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 $3 \times 3$ block-structured Jacobian matrix with a $2 \times 2$ 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 $2 \times 2$ structure. The proposed preconditioning framework is tested by an extensive experimentation, comprising both synthetic and realistic applications in Cartesian and non-Cartesian domains.
翻译:本文提出了一种原始预处理器,它将约束压力残差方法(CPR)与块预处理相结合,用于完全隐式多相流模型中出现的线性化方程组的高效求解。这个预处理器被称为块CPR(BCPR),是专门为基于拉格朗日乘数的流模型而设计的,例如由混合有限元(MHFE)近似产生的模型。本文参考了原始的基于MHFE的双相流模型公式,其中系统的未知数集包括元素和面压力,以及单元饱和度,从而产生一个 $3 \times 3$ 块状结构Jacobi矩阵,具有一个 $2 \times 2$ 的内部压力问题。CPR方法是油藏模拟中最成熟的技术之一,但大部分研究都聚焦于基于 TPFA 的离散化解决方案,不容易扩展到我们的问题公式。因此,我们设计了一种专用的两阶段策略,受 CPR 算法的启发,在压力部分使用块预处理,以利用内部 $2 \times 2$ 的结构。本文提出的预处理框架通过广泛的实验进行了测试,包括笛卡尔和非笛卡尔域中的合成和实际应用。