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Optimization of the “mature” fields development in machine learning algorithms is one of the urgent problems nowadays. The task is set to extend the effective operation of wells, optimize production management at the late stage of field development. Based on the task set, the article provides an overview of possible solutions in waterflooding management problems. Production management technology is considered as an alternative to intensification of operation, which is associated with an increase in the produciton rate and involves finding solutions aimed at reducing the water cut of well production. The practical implementation of the “Neural technologies for production improvement” includes the following steps: evaluation, selection, predictive analytics. The result is a digital technological regime of wells that corresponds to the set goal and the solution of the optimization problem in artificial intelligence algorithms using the software and hardware complex “Atlas – Waterflood Management”.“Neural technologies for production improvement” have been successfully tested at the pilot project site of the productive formation of the Vatyeganskoe field. The article provides a thorough and detailed analysis of the work performed, describes the algorithms and calculation results of the proxy model using the example of the pilot area, as well as the integration of the “Atlas – Waterflood Management” and the organization of the workflow with the field professionals of the Territorial Production Enterprise Povkhneftegaz.

Purpose. To assess the effectiveness of the practical application of mathematical modelling methods of the operation principles of oil production management systems in a fuzzy environment and the main aspects of their application in oil production. Methodology. The basis of the methodological approach in this study is a combination of methods of quantitative and qualitative analysis of the basic principles of the development of mathematical models for managing oil production processes in a fuzzy environment. Findings. The authors investigated the available methods of mathematical modeling in order to select the optimal possibilities for creating mathematical models. A qualitative assessment of the effectiveness of the practical application of methods of mathematical modeling of the principles of operation of oil production management systems in a fuzzy environment was formulated. The main aspects of application of methods of mathematical modeling directly in the process of oil production were established. Originality. A fuzzy approach is proposed for solving the problem of multi-criteria optimization in the development of a field and oil production, in which the task is set and solved in a fuzzy environment without previously converting them to equivalent clear tasks. This ensures the correctness and efficiency of the solution by increasing the adequacy of the description of the problem in a fuzzy environment. Practical value. The results obtained and the conclusions formulated on their basis are of considerable practical importance for employees of research institutes of the oil industry responsible for the development of effective methods of mathematical modelling of oil production process control systems and for employees of oil companies whose professional duties include the introduction of the mentioned mathematical models in oil fields. [ABSTRACT FROM AUTHOR]