Towards Building Scalable Grid Computing Environments for Reservoir Simulation

Abstract

Standard high performance clusters (HPC) are being extensively used for solving computationally intensive problems in various scientific fields, one of which is the field of reservoir simulation. In our work, we expand the conventional HPC systems to run larger reservoir simulations on a heterogeneous grid of HPCs. This expansion is accomplished by developing a unique domain decomposition technique to achieve higher load balancing and computational efficiency on the grid. The decomposer works as an adaptive detector of the available hardware resources on the grid, learns about the different processor speeds and adjusts its load distribution among the CPUs. As a result, our grid implementation for reservoir simulation outperforms the conventional methods of domain decomposition, which are designed to run on homogenous set of processors in a cluster.