CA2660227A1 - Numerical simulation and economic evaluation of hybrid solvent processes - Google Patents
Numerical simulation and economic evaluation of hybrid solvent processes Download PDFInfo
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- 238000004088 simulation Methods 0.000 title abstract description 108
- 238000000034 method Methods 0.000 title abstract description 46
- 230000008569 process Effects 0.000 title abstract description 44
- 239000002904 solvent Substances 0.000 title abstract description 34
- 238000011234 economic evaluation Methods 0.000 title description 2
- 239000001273 butane Substances 0.000 abstract description 37
- 238000010796 Steam-assisted gravity drainage Methods 0.000 abstract description 29
- 238000004458 analytical method Methods 0.000 abstract description 10
- 239000010426 asphalt Substances 0.000 abstract description 10
- 238000010797 Vapor Assisted Petroleum Extraction Methods 0.000 abstract description 8
- 238000011084 recovery Methods 0.000 abstract description 4
- 239000000295 fuel oil Substances 0.000 abstract description 3
- 235000009508 confectionery Nutrition 0.000 abstract description 2
- 239000003921 oil Substances 0.000 description 39
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 27
- 239000001294 propane Substances 0.000 description 21
- OFBQJSOFQDEBGM-UHFFFAOYSA-N Pentane Chemical compound CCCCC OFBQJSOFQDEBGM-UHFFFAOYSA-N 0.000 description 18
- IJDNQMDRQITEOD-UHFFFAOYSA-N n-butane Chemical compound CCCC IJDNQMDRQITEOD-UHFFFAOYSA-N 0.000 description 16
- 239000006185 dispersion Substances 0.000 description 15
- ATUOYWHBWRKTHZ-UHFFFAOYSA-N Propane Chemical compound CCC ATUOYWHBWRKTHZ-UHFFFAOYSA-N 0.000 description 14
- 238000002474 experimental method Methods 0.000 description 14
- 238000004519 manufacturing process Methods 0.000 description 11
- 238000009792 diffusion process Methods 0.000 description 9
- 229910001868 water Inorganic materials 0.000 description 9
- 238000002347 injection Methods 0.000 description 8
- 239000007924 injection Substances 0.000 description 8
- 230000000694 effects Effects 0.000 description 6
- 239000007788 liquid Substances 0.000 description 5
- 239000003208 petroleum Substances 0.000 description 4
- 238000010793 Steam injection (oil industry) Methods 0.000 description 3
- VLKZOEOYAKHREP-UHFFFAOYSA-N hexane Substances CCCCCC VLKZOEOYAKHREP-UHFFFAOYSA-N 0.000 description 3
- 239000007789 gas Substances 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- 206010039509 Scab Diseases 0.000 description 1
- 238000010795 Steam Flooding Methods 0.000 description 1
- 101100168473 Streptomyces griseolus cyp105B1 gene Proteins 0.000 description 1
- 230000003190 augmentative effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 230000001186 cumulative effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 239000013505 freshwater Substances 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 238000011065 in-situ storage Methods 0.000 description 1
- QWTDNUCVQCZILF-UHFFFAOYSA-N isopentane Chemical compound CCC(C)C QWTDNUCVQCZILF-UHFFFAOYSA-N 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 239000003345 natural gas Substances 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
- 102200115801 rs121918083 Human genes 0.000 description 1
- 101150063279 subC gene Proteins 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B43/00—Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells
- E21B43/16—Enhanced recovery methods for obtaining hydrocarbons
- E21B43/24—Enhanced recovery methods for obtaining hydrocarbons using heat, e.g. steam injection
- E21B43/2406—Steam assisted gravity drainage [SAGD]
- E21B43/2408—SAGD in combination with other methods
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- Fluid Mechanics (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Geochemistry & Mineralogy (AREA)
- Production Of Liquid Hydrocarbon Mixture For Refining Petroleum (AREA)
Abstract
Solvent-based processes for recovery of heavy oil and bitumen have potential application to a variety of reservoir situations. Potential processes range from SAGD to VAPEX, with a range of hybrid processes in between. Over 50 lab-scale and 80 field scale simulations were run to determine optimum operating points for various hybrid processes. The results showed that steam-butane simulations yielded two "sweet spots" where the cost objective function was lower than that for SAGD. Economic analysis was done based on a set of field scale simulations. This analysis showed that a hybrid solvent process for an Athabasca reservoir was an alternative to SAGD. The analysis may be extended to other reservoir types as needed.
Description
CANADIAN INTERNATIONAL
PETROLEUM CONFERENCE
Numerical Simulation and Economic Evaluation of Hybrid Solvent Processes T. FRAUENFELD, C. JOSSY AND J. IVORY
Alberta Research Council This paper is accepted for the Proceedings of the Canadian International Petroleum Conference (CIPC) 2009, Calgary, Alberta, Canada, 16-18 June 2009. This paper will be considered for publication in Petroleum Society journals.
Publication rights are reserved. This is a pre-print and subject to correction.
Heat may be injected by using vaporized solvent or steam.
Because of the low latent heat capacity of solvent, it is Abstract expedient to heat the solvent by co-injection of steam. The result is a Hybrid Solvent process (Figure 1). This process may Solvent-based processes for recovery of heavy oil and be operated at any set of steam and solvent rates between pure bitumen have potential application to a variety of reservoir SAGD and pure VAPEX. Detailed experimental, modelling and situations. Potential processes range from SAGD to VAPEX, economic studies were done to determine an optimum point or with a range of hybrid processes in between. Over 50 lab-scale points for this process.
and 80 field scale simulations were run to determine optimum operating points for various hybrid processes. The results Numerical 2D field-scale simulations were used to compare showed that steam-butane simulations yielded two "sweet VAPEX, SAGD and Hybrid solvent processes for an Athabasca spots" where the cost objective function was lower than that for bitumen reservoir. The comparisons considered propane, n-SAGD. Economic analysis was done based on a set of field butane and n-pentane as solvents, and considered effects of scale simulations. This analysis showed that a hybrid solvent steam rate, solvent rate, pressure and steam sub-cool setting of process for an Athabasca reservoir was an alternative to the production well.
The results are displayed in more detail in SAGD. The analysis may be extended to other reservoir types the following figures.
as needed.
Scaled Laboratory Models for Heavy Oil Introduction Recovery SAGD is the main commercial technology used for in-situ recovery of Athabasca bitumen. Due to the increasing costs for The Scaling Theory energy (natural gas) and the increasing restrictions on fresh water usage, VAPEX (Ref. 1) has been proposed. The numerical simulations were based on experiments done at Alberta Research Council to model the Steam-Solvent Hybrid The VAPEX process may be augmented by adding heat. process. Figure 2 shows a photo of the experimental apparatus.
Heating will reduce the oil viscosity sufficiently to produce a Figure 3 shows a diagram of the experimental model. The large increase in oil rate. The heat will serve to speed the scaling criteria used for ARC lab model experiments on thermal diffusion of solvent into the oil. The heat will also serve to processes are the Pujol and Boberg scaling criteria (Ref. 2).
initiate communication between the injector and the producer. This set of scaling criteria matches the ratios of gravity, viscous forces, conductive and convective heat transfer, and diffusion, at the expense of incorrectly scaling pressure drop vs. capillary Numerical Results forces, and dispersion vs. diffusion. This scaling method is acceptable for SAGD, where thermal conduction is the rate- Numerical simulations were first run to determine numerical controlling step. The scaling will be less certain for VAPEX and dispersion as a function of total dispersion. (Table 1) This gave hybrid solvent processes, where diffusion and dispersion play assurance that estimates of dispersion and diffusion from major roles in controlling process rates. Heat transfer, diffusion Blackwell5, Sudicky4,6 and Hayduk-Cheng7 could be used to and dispersion are all important in hybrid solvent processes. estimate dispersion at the lab scale, field scale dispersion and These values must be determined experimentally. Experimental diffusion, respectively, and that these values could be values of diffusion as a function of temperature are not yet meaningfully inserted into the numerical simulator.
available. The values were therefore derived by history matching. (Ref. 3) Table 2 contains results for the lab model simulations with propane. The SAGD simulation out-performed all of the Simulation Design simulations of the steam-propane process in terms of oil production. However, most of the steam-propane simulations Several sets of 2D STARS simulations were run to perform had a lower cost objective function than did the SAGD
field scale predictions of steam-solvent hybrid process simulation.
behaviour. Simulations first were done of experiments to validate the diffusion/ dispersion parameters selected. Figure 4 Table 3 contains results for the lab model simulations with shows the grid mesh used for the lab model simulations. butane. Here most of the steam-butane simulations out-Simulations were next done to find an optimum operating point performed the SAGD simulation in terms of oil production, but for a steam-propane lab model experiment. An extensive set of they all under-performed the SAGD simulation in terms of cost steam-butane simulations of the lab model experiment were also objective function.
done. These simulations attempted to optimize the steam-butane hybrid experiments in terms of steam rate, butane rate and Table 4 contains results for the field scale simulations with pressure. steam-propane. In the field scale simulations, the SAGD
simulation out-performed all of the steam-propane simulations, Simulations were run to determine the effect of diffusivity in both in terms of the oil production and in terms of the objective the simulations. Simulations at various levels of diffusivity function. This result was different than that of the lab scale were compared to back out the numerical dispersion for a field simulations.
scale problem. Simulations were then done to determine the effect of field scale dispersivity, based on dispersion data by Table 5 contains the results of field scale simulations for the Sudicky (Ref. 4). The effect of live oil and of random steam-butane simulations. All of the steam-butane simulations permeability variations was also assessed. out-performed the SAGD simulation in terms of oil production.
Some of the steam-butane simulations also out-performed the A set of simulations to optimize steam-propane at the field SAGD simulations in terms of the cost objective function.
scale was then run. Figure 5 is a typical field simulation grid These simulations were those using the lower butane injection mesh. The simulations considered steam rate, solvent rate and rates, i.e.
C4/steam ratios of 0.1275 to 0.0319 (liquid/liquid pressure. It was considered that operating of the steam-solvent ratio).
Optimal pressures were from 1200 to 2200 kPa. It was process in subcool mode, as SAGD is operated, would be most concluded that steam-butane was lower cost than SAGD as a efficient. method of producing bitumen.
