Falta PTTC - Clemson University

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Simulation of Steam Flooding
at West Coalinga Field
Lekan Fawumi, Scott Brame, and
Ron Falta
Clemson University
School 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
viscosity (cp)

1000
100
10
1
0.1
100
1000
Temperature (F)
Viscosity of West Coalinga
Crude 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


C

w
w
g krg k
  S g Cg  S wCw     
P   g gz  
 g  g

t




 Cww krw k

  
( Pg  Pcgw )  w gz  

 w

 qw
PDE for Oil component (pseudocomponent)
 Cgo krg k


o
o
  S g Cg  SoCo     
Pg   g gz 
t
 





g


 Coo kro k

  
( Pg  Pcgw  Pcow )  o gz  

 o

 qo
PDE for Multiphase Heat Transfer
An energy balance gives:

  S g  g u g  S w  wuw  So ouo   (1   )  R CRT
t


 hw w krw k

 hg  g krg k

( Pg  Pcgw )  w gz 

Pg   g gz     

 g

 w




 ho o kro k

  
( Pg  Pcgw  Pcow )  o gz   T 2T   q hj

j 1, n
 o


Lawrence Berkeley Laboratory TOUGH2 codes
http://www-esd.lbl.gov/TOUGH2/




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/ ; [email protected] . 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/
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 -- 5X
Smaller time-steps due to N-R convergence difficulties - 5-10X
Ill-conditioned, stiff matrices at each N-R iteration of
each time-step -- 2-5X
Net result: A steam flood simulation takes at least 150 500 times more computational effort than a singlephase flow simulation with the same resolution
Steam flood modeling resolution
compared to a single-phase flow
simulation
Single-phase
Gridblock
resolution
(same volume)
Modeled
Volume (same
resolution)
Multiphase
Estimated relationship between number
of gridblocks and simulation time (2Ghz
cpu)
Number of gridblocks
106
16 cpu
4 cpu
5x105
1 cpu
0
0
5
Simulation time, days
10
Standard repeated 5-spot pattern
Lines of
symmetry
Basic
Element
Of symmetry,
1/8 of five spot
injectors
producers
300800
300600
239
8-1
229
239W
300400
229W
22
8-2B
238
300200
238W
300000
228
228W
238A
8-2
Northing
299800
128B
128
118B
299600
237
227
299400
237W
8-3
Injection Well
299200
127B
127
299000
298800
236
8-4
118A
236W
298600
1587500 1587700 1587900 1588100 1588300 1588500
Easting
Production Well
Well 239
0
Gamma Radiation (API)
Facies
100
200Tracts
1460
BS-6
Subtidal
1480
BS-5
Diatomite
BS-4
1500
Tide- and Wave-Dominated Shoreline
1520
1540
1560
1580
1600
1620
1640
1660
1680
1700
BS-3
Estuarine
1720
1740
1760
1780
Base of the
Temblor Formation
BS-2
Facies
Groups
4
2
3
5
4
5
3
4
3
Well 118A
4
1
4
2
Gamma Radiation
(API)
0
200
100
300
1690
BS-5
1710
Facies Group
Number
4
3
5
Facies Tract
Number
5
4
3
1730
4
4
1750
1770
5
3
3
3
Kreyenhagen
1790
1810
1830
4
3
4
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.
2
1850
1
1870
4
Facies Tracts Used in Model
U
ni
t
Facies Tract
1
Incised Valley
Mean Permeability
(mD)
Lithology
Grain Size
Sorting
Basal conglomerate,
fining upward to crossbedded sand, silt, and
clay
Very fine to
coarse, minor
cobbles, pebbles,
silt and clay
Very poor
to good
562
Fine to medium
Moderate
316
Poor to
good
316
Interlaminated sand,
silt, and clay, burrowed
clay intervals,
sandy clay intervals
2
Estuarine
3
Tide-to Wavedominated
shoreline
Crossbedded sand
with burrowed sand
and clay; fossiliferous
sand
Medium to coarse
sand , minor
pebbles, very fine
to fine sand, silt
and clay
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
Facies Tract Model
Perm (mD)
400
300
200
100
50
0
-800
