Simulation of Steam Flooding at West Coalinga Field

Lekan Fawumi, Scott Brame, and Ron Falta

Clemson UniversitySchool of Environment

Objective

Evaluate the effects of different representations of interwell permeability on steam flood behavior

Outline Introduction to steam flooding Numerical simulation of steam

flooding West Coalinga model area and

permeability distributions Steam flood simulations using

facies tract, facies group, and facies fractal representations

Steam Flooding in Heavy Oil Reservoirs

The main benefit comes from a large reduction in the oil viscosity with increased temperature

Large pressure gradients also help mobilize oil

Lower interfacial tension and solvent bank effects may also help, but are secondary

0.1

1

10

100

1000

100 1000

Temperature (F)

visc

osity

(cp)

Viscosity of West CoalingaCrude Oil [Chevron]

Numerical Simulation of Steam Flooding – Physical Processes

A field steam flood simulator must include at a minimum:

• a mass balance on water and oil• an energy balance• three-phase flow of gas, water, and oil phases• heat transfer by convection and conduction

with phase change effects• capability for three-dimensional flow in

anisotropic heterogeneous media

PDE for water component

w wg g w wS C S C

t

( )ww rw

g cgw ww

C k kP P g z

wg rg

g gg

C k kP g z

wq

PDE for Oil component (pseudo-component)

o og g o oS C S C

t

( )oo ro

g cgw cow oo

C k kP P P g z

og rg

g gg

C k kP g z

oq

PDE for Multiphase Heat Transfer

An energy balance gives:

(1 )g g g w w w o o o R RS u S u S u C Tt

( )w w rwg cgw w

w

h k kP P g z

( )o o rog cgw cow o

o

h k kP P P g z

g g rgg g

g

h k kP g z

2T T

1,

hj

j n

q

Publicly available 3-D multiphase heat and compositional flow codes for heterogeneous porous and fractured systems

Developed over a ~20 year period, originally for geothermal reservoir modeling

Codes are distributed by (with FORTRAN source code) DOE Energy Science and Technology Software Center http://www.osti.gov/estsc/ ; estsc@adonis.osti.gov . The cost to organizations with DOE affiliations is $670, while the cost for private US companies is $2260.

A new graphical users interface (developed with DOE funding) is available from Thunderhead Engineering, Inc.: http://www.thunderheadeng.com/petrasim/

Lawrence Berkeley Laboratory TOUGH2 codes http://www-esd.lbl.gov/TOUGH2/

T2VOC version of TOUGH2 Special version of TOUGH2 developed for

environmental steam flood applications [Falta et al., 1995]

Code considers 3 phase flow of 3 mass components: air, water, and an organic chemical (which may be oil)

Full heat transfer and thermodynamics are included

Problem may involve 3-D flow in heterogeneous, anisotropic porous or fractured systems.

A new multicomponent hydrocarbon version called TMVOC was just released by LBNL in May.

Computational effort for steam flood simulation compared to single-phase isothermal flow

Increased number of simultaneous equations -- 3X

Newton-Raphson linearization at each time-step - 5 iterations per time-step -- 5X5X

Smaller time-steps due to N-R convergence Smaller time-steps due to N-R convergence difficulties -- difficulties -- 5-10X5-10X

Ill-conditioned, stiff matrices at each N-R iteration Ill-conditioned, stiff matrices at each N-R iteration of each time-step -- of each time-step -- 2-5X2-5X

Net result: Net result: A steam flood simulation takes at A steam flood simulation takes at least least 150 -500 times150 -500 times more computational effort more computational effort than a single-phase flow simulation with the same than a single-phase flow simulation with the same resolutionresolution

Steam flood modeling resolution compared to a single-phase flow simulation

Gridblock resolution (same volume)

ModeledVolume (sameresolution)

Single-phase Multiphase

Estimated relationship between number of gridblocks and simulation time (2Ghz cpu)

Simulation time, days

Nu

mb

er

of

gri

db

lock

s

0 5 10

106

5x105

0

1 cpu

4 cpu

16 cpu

Standard repeated 5-spot pattern

injectors

producers

Lines ofsymmetry

BasicElement Of symmetry,1/8 of five spot

298600

298800

299000

299200

299400

299600

299800

300000

300200

300400

300600

300800

1587500 1587700 1587900 1588100 1588300 1588500

Easting

227

118B

8-2B

228W228

22

8-2

128

8-3

127

8-4 118A

8-1

239W

239

238

238W

238A

128B

237

237W

127B

236W

236

229W229

Nor

thin

g

ProductionWell

Injection Well

Complete well log showing facies tracts, facies groups, and bounding surfaces. Logs such as this were compared to well 118A to characterize the location of bounding surfaces and facies groups.

