Adaptive Coarsening in Physical Representation for the Robust Thermal-Compositional Simulation

Abstract The nonlinear nature of flow and transport in porous media requires a linearization of the governing numerical model equations. We propose a new linearization approach and apply it to complex thermal-compositional problems of practical interest. The approach approximates exact physics of a simulation problem, which is similar to an approximate representation of space and time discretization performed in conventional simulation. Maintaining control of the error in approximate physics, we perform an adaptive parametrization to improve the performance of the method and adaptive coarsening to identify the major nonlinearities in the physical description. The global under-relaxation based on inflection points detection in parameterized space of the state variables provides a highly robust strategy to obtain nonlinear solution. This strategy was applied to several challenging compositional problems. In all cases, the proposed strategy improves the robustness and efficiency of the nonlinear solution.