Decisions for field development of oil and gas reservoirs are often based on uncertainties assessment on forecast productions and other variables which are highly impacted by the uncertainties on the reservoir characteristics. Using geostatistical models, it would require thousands of flow simulations of several hours each to consider the geological uncertainties. Each of these simulations would require several hours even with current high power computers. To bypass this restriction due to the computation time, one approach consists to replace the simulator by an approximation of it, also called proxy. This paper focuses on the use of Artificial Neural Networks (ANN) proposing an innovative method to build an optimal ANN.

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