0 100 200

3

4

3

2

4

1

4

3

4

3

5

4

5

3

2

4

FaciesGroups

Est

ua

rin

eT

ide

-a

nd

Wa

ve-D

om

ina

ted

Sh

ore

line

Diatomite

Subtidal

BS-3

BS-4

BS-5

BS-6

BS-2Base of theTemblor Formation

Gamma Radiation (API) FaciesTracts

Well 239

1460

1480

1500

1520

1540

1560

1580

1600

1620

1640

1660

1680

1700

1720

1740

1760

1780Kreyenhagen

1870

1850

1830

1810

1790

1770

1750

1730

1710

1690

4

1

4

3

4

3

5

4

53

Gamma Radiation(API) Facies Group

Number

2

3

4

5

Facies TractNumber0 100 200 300

4BS-5

Well 118A

Table 2.4 Characteristics of the facies Groups from Bridges (2001). 

  

Facies Tracts Used in ModelUnit

Facies Tract Lithology Grain Size Sorting Mean Permeability (mD)

 1

 Incised Valley

Basal conglomerate, fining upward to cross-bedded sand, silt, and

clay

Very fine to coarse, minor

cobbles, pebbles, silt and clay

Very poor to good

 562

 2

 Estuarine

 

Interlaminated sand, silt, and clay, burrowed clay

intervals,sandy clay intervals

 Fine to medium

 Moderate

 316

 3

 Tide-to Wave-

dominated shoreline

 

Crossbedded sand with burrowed sand

and clay; fossiliferous sand

Medium to coarse sand , minor

pebbles, very fine to fine sand, silt

and clay

 Poor to good

 316

 4

 Diatomite

 

 Clay, silt, and fine

sand

 Fine sand and clay

 Good

 22

 5

 Subtidal

Massive burrowed sand, thin intervals of

silt and clay; rare fossiliferous sand

 Sand, silt, and

clay

 Poor to good

 224

       

63

299000 299500 300000 300500

Northing

-1000

-800

Perm (mD)400300200100500

-1000

-800

1.5876E+06 1.588E+06 1.5884E+06

Easting

Perm (mD)400300200100500

Facies Tract Model

Complete well log showing facies tracts, facies groups, and bounding surfaces. Logs such as this were compared to well 118A to characterize the location of bounding surfaces and facies groups.

0 100 200

3

4

3

2

4

1

4

3

4

3

5

4

5

3

2

4

FaciesGroups

Est

ua

rin

eT

ide

-a

nd

Wa

ve-D

om

ina

ted

Sh

ore

line

Diatomite

Subtidal

BS-3

BS-4

BS-5

BS-6

BS-2Base of theTemblor Formation

Gamma Radiation (API) FaciesTracts

Well 239

1460

1480

1500

1520

1540

1560

1580

1600

1620

1640

1660

1680

1700

1720

1740

1760

1780Kreyenhagen

1870

1850

1830

1810

1790

1770

1750

1730

1710

1690

4

1

4

3

4

3

5

4

53

Gamma Radiation(API) Facies Group

Number

2

3

4

5

Facies TractNumber0 100 200 300

4BS-5

Well 118A

Table 2.4 Characteristics of the facies Groups from Bridges (2001). 

Facies Group Facies Present Permeability Range

Mean Permeability

Group 1 

Clean sand,cross-bedded sand,

pebbly sand

1500 md to 8000 md 3180 md

Group 2 

Interlaminated sand and clay,

Silt,Sandy clay,

Clay

75 md to 3000 md 500 md

Group 3 

Burrowed clayey sand,

Burrowed Interlaminated Sand

and Clay,Burrowed Sandy

Clay,Burrowed Clay

5 md to 800 md 255 md 

Group 4 

Bioturbated Sand,Carbonate Cemented

Zones

50 md to 1000 md 525 md

Group 5 

Fossiliferous Sand

Zero to 600 md 225 md

  

Facies Groups Used in Model

299000 299500 300000 300500

Northing

Ea

stin

g

-1000

-800

Perm (mD)300010005004003002502000

North

-1000

-800

1.5876E+06 1.588E+06 1.5884E+06

Easting

Perm (mD)300010005004003002502000

Facies Group Model

Facies Fractal Model A 3-D fractal distributions of k are generated

using the properties of each facies group on a fine grid

Based on the location in the coarser simulation grid, the facies group type is known, so the appropriate fractal k values are extracted, preserving the facies group structure in the model

The fine grid fractal k values are upscaled to the simulation grid using an arithmetic mean for the horizontal permeability, and a harmonic mean for the vertical permeability. This upscaling can have a large effect on the final k values used in the simulation!

