The article presents and summarizes the results of the research of solving issue of mutual well influence identication and detecting areas of the uncompensated production based on the analysis of production and injection volumes. The possibility of the residual oil reserves localization on the example of the 3rd block of Berezovskaya area on Romashkino field, based on the obtained proxy models is the indirect result of the conducted research. The information about the neural network algorithms being used and identification of the parameters of differential mass balances system of equations for estimating conductance in the interwell intervals is included. The flowchart of the implemented method for calculating resistance based on the introduced notion of block potential and resistance between blocks is presented, advantages and disadvantages of each of the proposed methods are indicated. The notion of the potential of the Voronoi block partitioning of the well`s bottom hole coordinates was introduced by analogy with the physical process of redistributing electrostatic potential; the ratio value of extraction/injection to the pore volume of the block is used as the potential. The sum of the absolute potentials in neighboring blocks minimizing issue is solved using the cross-entropy optimization method to identify resistances in the interwell intervals. The resulting set of resistances between blocks allows to reflect the existing structure of the fluid movement through the reservoir during the study period. The maps of the resistance between the blocks by sections of Berezovskaya area has been constructed. As a result of the maps analysis it was found that the main residual reserves are concentrated along the change boundary of the identified resistance field, and uncompensated selections partially correlate with the residual reserves by blocks.
2. Denisov O.V. Razrabotka avtomatizirovannoi sistemy identifikacii yavlenii interferencii i vzaimovliyaniya skvazhin po dannym telemetrii na osnove neirosetevyh algoritmov [Development of an automated system for identifying interference phenomena and well influence using telemetry data based on neural network algorithms] / Denisov O.V, Zheltukhin V.S., Lazareva R.G. // Proceedings of the XVIII International Conference on Computational Mechanics and Modern Applied Software Systems. - Moscow: Publishing House of the MAI, 2013. - p. 189-191. (in Russian)
3. Pat. RUS No. 2571470. Class G06F 17/00. Method of neural network analysis of telemetry data from the well stock / Bespalov A.P., Akhmetzyanov R.R., Yekimtsov S.A., Denisov O.V.; declare 10/24/2013, publ. 04/20/2015. Bul №12. 4. Pat. RUS No. 2597229. Class G06F 17/30. Crosswell conduction identification system. / Bespalov A.P., Akhmetzyanov R.R., Yekimtsov S.A., Girfanov R.G., Denisov O.V., Zakiev B.F., Lazareva R.G., Kalmykova E.N., Kuzmina A.V; declare 09/12/2014, publ. 09/10/2016. Bul №25.
5. Nasybullin A.V. Issledovanie interferencii skvazhin s ispol'zovaniem metodov sravnitel'nogo analiza [Investigation of well interference using benchmarking methods] / Nasybullin A.V., Zakiev B.F., Denisov O.V., Girfanov R.G. // Oil industry. - 2015. - №5. - p. 84-87. (in Russian)
6. Denisov O.V. Razrabotka informacionno-analiticheskoi sistemy monitoringa i upravleniya ekspluatacionnym fondom skvazhin NGDU «Al'met'evneft'» [Development of an information and analytical system for monitoring and managing the operating well stock of the Almetyevneft] / O.V. Denisov, R.G. Girfanov, A.V. Kuzmina // Exposure of oil gas. - 2016 - №5 - p. 73-77. (in Russian)
7. Zakiev B.F. Primenenie statisticheskih metodov analiza operativnyh dannyh telemetrii dlya vyrabotki reshenii po upravleniyu zakachkoi [The use of statistical methods for analyzing the operative data of telemetry for the development of solutions for the management of injection] / Zakiev B.F., Denisov O.V. // Engineering practice. –2015. – 6-7 ’. - pp. 12-17. (in Russian)
8. Denisov O.V. Vyyavlenie zon nedokompensacii na osnove analiza ob"emov otborov i nagnetaniya po ekspluatacionnomu fondu skvazhin [Identification of undercompensation zones on the basis of analysis of volumes of withdrawals and injections in the operating well stock] / O.V. Denisov, R.G. Girfanov // Exposure of oil gas. - 2019. - №3 (70) - p. 34-36. (in Russian)
9. Benham T., Duan Q., Kroese D.P., Liquet B. (2017) CEoptim: Cross-Entropy R package for optimization. Journal of Statistical Software, 76 (8), 1-29.
10. Nasybullin A.V. Sozdanie i promyshlennoe vnedrenie metodov upravleniya razrabotkoĭ mestorozhdeniĭ na osnove metodov avtomatizirovannogo proektirovaniya [Development and commercialization of CAD-based reservoir management methods]. A.V. Nasybullin, F.M. Latifullin, D.A. Razzhivin, R.Z. Sattarov, R.R. Ahmetzyanov, A.S. Sultanov. Neftyanoye Khozyaistvo, No. 7, 2007.pp. 88-91. (in Russian)
Nasybullin A.V., Dr.Sc,, Professor, Head of the Department for Development and Operation of Oil and Gas Fields, Almetyevsk State Oil Institute, Almetyevsk, Republic of Tatarstan, Russian Federation E-mail: email@example.com