Abstract
Abstract Reservoir flow simulation involves subdivision of the physical domain into a number of gridblocks. This is best accomplished with optimized grid point density and minimized number of gridblocks especially for coarse grid generation from a fine grid geological model. In any coarse grid generation, proper distribution of grid points, which form basis of numerical gridblocks, is a challenging task. We show that this can be effectively achieved by generating a background grid that stores grid point spacing parameter. Spacing (L) can be described by Poisson's equation (∇2L = G) where the local density of grid points is controlled by a variable source term (G). This source term can be based on different grid point density indicators such as permeability variations, fluid velocity or their combination e.g. vorticity, where they can be extracted from reference fine grid. Once background grid is generated, advancing front triangulation and then Delaunay tessellation are invoked to form the final (coarse) gridblocks. This algorithm is quite flexible, allowing choice of the gridding indicator and thus providing the possibility of comparing the grids generated with different indicators and selecting the best. In this paper, the capabilities of approach in generation of unstructured coarse grids from fine geological models are illustrated using a highly heterogeneous test case. Flexibility of algorithm to gridding indicator is demonstrated using vorticity, permeability variation and velocity. Quality of the coarse grids is evaluated by comparing their two-phase flow simulation results to those of fine grid and uniform coarse grid. Results demonstrate the robustness and attractiveness of approach, as well as relative quality/performance of grids generated by using different indicators.
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