论文标题
有效的重新排序的非线性高斯 - 西德尔求解器,用于黑油模型的高阶
Efficient Reordered Nonlinear Gauss-Seidel Solvers With Higher Order For Black-Oil Models
论文作者
论文摘要
完全隐式的方法是解决储层模拟中黑油问题的最常用方法。该方法需要重复对大型非线性系统的线性化,并产生不限制的线性系统。我们提出了一种策略,以减少依赖两个关键思想的计算时间:(\ textit {i})一个顺序的公式,将流动并运输到单独的子问题中,以及(\ textit {ii})一个高效的高斯 - 索引求解器,以解决运输问题。该求解器使用间透明通量根据其上游邻居对网格细胞进行重新排序,并将由于反向流入局部簇而相互依赖的细胞组。然后可以按顺序从流入和移动逐渐下游求解细胞和局部簇,因为每个新的单元格或局部群集仅取决于已经计算的上游邻居。总之,这给出了非线性解决方案过程的最佳定位和控制。 使用标准的一阶有限体积离散化,该方法已成功应用于实地问题。在这里,我们将这个想法扩展到完全非结构化的网格上的一阶DG方法。我们还使用开源OPM流量模拟器的原型变体将重新排序想法的概念证明用于重新排序的想法。
The fully implicit method is the most commonly used approach to solve black-oil problems in reservoir simulation. The method requires repeated linearization of large nonlinear systems and produces ill-condi\-tioned linear systems. We present a strategy to reduce computational time that relies on two key ideas: (\textit{i}) a sequential formulation that decouples flow and transport into separate subproblems, and (\textit{ii}) a highly efficient Gauss--Seidel solver for the transport problems. This solver uses intercell fluxes to reorder the grid cells according to their upstream neighbors, and groups cells that are mutually dependent because of counter-current flow into local clusters. The cells and local clusters can then be solved in sequence, starting from the inflow and moving gradually downstream, since each new cell or local cluster will only depend on upstream neighbors that have already been computed. Altogether, this gives optimal localization and control of the nonlinear solution process. This method has been successfully applied to real-field problems using the standard first-order finite volume discretization. Here, we extend the idea to first-order dG methods on fully unstructured grids. We also demonstrate proof of concept for the reordering idea by applying it to the full simulation model of the Norne oil field, using a prototype variant of the open-source OPM Flow simulator.