Fractal Aritmetic Mean Harmonic meanGroup Perm (mD) Perm (m2) Perm (mD) Perm (m2)

1 1744 1.721E-12 1413 1.395E-122 662 6.537E-13 181 1.787E-133 397 3.918E-13 196 1.931E-134 918 9.060E-13 128 1.262E-135 606 5.978E-13 159 1.573E-13

Facies Fractal Permeabilities

299000 299500 300000 300500

Northing

-1000

-800

Perm (mD)10000100050040030020010010

-1000

-800

1.5876E+06 1.588E+06 1.5884E+06

Easting

Perm (mD)10000100050040030020010010

Facies Fractal Model

Comments on water phase relative permeability and initial oil saturaton

Our choice of the water phase relative permeability curve was based on a fit of data from a core from Chevron

The initial oil saturation in the model was interpolated from Chevron values derived from the well logs

HOWEVER – these values resulted in simulations where the water to oil ratio was off by a factor of 10 or more compared to field values!

To better match the field values, we reduced the water relative permeability endpoint from .56 to .15, and

We increased the oil saturations everywhere by 20% (with an upper limit of 70% oil)

Normalized water oil relative permeabilities

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 20 40 60 80 100

Sw

Kro

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Krw

KroKrwmod krwkrwmod krn

Initial and final oil-water relative permeabilities

-1000

-800

1.5876E+06

1.588E+06

1.5884E+06Easting

299000

299500

300000

300500

Northing

Oil Saturation0.60.50.40.30.20.1

Estimated Oil Saturations at the Start of Steam Flooding

-1000

-800

1.5876E+06

1.588E+06

1.5884E+06Easting

299000

299500

300000

300500

Northing

Temp (C)1751501251007550

Facies Tract Temperatures at 5 years

Facies Tract Oil Saturations at 5 years

-1000

-800

1.5876E+06

1.588E+06

1.5884E+06Easting

299000

299500

300000

300500

Northing

Oil Saturation0.60.50.40.30.20.1

Facies Group Temperatures at 5 years

-1000

-800

1.5876E+06

1.588E+06

1.5884E+06Easting

299000

299500

300000

300500

Northing

Temp (C)1751501251007550

Facies Group Oil Saturations at 5 years

-1000

-800

1.5876E+06

1.588E+06

1.5884E+06Easting

299000

299500

300000

300500

Northing

Oil Saturation0.60.50.40.30.20.1

Facies Fractal Temperatures at 5 years

-1000

-800

1.5876E+06

1.588E+06

1.5884E+06Easting

299000

299500

300000

300500

Northing

Temp (C)1751501251007550

Facies Fractal Oil Saturations at 5 years

-1000

-800

1.5876E+06

1.588E+06

1.5884E+06Easting

299000

299500

300000

300500

Northing

Oil Saturation0.60.50.40.30.20.1

Simulated versus Field production(1.2xSn, Krw endpt=0.15)

0

200

400

600

800

0 1 2 3 4 5

Time (years)

Oil

Pro

du

ctio

n (

bb

l/day

)

Field

FaciesTract

FaciesGroup

Fractalkz/10

Simulated versus Field production(1.2xSn, Krw endpt=0.15)

0

1000

2000

3000

4000

5000

6000

0 1 2 3 4 5

Time (years)

Wat

er P

rod

uct

ion

(b

bl/

day

)

Field

Facies Tract

Facies Group

Fractal kz/10

Conclusions The three permeability representations predict similar oil and

water production from the field. The facies group model arguably provided the best match of the oil production rate

Only a single realization of the facies fractal model was simulated. A Monte Carlo simulation approach would be needed to see the true effect of the facies fractal permeability representation

Upscaling the fine grid fractal values to the simulation grid scale presents some important and unresolved issues. This could be a useful area for future theoretical research

The over-prediction of water rates may be due to the choice of boundary conditions.

The rate of water production is sensitive to the shape of the water relative permeability curve. The applicability of measured core values in field scale simulation seems questionable.