-1000
1.5876E+06
1.588E+06
1.5884E+06
Easting
-800
-1000
299000
Perm (mD)
400
300
200
100
50
0
299500
Northing
300000
300500
Well 239
0
Gamma Radiation (API)
Facies
100
200Tracts
1460
BS-6
Subtidal
1480
BS-5
Diatomite
BS-4
1500
Tide- and Wave-Dominated Shoreline
1520
1540
1560
1580
1600
1620
1640
1660
1680
1700
BS-3
Estuarine
1720
1740
1760
1780
Base of the
Temblor Formation
BS-2
Facies
Groups
4
2
3
5
4
5
3
4
3
Well 118A
4
1
4
2
Gamma Radiation
(API)
0
200
100
300
1690
BS-5
1710
Facies Group
Number
4
3
5
Facies Tract
Number
5
4
3
1730
4
4
1750
1770
5
3
3
3
Kreyenhagen
1790
1810
1830
4
3
4
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.
2
1850
1
1870
4
Facies Groups Used in Model
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 Group Model
Perm (mD)
3000
1000
500
400
300
250
200
0
-800
1.5876E+06
1.588E+06
1.5884E+06
N
Easting
or
th
-1000
-800
299000
Perm (mD)
3000
1000
500
400
300
250
200
0
299500
Northing
300000
300500
Easting
-1000
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!
Facies Fractal Permeabilities
Fractal
Group
1
2
3
4
5
Aritmetic Mean
Perm (mD) Perm (m2)
1744
1.721E-12
662
6.537E-13
397
3.918E-13
918
9.060E-13
606
5.978E-13
Harmonic mean
Perm (mD) Perm (m2)
1413
1.395E-12
181
1.787E-13
196
1.931E-13
128
1.262E-13
159
1.573E-13
Facies Fractal Model
Perm (mD)
10000
1000
500
400
300
200
100
10
-800
-1000
1.5876E+06
1.588E+06
1.5884E+06
Easting
-800
-1000
299000
Perm (mD)
10000
1000
500
400
300
200
100
10
299500
Northing
300000
300500
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)
Initial and final oil-water relative permeabilities
Normalized water oil relative permeabilities
1
1
0.9
0.9
0.8
0.8
Kro
0.6
0.5
0.7
0.6
0.5
0.4
0.4
0.3
0.3
0.2
0.2
0.1
0.1
0
0
20
40
60
Sw
80
0
100
Krw
Kro
Krw
mod krw
krw
mod krn
0.7
Estimated Oil Saturations at the Start of Steam Flooding
Oil Saturation
0.6
0.5
0.4
0.3
0.2
0.1
300500
300000
-800
g
n
i
299500
th
r
No
-1000
1.5876E+06
299000
1.588E+06
E as
ting
1.5884E+06
Facies Tract Temperatures at 5 years
Temp (C)
175
150
125
100
75
50
300500
300000
-800
g
n
i
299500
th
r
No
-1000
1.5876E+06
299000
1.588E+06
E as
ting
1.5884E+06
Facies Tract Oil Saturations at 5 years
Oil Saturation
0.6
0.5
0.4
0.3
0.2
0.1
300500
300000
-800
g
n
i
299500
th
r
No
-1000
1.5876E+06
299000
1.588E+06
E as
ting
1.5884E+06
Facies Group Temperatures at 5 years
Temp (C)
175
150
125
100
75
50
300500
300000
-800
g
n
i
299500
th
r
No
-1000
1.5876E+06
299000
1.588E+06
E as
ting
1.5884E+06
Facies Group Oil Saturations at 5 years
Oil Saturation
0.6
0.5
0.4
0.3
0.2
0.1
300500
300000
-800
g
n
i
299500
th
r
No
-1000
1.5876E+06
299000
1.588E+06
E as
ting
1.5884E+06
Facies Fractal Temperatures at 5 years
Temp (C)
175
150
125
100
75
50
300500
300000
-800
g
n
i
299500
th
r
No
-1000
1.5876E+06
299000
1.588E+06
E as
ting
1.5884E+06
Facies Fractal Oil Saturations at 5 years
Oil Saturation
0.6
0.5
0.4
0.3
0.2
0.1
300500
300000
-800
g
n
i
299500
th
r
No
-1000
1.5876E+06
299000
1.588E+06
E as
ting
1.5884E+06
Simulated versus Field production
(1.2xSn, Krw endpt=0.15)
800
Oil Production (bbl/day)
Field
Facies
Tract
600
Facies
Group
Fractal
kz/10
400
200
0
0
1
2
3
Time (years)
4
5
Simulated versus Field production
(1.2xSn, Krw endpt=0.15)
6000
Water Production (bbl/day)
Field
Facies Tract
5000
Facies Group
Fractal kz/10
4000
3000
2000
1000
0
0
1
2
3
Time (years)
4
5
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.
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