Electrical submersible pumps selection methodology in terms of well parameters uncertainty

UDK: 622.276.53.054.23:621.67-83

DOI: 10.24887/0028-2448-2025-9-80-85

Key words: electrical submersible pump, parameter uncertainty, well intervention, productivity index, gas-oil ratio, gas blockage, Monte Carlo method, multiphase flow, natural gas separation, probabilistic modeling, artificial lift, energy efficiency

Authors: B.M. Latypov (Ufa State Petroleum Technological University, RF, Ufa); R.A. Khabibullin (Gazprom Neft Companу Group, RF, Saint Petersburg); O.S. Kobzar (Gazprom Neft Companу Group, RF, Saint Petersburg); V.E. Chernyshov (Association «Digital technologies in industry», RF, Saint Petersburg); M.D. Shabunin (Research and Education Center Gazprom Neft – UGNTU, RF, Ufa); A.V. Ryzhikov (Association «Digital technologies in industry», RF, Saint Petersburg)

This paper presents a probabilistic electrical submersible pump selection methodology for conditions of high parameter uncertainty following geological and technical operations. The primary challenge is significant variability in productivity index during the post-workover period, which critically affects pump operating regimes. Wells with high gas-oil ratios present particular complexity, where the pump's ability to handle gas-liquid mixtures becomes the dominant factor in operational reliability. The research methodology is based on Monte Carlo simulation combined with hydrodynamic modeling in Unifloc VBA, using Standing correlations for PVT properties, Ansari and Beggs-Brill models for multiphase flow calculations accounting for hydrodynamic and thermal effects, and Marquez correlation for natural gas separation at pump intake. A comprehensive efficiency criterion was developed that integrates pump efficiency, energy performance indicators, mean time between failures, and production shortfall risks through normalized coefficients. Testing of the methodology on a Western Siberian mature oilfield demonstrated that small standard deviations in reservoir pressure and productivity index lead to substantial scatter in predicted flow rates, significantly affecting pump sizing selection. It is shown that reducing uncertainty in input parameters through field measurements such as well testing, production logging, or reservoir sampling substantially impacts equipment selection results, emphasizing the necessity for accurate data collection during design and well monitoring phases.

References

1. Pashali A.A., Kolonskikh A.V., Khalfin R.S. et al., A digital twin of well as a tool of digitalization of bringing the well on to stable production in Bashneft PJSOC (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2021, no. 3, pp. 80–84, https://doi.org/10.24887/0028-2448-2021-3-80-84

2. Baymukhametov M.K., Gulishov D.S., Mikhaylov V.G. et al., Analysis of causes of gas-oil ratio growth at late stages of oil fields exploration (In Russ.), Izvestiya Tomskogo politekhnicheskogo universiteta. Inzhiniring georesursov = Bulletin of the Tomsk Polytechnic University. Geo Assets, 2018, V. 329, no. 8, pp. 104-111.

3. Yudin E., Lubnin A., Simulation of multilayer wells operating, SPE-149924-MS, 2011, DOI: https://doi.org/10.2118/149924-ms

4. Galkin V.I., Koltyrin A.N., Development of a method for forecasting technological indicators of a well operation after application of geological-technical measures

(In Russ.), Neftepromyslovoe delo, 2020, no. 7(619), pp. 18–28, DOI: https://doi.org/10.30713/0207-2351-2020-7(619)-18-28

5. Galkin V.I., Koltyrin A.N., Justification of the predicted value of oil flow rate increase after applying WST with the help of the statistical method (In Russ.), Izvestiya Tomskogo politekhnicheskogo universiteta. Inzhiniring georesursov = Bulletin of the Tomsk Polytechnic University. Geo Assets Engineering, 2023, V. 334, no. 2, pp. 81–86.

6. Altunin A.E., Semukhin M.V., Kuzyakov O.N., Tekhnologicheskie raschety pri upravlenii protsessami neftegazodobychi v usloviyakh neopredelennosti (Technological calculations in the management of oil and gas production in the face of uncertainty), Tyumen: Publ. of TIU, 2015, 187 p.

7. Hajinorouz M., Alavi S.E., A new approach based on VIKOR and Monte-Carlo algorithms for determining the most efficient enhanced oil recovery methods: EOR screening, Journal of Petroleum Exploration and Production Technology, 2024, V. 14, no. 2, pp. 623–643, DOI: https://doi.org/10.1007/s13202-023-01726-y

8. Yudin E.V., Piotrovskiy G.A., Kolyuk O.A., Operational features and methods for determining the optimal operation parameters in fractured reservoirs with a gas cap: Oil rims of Orenburg OGCF case study (In Russ.), PRONEFT’’. Professional’no o nefti, 2020, no. 3, pp. 26–32.

9. Yudin E.V., Habibullin R.A., Smirnov N.A. et al., New approaches to gaslift and ESP well stock production management (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2021, no. 6, pp. 67–73, DOI: https://doi.org/10.24887/0028-2448-2021-6-67-73

10. Krasnov V.A., Sudeev I.V., Yudin E.V. et al., Reservoir parameters evaluation using the production data analysis (In Russ.), Nauchno-tekhnicheskiy Vestnik OAO “NK “Rosneft’”, 2010, no. 1, pp. 30–34.

11. Andrianova A.M., Yudin E.V., Ganeev T.A. et al., Application of intelligent methods for analysis high-frequency production data for solving oil engineering challenges

(In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2021, no. 9, pp. 70–75, DOI: https://doi.org/10.24887/0028-2448-2021-9-70-75