300


1 Grid block = 100 x 100 m2

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SUMMARY

During gas injection following foam

Gas first weakens foam in the entire core.

Then a collapsed-foam region forms near the inlet and propagates slowly

downstream.

During subsequent liquid injection

Liquid sweeps the entire core cross section in the collapsed-foam region.

Liquid fingers through the weakened-foam region.

Gas dissolution is the key for forming the liquid finger and directing liquid

to flow through the finger

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SUMMARY

Conventional simulation using Peaceman model

Underestimates injectivity.

Propagation of the collapsed-foam region.

Cannot represent the effect of previous gas injection on subsequent liquid

injectivity

A new set of experiments would need to be conducted and a new set of

parameters fit to those results is necessary for each field application.

With assumptions and approximations, this model is not predictive. It indicates

trends in expected behavior. Be prepared for adjusting injection rate in field.

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SUMMARY

Simulators face two challenges:

o Grid resolution near well

o Mechanisms not represented in model

Evaporation of liquid during gas injection

Dissolution of trapped gas during liquid injection

Capillary-pressure gradients during drying near well

Fingering of liquid through trapped gas

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SUMMARY

CO2 instead of N2?

o We expect similar overall behavior incl. bank-propagation

o Liquid evaporation and foam collapse during gas injection could be

different

o CO2 is more soluble

Faster gas dissolution into water

Faster propagation of the gas-dissolution front during liquid

injection









35

OUTLINE

Foam for gas-mobility control

Experiment investigation of foam flow regimes with oil

Modeling of steady-state foam-oil flow

CT study of foam corefloods with oil

Summary

Current challenges

36

FOAM FLOW REGIMES

Foam-flow regimes in porous media

High-quality regime at the upper left

Low-quality regime at the lower right

Crucial starting point for deeper

exploration in geological formations

Pressure gradient as a function of Uw

and Ug, Osterloh and Jante (1992)

[email protected]

37

EXPERIMENTAL INVESTIGATION:

FOAM-FLOW REGIMES WITH OIL

Co-inject foam and oil to ensure steady state

Fix Uo/Uw ratio to quantify the effect of oil

[email protected]

Water Oil

Gas

4P

2P

3P

1P

Bentheimer core sample

Foam mobility-reduction factor with oil

Two types of model oils used:

Hexadecane (C16), benign to foam stability

Mixture of C16 and oleic acid (OA), very

harmful to foam

C16

C16 + 20%OA

38

200250

300350400

450

450

500

550

600600

500

B

B

B

B B

B

B

B

B

B

B

BB

BB

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

BB

B

B

B

B

B

B

B

B

B

B

0

1

2

3

4

5

6

7

0 0.25 0.5 0.75 1 1.25 1.5 1.75 2

Ug,

ft/D

Uw, ft/D

Steady-state foam flow without oil

Reference without oil


FOAM AND C16

[email protected]

100

120

140

160

160

180

180

200

200

B

B

B

B

B

B

B

B

BB

B

B

B

B

B

B B

B

0

1

2

3

4

5

6

7

0 0.25 0.5 0.75 1 1.25 1.5 1.75 2

Ug

, ft

/D

Uw, ft/D

201

237

194

201

196

200

206

204

14493

107

104

158

217

193

181 198

204

∇P, 3 times lower

∇P, 2 times lower

Steady-state foam flow with C16

Uo/Uw=0.25 with C16

Two regimes still exist, oil affects both regimes, high-quality regime is more vulnerable to oil

Low-quality, tilted upward, not independent of Uw.

Tang, J. et. al., SPE J., 2019

39


FOAM AND C16 + 20%OA

Oil type plays as significant a role as oil saturation

Gas-mobility reduction is 40x lower in the high-quality regime

and 7x lower in the low-quality regime

200250

300350400

450

450

500

550

600600

500

B

B

B

B B

B

B

B

B

B

B

BB

BB

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

BB

B

B

B

B

B

B

B

B

B

B

0

1

2

3

4

5

6

7

0 0.25 0.5 0.75 1 1.25 1.5 1.75 2

Ug,

ft/D

Uw, ft/D

Steady-state foam flow without oil

10

10

20

20

30

30

30

40

40

40

50

50

60

60

70

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

BB B B0

1

2

3

4

5

6

7

0 0.5 1 1.5 2 2.5 3 3.5 4

Ug , ft/D

Uw , ft/D

6

7

7

9

9

9

11

13

13

18

19

20

31

30

32

51

52

58

71

77

79

161522 30

fg*=0.2

Steady state foam flow with 20% OA in oil

Uo/Uw=0.25 with 20%OAReference without oil

[email protected]


40

Implicit-texture modelling: "wet-foam" algorithm and "dry-out“ algorithm

Contour shift reflects the effect of oil on each regime.

