Abstract
We develop a computationally efficient and accurate adaptive simulation model that is specifically designed for non-isothermal and compositional recovery methods, including steam injection, in-situ combustion and miscible gas injection. The adaptivity is designed to accurately resolve fronts that typically form in the reservoir during such processes. Owing to steep gradients in the solution as well as the strong nonlinearities due to thermal and compositional effects, accurate adaptive modeling is challenging. It is difficult to achieve without appropriate high-order discretization and strong grid refinement. Our framework is based on a Cartesian Cell-based Anisotropic Refinement (CCAR) strategy. CCAR offers aggressive grid adaptation, which allows quick transition to the very fine local grids necessary to resolve solution fronts and the fine local grids desirable to resolve reservoir heterogeneity. We have formulated a higher order pressure solver on the CCAR grids. The discretization uses a compact stencil, which together with an effective storage scheme leads to computational efficiency.
We apply the framework in this paper to a black-oil steam formulation. Although simplified, the simulation demonstrates the main features of our adaptive strategy.