LAUSR

Subsurface simulations are computationally intensive tasks and require a considerable amount of time to solve. To gain computational speed in simulating subsurface scenarios, this paper investigates the use of graphical processing units (GPUs). Accelerators such as GPUs have a different architecture compared to the conventional central processing units, which necessitates a distinct approach. Various techniques that are well suited to deal with GPUs and simulating subsurface phenomena are explored with an emphasis on groundwater flow problems. Finite volume method with implicit time steps to solve groundwater scenarios is discussed and the associated challenges are highlighted. Krylov solvers used in large-scale systems along with preconditioners to improve convergence are described in detail. An appropriate solver preconditioner pair that provides speedup is identified to solve groundwater flow scenarios. The role of matrix storage formats is examined in a GPU environment, and recommendations that could further improve performance are made. This paper concludes by presenting simulation results that test the ideas explored on different generations of NVIDIA GPUs and the speedup attained in them.