Parallel Enriched Algebraic Multiscale Solver
A. Manea, Hadi Hajibeygi, Panayot S. Vassilevski, Hamdi A. Tchelepi · SPE Reservoir Simulation Conference · 2017
Abstract A Parallel Enriched Algebraic Multiscale Solver (PEAMS) for simulation of flow in heterogeneous formations with high contrasts is introduced. Built on the recently developed enrichment strategy for single processing algorithms, i.e., EAMS of Manea et al. (2016), the PEAMS describes an efficient parallel implementation procedure as to how to enrich a given multiscale formulation with additional local basis functions. These additional basis functions, constructed in parallel computational platform, aim to resolve large error components for a generic fine-scale system with no right-hand-side term. The design and computational overhead of the enrichment kernels in shared-memory parallel environments are discussed in detail. The robustness and scalability of PEAMS are then illustrated for highly heterogeneous and anisotropic 3D multi-milion-cell reservoir models. The presented results show that, by adding only a few locally- supported complementary basis functions, the convergence of the original multiscale method is significantly enhanced. This is achieved with incurring a marginal overhead in the complexity to the coarse-scale operator. Moreover, in shared-memory parallel environments, it is shown that both of the enrichment procedure and the resulting enriched solver are scalable. Therefore, PEAMS casts a promising framework for robust iterative multiscale formulations for real-field applications, where parallel processing architectures are essential.