This paper presents our work on developing parallel computational methods for two-phase flow on modern parallel computers, where techniques for linear solvers and nonlinear methods are studied and the standard and inexact Newton methods are investigated. A multi-stage preconditioner for two-phase flow is applied and advanced matrix processing strategies are studied. A local reordering method is developed to speed the solution of linear systems. Numerical experiments show that these computational methods are effective and scalable, and are capable of computing large-scale reservoir simulation problems using thousands of CPU cores on parallel computers. The nonlinear techniques, preconditioner and matrix processing strategies can also be applied to three-phase black oil, compositional and thermal models.
@article{arxiv.1701.06254,
title = {A Parallel Simulator for Massive Reservoir Models Utilizing Distributed-Memory Parallel Systems},
author = {Hui Liu and Lihua Shen and Yan Chen and Kun Wang and Bo Yang and Zhangxin Chen},
journal= {arXiv preprint arXiv:1701.06254},
year = {2017}
}
Comments
arXiv admin note: substantial text overlap with arXiv:1606.00556