Artificial intelligence hybrid methods application in the task of the heavy oilfields profitability increase

Authors: I.S. Korovin, M.G. Tkachenko, M.V. Khisamutdinov, A.I.Kalyaev (Scientific research institute of multiprocessor computing systems, RF, Taganrog)

Key words: heavy oil, primary cost reduction, data mining, artificial neural networks, genetic algorithms, methods of enhanced oil recovery (EOR), retrospective analysis

The article considers the problem of heavy oil production increasing by EOR methods. A new approach, based on the intelligent analysis of successful events historical data, is proposed. Based on database info analysis, the synthesis of a model, targeted to automated search of wells for EOR application, is worked out. The main data processing tool is a novel technology, based on neural network analysis techniques and evolutionary algorithms implementation. This approach allows to select EOR in fuzzy, hardly formalized oilfield conditions and reduces the dependence on the human factor.

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