Algebraic Multigrid Preconditioning for Adaptive-Implicit Black-Oil Simulation
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First, the research introduces the Algebraic multigrid (AMG), the effect of grid hierarchy and its advantages such as faster reduction of low frequency errors. The AMG preconditioners are developed for a black-oil simulation. Numerical experiments for serial and parallel simulations show that preconditioning is required for the speedup of data sets, and ILU iterations using SAMG can be reduced. Row-scaling provides the best speedup using AMG; Dynamic Rowsum (DRS) is the most robust preconditioner currently; AMG still has difficulties with some data sets possibly due to non-parabolic nature of PDE’s, and matrix checking and well scaling is our planned work to attempt to address these issues.