Vol. 337 No. 10 (2026)
DOI https://doi.org/10.18799/24131830/2026/10/5359
Optimization of low-permeability oil and gas condensate field development based on the analysis of streamlines and the Lorenz coefficient
Relevance. The oil and gas condensate field under consideration has a complex geological structure, highly heterogeneous reservoirs, and lithological complications, which pose significant challenges to efficient hydrocarbon recovery. Methods based on hydrodynamic modeling and flow analysis enable a detailed study of seepage flow distribution, identifying stagnation zones, and determining optimal development regimes. The relevance of this study lies in improving the efficiency of oil field development by optimizing well placement and selecting a displacement fluid injection regime. This will ensure more effective production management and maximize the potential of geological reservoirs, which is especially important for complex, heterogeneous formations. Aim. To substantiate the application of a method for optimizing field development based on the analysis of fluid flows in the reservoir using hydrodynamic modeling and the Lorenz coefficient for assessing heterogeneity. Object. Low-permeability deposit of an oil and gas condensate field. Methods. Mathematical optimization methods for well placement and fluid flow modeling, as well as fluid flow diagnostics. Flow diagnostics not only identifies weaknesses in the current development system but also proposes specific optimization solutions to address them. The combination of these methods is appropriate for the goals and objectives, object, and subject of this study. Results. This study modeled various reservoir types, ranging from homogeneous to complex heterogeneous systems with lithological complications and imperfect penetration. Using streamline tracing and the Pollock method, key flow redistribution zones, stagnation zones, and early breakthrough paths for the injected agent were identified. Modeling confirmed that reservoir heterogeneities significantly impact fluid flow, reducing displacement efficiency and increasing residual oil. Well placement optimization using the Lorenz coefficient and flow diagnostics methods demonstrated the potential for significantly improving reservoir sweep uniformity and increasing oil recovery. An iterative approach enabled us to find optimal well locations that minimize the impact of heterogeneities and filtration barriers. The proposed approaches and tools can be used for further planning and implementation of enhanced oil recovery methods, such as hydraulic fracturing or polymer flooding.
For citation: Zharikova N.Kh., Savenok O.V., Vykhristyuk M.S., Khayrullin A.A. Optimization of low-permeability oil and gas condensate field development based on the analysis of streamlines and the Lorenz coefficient. Bulletin of the Tomsk Polytechnic University. Geo Assets Engineering, 2026, vol. 337, no. 10, pp. 242–260. http://doi.org/10.18799/24131830/2026/10/5359
Keywords:
mathematical optimization methods, fluid flow diagnostic methods, well placement and fluid flow modeling, Lorenz coefficient and sweep efficiency, digital geological model, three-dimensional streamline tracing, well placement optimization method to improve Lorenz coefficient and reservoir sweep efficiency
References:
1. Fateev D.G. Evaluation of the compliance of a compositional hydrodynamic model based on the analysis of technological parameters of the gas treatment system. Problems of the development of the gas industry in Siberia. Abstracts of the XVI scientific-practical conference of young scientists and specialists of TyumenNIIgiprogaz. Tyumen, TyumenNIIgiprogaz LLC Publ., 2010. pp. 142–143. (In Russ.)
2. Sinitsa N.V., Prishchepa O.M. Methodological approaches to assessing the oil and gas potential of pre-Jurassic deposits in the south of Western Siberia. Mining Journal, 2024, no. 9, pp. 20–26. (In Russ.) DOI: 10.17580/gzh.2024.09.03.
3. Lake L.W., Jensen J.L. A review of heterogeneity measures used in reservoir characterization. In Situ, 1991, vol. 15, no. 4, pp. 409–439.
4. Iktisanov V.A. Description of steady-state fluid inflow to wells of various configurations and partial penetration. Journal of Mining Institute, 2020, vol. 243, pp. 305–312. (In Russ.)
5. Lyalin V.E., Sidelnikov K.A. Concepts of mathematical modeling of reservoir systems based on the method of streamlines. Online edition "Oil and Gas Business", 2005, no. 2. (In Russ.) Available at: http://ogbus.ru/files/ogbus/authors/Lyalin/Lyalin_1.pdf (accessed 02.11.2025).
6. Sidelnikov K.A., Lyalin V.E., Grigoriev I.M. Modeling based on the methods of tubes and streamlines. Bulletin of Udmurt University. Series Biology. Earth Sciences, 2012, no. 2, pp. 109–119. (In Russ.)
7. Denisov S.V., Sidelnikov K.A. Modeling by the streamline method of two-phase filtration in porous media of varying heterogeneity taking into account the influence of capillary number. Proceedings of the International Symposium "Reliability and Quality". Penza: Penza State University Publ., 2008. Vol. 1, pp. 355–362. (In Russ.)
8. Lyalin V.E., Sannikov V.A. Hydrodynamic modeling of heterogeneous areal reservoir formations with multiple wells based on the streamline method. Actual Problems of Humanities and Natural Sciences, 2011, no. 3, pp. 427–433. (In Russ.)
