Development of A Scalable Platform for Large-scale Reservoir Simulations on Parallel computers

TL;DR

This paper introduces a scalable parallel platform for large-scale reservoir simulations on distributed-memory systems, supporting various solvers and demonstrating excellent scalability on massive models.

Contribution

The paper presents a comprehensive, scalable parallel platform with detailed components and data structures for reservoir simulations on distributed-memory systems, including integration with advanced solvers.

Findings

Platform demonstrates excellent scalability on models with hundreds of millions of grid cells.

Supports various Krylov subspace solvers and integrates with HYPRE's BoomerAMG.

Enables simulation of giant reservoir models using thousands of CPU cores.

Abstract

This paper presents our work on designing a parallel platform for large-scale reservoir simulations. Detailed components, such as grid and linear solver, and data structures are introduced, which can serve as a guide to parallel reservoir simulations and other parallel applications. The main objective of platform is to support implementation of various parallel reservoir simulators on distributed-memory parallel systems, where MPI (Message Passing Interface) is employed for communications among computation nodes. It provides structured grid due to its simplicity and cell-centered data is applied for each cell. The platform has a distributed matrix and vector module and a map module. The matrix and vector module is the base of our parallel linear systems. The map connects grid and linear system modules, which defines various mappings between grid and linear systems. Commonly-used Krylov subspace linear solvers are implemented, including the restarted GMRES method and the BiCGSTAB method. It also has an interface to a parallel algebraic multigrid solver, BoomerAMG from HYPRE. Parallel general-purpose preconditioners and special preconditioners for reservoir simulations are also developed. Various data structures are designed, such as grid, cell, data, linear solver and preconditioner, and some key default parameters are presented in this paper. The numerical experiments show that our platform has excellent scalability and it can simulate giant reservoir models with hundreds of millions of grid cells using thousands of CPU cores.