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History Matching of Heavy Oil Production for Comparing New Approaches to Generating Reservoir Property Distributions, West Coalinga Field, California. S.E. Brame, J.W. Castle, SPE, O.K. Fawumi*, SPE and R.W. Falta, Clemson University * Now with Mobil Producing Nigeria Unltd. SPE 93469. - PowerPoint PPT Presentation
Citation preview
History Matching of Heavy Oil Production for Comparing New Approaches to
Generating Reservoir Property Distributions,
West Coalinga Field, California
S.E. Brame, J.W. Castle, SPE, O.K. Fawumi*, SPE and R.W. Falta, Clemson University
* Now with Mobil Producing Nigeria Unltd.
SPE 93469
This research was funded by the U.S. Department of Energy, Fossil Energy Oil Technology Program, through the National Petroleum Technology Office under contract number DE-AC26-98BC15119.
Objectives
• Assess the suitability of different permeability distributions generated from geological and fractal modeling.
• Examine the feasibility of creating realistic permeability distributions from fractal theory for reservoir simulation.
• Use steam flood simulations of a portion of the West Coalinga oil field in California for model assessment.
Location of the West Coalinga Field
Heavy Oil Sands of Coalinga• The West Coalinga oil field in California
produces from heavy oil sands of the Miocene Temblor Formation.
• The oil in this field has low API gravity (12o to 15o API) and is highly viscous (900 cp) at the 40oC initial reservoir temperature.
• This makes the field an ideal candidate for enhanced oil recovery through steam injection.
Steam injection well at Coalinga
Methods
• Characterize geology in outcrop and core
• Identify lithofacies
• Group lithofacies into Facies Groups
• Identify Facies Tracts
• Characterize Fractal Facies
• Construct geologic models
• Assign permeability distributions
• Simulate steam flooding of different models and assess results
Geologic Characterization • Coalinga offers a unique opportunity to observe
and characterize the reservoir rocks on the surface, immediately adjacent to the oil production area.
• Thus it was possible to relate cores of the producing formation to nearby outcrops.
Clemson Students examining outcrop of Temblor Fm. in hills north of Coalinga Field
Lithofacies Characterization• A total of fifteen lithofacies were identified from outcrops and cores based on observed lithological differences.• Statistical methods were used to consolidate the 15 different lithofacies groups into five facies groups.
Facies Group Major Lithology Mean Permeability
1 Clean sand 3180 mD
2 Interlaminated sand and clay 500 mD
3 Burrowed clayey sand 255 mD
4 Bioturbated Sand 525 mD
5 Fossiliferous Sand 225 mD
Facies Tract Characterization
Five facies tracts were interpreted based on detailed sedimentological analysis:
Facies Tract Lithology Mean Permeability
Incised Valley Basal conglomerate, cross-bedded sand, silt, and clay
562 mD
EstuarineInterlaminated sand, silt, and clay, burrowed clay intervals, sandy clay intervals
316 mD
Tide-to Wave-dominated shoreline
Crossbedded sand with burrowed sand and clay; fossiliferous sand 316 mD
Diatomite Clay, silt, and fine sand 22 mD
Subtidal Massive burrowed sand with intervals of silt and clay
224 mD
Facies CorrelationsBetween Wells
Correlation of well 239 with Type Well 118A to determine the location of bounding surfaces, facies tracts, and facies groups.
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
BS = bounding surface (depths are in feet)
Model Area
This map shows the 3 adjacent five-spot configurations that were modeled and the wells that were used.
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
Section 36D
Geologic Model Construction
• 3-D geologic models were constructed using GOCAD.
• Inputs included the bounding surface horizons, geophysical logs, and facies group and facies tract data.
• The grid consisted of 9600 cells:
- 32 vertical layers,
- 10 cells in the x direction
- 30 cells in the y direction
Geologic Models in GOCAD
Facies Group 1
Facies Group 2
Facies Group 3
Facies Group 4
Facies Group 5
200 ft
Facies Tract Facies Group
Fractal Group Model Development
• The cores of five West Coalinga wells were analyzed foot by foot.
• Analysis of the individual facies data revealed that a unique Gaussian fractal structure was present in each one.
• These results and others led to the development of a new model for representing natural heterogeneity called the fractal/facies concept.
Reservoir Simulation
• The geologic model grids were used as the framework for the flow simulation mesh.
• Petrophysical properties were assigned to all cells of the mesh.
• Permeability distributions of the facies tract, facies group, and fractal group models were assigned.
• Numerical simulations of steam injection were used to assess the different models.
