A Multi-Core Numerical Framework for Characterizing Flow in Oil Reservoirs

Leonardi, Christopher, Holmes, David W., Williams, John R. and Tilke, Peter G. (2011). A Multi-Core Numerical Framework for Characterizing Flow in Oil Reservoirs. In: Layne T. Watson, Gary Howell, William I. Thacker and Steven Seidel, Proceedings of the 19th High Performance Computing Symposium. 19th High Performance Computing Symposium (HCP2011), Boston USA, (166-174). 4-7 april, 2011.

Author Leonardi, Christopher
Holmes, David W.
Williams, John R.
Tilke, Peter G.
Title of paper A Multi-Core Numerical Framework for Characterizing Flow in Oil Reservoirs
Conference name 19th High Performance Computing Symposium (HCP2011)
Conference location Boston USA
Conference dates 4-7 april, 2011
Proceedings title Proceedings of the 19th High Performance Computing Symposium
Series Simulation series, v. 43, no. 2.; 2011 Spring Simulation Multiconference books, bk. 6.
Place of Publication San Diego, CA United States
Publisher Society for Computer Simulation International
Publication Year 2011
Sub-type Fully published paper
Open Access Status
ISBN 9781617828409
1617828408
Editor Layne T. Watson
Gary Howell
William I. Thacker
Steven Seidel
Start page 166
End page 174
Total pages 9
Language eng
Formatted Abstract/Summary
This paper presents a numerical framework that enables scalable, parallel execution of engineering simulations on multi-core, shared memory architectures. Distribution of the simulations is done by selective hash-tabling of the model domain which spatially decomposes it into a number of orthogonal computational tasks. These tasks, the size of which is critical to optimal cache blocking and consequently performance, are then distributed for execution to multiple threads using the previously presented task management algorithm, H-Dispatch. Two numerical methods, smoothed particle hydrodynamics (SPH) and the lattice Boltzmann method (LBM), are discussed in the present work, although the framework is general enough to be used with any explicit time integration scheme. The implementation of both SPH and the LBM within the parallel framework is outlined, and the performance of each is presented in terms of speed-up and efficiency. On the 24-core server used in this research, near linear scalability was achieved for both numerical methods with utilization efficiencies up to 95%. To close, the framework is employed to simulate fluid flow in a porous rock specimen, which is of broad geophysical significance, particularly in enhanced oil recovery.
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Conference Paper
Collection: School of Mechanical & Mining Engineering Publications
 
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Created: Fri, 01 May 2015, 10:51:48 EST by Rose Clements on behalf of School of Mechanical and Mining Engineering