TY - JOUR
T1 - Accelerating the solution of linear systems appearing in two-phase reservoir simulation by the use of POD-based deflation methods
AU - Diaz Cortes, Gabriela Berenice
AU - Vuik, Cornelis
AU - Jansen, Jan Dirk
PY - 2021
Y1 - 2021
N2 - We explore and develop a Proper Orthogonal Decomposition (POD)-based deflation method for the solution of ill-conditioned linear systems, appearing in simulations of two-phase flow through highly heterogeneous porous media. We accelerate the convergence of a Preconditioned Conjugate Gradient (PCG) method achieving speed-ups of factors up to five. The up-front extra computational cost of the proposed method depends on the number of deflation vectors. The POD-based deflation method is tested for a particular problem and linear solver; nevertheless, it can be applied to various transient problems, and combined with multiple solvers, e.g., Krylov subspace and multigrid methods.
AB - We explore and develop a Proper Orthogonal Decomposition (POD)-based deflation method for the solution of ill-conditioned linear systems, appearing in simulations of two-phase flow through highly heterogeneous porous media. We accelerate the convergence of a Preconditioned Conjugate Gradient (PCG) method achieving speed-ups of factors up to five. The up-front extra computational cost of the proposed method depends on the number of deflation vectors. The POD-based deflation method is tested for a particular problem and linear solver; nevertheless, it can be applied to various transient problems, and combined with multiple solvers, e.g., Krylov subspace and multigrid methods.
KW - Deflation
KW - Krylov Methods
KW - Porous media
KW - Two-phase reservoir simulation
UR - http://www.scopus.com/inward/record.url?scp=85107588266&partnerID=8YFLogxK
U2 - 10.1007/s10596-021-10041-6
DO - 10.1007/s10596-021-10041-6
M3 - Article
AN - SCOPUS:85107588266
SN - 1420-0597
VL - 25
SP - 1621
EP - 1645
JO - Computational Geosciences
JF - Computational Geosciences
IS - 5
ER -