In this paper we present the methodology to predict the value of the complex optimality criteria from the parameters of the oil field development system such as well spacing, the distortion factor, the type of well completion, the horizontal length of the end of switching time, etc. The method presented in this paper is based on the results of multivariate calculations in a hydrodynamic simulator and the use of correlation models of machine learning (ML).
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