New Reduced Parameters for Flash Calculations Based on Two-parameter BIP Formula

Gorucu, Seyhan Emre; Johns, Russell T.

doi:10.3997/2214-4609.20142597

Cited by 5 publications

(7 citation statements)

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“…. Nichita and Graciaa (2011), Nichita and Petitfrere (2013), and Gorucu and Johns (2014) linearize the natural logarithm of fugacity coefficient as…”

Section: Reduced Stability Analysismentioning

confidence: 99%

“…where m is the number of reduced variables, h  are the reduced variables, and i q  is a matrix of constant parameters. For the reduced variables of Gorucu and Johns (2014), m is always 6 and the parameters in Eq. (4) are…”

Section: Reduced Stability Analysismentioning

confidence: 99%

“…First, we briefly describe our algorithm for conventional phase equilibrium calculations. Then, we implement the reduced variables of Gorucu and Johns (2014) for both stability analysis and threephase flash calculations. We then give our methodology to test and compare the various algorithms using several example fluids where three-phase regions co-exist.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Robustness of three-phase equilibrium calculations

Gorucu¹,

Johns

2016

Journal of Petroleum Science and Engineering

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Phase equilibrium calculations converge less often as the number of phases and components increase, and for overall compositions closer to phase split boundaries and critical points. Computational speed and robustness of flash calculations are very important aspects for pipeline transmission and for reservoir simulation where billions of flash calculations may be done. Reduced methods have the potential to improve the robustness of phase equilibrium calculations because if chosen properly they can linearize the equations, use fewer independent variables and can be unbounded. Improved robustness could further improve the speed and accuracy of compositional simulation and avoid false two-phase solutions, where three or more phases may be present. In this paper, we use the reduced variables of Gorucu and Johns (2014) to test robustness in performing two-and three-phase stability analysis and corresponding flash calculations. These multiphase equilibrium calculations are compared with the conventional phase equilibrium calculations based on minimization of Gibbs energy and the reduced method proposed by Okuno et. al. (2010a). Using thousands of equally-spaced and unbiased multi-phase equilibrium calculations, the proposed multi-phase equilibrium calculations are shown to be more robust than the other two tested algorithms.

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“…. Nichita and Graciaa (2011), Nichita and Petitfrere (2013), and Gorucu and Johns (2014) linearize the natural logarithm of fugacity coefficient as…”

Section: Reduced Stability Analysismentioning

confidence: 99%

Section: Reduced Stability Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Robustness of three-phase equilibrium calculations

Gorucu¹,

Johns

2016

Journal of Petroleum Science and Engineering

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“…Phase equilibrium calculations are carried out in order to compute the distribution of components in different phases and the phase mole fractions (Michelsen, 1982a;Michelsen 1982b). These techniques are still being evaluated and have not been implemented to the commercial simulators to the best of our knowledge (Gorucu and Johns, 2014). These calculations are computationally expensive and unstable particularly near the critical region and the phase envelope.…”

Section: Reservoir Simulationmentioning

confidence: 99%

Integrated Asset Modeling Through Multi-Reservoir Optimization of Offshore Fields using Next-Generation Reservoir Simulators