Optimizations were then run for the steam-butane hybrid Figure 6 represents simulations of lab model experiments process. Simulations were run at a constant subcool (25 C) in using steam-propane at a low steam rate (240 g/h) and various order to optimize pressure and solvent injection rate. pressures. Each data point represents one numerical run. The simulations show an optimal oil production at 1200 kPa, and an A similar set of simulations was run for the steam-pentane optimal objective function of 1.25 at 1100 kPa.
hybrid process, to optimize the process in terms of pressure and steam rate. All simulations were compared in terms of an objective function that is related to supply cost. Figure 7 represents simulations of lab model experiments of a steam-propane hybrid process at a steam injection rate of 300 g/h. In this case the optimum for both the oil production and the Economic Assumptions minimum objective function (1.14) occurs at 1100 kPa.
In order to compare simulations where multiple performance Figure 8 represents numerical simulations of steam butane criteria exist, an objective function was devised. The function hybrid experiments using 500 g/h of steam. The oil production takes the form of: and objective function are plotted vs. butane injection rate. The optimal butane injection rate appears to be 200 cc/h. The jog in Supply-cost = (fixed cost) + (capital)/ (oil produced) + (steam the objective function curve at 400 g/h represents a comparison cost) x (steam-oil ratio) + (solvent cost) x (net solvent-oil between an experiment where the pressure is blown down at the ratio) + (solvent produced)/ (oil produced) x (solvent recycle end of the experiment to recover as much butane as possible cost) with a simulation where no blowdown was used. Most Objective function=supply cost/100 simulations were run without a blowdown.
The function was calculated for all simulations. Local minimums were plotted to illustrate optimum points, and Figure 9 shows performance vs. pressure for steam-butane selected simulations subjected to economic analysis to verify simulations that use 400 g/h steam. The optimum oil the optimums.
PETROLEUM CONFERENCE
Numerical Simulation and Economic Evaluation of Hybrid Solvent Processes T. FRAUENFELD, C. JOSSY AND J. IVORY
Alberta Research Council This paper is accepted for the Proceedings of the Canadian International Petroleum Conference (CIPC) 2009, Calgary, Alberta, Canada, 16-18 June 2009. This paper will be considered for publication in Petroleum Society journals.
Publication rights are reserved. This is a pre-print and subject to correction.
Heat may be injected by using vaporized solvent or steam.
Because of the low latent heat capacity of solvent, it is Abstract expedient to heat the solvent by co-injection of steam. The result is a Hybrid Solvent process (Figure 1). This process may Solvent-based processes for recovery of heavy oil and be operated at any set of steam and solvent rates between pure bitumen have potential application to a variety of reservoir SAGD and pure VAPEX. Detailed experimental, modelling and situations. Potential processes range from SAGD to VAPEX, economic studies were done to determine an optimum point or with a range of hybrid processes in between. Over 50 lab-scale points for this process.
and 80 field scale simulations were run to determine optimum operating points for various hybrid processes. The results Numerical 2D field-scale simulations were used to compare showed that steam-butane simulations yielded two "sweet VAPEX, SAGD and Hybrid solvent processes for an Athabasca spots" where the cost objective function was lower than that for bitumen reservoir. The comparisons considered propane, n-SAGD. Economic analysis was done based on a set of field butane and n-pentane as solvents, and considered effects of scale simulations. This analysis showed that a hybrid solvent steam rate, solvent rate, pressure and steam sub-cool setting of process for an Athabasca reservoir was an alternative to the production well.
The results are displayed in more detail in SAGD. The analysis may be extended to other reservoir types the following figures.
as needed.
Scaled Laboratory Models for Heavy Oil Introduction Recovery SAGD is the main commercial technology used for in-situ recovery of Athabasca bitumen. Due to the increasing costs for The Scaling Theory energy (natural gas) and the increasing restrictions on fresh water usage, VAPEX (Ref. 1) has been proposed. The numerical simulations were based on experiments done at Alberta Research Council to model the Steam-Solvent Hybrid The VAPEX process may be augmented by adding heat. process. Figure 2 shows a photo of the experimental apparatus.
Heating will reduce the oil viscosity sufficiently to produce a Figure 3 shows a diagram of the experimental model. The large increase in oil rate. The heat will serve to speed the scaling criteria used for ARC lab model experiments on thermal diffusion of solvent into the oil. The heat will also serve to processes are the Pujol and Boberg scaling criteria (Ref. 2).
initiate communication between the injector and the producer. This set of scaling criteria matches the ratios of gravity, viscous forces, conductive and convective heat transfer, and diffusion, at the expense of incorrectly scaling pressure drop vs. capillary Numerical Results forces, and dispersion vs. diffusion. This scaling method is acceptable for SAGD, where thermal conduction is the rate- Numerical simulations were first run to determine numerical controlling step. The scaling will be less certain for VAPEX and dispersion as a function of total dispersion. (Table 1) This gave hybrid solvent processes, where diffusion and dispersion play assurance that estimates of dispersion and diffusion from major roles in controlling process rates. Heat transfer, diffusion Blackwell5, Sudicky4,6 and Hayduk-Cheng7 could be used to and dispersion are all important in hybrid solvent processes. estimate dispersion at the lab scale, field scale dispersion and These values must be determined experimentally. Experimental diffusion, respectively, and that these values could be values of diffusion as a function of temperature are not yet meaningfully inserted into the numerical simulator.
available. The values were therefore derived by history matching. (Ref. 3) Table 2 contains results for the lab model simulations with propane. The SAGD simulation out-performed all of the Simulation Design simulations of the steam-propane process in terms of oil production. However, most of the steam-propane simulations Several sets of 2D STARS simulations were run to perform had a lower cost objective function than did the SAGD
field scale predictions of steam-solvent hybrid process simulation.
behaviour. Simulations first were done of experiments to validate the diffusion/ dispersion parameters selected. Figure 4 Table 3 contains results for the lab model simulations with shows the grid mesh used for the lab model simulations. butane. Here most of the steam-butane simulations out-Simulations were next done to find an optimum operating point performed the SAGD simulation in terms of oil production, but for a steam-propane lab model experiment. An extensive set of they all under-performed the SAGD simulation in terms of cost steam-butane simulations of the lab model experiment were also objective function.
done. These simulations attempted to optimize the steam-butane hybrid experiments in terms of steam rate, butane rate and Table 4 contains results for the field scale simulations with pressure. steam-propane. In the field scale simulations, the SAGD
simulation out-performed all of the steam-propane simulations, Simulations were run to determine the effect of diffusivity in both in terms of the oil production and in terms of the objective the simulations. Simulations at various levels of diffusivity function. This result was different than that of the lab scale were compared to back out the numerical dispersion for a field simulations.
scale problem. Simulations were then done to determine the effect of field scale dispersivity, based on dispersion data by Table 5 contains the results of field scale simulations for the Sudicky (Ref. 4). The effect of live oil and of random steam-butane simulations. All of the steam-butane simulations permeability variations was also assessed. out-performed the SAGD simulation in terms of oil production.
Some of the steam-butane simulations also out-performed the A set of simulations to optimize steam-propane at the field SAGD simulations in terms of the cost objective function.
scale was then run. Figure 5 is a typical field simulation grid These simulations were those using the lower butane injection mesh. The simulations considered steam rate, solvent rate and rates, i.e.
C4/steam ratios of 0.1275 to 0.0319 (liquid/liquid pressure. It was considered that operating of the steam-solvent ratio).
Optimal pressures were from 1200 to 2200 kPa. It was process in subcool mode, as SAGD is operated, would be most concluded that steam-butane was lower cost than SAGD as a efficient. method of producing bitumen.
Optimizations were then run for the steam-butane hybrid Figure 6 represents simulations of lab model experiments process. Simulations were run at a constant subcool (25 C) in using steam-propane at a low steam rate (240 g/h) and various order to optimize pressure and solvent injection rate. pressures. Each data point represents one numerical run. The simulations show an optimal oil production at 1200 kPa, and an A similar set of simulations was run for the steam-pentane optimal objective function of 1.25 at 1100 kPa.
hybrid process, to optimize the process in terms of pressure and steam rate. All simulations were compared in terms of an objective function that is related to supply cost. Figure 7 represents simulations of lab model experiments of a steam-propane hybrid process at a steam injection rate of 300 g/h. In this case the optimum for both the oil production and the Economic Assumptions minimum objective function (1.14) occurs at 1100 kPa.
In order to compare simulations where multiple performance Figure 8 represents numerical simulations of steam butane criteria exist, an objective function was devised. The function hybrid experiments using 500 g/h of steam. The oil production takes the form of: and objective function are plotted vs. butane injection rate. The optimal butane injection rate appears to be 200 cc/h. The jog in Supply-cost = (fixed cost) + (capital)/ (oil produced) + (steam the objective function curve at 400 g/h represents a comparison cost) x (steam-oil ratio) + (solvent cost) x (net solvent-oil between an experiment where the pressure is blown down at the ratio) + (solvent produced)/ (oil produced) x (solvent recycle end of the experiment to recover as much butane as possible cost) with a simulation where no blowdown was used. Most Objective function=supply cost/100 simulations were run without a blowdown.
The function was calculated for all simulations. Local minimums were plotted to illustrate optimum points, and Figure 9 shows performance vs. pressure for steam-butane selected simulations subjected to economic analysis to verify simulations that use 400 g/h steam. The optimum oil the optimums.
2 production, SOR and objective function (3.4) appears to be at Economic Analysis Results 800 kPa.
A supply cost economic analysis was done on several "best Figure 10 represents field scale SAGD baseline simulations. case" simulations.
The results were used to produce a more These simulations included a methane component in the accurate prediction of supply cost, and to validate the objective Athabasca bitumen. These simulations showed a minimum function ranking of numerical simulations. Figure 21 is the objective function of 0.95 at 1600 kPa. This (1600 kPa) incremental and cumulative cost by year for a SAGD baseline.
simulation was used as the steam-only baseline to which the This simulation shows a supply cost of $124/m3 at 5 years. The steam-solvent simulations were compared. objective function was 0.95. This was a 1600 kPa SAGD case, and was used as the benchmark cost value to which other Figure 11 represents a series of field scale simulations of a simulations were compared.
steam-propane hybrid process for a dead Athabasca bitumen.
