基于混合有限元的多孔介质两相流块约束压力残余预处理

IF 2.1 3区 地球科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Stefano Nardean, Massimiliano Ferronato, Ahmad Abushaikha
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引用次数: 0

摘要

摘要本文提出了一种新颖的预调节器,将约束压力剩余(CPR)方法与块预调节器相结合,用于求解由全隐式多相流模型引起的线性化方程组。该预调节器被称为块CPR (BCPR),是专门为基于拉格朗日乘数的流量模型而设计的,例如由混合混合有限元(MHFE)近似生成的流量模型。基于mhfe的两相流模型的原始公式被用作BCPR预调节器开发的参考,其中系统未知数集包括单元压力和面压力,以及细胞饱和度,从而产生具有$$2\times 2$$ 2 × 2内压力问题的$$3\times 3$$ 3 × 3块结构雅可比矩阵。CPR方法是油藏模拟中最成熟的技术之一,但大多数研究都集中在基于两点通量近似(TPFA)的离散化解决方案上,这并不容易扩展到我们的问题表述中。因此,受CPR算法的启发,我们设计了一种专用的两阶段策略,其中在压力部分使用了块预调节器,旨在利用内部$$2\times 2$$ 2 × 2结构。提出的预处理框架通过广泛的实验进行了测试,包括在笛卡尔和非笛卡尔领域的综合和现实应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Block constrained pressure residual preconditioning for two-phase flow in porous media by mixed hybrid finite elements
Abstract This work proposes an original preconditioner that couples the Constrained Pressure Residual (CPR) method with block preconditioning for the efficient solution of the linearized systems of equations arising from fully implicit multiphase flow models. This preconditioner, denoted as Block CPR (BCPR), is specifically designed for Lagrange multipliers-based flow models, such as those generated by Mixed Hybrid Finite Element (MHFE) approximations. An original MHFE-based formulation of the two-phase flow model is taken as a reference for the development of the BCPR preconditioner, in which the set of system unknowns comprises both element and face pressures, in addition to the cell saturations, resulting in a $$3\times 3$$ 3 × 3 block-structured Jacobian matrix with a $$2\times 2$$ 2 × 2 inner pressure problem. The CPR method is one of the most established techniques for reservoir simulations, but most research focused on solutions for Two-Point Flux Approximation (TPFA)-based discretizations that do not readily extend to our problem formulation. Therefore, we designed a dedicated two-stage strategy, inspired by the CPR algorithm, where a block preconditioner is used for the pressure part with the aim at exploiting the inner $$2\times 2$$ 2 × 2 structure. The proposed preconditioning framework is tested by an extensive experimentation, comprising both synthetic and realistic applications in Cartesian and non-Cartesian domains.
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来源期刊
Computational Geosciences
Computational Geosciences 地学-地球科学综合
CiteScore
6.10
自引率
4.00%
发文量
63
审稿时长
6-12 weeks
期刊介绍: Computational Geosciences publishes high quality papers on mathematical modeling, simulation, numerical analysis, and other computational aspects of the geosciences. In particular the journal is focused on advanced numerical methods for the simulation of subsurface flow and transport, and associated aspects such as discretization, gridding, upscaling, optimization, data assimilation, uncertainty assessment, and high performance parallel and grid computing. Papers treating similar topics but with applications to other fields in the geosciences, such as geomechanics, geophysics, oceanography, or meteorology, will also be considered. The journal provides a platform for interaction and multidisciplinary collaboration among diverse scientific groups, from both academia and industry, which share an interest in developing mathematical models and efficient algorithms for solving them, such as mathematicians, engineers, chemists, physicists, and geoscientists.
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