Enhanced decoupling and CPR-FSAI preconditioner for fully implicit reservoir simulations in OPM

Artikel i vetenskaplig tidskrift, 2026

Efficient and scalable linear solvers are critical for implicit reservoir simulation, where the linear solver can account for up to 90% of total runtime. In this work, we present an algorithmic framework that replaces the inherently sequential ILU stage of the popular CPR preconditioner with a highly parallel FSAI preconditioner enhanced by an augmented decoupling mechanism. To improve FSAI in the presence of strong transport-induced couplings, a local block-diagonal decoupling is applied on small cell-blocks. The resulting fully local decoupling approach combines quasi-IMPES scaling to reduce pressure-saturation couplings, a dynamic row summation to ensure solvability by AMG, and constrained pressure decoupling to improve FSAI preconditioning effect. This yields a highly effective and scalable CPR preconditioning framework. We implemented the preconditioned solver suite in C++/MPI and evaluated it with the OPM simulator on Norne, SPE11C, and Sleipner benchmarks. The resulting framework, deco, matches or improves upon default OPM solvers (DUNE and AMGCL) in a sequential setting (1 MPI rank) and delivers 2–4× speedups in strong-scaling tests with up to 2048 MPI ranks on a single domain.