The optimal steam-oil ratio, oil production and objective Figure 22 shows the cost performance of a steam-propane function occur at 1500 kPa. simulation using 1858 std. m3/d/10 in propane at 1500 kPa. The supply cost, at $142/m3 is substantially higher than the SAGD
Figure 12 represents the effects of pressure on a steam- cost, and roughly in agreement with the objective function score propane hybrid process for a live Athabasca bitumen. It was of 1.56 for this simulation, observed that the objective function had an optimum pressure range of 1200 - 1500 kPa when live oil was used. Oil Figure 23 shows economic performance of a steam-butane produced, objective function and SOR shared this optimum simulation having a 60 std. m3/d butane injection rate. The range. simulation had a supply cost of $86/m3 at 7 years, and an objective function of 0.872. This case also economically out-Figure 13 shows the performance predicted by a set of field performed SAGD.
scale simulations of a steam-propane hybrid process in live Figure 24 shows the supply cost profile for a steam-pentane Athabasca bitumen, for a steam injection rate of 6 m3/d (per 10 hybrid at 120 std. m3/d C5. The cost at maturity is $110hn3.
m of wellbore) The optimum objective function is 1.84 at 1400 Figure 25 shows a steam-hexane hybrid simulation at 240 std.
kPa, as compared to the objective function of 3.4 in Figure 9). in /d C6. The supply cost at maturity is $108 m3/.
Figure 14 represents field scale simulations of a steam-propane hybrid process with a steam injection rate of 5.35 m3/d Discussion per 10 in wellbore. The optimum pressure in this case is 1400-1500 kPa, and the objective function value is 1.81, slightly lower than for the simulations in Figure 13. All of the steam propane hybrid simulations resulted in a higher objective function (cost) than the SAGD simulations.
Figure 15 shows results from field scale simulations using a Two operating points in the steam-butane domain showed lower steam rate of 4.46 m3/d/10 in, a C3 rate of 1858 std m3/d/10 in objective functions and supply cost than did the SAGD
and a pressure of 1400 kPa. The amount of subcool was from simulations. The low butane-high steam simulations scored the 25 C to 65 C. An additional set of subcool simulations was run, lowest cost objective function, and the lowest supply cost.
shown in Figure 16. This set of simulations was run at 1500 Steam-pentane and steam-hexane processes has a lower supply kPa. The optimum amount of subcooling was found to be 25 C. cost than SAGD, but higher than the steam-butane hybrid A subcool setting of 25 C was chosen for all succeeding process.
simulations.
Lab scale simulations differed from field scale simulations in Figure 17 represents steam-butane hybrid simulations using terms of optimal pressure and optimal net solvent-oil ratio.
4.46 m3/d/10 m steam, 1858 std m3/d/lOm butane and 25 C Reasons for the difference between lab scale and field scale subcool. The lowest objective function was at 2200 kPa. Figure simulations are; heat loss through the side walls in lab model 18 shows a set of simulations of a steam-butane hybrid process experiments, and dead oil in lab models vs. live oil in field at 8 m3/d/10 in steam and 240 std. m3/d/10 in butane. The reservoir.
optimum pressure was at 1600 kPa. The objective function score was 0.911, lower than the score of 1.016 for the best Numerical simulations of lab experiments produced steam butane simulation at high butane rates. In Figure 18 the consistent under-prediction of the steam-butane performance, butane rate was doubled to 480 std. m3/d. The result was a One possible reason is the use of a constant molecular minimum objective function of 0.931 at an optimum pressure of diffusivity term rather than temperature dependant or viscosity 2200 kPa. In Figure 19 the simulations are run for cases where dependant diffusivity. Diffusivity may therefore be under-the butane injection rate is set to 120 std. m3/d/10 in, or '/2 the represented in some simulations.
rate in Figure 18. The result was a minimum objective function SAGD baseline simulations showed that the optimal pressure at 1400 kPa, with an objective function value of 0.876. This is for SAGD was 1600 kPa for the field scale simulation at the the lowest objective function found in this numerical study. conditions considered.
Figure 20 shows the results of a set of simulations of a A definite optimum pressure existed for the dead oil/propane steam-pentane Hybrid process. The simulations show a simulations (1500 kPa), in terms of the objective (cost) minimum objective function at 1000 kPa and a jog in the curve function.
Simulations of a "live oil scenario" in which the at 800 kPa, where an increase in the subcool from 25 C to 35 C bitumen has a small component of dissolved methane, had a significantly reduced the steam-oil ratio, but did not much broader optimum pressure range. Steam butane significantly change the cost objective function, which had a simulations similarly produced a broad optimal pressure range minimum value of 1.095. for a minimum objective (cost) function.
A supply cost economic analysis was done on several "best Figure 10 represents field scale SAGD baseline simulations. case" simulations.
The results were used to produce a more These simulations included a methane component in the accurate prediction of supply cost, and to validate the objective Athabasca bitumen. These simulations showed a minimum function ranking of numerical simulations. Figure 21 is the objective function of 0.95 at 1600 kPa. This (1600 kPa) incremental and cumulative cost by year for a SAGD baseline.
simulation was used as the steam-only baseline to which the This simulation shows a supply cost of $124/m3 at 5 years. The steam-solvent simulations were compared. objective function was 0.95. This was a 1600 kPa SAGD case, and was used as the benchmark cost value to which other Figure 11 represents a series of field scale simulations of a simulations were compared.
steam-propane hybrid process for a dead Athabasca bitumen.
The optimal steam-oil ratio, oil production and objective Figure 22 shows the cost performance of a steam-propane function occur at 1500 kPa. simulation using 1858 std. m3/d/10 in propane at 1500 kPa. The supply cost, at $142/m3 is substantially higher than the SAGD
Figure 12 represents the effects of pressure on a steam- cost, and roughly in agreement with the objective function score propane hybrid process for a live Athabasca bitumen. It was of 1.56 for this simulation, observed that the objective function had an optimum pressure range of 1200 - 1500 kPa when live oil was used. Oil Figure 23 shows economic performance of a steam-butane produced, objective function and SOR shared this optimum simulation having a 60 std. m3/d butane injection rate. The range. simulation had a supply cost of $86/m3 at 7 years, and an objective function of 0.872. This case also economically out-Figure 13 shows the performance predicted by a set of field performed SAGD.
scale simulations of a steam-propane hybrid process in live Figure 24 shows the supply cost profile for a steam-pentane Athabasca bitumen, for a steam injection rate of 6 m3/d (per 10 hybrid at 120 std. m3/d C5. The cost at maturity is $110hn3.
m of wellbore) The optimum objective function is 1.84 at 1400 Figure 25 shows a steam-hexane hybrid simulation at 240 std.
kPa, as compared to the objective function of 3.4 in Figure 9). in /d C6. The supply cost at maturity is $108 m3/.
Figure 14 represents field scale simulations of a steam-propane hybrid process with a steam injection rate of 5.35 m3/d Discussion per 10 in wellbore. The optimum pressure in this case is 1400-1500 kPa, and the objective function value is 1.81, slightly lower than for the simulations in Figure 13. All of the steam propane hybrid simulations resulted in a higher objective function (cost) than the SAGD simulations.
Figure 15 shows results from field scale simulations using a Two operating points in the steam-butane domain showed lower steam rate of 4.46 m3/d/10 in, a C3 rate of 1858 std m3/d/10 in objective functions and supply cost than did the SAGD
and a pressure of 1400 kPa. The amount of subcool was from simulations. The low butane-high steam simulations scored the 25 C to 65 C. An additional set of subcool simulations was run, lowest cost objective function, and the lowest supply cost.
shown in Figure 16. This set of simulations was run at 1500 Steam-pentane and steam-hexane processes has a lower supply kPa. The optimum amount of subcooling was found to be 25 C. cost than SAGD, but higher than the steam-butane hybrid A subcool setting of 25 C was chosen for all succeeding process.
simulations.
Lab scale simulations differed from field scale simulations in Figure 17 represents steam-butane hybrid simulations using terms of optimal pressure and optimal net solvent-oil ratio.
4.46 m3/d/10 m steam, 1858 std m3/d/lOm butane and 25 C Reasons for the difference between lab scale and field scale subcool. The lowest objective function was at 2200 kPa. Figure simulations are; heat loss through the side walls in lab model 18 shows a set of simulations of a steam-butane hybrid process experiments, and dead oil in lab models vs. live oil in field at 8 m3/d/10 in steam and 240 std. m3/d/10 in butane. The reservoir.
optimum pressure was at 1600 kPa. The objective function score was 0.911, lower than the score of 1.016 for the best Numerical simulations of lab experiments produced steam butane simulation at high butane rates. In Figure 18 the consistent under-prediction of the steam-butane performance, butane rate was doubled to 480 std. m3/d. The result was a One possible reason is the use of a constant molecular minimum objective function of 0.931 at an optimum pressure of diffusivity term rather than temperature dependant or viscosity 2200 kPa. In Figure 19 the simulations are run for cases where dependant diffusivity. Diffusivity may therefore be under-the butane injection rate is set to 120 std. m3/d/10 in, or '/2 the represented in some simulations.
rate in Figure 18. The result was a minimum objective function SAGD baseline simulations showed that the optimal pressure at 1400 kPa, with an objective function value of 0.876. This is for SAGD was 1600 kPa for the field scale simulation at the the lowest objective function found in this numerical study. conditions considered.
Figure 20 shows the results of a set of simulations of a A definite optimum pressure existed for the dead oil/propane steam-pentane Hybrid process. The simulations show a simulations (1500 kPa), in terms of the objective (cost) minimum objective function at 1000 kPa and a jog in the curve function.
Simulations of a "live oil scenario" in which the at 800 kPa, where an increase in the subcool from 25 C to 35 C bitumen has a small component of dissolved methane, had a significantly reduced the steam-oil ratio, but did not much broader optimum pressure range. Steam butane significantly change the cost objective function, which had a simulations similarly produced a broad optimal pressure range minimum value of 1.095. for a minimum objective (cost) function.
3 The use of a 25 C subcool setting to control the production 3. FRAUENFELD, T.W., DENG, X. and JOSSY, C., well increased the efficiency of the steam-propane process. The Economic Analysis of Thermal Solvent Processes, optimal subcool was from 25 C to 45 C for the steam-butane paper 2006-164 presented at the 57`h Annual Technical simulations. Meeting of the Petroleum Society of CIM, Calgary, AB, Numerical dispersion contributed significantly to the total Canada, 13-15 June 2006.
dispersion in hybrid solvent simulations. The fraction of 4. SUDICKY, E.A., A
Natural Gradient Experiment on numerical dispersion to total dispersion was about 0.25 in field Solute Transport in a Sand Aquifer: Spatial variability of scale simulations. Hydraulic Conductivity and its role in the Dispersion Process, Symposium on Field Approaches and The objective function used is an adequate guide for quickly Measurement Techniques for Quantifying Spatial evaluating simulations, but a full economic analysis is required Variability in Porous Media, AGU Spring Meeting, to get a better prediction of process cost. Baltimore, May 1987.
