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Volume 16, Issue 6
Application of Parallel Aggregation-Based Multigrid to High Resolution Subsurface Flow Simulations

Meng-Huo Chen & Shuyu Sun

Int. J. Numer. Anal. Mod., 16 (2019), pp. 873-890.

Published online: 2019-08

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  • Abstract

In this paper we assess the parallel efficiency issues for simulating single phase subsurface flow in porous media, where the permeability tensor contains anisotropy rotated with certain angles or severe discontinuity. Space variables are discretized using multi-points flux approximations and the pressure equations are solved by aggregation-based algebraic multigrid method. The involved issues include the domain decomposition of space discretization and coarsening, smoothing, the coarsest grid solving of multigrid solving steps. Numerical experiments exhibit that the convergence of the multigrid algorithm suffers from the parallel implementation. The linear system at the coarsest grid is solved and by various iterative methods and the experimental results show that the parallel efficiency is less attenuated when sparse approximate inverse preconditioning conjugate gradient is used.

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XX

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COPYRIGHT: © Global Science Press

  • Email address

m.h.chen@leeds.ac.uk (Meng-Huo Chen)

shuyu.sun@kaust.edu.sa (Shuyu Sun)

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@Article{IJNAM-16-873, author = {Chen , Meng-Huo and Sun , Shuyu}, title = {Application of Parallel Aggregation-Based Multigrid to High Resolution Subsurface Flow Simulations}, journal = {International Journal of Numerical Analysis and Modeling}, year = {2019}, volume = {16}, number = {6}, pages = {873--890}, abstract = {

In this paper we assess the parallel efficiency issues for simulating single phase subsurface flow in porous media, where the permeability tensor contains anisotropy rotated with certain angles or severe discontinuity. Space variables are discretized using multi-points flux approximations and the pressure equations are solved by aggregation-based algebraic multigrid method. The involved issues include the domain decomposition of space discretization and coarsening, smoothing, the coarsest grid solving of multigrid solving steps. Numerical experiments exhibit that the convergence of the multigrid algorithm suffers from the parallel implementation. The linear system at the coarsest grid is solved and by various iterative methods and the experimental results show that the parallel efficiency is less attenuated when sparse approximate inverse preconditioning conjugate gradient is used.

}, issn = {2617-8710}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/ijnam/13258.html} }
TY - JOUR T1 - Application of Parallel Aggregation-Based Multigrid to High Resolution Subsurface Flow Simulations AU - Chen , Meng-Huo AU - Sun , Shuyu JO - International Journal of Numerical Analysis and Modeling VL - 6 SP - 873 EP - 890 PY - 2019 DA - 2019/08 SN - 16 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/ijnam/13258.html KW - Parallel computation, porous media flow, multi-points flux approximations, algebraic multigrid. AB -

In this paper we assess the parallel efficiency issues for simulating single phase subsurface flow in porous media, where the permeability tensor contains anisotropy rotated with certain angles or severe discontinuity. Space variables are discretized using multi-points flux approximations and the pressure equations are solved by aggregation-based algebraic multigrid method. The involved issues include the domain decomposition of space discretization and coarsening, smoothing, the coarsest grid solving of multigrid solving steps. Numerical experiments exhibit that the convergence of the multigrid algorithm suffers from the parallel implementation. The linear system at the coarsest grid is solved and by various iterative methods and the experimental results show that the parallel efficiency is less attenuated when sparse approximate inverse preconditioning conjugate gradient is used.

Chen , Meng-Huo and Sun , Shuyu. (2019). Application of Parallel Aggregation-Based Multigrid to High Resolution Subsurface Flow Simulations. International Journal of Numerical Analysis and Modeling. 16 (6). 873-890. doi:
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