Fast linear solver for pressure computation in layered domains

P. Slingerland, C. Vuik
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引用次数: 1

Abstract

Accurate simulation of fluid pressures in layered reservoirs with strong permeability contrasts is a challenging problem. For this purpose, the Discontinuous Galerkin (DG) method has become increasingly popular. Unfortunately, standard linear solvers are usually too inefficient for the aforementioned application. To increase the efficiency of the Conjugate Gradient (CG) method for linear systems resulting from Symmetric Interior Penalty (discontinuous) Galerkin (SIPG) discretizations, we have cast an existing two-level preconditioner into the deflation framework. The main idea is to use coarse corrections based on the DG solution with polynomial degree p=0. This paper provides a numerical comparison of the performance of both two-level methods in terms of scalability and overall efficiency. Furthermore, it studies the influence of the SIPG penalty parameter, the smoother, damping of the smoother, and the strategy for solving the coarse systems. We have found that the penalty parameter can best be chosen diffusion-dependent. In that case, both two-level methods yield fast and scalable convergence. Whether preconditioning or deflation is to be favored depends on the choice for the smoother and on the damping of the smoother. Altogether, both two-level methods can contribute to faster and more accurate fluid pressure simulations.
层状域压力计算的快速线性求解器
具有强渗透率对比的层状储层流体压力的精确模拟是一个具有挑战性的问题。为此,不连续伽辽金(DG)方法变得越来越流行。不幸的是,对于上述应用程序,标准线性求解器通常效率太低。为了提高求解对称内罚(不连续)伽辽金(SIPG)离散引起的线性系统的共轭梯度(CG)方法的效率,我们在紧缩框架中引入了一个已有的两级预条件。主要思想是使用基于多项式次p=0的DG解的粗校正。本文在可扩展性和总体效率方面对两种两级方法的性能进行了数值比较。进一步研究了SIPG惩罚参数、平滑度、平滑度阻尼的影响,以及求解粗糙系统的策略。我们发现惩罚参数的选择最好与扩散相关。在这种情况下,两级方法都可以产生快速和可伸缩的收敛。选择预处理还是放气取决于对平滑器的选择和平滑器的阻尼。总之,这两种两级方法都有助于更快、更准确地模拟流体压力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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