Parallel multi-stage preconditioners with adaptive setup for the black oil model

doi:10.1016/j.cageo.2022.105230

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	Parallel multi-stage preconditioners with adaptive setup for the black oil model
	Zhao, Li 1; Feng, Chunsheng 2,3; Zhang, Chen-Song 4; Shu, Shi 1
	2022-11-01
发表期刊	COMPUTERS & GEOSCIENCES
ISSN	0098-3004
卷号	168 页码:16
摘要	The black oil model is widely used to describe multiphase porous media flow in the petroleum industry. The fully implicit method features strong stability and weak constraints on timestep sizes; hence, it is commonly used in current mainstream commercial reservoir simulators. In this paper, a Constrained Pressure Residual (CPR) preconditioner with an adaptive "setup phase"is developed to improve the parallel efficiency of a petroleum reservoir simulation. Furthermore, we propose a multi-color Gauss-Seidel (GS) algorithm for the algebraic multigrid method based on the coefficient matrix of strong connections. Numerical experiments show that the proposed preconditioner can improve the parallel performance for both OpenMP and Compute Unified Device Architecture (CUDA) implements. Moreover, the proposed algorithm yields good parallel speedup as well as the same convergence behavior as the corresponding single-thread algorithm. In particular, for a three-phase benchmark problem (about 3.28 million degrees of freedom), the parallel speedup of the OpenMP version is over 6.5 with 16 threads, and the CUDA version reaches more than 9.5.
关键词	Black oil model Fully implicit method Parallel computing Multi-color Gauss-Seidel smoother Multi-stage preconditioners
DOI	10.1016/j.cageo.2022.105230
收录类别	SCI
语种	英语
资助项目	Postgraduate Scientific Research Innovation Project of Hunan Province, China ; Postgraduate Scientific Research Innovation Project of Xiangtan Uni-versity, China ; Excellent Youth Foundation of SINOPEC, China ; National Science Foundation of China ; [CX20210607] ; [XDCX2021B110] ; [P20009] ; [11971414]
WOS研究方向	Computer Science ; Geology
WOS类目	Computer Science, Interdisciplinary Applications ; Geosciences, Multidisciplinary
WOS记录号	WOS:000869700900004
出版者	PERGAMON-ELSEVIER SCIENCE LTD
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/60750
专题	中国科学院数学与系统科学研究院
通讯作者	Zhang, Chen-Song
作者单位	1.Xiangtan Univ, Sch Math & Computat Sci, Xiangtan 411105, Peoples R China 2.Xiangtan Univ, Natl Ctr Appl Math Hunan, Xiangtan 411105, Peoples R China 3.Hunan Shaofeng Inst Appl Math, Xiangtan 411105, Peoples R China 4.Acad Math & Syst Sci, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Li,Feng, Chunsheng,Zhang, Chen-Song,et al. Parallel multi-stage preconditioners with adaptive setup for the black oil model[J]. COMPUTERS & GEOSCIENCES,2022,168:16.
APA	Zhao, Li,Feng, Chunsheng,Zhang, Chen-Song,&Shu, Shi.(2022).Parallel multi-stage preconditioners with adaptive setup for the black oil model.COMPUTERS & GEOSCIENCES,168,16.
MLA	Zhao, Li,et al."Parallel multi-stage preconditioners with adaptive setup for the black oil model".COMPUTERS & GEOSCIENCES 168(2022):16.