Sequential Local Mesh Refinement Solver with Separate Temporal and Spatial Adaptivity for Non-linear Two-phase Flow Problems
Convergence failure and slow convergence rates are among the biggest challenges with solving the system of non-linear equations numerically. Although mitigated, such issues still linger when using strictly small time steps and unconditionally stable fully implicit schemes. The price that comes with restricting time steps to small scales is the enormous computational load, especially in large-scale models. To address this problem, we introduce a sequential local mesh refinement framework to optimize convergence rate and prevent convergence failure, while not restricting the whole system to small time steps, thus improving computational efficiency. We test the algorithm with the non-linear two-phase flow model. Starting by solving the problem on the coarsest space-time mesh, the algorithm refines the domain in time at water saturation front to prevent convergence failure. It then deploys fine spatial grid in regions with large saturation variation to assure solution accuracy. After each refinement, the solution from the previous mesh is used to estimate the initial guess of unknowns on the current mesh for faster convergence. Numerical results are presented to confirm accuracy of our algorithm as compared to the uniformly fine time step and fine spatial discretization solution. We observe approximately 25 times speedup in the solution time by using our algorithm.