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Parallelization of a commercial streamline simulator and performance on practical models

 
: Batycky, R.P.; Förster, M.; Thiele, M.R.; Stüben, K.

Society of Petroleum Engineers -SPE-, Richardson/Tex.:
SPE Reservoir Simulation Symposium Proceedings. Vol.1
Red Hook: Curran, 2009
ISBN: 978-1-605-60777-1
S.36-45
SPE Reservoir Simulation Symposium <2009, The Woodlands>
Englisch
Konferenzbeitrag
Fraunhofer SCAI ()

Abstract
We present the extension of a serial execution commercial streamline simulator to mulit-core architectures based on the OpenMP programming model and its performance on various field examples. This work is an extension of recent work by Gerritsen et al. (2008) in which a research streamline simulator was extended for parallel execution due to its intrinsically parallel algorithm. We identified that the streamline-transport step represents the bulk of the run time (65%-85%). It is exactly this step that is straightforward to parallelize owing to the independent solution of each streamline that is at the heart of streamline simulation. Because we are working with an existing large serial code base, we used specialty software to quickly and easily identify variables that required special handling for implementing the parallel extension. Minimal rewrite to existing code was required to extend the streamline-transport step to OpenMP. As part of this work we also parallelized an additional 2% of the runtime code which included the gravity-line solver and some simple routines required for constructing the pressure matrix. We tested our parallel simulator on a variety of models including SPE 10, a Forties UK oil/water model, a Judy Creek waterflood/WAG model, and a Middle East dual-porosity model. We noted speedup factors of between 2.5x to 3.5x for 8-threads. In terms of real time, this implies that large-scale streamline simulation models as tested here can be simulated in less than 4 hrs. We noted speedup scaling results that were reasonable when compared with Amdahl's ideal scaling law. Beyond 8-threads we did observe reduced speedups and attribute this to memory bandwidth limits on our test machine (AMD 8x Opteron 8218 2.6Ghz dual core).

: http://publica.fraunhofer.de/dokumente/N-173375.html