Linear solvers for reservoir simulation applications are the objective of this review.
Specifically, we focus on techniques for Fully Implicit (FI) solution methods, in which the set …

The demand for accurate and efficient simulation of geomechanical effects is widely
increasing in the geoscience community. High resolution characterizations of the …

We propose a two-stage preconditioner for accelerating the iterative solution by a Krylov
subspace method of Biot's poroelasticity equations based on a displacement-pressure …

In this article, we introduce a methodology for improving the accuracy and efficiency of
reduced order models (ROMs) constructed using the least‐squares Petrov–Galerkin (LSPG) …

Recent advances in the field of machine learning open a new era in high performance
computing for challenging computational science and engineering applications. In this …

Nonlinearly preconditioned inexact Newton methods have been applied successfully for
some difficult nonlinear systems of algebraic equations arising from the discretization of …

The reduced order model (ROM) methods allow to significantly improve the computation
time and memory usage. Therefore these methods are very useful for real-time or many …

Computational fluid dynamics (CFD) simulations of viscous fluids described by the Navier-
Stokes equations are considered. Depending on the Reynolds number of the flow, the …

A preconditioning framework for the coupled problem of frictional contact mechanics and
fluid flow in the fracture network is presented. We focus on a blended finite element/finite …

We study fast and robust iterative solvers for large systems of linear equations resulting from
simulation of flow through strongly heterogeneous porous media. We propose the use of …