K.F. Tagirova, A.G. Gimaztdinova

One of the problems of the oil industry over the years is to increase the amount of recoverable oil from the reservoir and the rate of development of oil field. For stimulation of oil recovery by selecting the appropriate sound properties of the reservoir GTO it was proposed to use neural networks as an alternative to traditional methods: the above figures will be input into the neural network, and the output will be appropriate for a specific group of objects of geological and technical measures to ensure enhanced oil recovery. During the works the results of geological and engineering operations in the oil fields of Western Siberia were cataloged and processed. Objects of field development of Western Siberia are grouped with a wide range of geological and physical properties of rocks and physical-chemical properties of reservoir fluids based on principal component analysis. Geological features of each of the groups of objects were determined allowing to find ways for enhanced oil recovery on the basis of existing criteria applicability of its increase. Neural network for determining the optimal process parameters of geological and technical measures to intensify oil production was made and trained.