This study addresses the problem of transferring uncertainty in the geological model through the flow simulation model (the comprehensive simulator – CS) up to the reservoir production forecasts. The uncertainty in the geological model is characterized by the differences between many equally probable reservoir descriptions that honor available data and that are generated by geostatistical stochastic simulation. The uncertainty in the production forecasts can be characterized by the variability or spread in the responses derived from the flow simulation, or more precisely by the probability distribution of response variables, such as cumulative oil production, oil recovery, breakthrough time, cumulative water-oil ratio, etc.

A new methodology to perform this transfer of uncertainty is summarized. Each reservoir description is first ranked using a fast simulator (FS) rather than the comprehensive flow simulator (CS). A few selected descriptions are then processed through the CS to generate an approximate probability distribution of the reservoir production response.

This new methodology is applied with a coarse grid as the FS model to a two-phase, three-dimensional field scale problem with five producing wells, 8×106 STm3 original oil in place, and a very large and active aquifer. The impact of uncertainty in absolute permeability and porosity on the field cumulative oil production is considered over 7.8 years of production. Good results are achieved with a 85% to 93% reduction in the computer time over the use of the CS alone. The favorable results achieved show that extension of the proposed approach to other types of problems is worthwhile.

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