Patent ID: 8392164

Claim:
A method for evaluating underground reservoir production, wherein physical properties characterizing the reservoir and the production are selected, the properties being input parameters of a flow simulator implemented in a computer allowing simulation of reservoir responses and constructing an analytical model implemented in a computer allowing the reservoir responses to be predicted comprising: adjusting the analytical model with an iterative process including: a) defining, for each of the responses, a desired degree of accuracy, the degree of accuracy measuring a difference between the reservoir responses predicted by the analytical model and the reservoir responses simulated by the simulator; b) calculating a degree of accuracy of reservoir predictions of the approximate analytical model; c) continuing the iterative process when the calculated degree of accuracy is above the desired degree of accuracy to: d) construct a design of experiments to select simulations of the reservoir responses to be carried out for adjusting the analytical model; e) carry out the simulations selected by the experiments with the flow simulator implemented in a computer, and, for each response simulated by the simulator, adjust the analytical model using an approximation to adjust the reservoir responses predicted by the analytical model to the reservoir responses simulated by the simulator; f) repeat steps c)-e) until the desired degree of accuracy is reached; g) evaluate the production by analyzing the reservoir responses predicted by the analytical model; and h) stop the iterative process without performing steps d)-g) if the degree of accuracy is below the desired degree of accuracy, and wherein the reservoir responses predicted by the analytical model are analyzed by quantifying an influence of each input parameter on each response, with a global sensitivity analysis, and sensitivity indices are calculated using the analytical model and the input parameters comprise at least one stochastic field, the stochastic field is decomposed into components via a Karhunen-Loeve decomposition and the stochastic field components having an impact on the responses are selected using the global sensitivity analysis.