Geostatistical methods for reservoir characterization aims at obtaining petrophysical models conditioned to different direct and indirect data. For example geophysical data, such as seismic and electromagnetic data, through geostatistical inversion algorithms, well log data using stochastic simulations and production data by geostatistical history matching processes. The objective of the proposed methodology of this study, is to generate numerical models of a reservoir petrophysical properties, conditioned to a production strategy obtained with a closed loop optimization technique. In a first step of the proposed methodology a best production strategy, L0, is obtained by closed loop optimization using Particle Swarm Optimization. In a second step, one intends characterizing the spatial dispersion of parameters Z(x), conditioned to L0, by using an iterative procedure based on stochastic simulations of Z(x). In this way one succeed to obtain a geological consistent solution of petrophysical properties Z(x), which are conditioned to the chosen production strategy L0, while optimizing the spatial patterns characteristics of Z(x) like connectivity of sand bodies.


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