Vol. 337 No. 5 (2026)
DOI https://doi.org/10.18799/24131830/2026/5/5252
Optimization of gas-lift systems in gas-condensate wells using ejectors and numerical modeling
Relevance. The need to enhance the development efficiency of late-stage gas-condensate fields, where reservoir pressure decline leads to retrograde condensation and reduced well productivity. Addressing this challenge is crucial for extending the profitable operational life of assets and maximizing the recovery of valuable hydrocarbons. Aim. To conduct a comparative analysis and quantitatively evaluate the key performance indicators (condensate production rate, specific gas consumption) for three gas-lift operation scenarios in a gas-condensate well: 1) standard gas-lift with a non-optimal injection gas flow rate; 2) mode with an optimized gas flow rate; 3) a combined "gas-lift+ejector" system. Methods. Numerical modeling of multiphase flow in the "reservoir–well" system. Results and conclusions. The author has developed a comprehensive hydrodynamic model of a typical gas-condensate well, for which the optimal injection gas flow rate (35,000 m³/day) was determined, yielding a maximum condensate production rate (45 t/day). It was shown that operation at a non-optimal flow rate (50,000 m³/day) leads to a 9% decrease in production. With the integration of a two-phase jet pump (ejector) into the well completion, the condensate production rate increases to 52 t/day at the same optimal gas flow rate, which is 15% higher than in the standard optimized system. Additionally, a 22% reduction in the specific gas consumption was established. It was concluded that the ejector efficiency is due to the creation of additional drawdown on the reservoir. Thus, the high technological and economic feasibility of the integrated approach, combining injection mode optimization and the application of ejector technologies for production enhancement in depleted fields, was proven.
For citation: Zeynalov F.S. Optimization of gas-lift systems in gas-condensate wells using ejectors and numerical modeling. Bulletin of the Tomsk Polytechnic University. Geo Assets Engineering, 2026, vol. 337, no. 5, pp. 7–13. https://doi.org/10.18799/24131830/2026/5/5252
Keywords:
gas lift, gas-condensate field, numerical modeling, production optimization, jet pump, ejector, multiphase flow
References:
1. Minimah M., Ifeanyi S., Bright B. Prediction of condensate banking with relative permeability to oil-gas and saturation in a gas condensate reservoir. African Journal of Engineering and Environment Research, 2020, vol. 1, no. 2, pp. 2–18.
2. Fan L., Harris B.W., Jamaluddin A., Kamath J., Mott R., Pope G.A., Shandrygin A., Whitson C.H. Understanding gas-condensate reservoirs. Oilfield Review, 2005, vol. 17, no. 4, pp. 14–27.
3. Myhr E.L. Analysis and prediction of gas lift stability from field data. Modern Petroleum Production Engineering. Ed. by A.A. Harald. Trondheim, Stavanger Tech Press, 2017. pp. 27–68.
4. Mishchenko I.T. Oil well production. Moscow, Neft i gaz Publ., 2003. 816 p. (In Russ.)
5. Mukhametshin A.A., Mukhametshin V.V. Gas-lift wells. Design and optimization models. PROneft. Professionally about oil, 2017, vol. 2, no. 2, pp. 28–39. (In Russ.)
6. Aliyev F.A., Ilyasov M.Kh., Djamalbekov M.A. Modeling of gas-lift well operation. Doklady NANA, 2008, no. 4, pp. 107–116. (In Russ.)
7. Igemhokhai S., Bello K., Okeligho U., Ajayi A., Adejumo A. Machine learning for predicting and optimizing well rates in gas-lifted wells with web application integration. SPE Nigeria Annual International Conference and Exhibition, 2025. DOI: 10.2118/228708-MS.
8. Amao A. Mathematical model for Darcy–Forchheimer flow with applications to well performance analysis: master thesis. Austin, 2007. 154 p.
9. Gallyamov R.R. Development of models and algorithms for calculation and optimization of gas-lift wells operation considering non-linear effects. Cand. Diss. Abstract. Ufa, 2012. 24 p. (In Russ.)
10. Brusilovsky A.I. Phase transformations in the development of oil and gas fields. Moscow, Graal Publ., 2002. 575 p. (In Russ.)
11. Basniev K.S., Dmitriev N.M., Rosenberg G.D. Nonlinear effects in gas filtration in porous media. Neftegazovaya geologiya. Teoriya i praktika, 2012, vol. 7, no. 1, pp. 1–15. (In Russ.)
12. Yudin E., Khabibullin R. Modeling of a gas-lift well operation with an automated gas-lift gas supply control system. SPE Russian Petroleum Technology Conference, 2019. DOI: 10.2118/196816-MS.
13. Aliev F., Jamalbayov M. Theoretical basics of mathematical modeling of the gas lift process in the well-reservoir system. SPE Annual Caspian Technical Conference & Exhibition, 2015. DOI: 10.2118/176641-MS.
14. Al-Kadem M.S., Al-Mashhad A.S., Al-Dabbous M.S., Sultan A.S. Integrating Peng Robinson EOS with association term for better minimum miscibility pressure estimation. SPE Kingdom of Saudi Arabia Annual Technical Symposium and Exhibition, 2018. DOI: 10.2118/192327-MS
15. Nikolayev E.V., Kharlamov S.N. Research of multicomponent hydrocarbon systems separation in modes of functioning of oil preliminary preparation equipment. Bulletin of the Tomsk Polytechnic University. Geo Assets Engineering, 2016, vol. 327, no. 7, pp. 84–99. (In Russ.)
16. Voutsas E., Novak N., Thermodynamic modeling of natural gas and gas condensate mixtures. Natural Gas Processing from Midstream to Downstream. Eds. J.H. Williams, R.D. Clark. Hoboken, Wiley, 2018. Vol. 1, pp. 57–87. DOI: 10.1002/9781119269618.ch3.
17. Hashemi M., Monfaredi K., Sedaee B. An inclusive consistency check procedure for quality control methods of the black oil laboratory data. Journal of Petroleum Exploration and Production Technology, 2020, vol. 10, pp. 1759–1781. DOI: 10.1007/s13202-020-00869-6
18. Jansen J.D. Multiphase flow correlations. Nodal Analysis of Oil and Gas Production Systems. Ed. by J.D. Jansen. Society of Petroleum Engineers, 2017. pp. 53–70. DOI: 10.2118/9781613995648.
19. Ughulu E.O., Soremukun I.O., Farotimi T.A. A new modification to the Hagedorn – brown correlation for prediction of two-phase pressure gradient in horizontal wells. SPE Nigeria Annual International Conference and Exhibition, 2025. DOI: 10.2118/228663-MS.
20. Lin L. Evaluation of multiphase flow models in wellbores. Preprints, 2023, vol. 1, pp. 1–12. DOI: 10.20944/preprints202312.1807.v1
21. Abbasova S., Mammadova G. Selection of the operation mode of a gaslift wells group based on the theory of decision-making under risk conditions. RT&A, 2024, vol. 19, no. 6, pp. 374–380.
