Abstract

Parallel computations have become standard practice for simulating the complicated multi-phase flow in a petroleum reservoir. Increasingly sophisticated numerical techniques have been developed in this context. During the chase of algorithmic superiority, however, there is a risk of forgetting the ultimate goal, namely, to efficiently simulate real-world reservoirs on realistic parallel hardware platforms. In this paper, we quantitatively analyse the negative performance impact caused by non-contributing computations that are associated with the “ghost computational cells” per subdomain, which is an insufficiently studied subject in parallel reservoir simulation. We also show how these non-contributing computations can be avoided by reordering the computational cells of each subdomain, such that the ghost cells are grouped together. Moreover, we propose a new graph-edge weighting scheme that can improve the mesh partitioning quality, aiming at a balance between handling the heterogeneity of geological properties and restricting the communication overhead. To put the study in a realistic setting, we enhance the open-source Flow simulator from the OPM framework, and provide comparisons with industrial-standard simulators for real-world reservoir models.

Highlights

  • Introduction and motivationComputer simulation is extensively used in the oil industry to predict and analyse the flow of fluids in petroleum reservoirs

  • The multi-phased flow in such porous media is mathematically described by a complicated system of partial differential equations (PDEs), only numerically solvable for realistic cases

  • 7 Conclusion In this paper, we have given a detailed description of the domain decomposition strategy used to parallelize the simulation of fluid flow in petroleum reservoirs

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Summary

Introduction

Introduction and motivationComputer simulation is extensively used in the oil industry to predict and analyse the flow of fluids in petroleum reservoirs. The action of a parallelized preconditioner M–1 is typically applying wp = A –p1up per sub-mesh, where A –p1 denotes an inexpensive numerical approximation of the inverse of Ap. One commonly used strategy for constructing A –p1 is to carry out an incomplete LU (ILU) factorization [6] of Ap. Similar to the case of parallel matrix-vector multiplication, the floating-point operations and memory traffic associated with the ghost-cell entries in wp and the ghost-cell rows in Ap are non-contributing.

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