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A Critical Comparison of Reduced and Conventional EOS Algorithms

By: Language: Inglés Publication details: abr. 2013Description: 10 p. ; 378-388 In: SPE Journal 18Summary: Transcripción del resumen del autor: Phase-equilibrium calculations can be a time-consuming part of process simulators and compositional reservoir simulations. Various authors have presented encouraging speed improvements based on reduced methods that can lower the computational cost by reducing the number of independent variables and thus generating a smaller system of equations to solve. This paper presents a careful comparison of conventional and reduced algorithms, showing that they can be expressed as linear transformations of each other. Consequently, the two sets of algorithms exhibit identical convergence behavior, and the performance gain of the reduced methods is entirely caused by reducing the cost of linear algebra operations. Performance benchmarks show much smaller speed-up numbers than seen in previously published material. Highly optimized linear-algebra operations significantly limit the opportunity for further speed improvement from reduced methods. Only a marginal speed-up potential is observed for mixtures with 15 components or less. This suggests that reduced methods may be less attractive for reservoir simulation than previously thought.
Item type: Artículo de Revista
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Biblioteca Alejandro Angel Bulgheroni Not for loan 200059886

Transcripción del resumen del autor: Phase-equilibrium calculations can be a time-consuming part of process simulators and compositional reservoir simulations. Various authors have presented encouraging speed improvements based on reduced methods that can lower the computational cost by reducing the number of independent variables and thus generating a smaller system of equations to solve. This paper presents a careful comparison of conventional and reduced algorithms, showing that they can be expressed as linear transformations of each other. Consequently, the two sets of algorithms exhibit identical convergence behavior, and the performance gain of the reduced methods is entirely caused by reducing the cost of linear algebra operations. Performance benchmarks show much smaller speed-up numbers than seen in previously published material. Highly optimized linear-algebra operations significantly limit the opportunity for further speed improvement from reduced methods. Only a marginal speed-up potential is observed for mixtures with 15 components or less. This suggests that reduced methods may be less attractive for reservoir simulation than previously thought.

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