Each algorithm represents the effect of oil only on one regime or the other.

[email protected]

MODELLING OF STEADY-STATE FOAM + OIL FLOW

0 1 2 3 4 5

0

1

2

3

4

5

6

7

Ug,

ft/D

Uw, ft/D

200 psi/ft

300 psi/ft

400 psi/ft

500 psi/ft

600 psi/ft

700 psi/ft

0 1 2 3 4 5

0

1

2

3

4

5

6

7

Ug,

ft/D

Uw, ft/D

200 psi/ft

300 psi/ft

400 psi/ft

500 psi/ft

600 psi/ft

700 psi/ft

0 1 2 3 4 5

0

1

2

3

4

5

6

7

Ug,

ft/D

Uw, ft/D

200 psi/ft

300 psi/ft

400 psi/ft

500 psi/ft

600 psi/ft

700 psi/ft

0 1 2 3 4 5

0

1

2

3

4

5

6

7

Ug,

ft/D

Uw, ft/D

200 psi/ft

300 psi/ft

400 psi/ft

500 psi/ft

600 psi/ft

700 psi/ft

(Uo/Uw)=0.25

With wet-foam algorithm

0 1 2 3 4 5 6 7

0

1

2

3

4

5

Ug,

ft/D

Uw, ft/D

200 psi/ft

300 psi/ft

400 psi/ft

500 psi/ft

600 psi/ft

700 psi/ft

0 1 2 3 4 5 6 7

0

1

2

3

4

5

Ug,

ft/D

Uw, ft/D

200 psi/ft

300 psi/ft

400 psi/ft

500 psi/ft

600 psi/ft

700 psi/ft

0 1 2 3 4 5 6 7

0

1

2

3

4

5

Ug,

ft/D

Uw, ft/D

200 psi/ft

300 psi/ft

400 psi/ft

500 psi/ft

600 psi/ft

700 psi/ft

0 1 2 3 4 5 6 7

0

1

2

3

4

5

Ug,

ft/D

Uw, ft/D

200 psi/ft

300 psi/ft

400 psi/ft

500 psi/ft

600 psi/ft

700 psi/ft

(Uo/Uw)=0.25

With dry-out algorithm

( , )f o

rg rg w ok k FM S S

41

Foam properties were estimated from steady-state data.

Good match to experimental data, except for the upward-tilting ∇P contours in the low-

quality regime.

[email protected]


100

120

140

140

160

160

180

180

200220

200

B

B

B

B

B

B

B

B

BB

B

B

B

B

B

B B

B

0

1

2

3

4

5

6

7

0 0.25 0.5 0.75 1 1.25 1.5 1.75 2

Ug ,

ft/D

Uw , ft/D

201

237

194

201

196

200

206

204

144

93

107

104

158

217

193

181 198

204

Data on foam flow with C16

0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.000

1

2

3

4

5

6

7

Ug,

ft/D

Uw, ft/D

100 psi/ft

140 psi/ft

160 psi/ft

180 psi/ft

200 psi/ft

Model fit to data

MODEL FIT TO STEADY-STATE FOAM WITH C16


42

One must combine wet-foam and dry-out algorithms to represent the effect of oil on

both regimes.

[email protected]


MODEL FIT TO STEADY-STATE FOAM WITH C16 + 20% OA

Data on foam flow with 20% OA Model fit to data

10

10

20

20

30

30

30

40

40

40

50

50

60

60

70

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

B

BB B B0

1

2

3

4

5

6

7

0 0.5 1 1.5 2 2.5 3 3.5 4

Ug , ft/D

Uw , ft/D

6

7

7

9

9

9

11

13

13

18

19

20

31

30

32

51

52

58

71

77

79

161522 30

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.00

1

2

3

4

5

6

7

Ug,

ft/D

Uw, ft/D

7 psi/ft

10 psi/ft

20 psi/ft

30 psi/ft

40 psi/ft

50 psi/ft

60 psi/ft

70 psi/ft


43

Pre-generated foam vs.

in-situ-generated foam

with C16.

