9:15 AM-10:00 AM
Chair: James G. Glimm, State University of New York, Stony Brook
Rio Grande Ballroom
Risk management and risk reduction are increasingly important in the recovery of oil. A challenging component of the risk assessment problem is to estimate uncertainties in oil production resulting from uncertainties in geological models. An approach to performing these estimates on the basis of fine scale simulations in highly detailed geologies leads to prohibitively expensive computations, and there is a compelling need for rapid and accurate simulation methods based on fluid flow grids coarser than those used in describing the geology. This is the scale-up problem. The present state of the art is to run a few sensitivity studies (alternate geology models) using fine scale reservoir descriptions which have been "scaled-up" to fit into reservoir simulators. In this presentation, the speaker will address new scale-up results obtained with an approach that combines three strategies: (i) a computational renormalization group (RNG) technique for the scale-up of multiphase flow, (ii) scale-up of absolute permeabilities using an (extended) homogenization method, and (iii) a (limited) implementation of adaptive mesh refinement. The speaker will also discuss more fundamental computations aimed at assessing the validity of RNG methods for porous media flow.
David H. Sharp
Los Alamos National Laboratory
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