Reservoir History Matching by Bayesian Estimation

Abstract

The estimation of reservoir properties is inherently an underdetermined problem (one having a nonunique solution) because of the large number of unknown parameters relative to the available data. parameters relative to the available data. The common zonation approach to reducing the number of parameters introduces considerable modeling error by insisting that reservoir properties are uniform within each zone and by assigning the boundaries of these zones more or less arbitrarily. In this paper, Bayesian estimation theory is applied to history matching as an alternative to zonation. By using a priori statistical information on the unknown parameters, the problem becomes statistically better determined. Bayesian estimation and zonation are applied to the problem of porosity and permeability estimation in a one-dimensional, permeability estimation in a one-dimensional, one-phase reservoir.

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