5. BLACKWELL, R.J., Laboratory Studies of Microscopic Dispersion Phenomena, Society of Petroleum Engineering Journal, p. 1, March 1962.
Conclusions 6. FARREL, D., WOODBURY, A.D., SUDICKY, E.A., and RIVETT, M., Stochastic and Deterministic Analysis 1. The steam-butane hybrid process was predicted to have of Dispersion in Unsteady Flow at the Borden Tracer optimum operating points which had lower SOR and Test Site, Ontario, Canada, Contaminant Hydrology, lower objective (cost) function than SAGD. Vol. 15, pp. 159-185, 1994.
2. The lowest cost process for production of Athabasca 7. REID, ROBERT C., PRAUSNITZ, JOHN M., and bitumen was predicted to be the steam-butane hybrid SHERWOOD, THOMAS K., The Properties of Gasses process using a butane-steam ratio of 0.082 m3/m3 and Liquids, Third Edition, McGraw Hill, pp. 569-590, liquid. 1977.
3. A low cost optimum for the steam-butane hybrid process will also occur at a butane-steam ratio of approximately 0.11 m3/m3 liquid.
dispersion in hybrid solvent simulations. The fraction of 4. SUDICKY, E.A., A
Natural Gradient Experiment on numerical dispersion to total dispersion was about 0.25 in field Solute Transport in a Sand Aquifer: Spatial variability of scale simulations. Hydraulic Conductivity and its role in the Dispersion Process, Symposium on Field Approaches and The objective function used is an adequate guide for quickly Measurement Techniques for Quantifying Spatial evaluating simulations, but a full economic analysis is required Variability in Porous Media, AGU Spring Meeting, to get a better prediction of process cost. Baltimore, May 1987.
5. BLACKWELL, R.J., Laboratory Studies of Microscopic Dispersion Phenomena, Society of Petroleum Engineering Journal, p. 1, March 1962.
Conclusions 6. FARREL, D., WOODBURY, A.D., SUDICKY, E.A., and RIVETT, M., Stochastic and Deterministic Analysis 1. The steam-butane hybrid process was predicted to have of Dispersion in Unsteady Flow at the Borden Tracer optimum operating points which had lower SOR and Test Site, Ontario, Canada, Contaminant Hydrology, lower objective (cost) function than SAGD. Vol. 15, pp. 159-185, 1994.
2. The lowest cost process for production of Athabasca 7. REID, ROBERT C., PRAUSNITZ, JOHN M., and bitumen was predicted to be the steam-butane hybrid SHERWOOD, THOMAS K., The Properties of Gasses process using a butane-steam ratio of 0.082 m3/m3 and Liquids, Third Edition, McGraw Hill, pp. 569-590, liquid. 1977.
3. A low cost optimum for the steam-butane hybrid process will also occur at a butane-steam ratio of approximately 0.11 m3/m3 liquid.
4. The steam-butane hybrid process had lower supply cost than steam-propane, steam-pentane or steam-hexane.
5. The simulations could be improved by including mechanisms such as viscosity-dependant diffusivity, improved oil-solvent phase behavior, and the effects on produced oil viscosity.
Acknowledgements The authors thank the AERI/ARC/ Core/Industry Research program for their financial and technical support. Discussions with Dr. Xiaohui Deng, concerning the numerical simulation of the experiments, and concerning the economic analysis inputs, were much appreciated. Thanks to Ms. Valerie Pinkoski for final formatting and editing of the manuscript.
Nomenclature kPa = pressure C = temperature C4/steam ratio = m3/m3 liquid vol.
g/h = grams/hour In Figures:
m3/d steam flow = liquid H2O equivalent m3/d gas flow = gas @ standard conditions (std. m3/d) REFERENCES
1. DAS, S.K. and BUTLER, R. Enhancement of Extraction Rate in the VAPEX Process by Water Injection, paper 96-28 presented at the Petroleum Society of CIM
Conference, Calgary, AB, 1996.
2. PUJOL, L. and BOBERG, T.C., Scaling Accuracy of Laboratory Steamflooding Models, paper presented at the 43' Annual California Regional Meeting, Bakersfield, CA, SPE Paper No. 4191, 1972.
Table 1. Numerical simulations to estimate numerical dispersion Run Description add. Disp. sqrt. Ad. Disp oil prod. oil @ 2000 H2O inj (meld) (m) (m) @ 2000 d(i R2D-02 Lab dispersion 3.00E-04 1.73E-02 6874 4875 8986 R2d-03 no add. Dispersion 0.00E+00 0.00E+00 6698 2867 9028 R2D-04 labd., no gas dispersion 6926 8887 R2D-05 1/2 diff+disp. 1.50E-04 1.22E-02 6845 4308 9018 R2D-06 0.2 diff+disp 6.00E-05 7.75E-03 6874 3894 8888 R2D-08 0.1 diff+disp 3.00E-05 5.48E-03 6843 3614 8900 R2D-09 steam-CH4, no disp 0.00E+00 0.00E+00 4007 1480 8884 R2D-10 Steam-CH4,lab disp 0.00E+00 0.00E+00 4077 1615 R2D-11 lab diff., no disp. 3.00E-04 1.73E-02 6770 3864 8870 R2D-12 1/2 lab diff., no disp 1.50E-04 1.22E-02 6837 3793 8039 R2d-03 no add. Diff. 0.00E+00 0.00E+00 6698 2867 9028 R2D-13 steam-CH4,lab diff only 0.00E+00 0.00E+00 3941 1506 8988 R2D-14 field disp only 2.50E-04 1.58E-02 6716 2964 R2D-15 1/2 size grid mesh 0.00E+00 0.00E+00 6625 2865 8924 R2D-16 1/4 size grid mesh 0.00E+00 0.00E+00 ? 2724 8919 Table 2. Numerical simulations of lab scale steam-propane hybrid process Run # steam Propane Pressure oil prod solvent prod H2O prod solvent procsolvent Steam/oil ra solvent/oil r net solvent/ mass bal. objective (g/h) (cclh) (kPa) (g)@ 600 mi (g) (g) in pack(g) (cc/cc) (cc/cc) oil ratio(cc/ccerr.(g) func.
16e 300 100 900 2450 422.08 4500 1533 102.8 1.84 0.61 0.075 1.449 16a 300 100 1000 3023 400 4493 615.4 153 1.49 0.50 0.090 1.258 16g 300 100 1000 2750 391 4500 612 151.8 1.64 0.55 0.099 1.374 16f 300 100 1100 4000 323 4500 465 298 1.13 0.38 0.133 1.171 16b 300 100 1200 2601 300 4100 440 689.7 1.73 0.58 0.474 2.382 16c 300 100 1400 1644 264 4440 13.7 755 2.74 0.91 0.820 0.32 3.884 16d 300 100 1600 576 70.26 4500 112 650.7 7.81 2.60 2.017 10.679 16j 300 200 1000 3006 895 4492 1380 156 1.50 1.00 0.093 1.299 16k 300 200 1100 3984 820 4500 1224 312 1.13 0.75 0.140 1.213 161 300 200 1200 4927 353 4260 344 1204 0.91 0.61 0.436 9.21 1.936 16m 300 200 1300 4296 105.9 4571 136 1488 1.05 0.70 0.619 96.8 2.586 16h 240 200 1000 2732 898 3605 1383 153.5 1.32 1.10 0.100 1.273 16i 240 300 1000 2739 1406 3595 2149 155.3 1.31 1.64 0.101 0.07 1.298 16n 240 400 1000 2623 1917 3604 2902 151.6 1.37 2.29 0.103 1.367 16b-aa; 1500 0 1600 5523 0 14327 0 0 4.07 0.00 0.000 1.883 Table 3. Numerical simulations of lab-scale steam-butane hybrid process Run # steam Butane Pressure oil prod solvent inj H20 prod solvent procsolvent Steam/oil ratisolvent/oil rnet solvenmass bal. Objective I
