QUANTITATIVE FORECAST OF MAPS OF EFFECTIVE PARAMETERS OF OIL AND GAS PRODUCTIVITY USING SEISMIC DATA WITH THE HELP OF DEEP NEURAL NETWORKS
(Priezzhev I.I. Egorov S.V. Tschelkunov A.E. )
A new productivity parameters prediction has been developed based on nonlinear operator using combination of deep learning neural network, genetic algorithm, gradient learning method and Tikhonov regularization. Proposed technology and methodology compares to classic attribute analysis based on linear regression approach.......