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Angelo Lucia
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A multi-scale reservoir simulation framework for large-scale, multiphase flow with mineral precipitation in CO2-brine systems is proposed. The novel aspects of this reservoir modeling and simulation framework are centered around the seminal coupling of rigorous reactive transport with full compositional modeling and consist of (1) thermal, multi-phase flow tightly coupled to complex phase behavior, (2) the use of the Gibbs-Helmholtz Constrained (GHC) equation of state, (3) the presence of multiple homogeneous/heterogeneous chemical reactions, (4) the inclusion of mineral precipitation/dissolution, and (5) the presence of homogeneous/heterogeneous formations. The proposed modeling and simulation framework is implemented using the ADGPRS/GFLASH system. A number of examples relevant to CO2 sequestration including salt precipitation and solubility/mineral trapping are presented and geometric illustrations are used to elucidate key attributes of the proposed modeling framework.
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A multi-scale reservoir simulation framework for large-scale, multiphase flow with mineral precipitation in CO2-brine systems is proposed. The novel aspects of this reservoir modeling and simulation framework are centered around the seminal coupling of rigorous reactive transport with full compositional modeling and consist of (1) thermal, multi-phase flow tightly coupled to complex phase behavior, (2) the use of the Gibbs-Helmholtz Constrained (GHC) equation of state, (3) the presence of multiple homogeneous/heterogeneous chemical reactions, (4) the inclusion of mineral precipitation/dissolution, and (5) the presence of homogeneous/heterogeneous formations. The proposed modeling and simulation framework is implemented using the ADGPRS/GFLASH system. A number of examples relevant to CO2 sequestration including salt precipitation and solubility/mineral trapping are presented and geometric illustrations are used to elucidate key attributes of the proposed modeling framework.
Primary oil recovery methods in heavy oil basins generally extract 5-10% of the available resource, with the vast majority left in the ground and recoverable only through Enhanced Oil Recovery (EOR) methods. Traditional EOR methods, such as SAGD and solvent-assisted SAGD, generate steam in surface facilities and inject it underground to mobilize the oil for production. However, these methods can have considerable energy losses that significantly impact process performance. In contrast, the Solvent Thermal Resource Innovation Process (STRIP) technology, which uses down hole combustion of methane to produce CO2 and steam, reduces the operating and capital costs of surface facilities, saving more than 50% of the energy typically required for thermal production. In this work, simulations of conventional SAGD, SAGD with a non-condensing solvent (propane), and STRIP-SAGD for a typical bitumen reservoir in the Fort McMurray region in Alberta, Canada were performed using the combined software system ADGPRS/GFLASH. SAGD simulations used steam injection with a quality of 0.8 while STRIP simulations injected a vapor-liquid mixture with a quality of 0.8. Furthermore, both solvent-based EOR methods required longer operation periods than conventional SAGD to recover a similar amount of oil. However, when compared on the basis of cumulative oil produced for the same overall energy input, it is shown that STRIP-SAGD recovered more oil per kJ of energy input to the reservoir than either SAGD or SAGD with propane co-injection.
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Primary oil recovery methods in heavy oil basins generally extract 5-10% of the available resource, with the vast majority left in the ground and recoverable only through Enhanced Oil Recovery (EOR) methods. Traditional EOR methods, such as SAGD and solvent-assisted SAGD, generate steam in surface facilities and inject it underground to mobilize the oil for production. However, these methods can have considerable energy losses that significantly impact process performance. In contrast, the Solvent Thermal Resource Innovation Process (STRIP) technology, which uses down hole combustion of methane to produce CO2 and steam, reduces the operating and capital costs of surface facilities, saving more than 50% of the energy typically required for thermal production. In this work, simulations of conventional SAGD, SAGD with a non-condensing solvent (propane), and STRIP-SAGD for a typical bitumen reservoir in the Fort McMurray region in Alberta, Canada were performed using the combined software system ADGPRS/GFLASH. SAGD simulations used steam injection with a quality of 0.8 while STRIP simulations injected a vapor-liquid mixture with a quality of 0.8. Furthermore, both solvent-based EOR methods required longer operation periods than conventional SAGD to recover a similar amount of oil. However, when compared on the basis of cumulative oil produced for the same overall energy input, it is shown that STRIP-SAGD recovered more oil per kJ of energy input to the reservoir than either SAGD or SAGD with propane co-injection.