(g/h) (cc/h) (kPa) (g)@600min(g) (g)@600mir in pac k(g) (cc/cc) (cc/g) oil ratio (g) 1613-a 500 120 800 3656 730.8 7300 265 927 2.05 0.49 0.254 4.056 2.999 16B-b 500 200 800 6737 1218 7500 500 1524 1.11 0.45 0.226 169 2.334 16B-c 500 300 800 7724 1827 7500 605 2034 0.97 0.58 0.263 354 2.710 16B-d 500 400 800 7 330 2436 7500 1061 2139 0.95 0.76 0.270 481 3.060 16B-db 500 400 800 7900 2436 7500 1062 583 0.95 0.76 0.074 490 2.509 16B-f 500 500 800 7975 3045 7500 1574 2138 0.94 0.94 0.268 500 3.407 1613-e 400 400 800 7890 2436 6000 970 2299 0.76 0.76 0.291 483 3.073 16B-eb 400 400 800 7859 2436 6000 965 710 0.76 0.76 0.090 567 2.510 16B-g 400 500 800 7996 3045 6000 1519 2310 0.75 0.94 0.289 576 3.394 16B-h 400 600 800 8034 3654 6000 2105 2293 0.75 1.12 0.285 587 3.718 16B-qb 400 600 700 7548 3654 6000 2288 65 0.79 1.19 0.009 436 3.066 16B-rb 400 600 900 8267 3654 5845 2047 40 0.73 1.09 0.005 610 2.852 16B-sb 400 600 1000 8414 3654 5820 1921 37 0.71 1.07 0.004 715 2.830 168-j 400 500 900 5755 3045 7443 1523 1676 1.04 1.30 0.291 124 4.357 16B-g 400 500 800 7996 3045 7500 1519 2310 0.75 0.94 0.289 576 3.401 168-K 400 500 700 7556 3045 6055 1706 2281 0.79 0.99 0.302 3.530 1613-i 300 508 800 7077 3093.72 4401 1634 2202 0.64 1.08 0.311 419 3.699 16B-L 300 400 800 7407 2436 4443 1010 2388 0.61 0.81 0.322 502 3.205 16B-m 300 600 800 7253 3654 4376 2183 2249 0.62 1.24 0.310 344 3.981 16b-n 300 500 800 7798 3045 4377 1576 2434 0.58 0.96 0.312 531 3.429 16B-ob 300 500 700 7246 3045 4495 1731 75 0.62 1.00 0.010 617 2.653 16B-pb 300 500 900 7552 3045 4477 540 63 0.60 0.96 0.008 2.820 16B-nb 300 500 800 7691 3045 4441 1577 60 0.59 0.94 0,008 2.536 16B-tb 240 600 800 6964 3654 3553 2218 88 0.52 1.25 0.013 645 3.117 16B-ub 240 600 700 6927 3654 3547 2385 89 0.52 1.26 0.013 656 3.092 16b-Vb 240 600 900 7864 3654 3546 2113 84.4 0.46 1.11 0.011 629 2.798 16B-Wb 500 700 900 8277 4263 7365 2678 19.4 0.91 1.23 0.002 719 3.168 16B-yb 400 700 900 8295 4263 5810 2621 41.47 0.72 1.22 0.005 690 3.105 16B-xb 280 700 900 7261 4263 4130 2714 83.4 0.58 1.40 0.011 690 3.420 16B-zb 240 700 900 6322 4263 3510 2709 80.53 0.57 1.61 0.013 3.867 16b-adb 300 800 1100 7915 4872 4394 3050 38.04 0.57 1.47 0.005 3.542 16b-acb 300 800 1000 8197 4872 4375 3154 51.3 0.55 1.42 0.006 3.408 16b-aab 300 800 900 7726 4872 4298 3332 61.87 0.58 1.50 0.008 3.570 16b-abb 300 800 800 7701 4872 4282 3446 60.33 0.58 1.51 0.008 3.555 16b-aeb 400 800 1000 8518 4872 6000 3135 1979 0.70 1.36 0.232 4.007 16b-aca 1500 0 1400 5497 0 13922 0 0 4.09 0.00 0.000 1.888 16b-aaa 1500 0 1600 5523 0 14327 0 0 4.07 0.00 0.000 1.883 16B-aba 1800 0 1800 5874 0 15237 0 0 4.60 0.00 0.000 2.072 Table 4. Numerical simulations of field scale steam-propane hybrid process Run Description Stm inj. C3 inj. Pressure Subcool oil prod. oil @ 1000011 @
200O H20 inj H2O prod solvent Injsolvent pr net solvenSOR net C30R
(mild) (std mild (kPa) ( C) (m3) (m3) (m3) @ 2000 d(i (m3) @ 2000d @2000d (m3) @2000d 8g2000d R2D-14 field disp only, 1200 We 4.46E+00 1.86E+03 1200 5 6716 1717 2964 8912 9023 3.69E+08 3.65E+06 4.50E+04 3.01 0.063 P20-17 no add disp. disp, 1400 We 4.46 1858 1400 5 6691 2286 3365 8920 9092 3.69E+06 3.58E+06 1.04E+05 2.65 0.129 R2D-18 field scab d8fl, 1200 We 4.46 1858 1200 5 6799 2200 3738 8933 9091 3.69E+06 3.58E+06 1.04E+05 2.39 0.116 R2D-19 Sudicky field disp&diff, 1200 kPa 4.46 1858 1200 5 6821 2359 3926 8928 9097 3.70E+06 3.59E+06 1,06E+05 2.27 0.112 R20.22 Sud. Field D&D, 1300 kPa 4.46 1858 1300 5 7014 2670 4202 89DB 9041 3.68E+06 3.53E+06 1,49E+05 2.12 0.148 R2D-20 S" field D & 0, 1400 kPa 4.46 1858 1400 5 7218 3016 4430 8902 9041 3.67E+06 3,53E+06 1.40E+05 2.01 0.132 R20-20a S" field D & D, 1500 kPa 4.46 1858 1500 5 3243 4510 6941 9099 3.69E+06 3.55E+06 1.34E+05 1.54 0.124 820-21 Sud. Field D&D, 1600 We 4.46 1858 1600 5 6647 2317 3498 8912 9060 3.69E+06 3.64E+06 5,40E+04 2.55 0.064 820-23 S. field D&D, live oil, stm. Only 4.45 0 1100-2360 5 6480 3035 5563 8958 9127 0 0 0.00E+00 1.61 0.000 R20-24 S. Bd. D&D, live 0.,stm.o., Kh 4.46 0 1080-2360 5 6250 3151 5669 8975 8989 0 0 0.00E+00 1.58 0.000 R20-25 S. 6d. 050, live 0.,stm.o., Kh 2.98-1.03 0 800 5 4733 1891 3316 4994 4981 0 0 0.00E+00 1.51 0.000 R20-26 S. Bd. D&D, live 0.,stm.o., Kh 5,8-0.85 0 1200 5 5930 3370 4988 7562 7645 0 0 0,00E+00 1.52 0.000 R2D-27 S. fid. D&D, live O.,stm.o., Kh 8.0- 0.85 0 1600 5 6177 4135 5867 9312 9387 0 0 0.00E+00 1.59 0.000 R2D-28 S. Pd. D&D, live 0.,stm.o., Kh 12.0-0.9 0 2000 5 6292 4884 6178 10613 10678 0 0 0,00E+00 1.72 0,000 R2D-29 S. Pd. D&D, live 0.,stm.o., Kh 14.0- 0.9 0 2200 5 6333 5244 6261 11161 11187 0 0 0,00E+00 1.78 0.000 R20.31 S. 04. D&D, live O.,stm.o., Kh 4.46 900 1450 5 3230 2480 3150 4016 3682 1.78E+08 1.43E+06 3,46E+05 1.27 0.458 R2D-33 5" field D & D, live 0., 1400 We 4.46 2300 1400 5 7261 2648 4020 8940 9091 4.56E+06 4.44E+06 1,22E+05 2.22 0.126 R2D-35 S" field D & D, live 0., 3.Ostm 3 1858 1000 5 4652 1195 2132 5934 5898 3.68E+06 3.64E+06 3,30E+04 2.78 0,064 R2D-34 S" field D & D, live 0., 3.Ostm 3 1858 1200 5 6804 2027 3541 5963 6075 3.70E+06 3.59E+06 1,12E+05 1.68 0.132 R2D-37 S" field D & D, live 0., 3.0stm 3 1858 1300 5 7061 2235 3606 5920 6043 3.68E+06 3.55E+06 1.34E+05 1.64 0.155 R20-36 S" field D & D, live 0., 3.0stm 3 1858 1400 5 7212 2334 3522 5955 6049 3.68E+06 3.56E+06 1,27E+05 1.69 0.150 2d-39B S" field 0 & D, live 0., 3.0stm 3 1858 1500 5 7128 2204 3339 5944 6075 3.69E+06 3.58E+06 1,10E+05 1.78 0.137 R2d-39a S" field 0 & D, live 0., 3.Ostm 3 1858 1600 5 6096 1669 2695 5945 3.69E+06 3.67E+06 2.00E+04 2.21 0.031 R2d-41 S" field D & D, live 0., 6.Ostm 6 1858 1200 5 6852 2504 4114 11843 11969 3.70E+06 3.60E+06 1.03E+05 2.88 0.104 R2D-38 5" field D & D, live 0., 6.0stm 6 1858 1400 5 7196 2927 4600 11887 11986 3.68E+06 3.55E+06 1.32E+05 2.58 0.120 82045 S" field D & D, five O., 6.0stm 6 1858 1500 5 7367 3050 4458 11897 11993 3.68E+06 3.56E+06 1,20E+05 2.67 0.112 R2d-39 S" field D & D, rive 0., 3.0stm 6 1858 1600 5 6784 2354 3700 11900 11904 3.68E+06 3.66E+06 2.20E+04 3.22 0.025 2D-40 S" field 0 & 0, live 0., 6.0stm 6 1858 1800 5 6831 2390 3783 11911 11908 3.68E+06 3.67E+06 1,20E+04 3.15 0.013 R2d-42 S" field 0 & D, live 0., 6.0stm 6 1858 2000 5 6852 2458 3899 11918 11954 3.69E+06 3.67E+06 2.30E+04 3.06 0.025 020-43 5" field 0 & D, live 0., 5.35stm 5.35 1858 1400 5 7206 2815 4380 10546 10672 3.68E+06 3.55E+06 1.32E+05 2.41 0.126 820.46 S" field D & D, live 0., 5.35s1m 5.35 1858 1500 5 7394 2957 4241 10604 10718 3.69E+06 3.57E+06 1,18E+05 2.50 0,116 R2D.44 S" field D & D, live 0., 5.35stm 5.35 1858 1600 5 6714 2245 3521 10608 10618 3.69E+06 3.67E+06 2.10E+04 3.01 0.025 R2D-47 5" field 0 & D, live 0., 75C sub 4.46 1858 1400 75 3926 1232 1710 1562 1616 3.67E+06 3.59E+06 770E+04 0.91 0,188 R2D-51 S" field D & D, live 0., 65C sub 4.46 1858 1400 65 1714 2572 2662 2746 3.68E+06 3.56E+06 1.17E+05 1.03 0.190 R2D-52 S" field D & 0, five 0., 45C sub 4.46 1858 1400 45 2276 3272 4267 4363 3.68E+06 3.55E+06 