On robust and efficient parallel reservoir simulation on tianhe-2

Wenchao Guan, Changhe Qiao, Hongxuan Zhang, Chen Song Zhang, Meipeng Zhi, Zhifan Zhu, Zhenying Zheng, Weicai Ye, Yongdong Zhang, Xiaozhe Hu, Zheng Li, Chunsheng Feng, Yuesheng Xu, Jinchao Xu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

Parallel reservoir simulators are now widely used with availability of super computers. Modern massively parallel supercomputers demonstrate great power for simulating large-scale reservoir models. However, improving scalability and efficiency for fully implicit methods on emerging parallel architectures is still challenging. In this paper, we present a robust discretization together with a parallel linear solver algorithm; and we explore the parallel implementation on the world's fastest supercomputer Tianhe-2. Starting with a general compositional model, we focus on the black oil model and developed Parallel eXtension Framework for parallelizing the serial simulator. A parallel preconditioner based on fast auxiliary space preconditioning (FASP) is applied to solve the Jacobian system arising from the fully implicit discretization. The parallel simulator was validated using large-scale black oil benchmark problems, for which parallel scalabilities were tested. Giant reservoir models with over 100 million grid blocks have been simulated within a few minutes, and test the strong scalability of AMG solver with 1 billion unknown. We also demonstrate the parallelization and acceleration using Intel Xeon Phi coprocessors. In the end, the efficiency of the parallel simulator is illustrated by a giant reservoir using up to 10,000 cores, for which the CPU and communication time are summarized for the linear and nonlinear algorithms.
Original languageEnglish (US)
Title of host publicationSociety of Petroleum Engineers - SPE Reservoir Characterisation and Simulation Conference and Exhibition, RCSC 2015
PublisherSociety of Petroleum Engineers
Pages933-945
Number of pages13
ISBN (Print)9781510813427
DOIs
StatePublished - Jan 1 2015
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-02-15

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