Productivity Parameters Prediction on Maps Using Neural Networks

Abstract

SUMMARYThe presentation shows the technique and examples for predicting the oil and gas productivity parameters on the map on the basis of a deep neural network with hybrid training and Tikhonov regularization. The results of predicting the effective thickness in continental facies of Western Siberia are shown. The results of comparison between prediction maps obtained by the neural network technique and multidimensional regression are also shown. The advantages of a neural network are efficiency, higher resolution and better correlation coefficient with well data.