1,34E+05 1.30 0.171 820.53 S" field D & D, five O., 25C sub 4.46 1858 1400 25 7291 2756 3960 7658 7772 3.68E+06 3.55E+06 1.35E+05 1.93 0.142 R20-47 S" field 0 & D, live 0., 75C sub 4.46 1858 1400 75 3926 1232 1710 1562 1616 3.87E+06 3.59E+06 7,70E+04 0.91 0.188 R213-48 S" field D & D, live 0., 75C subC 4.46 1858 1600 75 6754 1626 2685 1544 1603 3.58E+06 2.88E+06 7.06E+05 0.58 1.096 R20-49 S" field 0 & D, live 0., 55C subc 4.46 1858 1800 55 7132 1991 4470 4186 4342 3.69E+06 2.59E+06 1,09E+06 0.93 1.019 R2D-50 S" field 0 & D, live 0., 45C subc 4.46 1858 2000 45 2559 4455 5425 5599 3.69E+06 2.94E+06 7,43E+05 1.22 0.695 R2D-54 S" field 0 & D, live 0., 65C subc 4.46 1858 1500 85 7400 2047 3394 3099 3201 3.35E+06 2.97E+06 3,81E+05 0.91 0.468 R20-55 S" field D & D, live 0., 45C subc 4.46 1858 1500 45 5500 1743 2796 3235 3352 3.68E+06 3.48E+06 1,95E+05 1.16 0.291 MD-56 S" field D & D, live 0., 25C subc 4.46 1858 1500 25 7700 2837 3619 5680 5776 168E+06 3.54E+06 1.43E+05 1.57 0.165 R2D-57 S" field D & D, live 0., 25C subc 4.46 1858 1500 15 7411 2765 3927 8831 8878 3.68E+06 3.57E+06 1,13E+05 2.25 0.120 R20-58 S" field 0 & D, live 0., 4.46 515. 4.46 1858 1500 5 7409 2772 3927 8837 8930 3.69E+06 3.56E+06 1,30E+05 2.25 0.138 R213-56b 5" field D & D, live 0., 25C subc 4.46 1858 1500 25 7800 2837 3617 5681 5779 3.69E+06 3.55E+06 1,39E+05 1.57 0,160 R213-52b S" field D & D, live 0., 45C sub 4.46 1858 1500 45 2272 3275 4271 4372 3.68E+06 3.55E+06 1.27E+05 1.30 0.162 Table 5. Numerical simulations of field scale steam-butane hybrid process Run Description Sam inj. C, inj. Pressure Subcool oil prod. oil @ 1000oil @
2000 H2O inj H2O prod C4 inj. C4 prod net C4 in FSOR
(mild) (std mild (kPa) (C) (m3) (m3) (m3) @ 2000 d(i(m3) @ 2000d @2000d (m3) @2000d 0205-17 field disp, 2100 kPa,CH4 6 1860 2100 25 7110 6587 7094 9936 10032 3.41E+06 3.33E+06 7.20E+04 1.40 R2136-15 field disp, 1900 kPa,CH4 4.46 1860 1900 25 7186 6367 7163 8685 8678 3.67E+06 3.55E+06 1.17E+05 1.21 R2DB-13 field disp, 1700 kPa,CH4 4.46 1860 1700 25 7179 8266 7152 8404 8479 3.65E+06 3.52E+08 1.30E+05 1.18 R2DB-ll field disp, 1500 kPa,CH4 4.46 1860 1500 25 7173 5996 7130 8174 8300 3.82E+06 3.48E+06 1.42E+05 1.15 R20B-09 field disp, 1300 kPa,CH4 4.46 1860 1300 25 7176 5436 7099 8063 8191 3.67E+06 3.50E+06 1.68E+05 1.14 R205-05 field disp, 1100 kPa,CH4 4.46 1860 1100 25 7172 4630 7015 7610 7759 367E+06 3.48E+06 1.90E+05 1.08 8208-04 field disp, 1000 kPa,CH4 4.46 1860 1000 25 7181 4194 6924 7065 7234 3.67E+06 3.46E+06 2.13E+05 1.02 R2DB-01 field disp only, 900 kPa 4.46 1858 900 25 7214 3743 6806 6344 6342 3.67E+06 3.45E+06 2.21E+05 0.93 8208.02 field disp, 800 We 4.46 1860 800 25 7222 3157 6471 4983 5114 3.65E+06 3.40E+06 2.58E+05 0.77 R2DB-02a field disp, 800 kPa,CH4 4.46 1860 800 25 7196 3132 6432 4998 5125 3.66E+06 3.40E+06 2.63E+05 0.78 R2DB-03a field disp, 700 kPa,CH4 4.46 1860 700 25 7203 2550 5469 3805 3914 3,66E+06 3.32E+06 3.42E+05 0.70 02DB-08 field disp,1400 kPa,CH4 8 240 1400 25 7068 5381 6902 6527 6688 4,76E+05 3.23E+05 1.53E+05 0.95 8208-06 fielldisp,1600kPaCH4 8 240 1600 25 7028 5781 6924 7113 7260 4,80E+05 3.48E+05 1.32E+05 1.03 R2DB-07 fielldisp,1800kPa,CH4 8 240 1800 25 6988 6043 6918 7753 7866 4.75E+05 3.62E+05 1.13E+05 1.12 R2138-10 field disp,1600 kPa,CH4 8 480 1600 25 7106 6014 7047 7675 7779 9.53E+05 8.05E+05 1.48E+05 1.09 0208-12 field disp,1800 kPa,CH4 8 480 1800 25 7057 6240 7018 8196 8261 9.54E+05 8.33E+05 1.22E+05 1.17 0208-14 field disp,2000 kPa,CH4 8 480 2000 25 7016 6377 6983 8495 8505 9.52E+05 8.46E+05 1.05E+05 1,22 R2DB-16 field disp,2200 kPa,CH4 8 480 2200 25 6984 6429 6952 8664 8681 9.43E+05 8.52E+05 9.11E+04 1,25 R2 DB-20 field disp, 1200 kPa, CH4 8 120 1200 25 6953 4263 6553 5837 6024 2.35E+05 1.15E+05 1.20E+05 1.18 R2139-18 field disp, 1400 kPa,CH4 8 120 1400 25 6923 4914 6680 6506 6687 2.41E+05 1.28E+05 1.13E+05 0.97 8208-19 field disp,1600 kPa,CH4 8 120 1600 25 6874 5229 6703 7106 7242 2.40E+05 1.36E+05 1.05E+05 1.06 R20B-21 field disp,1200 kPa,CH4 8 60 1200 25 6797 3603 6108 5961 6103 1.19E+05 4.01E+04 7.88E+04 0.98 R20B-23 field disp,1400 kPa,CH4 8 60 1400 25 6725 4025 6188 6508 6529 1.21E+05 420E+04 7.86E+04 1.05 8205.22 field disp,1600 kPa,CH4 8 60 1600 25 6695 4401 6279 7201 7318 1.20E+05 4.18E+04 7.81E+04 1.15 R20.27 S. fid. D&D, live 0.,stm.o., Kh 8.0- 0.85 0 1400 13.8 6177 4135, 5867 9312 9387 0 0 0.00E+00 1.59
Acknowledgements The authors thank the AERI/ARC/ Core/Industry Research program for their financial and technical support. Discussions with Dr. Xiaohui Deng, concerning the numerical simulation of the experiments, and concerning the economic analysis inputs, were much appreciated. Thanks to Ms. Valerie Pinkoski for final formatting and editing of the manuscript.
Nomenclature kPa = pressure C = temperature C4/steam ratio = m3/m3 liquid vol.
g/h = grams/hour In Figures:
m3/d steam flow = liquid H2O equivalent m3/d gas flow = gas @ standard conditions (std. m3/d) REFERENCES
1. DAS, S.K. and BUTLER, R. Enhancement of Extraction Rate in the VAPEX Process by Water Injection, paper 96-28 presented at the Petroleum Society of CIM
Conference, Calgary, AB, 1996.
2. PUJOL, L. and BOBERG, T.C., Scaling Accuracy of Laboratory Steamflooding Models, paper presented at the 43' Annual California Regional Meeting, Bakersfield, CA, SPE Paper No. 4191, 1972.
Table 1. Numerical simulations to estimate numerical dispersion Run Description add. Disp. sqrt. Ad. Disp oil prod. oil @ 2000 H2O inj (meld) (m) (m) @ 2000 d(i R2D-02 Lab dispersion 3.00E-04 1.73E-02 6874 4875 8986 R2d-03 no add. Dispersion 0.00E+00 0.00E+00 6698 2867 9028 R2D-04 labd., no gas dispersion 6926 8887 R2D-05 1/2 diff+disp. 1.50E-04 1.22E-02 6845 4308 9018 R2D-06 0.2 diff+disp 6.00E-05 7.75E-03 6874 3894 8888 R2D-08 0.1 diff+disp 3.00E-05 5.48E-03 6843 3614 8900 R2D-09 steam-CH4, no disp 0.00E+00 0.00E+00 4007 1480 8884 R2D-10 Steam-CH4,lab disp 0.00E+00 0.00E+00 4077 1615 R2D-11 lab diff., no disp. 3.00E-04 1.73E-02 6770 3864 8870 R2D-12 1/2 lab diff., no disp 1.50E-04 1.22E-02 6837 3793 8039 R2d-03 no add. Diff. 0.00E+00 0.00E+00 6698 2867 9028 R2D-13 steam-CH4,lab diff only 0.00E+00 0.00E+00 3941 1506 8988 R2D-14 field disp only 2.50E-04 1.58E-02 6716 2964 R2D-15 1/2 size grid mesh 0.00E+00 0.00E+00 6625 2865 8924 R2D-16 1/4 size grid mesh 0.00E+00 0.00E+00 ? 2724 8919 Table 2. Numerical simulations of lab scale steam-propane hybrid process Run # steam Propane Pressure oil prod solvent prod H2O prod solvent procsolvent Steam/oil ra solvent/oil r net solvent/ mass bal. objective (g/h) (cclh) (kPa) (g)@ 600 mi (g) (g) in pack(g) (cc/cc) (cc/cc) oil ratio(cc/ccerr.(g) func.