Two injection methods

show similarities in

foam dynamics.

Foam develops quickly,

followed by refinement

in texture.

[email protected]

CT STUDY OF DYNAMIC FOAM COREFLOODS WITH OIL

Mobility reduction factor (MRF)

Simjoo and Zitha (2013)

0 1 2 3 4 5 6 7 8

0

1

2

3

4

5

6

7

Se

ctio

na

l p

ressu

re d

rop

, 1

05 P

a

Number of pore volume injected (PVI)

dp for section 2

dp for section 3

dp for section 4

dp for section 5

dp for section 6

~ 1.5 PVITexture refinement

Sectional pressure drop

Tang (2019)

In-situ-generated foam Pre-generated foam

0.5 wt%

44

Pre-generated foam vs.

in-situ-generated foam

with C16 + 20% OA.

Foam behavior is very

different.

In-situ foam generation

is very difficult even at

Sor ~0.1.

Pre-generated foam

shows two stages of

[email protected]

CT STUDY OF DYNAMIC FOAM COREFLOODS WITH OIL


In-situ-generated foam Pre-generated foam

0 5 10 15 20 25 300.0

0.1

0.2

0.3

0.4

0.5 dp for section 1

dp for section 2

dp for section 3

dp for section 4

dp for section 5

dp for section 6

Se

ctio

na

l p

ressu

re d

rop

, 1

05 P

a

Number of pore volume injected (PVI)(a)

0 1 2 3 4 5 6 7 8

0

1

2

3

4

5

6

7

~ 7.3 PVI

Secondary propagation

Se

ctio

na

l p

ressu

re d

rop

, 1

05 P

a

Number of pore volume injected (PVI)

dp for section 2

dp for section 3

dp for section 4

dp for section 5

dp for section 6

Primary propagation

~ 2.6 PVI


45

Foam-flow regimes in porous media with oil

The two regimes for foam without oil apply to foam with oil.

Oil affects both regimes, but has a stronger impact on the high-quality regime.

Modeling of foam flow with oil

Each of the two algorithms for foam represents the effect of oil only on one regime or

the other.

The currently applied foam model, though simplified, give a good match to data.

[email protected]

SUMMARY

46

Dynamics of foam with oil

Pre-generated foam behaves very differently than in-situ generated foam, depending

on oil type.

Currently applied foam models needs further investigation for reliable prediction of

foam EOR.

[email protected]

SUMMARY

47

Need an effective approach for estimation of oil-related foam-simulation-model

parameters.

Implicit-texture modeling of foam EOR uses steady-state data to predict dynamic

behavior. The reliability needs to be verified.

With N2 foam, oil affects foam through its interaction with aqueous phase. With CO2

foam, oil interacts with both aqueous and gas phases, especially when miscibility is

involved.

[email protected]

CURRENT CHALLENGES









Foam Generation by Snap-off in Flow Across a

Sharp Permeability Transition

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What dominates in the reservoir?

In the near-well region,

o SAG flood, gas draining liquid → leave-behind, snap-off

o High ∇P → lamella division

What happens away from the wells?

o Low ∇P, low velocity, surfactant and gas slugs might’ve mixed.

o Can we still expect foam?

HOW DOES FOAM GENERATE IN POROUS MEDIA?

Distance from well

Pressure

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WHY ARE WE INTERESTED IN THIS?

Snap-off doesn’t only happen during drainage.

There are several documented ways in which snap-off

can occur.1

A particular mechanism of snap-off could help

generate foam and improve sweep efficiency away

from wells. Snap-off (Roof, 1970)

----------------------------

---------------------------------

----------------------------

---------------------------------

----------------------------

---------------------------------

----------------------------

---------------------------------

----------------------------

---------------------------------

Snap-off in flow across a

sharp increase in permeability.

----------------------------

---------------------------------1Rossen, W.R., 2003

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Snap-off can cause foam generation independent of pressure gradient in flow across a sharp

increase in permeability (Falls, A.H. et al. 1988, Hirasaki. et al. 1997).