Journal article
(2014)
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Rustem Zaydullin, Denis V. Voskov, Scott C. James, Heath Henley, Angelo Lucia
Fully compositional and thermal reservoir simulation capabilities are important in oil exploration and production. There are significant resources in existing wells and in heavy oil, oil sands, and deep-water reservoirs. This article has two main goals: (1) to clearly identify chemical engineering sub-problems within reservoir simulation that the PSE community can potentially make contributions to and (2) to describe a new computational framework for fully compositional and thermal reservoir simulation based on a combination of the Automatic Differentiation-General Purpose Research Simulator (AD-GPRS) and the multiphase equilibrium flash library (GFLASH). Numerical results for several chemical engineering sub-problems and reservoir simulations for two EOR applications are presented. Reservoir simulation results clearly show that the Solvent Thermal Resources Innovation Process (STRIP) outperforms conventional steam injection using two important metrics - sweep efficiency and oil recovery.
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Fully compositional and thermal reservoir simulation capabilities are important in oil exploration and production. There are significant resources in existing wells and in heavy oil, oil sands, and deep-water reservoirs. This article has two main goals: (1) to clearly identify chemical engineering sub-problems within reservoir simulation that the PSE community can potentially make contributions to and (2) to describe a new computational framework for fully compositional and thermal reservoir simulation based on a combination of the Automatic Differentiation-General Purpose Research Simulator (AD-GPRS) and the multiphase equilibrium flash library (GFLASH). Numerical results for several chemical engineering sub-problems and reservoir simulations for two EOR applications are presented. Reservoir simulation results clearly show that the Solvent Thermal Resources Innovation Process (STRIP) outperforms conventional steam injection using two important metrics - sweep efficiency and oil recovery.
Conference paper
(2013)
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Angelo Lucia, Denis Voskov, Scott C. James, Rustem Zaydullin, Heath Henley
Primary oil recovery methods in Saskatchewan's heavy oil basin extract 5 to 10% of the available resource with the vast majority left in the ground and recoverable only through Enhanced Oil Recovery (EOR) methods. Traditional EOR generates steam in surface facilities and injects it underground to mobilize the oil for production with considerable energy losses inherent in the process. R.I.I. North America's Solvent Thermal Resource Innovation Process (STRIP) technology moves the steam generator underground, reducing the operating and capital costs of a surface thermal production facility by 30% and 50% respectively, and saving more than 30% of the energy typically required for thermal production. STRIP technology combusts methane to produce in situ CO 2 and steam. Because CO2 acts as a co-solvent, STRIP outperforms traditional steam-injection technology. This is demonstrated using a breakthrough modeling technique that couples fully compositional and thermal reservoir flow simulation capabilities. This new approach couples FlashPoint's equation-of-state solver for the multiphase, multi-component, isothermal, isobaric flash problem, GFLASH, with Stanford's Automatic Differentiation General Purpose Research Simulator for thermal reservoir flow simulations. This new computational framework exploits advanced techniques for skipping phase-identification computations and only uses exact phase equilibria from GFLASH when needed, reducing computational times by one to two orders of magnitude compared to the full rigorous solution.
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Primary oil recovery methods in Saskatchewan's heavy oil basin extract 5 to 10% of the available resource with the vast majority left in the ground and recoverable only through Enhanced Oil Recovery (EOR) methods. Traditional EOR generates steam in surface facilities and injects it underground to mobilize the oil for production with considerable energy losses inherent in the process. R.I.I. North America's Solvent Thermal Resource Innovation Process (STRIP) technology moves the steam generator underground, reducing the operating and capital costs of a surface thermal production facility by 30% and 50% respectively, and saving more than 30% of the energy typically required for thermal production. STRIP technology combusts methane to produce in situ CO 2 and steam. Because CO2 acts as a co-solvent, STRIP outperforms traditional steam-injection technology. This is demonstrated using a breakthrough modeling technique that couples fully compositional and thermal reservoir flow simulation capabilities. This new approach couples FlashPoint's equation-of-state solver for the multiphase, multi-component, isothermal, isobaric flash problem, GFLASH, with Stanford's Automatic Differentiation General Purpose Research Simulator for thermal reservoir flow simulations. This new computational framework exploits advanced techniques for skipping phase-identification computations and only uses exact phase equilibria from GFLASH when needed, reducing computational times by one to two orders of magnitude compared to the full rigorous solution.