On The Acceleration Of Ill-Conditioned Linear Systems

A Pod-Based Deflation Method For The Simulation Of Two-Phase Flow

Conference Paper (2018)
Author(s)

Gabriela Diaz Cortes (TU Delft - Numerical Analysis)

J.D. Jansen (TU Delft - Geoscience and Engineering, TU Delft - Civil Engineering & Geosciences)

Kees Vuik (TU Delft - Numerical Analysis)

Research Group
Numerical Analysis
Copyright
© 2018 G.B. Diaz Cortes, J.D. Jansen, Cornelis Vuik
DOI related publication
https://doi.org/10.3997/2214-4609.201802122
More Info
expand_more
Publication Year
2018
Language
English
Copyright
© 2018 G.B. Diaz Cortes, J.D. Jansen, Cornelis Vuik
Related content
Research Group
Numerical Analysis
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Pages (from-to)
1-22
ISBN (print)
9789462822603
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

We explore and develop POD-based deflation methods to accelerate the solution of large-scale linear systems resulting from two-phase flow simulation. The techniques here presented collect information from the system in a POD basis, which is later used in a deflation scheme. The snapshots required to obtain the POD basis are captured in two ways: a moving window approach, where the most recently computed solutions are used, and a training phase approach, where a full pre-simulation is run. We test this methodology in highly heterogeneous porous media: a full SPE 10 model containing O(10^6) cells, and in an academic layered problem presenting a contrast in permeability layers up to 10^6. Among the experiments, we study cases including gravity and capillary pressure terms. With the POD-based deflated procedure, we accelerate the convergence of a Preconditioned Conjugate Gradient (PCG) method, reducing the required number of iterations to around 10-30 %, i.e., we achieve speed-ups of factors three to ten.

Files

Mo_A2_02.pdf
(pdf | 2.53 Mb)
- Embargo expired in 03-03-2019
License info not available