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

Journal article, 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.