Multilevel Spectral Coarsening for Graph Laplacian Problems with Application to Reservoir Simulation
Abstract
We extend previously developed two-level coarsening procedures for graph Laplacian problems written in a mixed saddle point form to the fully recursive multilevel case. The resulting hierarchy of discretizations gives rise to a hierarchy of upscaled models, in the sense that they provide approximation in the natural norms (in the mixed setting). This property enables us to utilize them in three applications: (i) as an accurate reduced model, (ii) as a tool in multilevel Monte Carlo simulations (in application to finite volume discretizations), and (iii) for providing a sequence of nonlinear operators in a full approximation scheme for solving nonlinear pressure equations discretized by the conservative two-point flux approximation. Finally, we illustrate the potential of the proposed multilevel technique in all three applications on a number of popular benchmark problems used in reservoir simulation.
- Authors:
-
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Portland State Univ., OR (United States)
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Portland State Univ., OR (United States)
- Publication Date:
- Research Org.:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1824746
- Report Number(s):
- LLNL-JRNL-795643
Journal ID: ISSN 1064-8275; 996879
- Grant/Contract Number:
- AC52-07NA27344
- Resource Type:
- Accepted Manuscript
- Journal Name:
- SIAM Journal on Scientific Computing
- Additional Journal Information:
- Journal Volume: 43; Journal Issue: 4; Journal ID: ISSN 1064-8275
- Publisher:
- Society for Industrial and Applied Mathematics (SIAM)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 58 GEOSCIENCES; 97 MATHEMATICS AND COMPUTING; graph Laplacian; algebraic multigrid; finite volume methods; numerical upscaling; multilevel Monte Carlo; full approximation scheme
Citation Formats
Barker, Andrew T., Gelever, Stephan V., Lee, Chak S., Osborn, Sarah V., and Vassilevski, Panayot S. Multilevel Spectral Coarsening for Graph Laplacian Problems with Application to Reservoir Simulation. United States: N. p., 2021.
Web. doi:10.1137/19m1296343.
Barker, Andrew T., Gelever, Stephan V., Lee, Chak S., Osborn, Sarah V., & Vassilevski, Panayot S. Multilevel Spectral Coarsening for Graph Laplacian Problems with Application to Reservoir Simulation. United States. https://doi.org/10.1137/19m1296343
Barker, Andrew T., Gelever, Stephan V., Lee, Chak S., Osborn, Sarah V., and Vassilevski, Panayot S. Wed .
"Multilevel Spectral Coarsening for Graph Laplacian Problems with Application to Reservoir Simulation". United States. https://doi.org/10.1137/19m1296343. https://www.osti.gov/servlets/purl/1824746.
@article{osti_1824746,
title = {Multilevel Spectral Coarsening for Graph Laplacian Problems with Application to Reservoir Simulation},
author = {Barker, Andrew T. and Gelever, Stephan V. and Lee, Chak S. and Osborn, Sarah V. and Vassilevski, Panayot S.},
abstractNote = {We extend previously developed two-level coarsening procedures for graph Laplacian problems written in a mixed saddle point form to the fully recursive multilevel case. The resulting hierarchy of discretizations gives rise to a hierarchy of upscaled models, in the sense that they provide approximation in the natural norms (in the mixed setting). This property enables us to utilize them in three applications: (i) as an accurate reduced model, (ii) as a tool in multilevel Monte Carlo simulations (in application to finite volume discretizations), and (iii) for providing a sequence of nonlinear operators in a full approximation scheme for solving nonlinear pressure equations discretized by the conservative two-point flux approximation. Finally, we illustrate the potential of the proposed multilevel technique in all three applications on a number of popular benchmark problems used in reservoir simulation.},
doi = {10.1137/19m1296343},
journal = {SIAM Journal on Scientific Computing},
number = 4,
volume = 43,
place = {United States},
year = {Wed Aug 04 00:00:00 EDT 2021},
month = {Wed Aug 04 00:00:00 EDT 2021}
}
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