A novel approach for reservoir forecasting under uncertainty
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This paper presents a novel approach for developing statistical estimates of uncertainty in reservoir performance from only a limited number of multiphase flow simulations while using information from a full suite of geostatistical realizations. The proposed methodology involves ranking and weighting geostatistical models on the basis of a surrogate performance measure, and estimating the mean/variance of the desired performance measure via a weighted average of simulation results from a few selected realizations. The streamline time-of-flight based volumetric sweep efficiency is used as the surrogate performance measure to rank geostatistical models, and their weights are determined from a moment-matching algorithm which enables the approximation of a continuous distribution by a discrete distribution. A field example is used to demonstrate the applicability and computational efficiency of the proposed methodology.
SPE Reservoir Engineering (Society of Petroleum Engineers)
author list (cited authors)
Mishra, S., Choudhary, M. K., & Datta-Gupta, A.
complete list of authors
Mishra, S||Choudhary, MK||Datta-Gupta, A