Previous experiments were all under drainage and questions still remain.

fg=80% fg=90%

“Internal” capillary end-effect

Rossen, W.R., 1999

Tanzil, D. et al. 2002


4

53

Sharp heterogeneities do exist in subsurface formations1,2,3 (e.g. laminations, cross-

strata, layer boundaries).

Design an experiment with no foam generation by other mechanisms.

Do we observe foam generation? Validate (or contradict) theoretical predictions.

Investigate the effect of:

permeability contrast (kH/kL) – Shah et. al., SPE J., 2018

fractional flow (fg) – Shah et. al., SPE J., 2019

velocity (ut) – Shah et. al., SPE J., 2019

Does the foam mobilize and propagate at field-like velocities?1Reineck and Singh, 19802Collinson and Thompson, 19893Hartkamp-Bakker, 1993


54

EXPERIMENTAL METHODOLOGY

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So what do we observe?

Here’s an experiment assisted with CT-scanning, ut=0.67 ft/d, fg=60%, kH/kL ≈ 4:1, core placed

horizontally.

RESULTS

In-situ saturation measurements

Shah, S.Y. et. al., SPE J., 2019

56

RESULTS


57

RESULTS


58

RESULTS


59

RESULTS


60

RESULTS


61

RESULTS


62

Magnitude of pressure gradient is similar but that of fluctuations increases as velocity decreases.

RESULTS

Effect of velocity

fg=80%

kH/kL ≈ 4:1


63

RESULTS

Effect of velocity

<

Observed weaker foam in outlet tubing at

lower velocity.

64

RESULTS

No clear effect of fg observed. At fg<60%, foam was generated in the low-perm zone itself.

Effect of fractional flow

ut=0.67 ft/d,

kH/kL ≈ 4:1

CT images

𝜇appH =

kH∇P

ul+ug


65

RESULTS

Foam strength appears to increase with increase in permeability contrast.

Effect of permeability contrast

ut=0.67 ft/d, fg=80%.

𝜇appH =

kH∇P

ul+ug


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At a given permeability contrast, we observe foam

generation in drier flows than predicted by theory.

Effect of fg unclear.

CAN WE VALIDATE THEORETICAL RESPONSES?

fg=80% fg=90%

Rossen, W.R., 1999

67


Analytical saturation response to

a sharp change in permeability

(Yortsos and Chang, 1990)

68


Analytical saturation response to

a sharp change in permeability

(Yortsos and Chang, 1990)

Falls, A.H. et al. (1988)

estimated Pcsn≈1/2 Pc

e

69

We obtained Pc curves for sintered glass porous media from Berg et al. (2014).

These curves were extended to the petrophysical and fluid properties of our system.


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Phase saturations extracted from CT results (sensitive to CT error and slice width).


71

Pc < Pcsn (≈1/2 Pc

e) at the boundary of the low-permeability zone.

Foam generation is observed as soon as surfactant reaches the boundary.



72

SUMMARY

Demonstrated foam generation across a sharp increase in permeability.

Demonstrated propagation at field-like velocities (< 1ft/d).

Reduced λg high-permeability zone (benefits sweep efficiency away from wells).

Foam generation triggered as soon as surfactant reaches the boundary.

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SUMMARY

Foam strength higher with greater permeability contrast.

Foam generation takes longer across greater permeability contrast.

No clear effect of fg in range of conditions studied.

Some theoretical responses verified and some inconsistencies observed.

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This process is intermittent (also reported by Falls et al., 1988).

Intermittency greater with greater kH/kL, higher fg and lower ut.

SUMMARY

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Implications for the field:

Foam generation deep in the reservoir

Propagation even at field-like superficial velocities

Foam generates in the high-permeability layers, blocks flow and reduces:

λV

Extent of gravity segregation

Reduced cross-flow

Improved reservoir scale sweep efficiency

WHAT DOES IT MEAN FOR THE FIELD?

THANK YOU

Herru As Syukri

Michiel Slob

Ellen Meijvogel-de Koning

Marc Friebel

Karel Heller

Joost van Meel

Jens van den Berg

Jolanda van Haagen-Donker

ACKNOWLEDGEMENTS

Special thanks to:

Documents

Studies of Foam for EOR and CO storage: Liquid Injectivity