This paper presents a novel approach for developing statistical estimates of uncertainty in reservoir performance from a limited number of simulations. The methodology involves ranking and weighting the full suite of geostatistical models on the basis of a surrogate performance measure, then estimating the mean/variance of the desired performance measure by using 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.

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