If the relevant reservoir parameters were known precisely, then one could simulate the enhanced oil recovery processes numerically on a computer to track the injected fluids; unfortunately, this is not true in practice. Hence the ability to identify these reservoir parameters from the pressure and/or saturation measurements at the sparsely located existing observation wells becomes necessary prior to the reservoir simulation. The identification can be achieved by extending the proven iterative numerical algorithm, the Generalized Pulse-Spectrum Technique (GPST).' In Phase I, GPST will be used to identify the unknown reservoir parameters from the pressure and/or saturation measurements at those sparsely located observation wells in a twodimensional and two-phase flow reservoir model and to track the injected fluid everywhere in the reservoir accurately. In Phase II, GPST will be further generalized and made super-efficient by taking advantage of parallelism, vectorization, adaptive grids, domain decomposition, etc., to identify the unknown reservoir parameters from the pressure and/or saturation measurements at those sparsely located observation wells in a three-dimensional and three-phase flow reservoir model and to track the injected fluids everywhere in the reservoir accurately.Anticipated Results/Potential Commercial Applications as described by the awardee:The success of this project would provide the scientists and engineers in the Federal government and the private energy industries a powerful tool to identify the global reservoir parameters from the pressure and/or saturation data at the observation wells, and to track the injected fluids accurately in reservoir models of enhanced oil recovery processes.