Temizel¹,

Tiwari

2016

Day 4 Thu, May 05, 2016

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Objective/Scope: Integrated asset modeling (IAM) offers the oil industry several benefits. The next-generation reservoir simulators help achieve faster runtimes, insight into interaction between various components of a development, and can be used as an effective tool in detecting bottlenecks in a production system as well as a constant and more effective communication tool between various departments. IAM provides significant opportunities for optimization of very large or complex infrastructures and life-offield analysis of production optimization scenarios.Simultaneous modeling of surface and subsurface components helps reduce time and enhances efficiency during the decision-making process which eliminates the requirement for tedious, time-consuming work and iterations between separate solutions of reservoir and surface networks. Beyond this convenience, this technology makes it possible to reach more robust results more quickly using surface-subsurface coupling. The objective of this study is to outline the advantages and the challenges in using next-generation simulators on simulation of multiple reservoirs in integrated asset management.Methods/Processes: Simultaneous simulation of multiple reservoirs adds another dimension of complexity to the process of integrated asset modeling. Several sub-reservoir models can be simulated simultaneously in large fields comprising sub-reservoirs with complex surface systems, which could otherwise become very tedious to handle. In this study, a next-generation reservoir simulator is coupled with an optimization and uncertainty tool that is used to optimize the net present value of the entire asset. Several constraints and bottlenecks in such a large system exist, all connected to one another. IAM proves useful in debottlenecking to increase efficiency of the thorough system. The strengths and difficulties associated with simultaneous simulation and optimization of multiple reservoirs are compared to the more conventional way of simulating the assets separately, thus illustrating the benefits of using next-generation reservoir simulators during optimization of multiple reservoirs. Results/Observations:The results show that simultaneous solution of the surface-subsurface coupling gives significantly faster results than that of a system that consists of separate solution of surface and subsurface. The speed difference becomes more significant when the number of reservoirs simulated is more than one. This study outlines the workflow in setting up the model, the CPU time for each component of the simulation, the explanation of each important item in this process to illustrate the

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“…Phase-equilibrium calculations are carried out to compute the distribution of components in different phases and the phase-mole fractions (Michelsen 1982a;Michelsen 1982b). These techniques are still being evaluated and have not been implemented to the commercial simulators to the best of our knowledge (Gorucu and Johns 2014). These calculations are computationally expensive and unstable, particularly near the critical region and the phase envelope.…”

Section: Otc-25923-msmentioning

confidence: 99%

Integrated Asset Modeling Through Optimization of Multiple Reservoirs Using Next-Generation Reservoir Simulators

Temizel¹,

Purwar²,

Abdullayev³

et al. 2015

All Days

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Integrated asset modeling (IAM) offers the oil industry several benefits. Next-generation reservoir simulators help achieve faster runtimes, offer insight into interaction between various components of a development, and can be used as an effective tool in detecting bottlenecks in a production system as well as a constant and more effective communication tool between various departments. IAM provides significant opportunities for the optimization of very large or complex infrastructures and life-of-field analyses of production optimization scenarios.Simultaneous modeling of surface and subsurface components helps reduce time and enhances efficiency during the decision-making process, which eliminates the requirement for tedious, timeconsuming work and iterations between separate solutions of reservoir and surface networks. Beyond this convenience, this technology makes it possible to reach more robust results more quickly using surfacesubsurface coupling. The objective of this study is to outline the advantages and the challenges in using next-generation simulators for the simulation of multiple reservoirs in integrated asset management.Simultaneous simulation of multiple reservoirs adds another dimension of complexity to the process of integrated asset modeling. Several sub-reservoir models can be simulated simultaneously in large fields comprising sub-reservoirs with complex surface systems, which could otherwise become very tedious to handle. In this study, a next-generation reservoir simulator is coupled with an optimization and uncertainty tool that is used to optimize the net present value of the entire asset. Several constraints and bottlenecks in such a large system exist all connected to one another. IAM proves useful in debottlenecking to increase the efficiency of the total system. The strengths and difficulties associated with simultaneous simulation and optimization of multiple reservoirs are compared to the more conventional way of simulating the assets separately, thus illustrating the benefits of using next-generation reservoir simulators during the optimization of multiple reservoirs.The results show that a simultaneous solution of the surface-subsurface coupling gives significantly faster results than that of a system that consists of separate solutions for surface and subsurface. The speed difference becomes more significant when the number of reservoirs simulated is greater than one. This study outlines the workflow in setting up the model, the CPU time for each component of the simulation, and the explanation of each important item in this process to illustrate the incremental benefits of the use

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New Reduced Parameters for Flash Calculations Based on Two-parameter BIP Formula

Cited by 5 publications

References 0 publications

Robustness of three-phase equilibrium calculations

Robustness of three-phase equilibrium calculations

Integrated Asset Modeling Through Multi-Reservoir Optimization of Offshore Fields using Next-Generation Reservoir Simulators

Integrated Asset Modeling Through Optimization of Multiple Reservoirs Using Next-Generation Reservoir Simulators

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