Parallel Computation for Complex Wells Modeling in Full-Field Reservoir Simulation

Abstract

Abstract This paper discusses the parallel implementation of complex wells modeling in a large-scale simulation. Due to intensive computational requirements of giant reservoirs with hundreds of these complex wells, parallel implementation is essential for practical simulation studies. In this work, a distributed memory approach using message passing interface (MPI) is employed for parallelization where each processor is responsible for the computation of one or more complex wells. For inter-processor communication, a non-blocking technique is utilized to increase the parallel efficiency. Parallel implementation is not the only challenge for large-scale simulation. For instance, full-field simulation with hundreds of complex wells increases the probability of a nonconvergence solution for at least one or more complex wells during reservoir simulation. Robust algorithms are needed to guarantee convergence and improve performance. Therefore, in this paper, we propose treating complex wells as a subsurface network where it can be represented using graph theory. In addition, simulation results for a full-field with hundreds of intelligent complex wells are included. This will show the importance of well coupling with rigorous treatment of downhole controls and devices on accurately modeling large-scale and complex reservoir.