Frans J T Floris Christian F M Bos

Abstract:  Making decisions in reservoir management requires a method for quantifying uncertainty. In reservoir volumetrics, expectation curves for quantifying reservoir properties such as gross rock volume, average porosity, are well accepted. Using Monte Carlo simulation, the uncertainty in average reservoir properties are propagated to uncertainty in hydrocarbons initially in place, and eventually to uncertainty in ultimate recovery. For dynamic reservoir modelling, in which production data are inverted back to reservoir properties through history matching, the use of expectation curves as a means of quantifying uncertainty is a field of current research. In this paper, we present a formal method for quantifying the reduction in uncertainty due to the conditioning of a reservoir model to dynamic production data. The method starts from a parameterisation of the reservoir model and prior guesses on the parameters in terms of probability density functions (pdf's). Through the Bayesian inversion f...