16e 300 100 900 2450 422.08 4500 1533 102.8 1.84 0.61 0.075 1.449 16a 300 100 1000 3023 400 4493 615.4 153 1.49 0.50 0.090 1.258 16g 300 100 1000 2750 391 4500 612 151.8 1.64 0.55 0.099 1.374 16f 300 100 1100 4000 323 4500 465 298 1.13 0.38 0.133 1.171 16b 300 100 1200 2601 300 4100 440 689.7 1.73 0.58 0.474 2.382 16c 300 100 1400 1644 264 4440 13.7 755 2.74 0.91 0.820 0.32 3.884 16d 300 100 1600 576 70.26 4500 112 650.7 7.81 2.60 2.017 10.679 16j 300 200 1000 3006 895 4492 1380 156 1.50 1.00 0.093 1.299 16k 300 200 1100 3984 820 4500 1224 312 1.13 0.75 0.140 1.213 161 300 200 1200 4927 353 4260 344 1204 0.91 0.61 0.436 9.21 1.936 16m 300 200 1300 4296 105.9 4571 136 1488 1.05 0.70 0.619 96.8 2.586 16h 240 200 1000 2732 898 3605 1383 153.5 1.32 1.10 0.100 1.273 16i 240 300 1000 2739 1406 3595 2149 155.3 1.31 1.64 0.101 0.07 1.298 16n 240 400 1000 2623 1917 3604 2902 151.6 1.37 2.29 0.103 1.367 16b-aa; 1500 0 1600 5523 0 14327 0 0 4.07 0.00 0.000 1.883 Table 3. Numerical simulations of lab-scale steam-butane hybrid process Run # steam Butane Pressure oil prod solvent inj H20 prod solvent procsolvent Steam/oil ratisolvent/oil rnet solvenmass bal. Objective I
(g/h) (cc/h) (kPa) (g)@600min(g) (g)@600mir in pac k(g) (cc/cc) (cc/g) oil ratio (g) 1613-a 500 120 800 3656 730.8 7300 265 927 2.05 0.49 0.254 4.056 2.999 16B-b 500 200 800 6737 1218 7500 500 1524 1.11 0.45 0.226 169 2.334 16B-c 500 300 800 7724 1827 7500 605 2034 0.97 0.58 0.263 354 2.710 16B-d 500 400 800 7 330 2436 7500 1061 2139 0.95 0.76 0.270 481 3.060 16B-db 500 400 800 7900 2436 7500 1062 583 0.95 0.76 0.074 490 2.509 16B-f 500 500 800 7975 3045 7500 1574 2138 0.94 0.94 0.268 500 3.407 1613-e 400 400 800 7890 2436 6000 970 2299 0.76 0.76 0.291 483 3.073 16B-eb 400 400 800 7859 2436 6000 965 710 0.76 0.76 0.090 567 2.510 16B-g 400 500 800 7996 3045 6000 1519 2310 0.75 0.94 0.289 576 3.394 16B-h 400 600 800 8034 3654 6000 2105 2293 0.75 1.12 0.285 587 3.718 16B-qb 400 600 700 7548 3654 6000 2288 65 0.79 1.19 0.009 436 3.066 16B-rb 400 600 900 8267 3654 5845 2047 40 0.73 1.09 0.005 610 2.852 16B-sb 400 600 1000 8414 3654 5820 1921 37 0.71 1.07 0.004 715 2.830 168-j 400 500 900 5755 3045 7443 1523 1676 1.04 1.30 0.291 124 4.357 16B-g 400 500 800 7996 3045 7500 1519 2310 0.75 0.94 0.289 576 3.401 168-K 400 500 700 7556 3045 6055 1706 2281 0.79 0.99 0.302 3.530 1613-i 300 508 800 7077 3093.72 4401 1634 2202 0.64 1.08 0.311 419 3.699 16B-L 300 400 800 7407 2436 4443 1010 2388 0.61 0.81 0.322 502 3.205 16B-m 300 600 800 7253 3654 4376 2183 2249 0.62 1.24 0.310 344 3.981 16b-n 300 500 800 7798 3045 4377 1576 2434 0.58 0.96 0.312 531 3.429 16B-ob 300 500 700 7246 3045 4495 1731 75 0.62 1.00 0.010 617 2.653 16B-pb 300 500 900 7552 3045 4477 540 63 0.60 0.96 0.008 2.820 16B-nb 300 500 800 7691 3045 4441 1577 60 0.59 0.94 0,008 2.536 16B-tb 240 600 800 6964 3654 3553 2218 88 0.52 1.25 0.013 645 3.117 16B-ub 240 600 700 6927 3654 3547 2385 89 0.52 1.26 0.013 656 3.092 16b-Vb 240 600 900 7864 3654 3546 2113 84.4 0.46 1.11 0.011 629 2.798 16B-Wb 500 700 900 8277 4263 7365 2678 19.4 0.91 1.23 0.002 719 3.168 16B-yb 400 700 900 8295 4263 5810 2621 41.47 0.72 1.22 0.005 690 3.105 16B-xb 280 700 900 7261 4263 4130 2714 83.4 0.58 1.40 0.011 690 3.420 16B-zb 240 700 900 6322 4263 3510 2709 80.53 0.57 1.61 0.013 3.867 16b-adb 300 800 1100 7915 4872 4394 3050 38.04 0.57 1.47 0.005 3.542 16b-acb 300 800 1000 8197 4872 4375 3154 51.3 0.55 1.42 0.006 3.408 16b-aab 300 800 900 7726 4872 4298 3332 61.87 0.58 1.50 0.008 3.570 16b-abb 300 800 800 7701 4872 4282 3446 60.33 0.58 1.51 0.008 3.555 16b-aeb 400 800 1000 8518 4872 6000 3135 1979 0.70 1.36 0.232 4.007 16b-aca 1500 0 1400 5497 0 13922 0 0 4.09 0.00 0.000 1.888 16b-aaa 1500 0 1600 5523 0 14327 0 0 4.07 0.00 0.000 1.883 16B-aba 1800 0 1800 5874 0 15237 0 0 4.60 0.00 0.000 2.072 Table 4. Numerical simulations of field scale steam-propane hybrid process Run Description Stm inj. C3 inj. Pressure Subcool oil prod. oil @ 1000011 @
200O H20 inj H2O prod solvent Injsolvent pr net solvenSOR net C30R
(mild) (std mild (kPa) ( C) (m3) (m3) (m3) @ 2000 d(i (m3) @ 2000d @2000d (m3) @2000d 8g2000d R2D-14 field disp only, 1200 We 4.46E+00 1.86E+03 1200 5 6716 1717 2964 8912 9023 3.69E+08 3.65E+06 4.50E+04 3.01 0.063 P20-17 no add disp. disp, 1400 We 4.46 1858 1400 5 6691 2286 3365 8920 9092 3.69E+06 3.58E+06 1.04E+05 2.65 0.129 R2D-18 field scab d8fl, 1200 We 4.46 1858 1200 5 6799 2200 3738 8933 9091 3.69E+06 3.58E+06 1.04E+05 2.39 0.116 R2D-19 Sudicky field disp&diff, 1200 kPa 4.46 1858 1200 5 6821 2359 3926 8928 9097 3.70E+06 3.59E+06 1,06E+05 2.27 0.112 R20.22 Sud. Field D&D, 1300 kPa 4.46 1858 1300 5 7014 2670 4202 89DB 9041 3.68E+06 3.53E+06 1,49E+05 2.12 0.148 R2D-20 S" field D & 0, 1400 kPa 4.46 1858 1400 5 7218 3016 4430 8902 9041 3.67E+06 3,53E+06 1.40E+05 2.01 0.132 R20-20a S" field D & D, 1500 kPa 4.46 1858 1500 5 3243 4510 6941 9099 3.69E+06 3.55E+06 1.34E+05 1.54 0.124 820-21 Sud. Field D&D, 1600 We 4.46 1858 1600 5 6647 2317 3498 8912 9060 3.69E+06 3.64E+06 5,40E+04 2.55 0.064 820-23 S. field D&D, live oil, stm. Only 4.45 0 1100-2360 5 6480 3035 5563 8958 9127 0 0 0.00E+00 1.61 0.000 R20-24 S. Bd. D&D, live 0.,stm.o., Kh 4.46 0 1080-2360 5 6250 3151 5669 8975 8989 0 0 0.00E+00 1.58 0.000 R20-25 S. 6d. 050, live 0.,stm.o., Kh 2.98-1.03 0 800 5 4733 1891 3316 4994 4981 0 0 0.00E+00 1.51 0.000 R20-26 S. Bd. D&D, live 0.,stm.o., Kh 5,8-0.85 0 1200 5 5930 3370 4988 7562 7645 0 0 0,00E+00 1.52 0.000 R2D-27 S. fid. D&D, live O.,stm.o., Kh 8.0- 0.85 0 1600 5 6177 4135 5867 9312 9387 0 0 0.00E+00 1.59 0.000 R2D-28 S. Pd. D&D, live 0.,stm.o., Kh 12.0-0.9 0 2000 5 6292 4884 6178 10613 10678 0 0 0,00E+00 1.72 0,000 R2D-29 S. Pd. D&D, live 0.,stm.o., Kh 14.0- 0.9 0 2200 5 6333 5244 6261 11161 11187 0 0 0,00E+00 1.78 0.000 R20.31 S. 04. D&D, live O.,stm.o., Kh 4.46 900 1450 5 3230 2480 3150 4016 3682 1.78E+08 1.43E+06 3,46E+05 1.27 0.458 R2D-33 5" field D & D, live 0., 1400 We 4.46 2300 1400 5 7261 2648 4020 8940 9091 4.56E+06 4.44E+06 1,22E+05 2.22 0.126 R2D-35 S" field D & D, live 0., 3.Ostm 3 1858 1000 5 4652 1195 2132 5934 5898 3.68E+06 3.64E+06 3,30E+04 2.78 0,064 R2D-34 S" field D & D, live 0., 3.Ostm 3 1858 1200 5 6804 2027 3541 5963 6075 3.70E+06 3.59E+06 1,12E+05 1.68 0.132 R2D-37 S" field D & D, live 0., 3.0stm 3 1858 1300 5 7061 2235 3606 5920 6043 3.68E+06 3.55E+06 1.34E+05 1.64 0.155 R20-36 S" field D & D, live 0., 3.0stm 3 1858 1400 5 7212 2334 3522 5955 6049 3.68E+06 3.56E+06 1,27E+05 1.69 0.150 2d-39B S" field 0 & D, live 0., 3.0stm 3 1858 1500 5 7128 2204 3339 5944 6075 3.69E+06 3.58E+06 1,10E+05 1.78 0.137 R2d-39a S" field 0 & D, live 0., 3.Ostm 3 1858 1600 5 6096 1669 2695 5945 3.69E+06 3.67E+06 2.00E+04 2.21 0.031 R2d-41 S" field D & D, live 0., 6.Ostm 6 1858 1200 5 6852 2504 4114 11843 11969 3.70E+06 3.60E+06 1.03E+05 2.88 0.104 R2D-38 5" field D & D, live 0., 6.0stm 6 1858 1400 5 7196 2927 4600 11887 11986 3.68E+06 3.55E+06 1.32E+05 2.58 0.120 82045 S" field D & D, five O., 6.0stm 6 1858 1500 5 7367 3050 4458 11897 11993 3.68E+06 3.56E+06 1,20E+05 2.67 0.112 R2d-39 S" field D & D, rive 0., 3.0stm 6 1858 1600 