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Computing and Visualization in Science
Published in: Computing and Visualization in Science 2-3/2017

21-12-2016

Numerical studies of a class of linear solvers for fine-scale petroleum reservoir simulation

Authors: Zheng Li, Shuhong Wu, Chen-Song Zhang, Jinchao Xu, Chunsheng Feng, Xiaozhe Hu

Published in: Computing and Visualization in Science | Issue 2-3/2017

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Abstract

Numerical simulation based on fine-scale reservoir models helps petroleum engineers in understanding fluid flow in porous media and achieving higher recovery ratio. Fine-scale models give rise to large-scale linear systems, and thus require effective solvers for solving these linear systems to finish simulation in reasonable turn-around time. In this paper, we study convergence, robustness, and efficiency of a class of multi-stage preconditioners accelerated by Krylov subspace methods for solving Jacobian systems from a fully implicit discretization. We compare components of these preconditioners, including decoupling and sub-problem solvers, for fine-scale reservoir simulation. Several benchmark and real-world problems, including a ten-million-cell reservoir problem, were simulated on a desktop computer. Numerical tests show that the combination of the alternating block factorization method and multi-stage subspace correction preconditioner gives a robust and memory-efficient solver for fine-scale reservoir simulation.
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Metadata
Title
Numerical studies of a class of linear solvers for fine-scale petroleum reservoir simulation
Authors
Zheng Li
Shuhong Wu
Chen-Song Zhang
Jinchao Xu
Chunsheng Feng
Xiaozhe Hu
Publication date
21-12-2016
Publisher
Springer Berlin Heidelberg
Published in
Computing and Visualization in Science / Issue 2-3/2017
Print ISSN: 1432-9360
Electronic ISSN: 1433-0369
DOI
https://doi.org/10.1007/s00791-016-0273-3

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