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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 gz g g t Cww krw k ( Pg Pcgw ) w gz w qw PDE for Oil component (pseudocomponent) Cgo krg k o o S g Cg SoCo Pg g gz t g Coo kro k ( Pg Pcgw Pcow ) o gz 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 gz Pg g gz g w ho o kro k ( Pg Pcgw Pcow ) o gz 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.