5 6784 2354 3700 11900 11904 3.68E+06 3.66E+06 2.20E+04 3.22 0.025 2D-40 S" field 0 & 0, live 0., 6.0stm 6 1858 1800 5 6831 2390 3783 11911 11908 3.68E+06 3.67E+06 1,20E+04 3.15 0.013 R2d-42 S" field 0 & D, live 0., 6.0stm 6 1858 2000 5 6852 2458 3899 11918 11954 3.69E+06 3.67E+06 2.30E+04 3.06 0.025 020-43 5" field 0 & D, live 0., 5.35stm 5.35 1858 1400 5 7206 2815 4380 10546 10672 3.68E+06 3.55E+06 1.32E+05 2.41 0.126 820.46 S" field D & D, live 0., 5.35s1m 5.35 1858 1500 5 7394 2957 4241 10604 10718 3.69E+06 3.57E+06 1,18E+05 2.50 0,116 R2D.44 S" field D & D, live 0., 5.35stm 5.35 1858 1600 5 6714 2245 3521 10608 10618 3.69E+06 3.67E+06 2.10E+04 3.01 0.025 R2D-47 5" field 0 & D, live 0., 75C sub 4.46 1858 1400 75 3926 1232 1710 1562 1616 3.67E+06 3.59E+06 770E+04 0.91 0,188 R2D-51 S" field D & D, live 0., 65C sub 4.46 1858 1400 65 1714 2572 2662 2746 3.68E+06 3.56E+06 1.17E+05 1.03 0.190 R2D-52 S" field D & 0, five 0., 45C sub 4.46 1858 1400 45 2276 3272 4267 4363 3.68E+06 3.55E+06 1,34E+05 1.30 0.171 820.53 S" field D & D, five O., 25C sub 4.46 1858 1400 25 7291 2756 3960 7658 7772 3.68E+06 3.55E+06 1.35E+05 1.93 0.142 R20-47 S" field 0 & D, live 0., 75C sub 4.46 1858 1400 75 3926 1232 1710 1562 1616 3.87E+06 3.59E+06 7,70E+04 0.91 0.188 R213-48 S" field D & D, live 0., 75C subC 4.46 1858 1600 75 6754 1626 2685 1544 1603 3.58E+06 2.88E+06 7.06E+05 0.58 1.096 R20-49 S" field 0 & D, live 0., 55C subc 4.46 1858 1800 55 7132 1991 4470 4186 4342 3.69E+06 2.59E+06 1,09E+06 0.93 1.019 R2D-50 S" field 0 & D, live 0., 45C subc 4.46 1858 2000 45 2559 4455 5425 5599 3.69E+06 2.94E+06 7,43E+05 1.22 0.695 R2D-54 S" field 0 & D, live 0., 65C subc 4.46 1858 1500 85 7400 2047 3394 3099 3201 3.35E+06 2.97E+06 3,81E+05 0.91 0.468 R20-55 S" field D & D, live 0., 45C subc 4.46 1858 1500 45 5500 1743 2796 3235 3352 3.68E+06 3.48E+06 1,95E+05 1.16 0.291 MD-56 S" field D & D, live 0., 25C subc 4.46 1858 1500 25 7700 2837 3619 5680 5776 168E+06 3.54E+06 1.43E+05 1.57 0.165 R2D-57 S" field D & D, live 0., 25C subc 4.46 1858 1500 15 7411 2765 3927 8831 8878 3.68E+06 3.57E+06 1,13E+05 2.25 0.120 R20-58 S" field 0 & D, live 0., 4.46 515. 4.46 1858 1500 5 7409 2772 3927 8837 8930 3.69E+06 3.56E+06 1,30E+05 2.25 0.138 R213-56b 5" field D & D, live 0., 25C subc 4.46 1858 1500 25 7800 2837 3617 5681 5779 3.69E+06 3.55E+06 1,39E+05 1.57 0,160 R213-52b S" field D & D, live 0., 45C sub 4.46 1858 1500 45 2272 3275 4271 4372 3.68E+06 3.55E+06 1.27E+05 1.30 0.162 Table 5. Numerical simulations of field scale steam-butane hybrid process Run Description Sam inj. C, inj. Pressure Subcool oil prod. oil @ 1000oil @
2000 H2O inj H2O prod C4 inj. C4 prod net C4 in FSOR
(mild) (std mild (kPa) (C) (m3) (m3) (m3) @ 2000 d(i(m3) @ 2000d @2000d (m3) @2000d 0205-17 field disp, 2100 kPa,CH4 6 1860 2100 25 7110 6587 7094 9936 10032 3.41E+06 3.33E+06 7.20E+04 1.40 R2136-15 field disp, 1900 kPa,CH4 4.46 1860 1900 25 7186 6367 7163 8685 8678 3.67E+06 3.55E+06 1.17E+05 1.21 R2DB-13 field disp, 1700 kPa,CH4 4.46 1860 1700 25 7179 8266 7152 8404 8479 3.65E+06 3.52E+08 1.30E+05 1.18 R2DB-ll field disp, 1500 kPa,CH4 4.46 1860 1500 25 7173 5996 7130 8174 8300 3.82E+06 3.48E+06 1.42E+05 1.15 R20B-09 field disp, 1300 kPa,CH4 4.46 1860 1300 25 7176 5436 7099 8063 8191 3.67E+06 3.50E+06 1.68E+05 1.14 R205-05 field disp, 1100 kPa,CH4 4.46 1860 1100 25 7172 4630 7015 7610 7759 367E+06 3.48E+06 1.90E+05 1.08 8208-04 field disp, 1000 kPa,CH4 4.46 1860 1000 25 7181 4194 6924 7065 7234 3.67E+06 3.46E+06 2.13E+05 1.02 R2DB-01 field disp only, 900 kPa 4.46 1858 900 25 7214 3743 6806 6344 6342 3.67E+06 3.45E+06 2.21E+05 0.93 8208.02 field disp, 800 We 4.46 1860 800 25 7222 3157 6471 4983 5114 3.65E+06 3.40E+06 2.58E+05 0.77 R2DB-02a field disp, 800 kPa,CH4 4.46 1860 800 25 7196 3132 6432 4998 5125 3.66E+06 3.40E+06 2.63E+05 0.78 R2DB-03a field disp, 700 kPa,CH4 4.46 1860 700 25 7203 2550 5469 3805 3914 3,66E+06 3.32E+06 3.42E+05 0.70 02DB-08 field disp,1400 kPa,CH4 8 240 1400 25 7068 5381 6902 6527 6688 4,76E+05 3.23E+05 1.53E+05 0.95 8208-06 fielldisp,1600kPaCH4 8 240 1600 25 7028 5781 6924 7113 7260 4,80E+05 3.48E+05 1.32E+05 1.03 R2DB-07 fielldisp,1800kPa,CH4 8 240 1800 25 6988 6043 6918 7753 7866 4.75E+05 3.62E+05 1.13E+05 1.12 R2138-10 field disp,1600 kPa,CH4 8 480 1600 25 7106 6014 7047 7675 7779 9.53E+05 8.05E+05 1.48E+05 1.09 0208-12 field disp,1800 kPa,CH4 8 480 1800 25 7057 6240 7018 8196 8261 9.54E+05 8.33E+05 1.22E+05 1.17 0208-14 field disp,2000 kPa,CH4 8 480 2000 25 7016 6377 6983 8495 8505 9.52E+05 8.46E+05 1.05E+05 1,22 R2DB-16 field disp,2200 kPa,CH4 8 480 2200 25 6984 6429 6952 8664 8681 9.43E+05 8.52E+05 9.11E+04 1,25 R2 DB-20 field disp, 1200 kPa, CH4 8 120 1200 25 6953 4263 6553 5837 6024 2.35E+05 1.15E+05 1.20E+05 1.18 R2139-18 field disp, 1400 kPa,CH4 8 120 1400 25 6923 4914 6680 6506 6687 2.41E+05 1.28E+05 1.13E+05 0.97 8208-19 field disp,1600 kPa,CH4 8 120 1600 25 6874 5229 6703 7106 7242 2.40E+05 1.36E+05 1.05E+05 1.06 R20B-21 field disp,1200 kPa,CH4 8 60 1200 25 6797 3603 6108 5961 6103 1.19E+05 4.01E+04 7.88E+04 0.98 R20B-23 field disp,1400 kPa,CH4 8 60 1400 25 6725 4025 6188 6508 6529 1.21E+05 420E+04 7.86E+04 1.05 8205.22 field disp,1600 kPa,CH4 8 60 1600 25 6695 4401 6279 7201 7318 1.20E+05 4.18E+04 7.81E+04 1.15 R20.27 S. fid. D&D, live 0.,stm.o., Kh 8.0- 0.85 0 1400 13.8 6177 4135, 5867 9312 9387 0 0 0.00E+00 1.59
Claims
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| CA2660227A1 true CA2660227A1 (en) | 2010-09-26 |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10487636B2 (en) | 2017-07-27 | 2019-11-26 | Exxonmobil Upstream Research Company | Enhanced methods for recovering viscous hydrocarbons from a subterranean formation as a follow-up to thermal recovery processes |
| US11002123B2 (en) | 2017-08-31 | 2021-05-11 | Exxonmobil Upstream Research Company | Thermal recovery methods for recovering viscous hydrocarbons from a subterranean formation |
| US11142681B2 (en) | 2017-06-29 | 2021-10-12 | Exxonmobil Upstream Research Company | Chasing solvent for enhanced recovery processes |
| US11261725B2 (en) | 2017-10-24 | 2022-03-01 | Exxonmobil Upstream Research Company | Systems and methods for estimating and controlling liquid level using periodic shut-ins |
-
2009
- 2009-03-26 CA CA 2660227 patent/CA2660227A1/en not_active Abandoned
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11142681B2 (en) | 2017-06-29 | 2021-10-12 | Exxonmobil Upstream Research Company | Chasing solvent for enhanced recovery processes |
| US10487636B2 (en) | 2017-07-27 | 2019-11-26 | Exxonmobil Upstream Research Company | Enhanced methods for recovering viscous hydrocarbons from a subterranean formation as a follow-up to thermal recovery processes |
| US11002123B2 (en) | 2017-08-31 | 2021-05-11 | Exxonmobil Upstream Research Company | Thermal recovery methods for recovering viscous hydrocarbons from a subterranean formation |
| US11261725B2 (en) | 2017-10-24 | 2022-03-01 | Exxonmobil Upstream Research Company | Systems and methods for estimating and controlling liquid level using periodic shut-ins |
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