T2VOC Flow Simulator
• Uses a general finite difference formulation. • Can solve multi-phase, multi-component mass and
energy balance equations. • Has been used to simulate a variety of subsurface
processes such as:
nonaqueous phase liquid (NAPL) migration, soil vapor extraction, air-sparging, steam injection, and direct pumping of water and NAPL.
Permeability Distribution of the Facies Tract Model
-1000
-800
1.5876E+06 1.588E+06 1.5884E+06
Easting
Perm (mD)400300200100500
Permeability Distribution of the Facies Group Model
-1000
-800
1.5876E+06 1.588E+06 1.5884E+06
Easting
Perm (mD)300010005004003002502000
Fractal Permeability Distribution
• Fractal permeabilities were stochastically generated for the 5 different facies groups.
• The values were assigned to the flow grid but using a finer grid (~3,000,000 cells).
• The fractal permeabilities were upscaled to the standard flow grid cell size (9600 cells).
• An arithmetic mean was used for the horizontal permeability.
• A harmonic mean was used for the vertical permeability.
Permeability Distribution of the Fractal Model
-1000
-800
1.5876E+06 1.588E+06 1.5884E+06
Easting
Perm (mD)10000100050040030020010010
Simulation Period• A five year period (Oct. 1995 to Oct. 2000) was used.• The injected steam volume changed monthly.• Some injection wells were not online until 1997.• All changes in production and injection were
honored.
0
2000
4000
6000
0 1 2 3 4 5
Time (years)
vo
lum
e o
f s
tea
m in
jec
ted
(b
bl/d
ay
of
wa
ter)
Vol
um
e of
Ste
am (
bb
ls o
f w
ater
)
Time (years)
Parameters Adjusted for Better Fit
• The oil-water relative permeability curves provided for the field were based on a data fit from a core.
• The initial oil saturation was interpolated from well logs.
• Problem: these values resulted in simulations where the water to oil ratio was off by a factor of 10 or more compared to field values!
Solution: The water relative permeability endpoint was reduced from .56 to .15, and the oil saturations were increased everywhere by 20% (upper limit of 70%).
Kro Krw
■ Kro Field Data
● Krw Field Data
Kro used in Model
Krw used in Model
Normalized Water-oil Relative Permeabilities
Water Saturation (%)
-1000
-800
1.5876E+06
1.588E+06
1.5884E+06Easting
299000
299500
300000
300500
Northing
Temp (C)1751501251007550
-1000
-800
1.5876E+06
1.588E+06
1.5884E+06Easting
299000
299500
300000
300500
Northing
Temp (C)1751501251007550
Reservoir Temperatures at 5 Years
-1000
-800
1.5876E+06
1.588E+06
1.5884E+06Easting
299000
299500
300000
300500
Northing
Temp (C)1751501251007550
-1000
-800
1.5876E+06
1.588E+06
1.5884E+06Easting
299000
299500
300000
300500
Northing
Temp (C)1751501251007550
FaciesTract
FractalGroup
FaciesGroup
Oil Saturations at 5 Years
-1000
-800
1.5876E+06
1.588E+06
1.5884E+06
299000
299500
300000
300500
Oil Saturation0.60.50.40.30.20.1
-1000
-800
1.5876E+06
1.588E+06
1.5884E+06
299000
299500
300000
300500
Oil Saturation0.60.50.40.30.20.1
-1000
-800
1.5876E+06
1.588E+06
1.5884E+06
299000
299500
300000
300500
Oil Saturation0.60.50.40.30.20.1
-1000
-800
1.5876E+06
1.588E+06
1.5884E+06
299000
299500
300000
300500
Oil Saturation0.60.50.40.30.20.1
FractalGroup
FaciesTract
FaciesGroup
Simulated versus Field Production of Oil (Combined Production)
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 of Water (Combined Production)
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
Summary
• Three models were assessed using simulations of steam injection and heavy oil production.
• Lowering the water relative permeability curve endpoint decreased water production.
• Increasing the initial oil saturation resulted in a better prediction of oil production.
• The fractal realization matched oil production up to Year 3.
• Additional realizations could be generated to improve the history match.
Conclusions
• Permeability distributions from the geologic models provided reasonable matches of oil production.
• The fractal/facies approach is a viable method of generating geologically realistic permeability distributions.
• Steamflood simulations demonstrate that the fractal/facies approach is feasible for modeling heavy oil reservoirs.
Acknowledgments
• Chevron contributed core data, production data, and geophysical logs.
• Many thanks to Venton Shoemaker, George Anderson, Louis Klonsky, Paul Henshaw, and Mike Clark of Chevron.
• Fred Molz and Silong Lu of Clemson University performed the fractal analysis
• Ray Christopher of Clemson University assisted with the statistical treatment of the lithofacies.