How to Improve the Scalability of an Industrial Parallel Reservoir Simulator

J.-M. Gratien, T. Guignon, J.-F. Magras, P. Quandalle, and O. Ricois (France)


Cluster, Reservoir Simulation, Solver, Parallel IO, scalability.


Reservoir Engineering industry is very interested in using ever growing dataset with more and more complex physics and detailed models. The key issue still remains running simulations in an acceptable CPU time. Regarding the trend in hardware technologies, the challenge is to improve the efficiency of reservoir simulation software on a large number of processors. New numerical difficulties and performance problems appear when the number of cells and the number of processors are growing. In this paper, we present different approaches to overcome these kinds of problems. We discuss technical choices such like advanced scalable linear solver algorithm, load balancing issue with different domain decomposition strategies, dynamic space criteria, mesh partitioner strategy and parallel solver performance management, flexible IO strategy from simple file system to more complex parallel file system or database. We have developed and benchmarked these different solutions on published reference large scale problems and actual case studies with several tens millions of cells. We analyse the results and discuss the efficiency of each solution to overcome the scalability difficulties and performance limitations due to load unbalance.

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