9. Sidelnikov K.A. Application of the streamline method for hydrodynamic modeling of areal reservoir systems. Information technologies in science, sociology, economics and business. Materials of the XXXIII International conference and discussion scientific club. Yalta, October 5–15, 2006. pp. 190–192. (In Russ.)
10. Sidelnikov K.A. Features of using the mixed method of streamlines and finite volumes for semi-analytical solution of areal problems. Information technologies in science, sociology, economics and business. Materials of the XXXIII International conference and discussion scientific club. Yalta, October 5–15, 2006. pp. 192–194. (In Russ.)
11. Nikitin V.I. Analysis of the solution to the problem of finding the velocity distribution during laminar motion of a non-linearly viscous flushing fluid in the annular space of a well. Journal of Mining Institute, 2022, vol. 258, pp. 964–975. (In Russ.) DOI: 10.31897/PMI.2022.93.
12. Batty C., Batty M. A study of the Lorenz coefficient as a measure of heterogeneity in petroleum reservoirs. Journal of Petroleum Science and Engineering, 2007, vol. 59, Iss. 3–4, pp. 213–223.
13. Sukhomlinov V.S., Mustafaev A.S., Strakhova A.A., Timofeev N.A. Destruction of a stationary vortex in an elastic medium due to external energy impact. Journal of Technical Physics, 2020, vol. 90, no. 4, pp. 574–580. (In Russ.) DOI: 10.21883/JTF.2020.04.49079.249-18.
14. Datta-Gupta A., King M.J. Streamline simulation: theory and practice. Richardson, TX, Society of Petroleum Engineers, 2007. 345 p.
15. Awotunde A.A. On the joint optimization of well placement and control. SPE Kingdom of Saudi Arabia Annual Technical Symposium and Exhibition, 2014. Paper Number SPE-172206-MS. DOI: 10.2118/172206-MS.
16. Bellout M.C., Ciaurri D.E., Durlofsky L.J., Foss B., Kleppe J. Joint optimization of oil well placement and controls. Computational Geosciences, 2012, vol. 16, Iss. 4, pp. 1061–1079. DOI: 10.1007/s10596-012-9303-5.
17. Humphries T.D., Haynes R.D., James L.A. Simultaneous and sequential approaches to joint optimization of well placement and control. Computational Geosciences, 2013, vol. 18, Iss. 3-4, pp. 433–448. DOI: 10.1007/s10596-013-9375-x.
18. Gospodarikov A.P., Zatsepin M.A. Mathematical modeling of nonlinear boundary problems of geomechanics. Journal of Mining Institute, 2019, no. 12, pp. 16–20. (In Russ.) DOI: 10.17580/gzh.2019.12.03.
19. Møyner O., Krogstad S., Lie K.-A. The application of flow diagnostics for reservoir management. SPE Journal, 2014, vol. 20, Iss. 02, pp. 306–323. Paper Number: SPE-171557-PA. DOI: 10.2118/171557-PA.
20. Pal M., Lamine S., Lie K.-A., Krogstad S. Validation of the multiscale mixed finite-element method. International Journal for Numerical Methods in Fluids, 2015, vol. 77, Iss. 4, pp. 206–223. DOI: 10.1002/fld.3978.
21. Shah S., Møyner O., Tene M., Lie K.-A., Hajibeygi H. The multiscale restriction smoothed basis method for fractured porous media. Journal of Computational Physics, 2016, vol. 318, pp. 36–57. DOI: 10.1016/j.jcp.2016.05.001.
22. Burenina I.V., Avdeeva L.A., Khalikova M.A., Gerasimova M.V., Solovyova I.A. Improvement of the methodological approach to planning hydraulic fracturing operations at oil fields. Journal of Mining Institute, 2019, vol. 237, pp. 344–353. (In Russ.) DOI: 10.31897/PMI.2019.3.344.
23. Savenok O.V., Chuikova E.P., Agaguena A. Justification of waterless hydraulic fracturing methods. International Journal of Engineering, Transactions A: Basics, 2025, vol. 38, Iss. 7, pp. 1462–1475. DOI: 10.5829/ije.2025.38.07a.03.
24. Korolev M.I., Nanishvili O.A., Yusupov I.M. Substantiation of the optimal design of hydraulic fracturing in complex reservoirs. Bulletin of Science and Practice, 2023, vol. 9, no. 8, pp. 126–133. (In Russ.) DOI: 10.33619/2414-2948/93/13.
25. Kuzmenkov S.G., Korolev M.I., Novikov M.V. [et al.] Efficiency of application of enhanced oil recovery methods and intensification of oil production at the fields of the Khanty-Mansi Autonomous Okrug – Yugra. Georesources, 2023, vol. 25, no. 3, pp. 129–139. (In Russ.) DOI: 10.18599/grs.2023.3.16.
26. Podoprigora D.G., Byazrov R.R., Lagutina M.A., Arabov D.V., Galimov V.V., Ermolin D.S. A novel integrated methodology for screening, assessment and ranking of promising oilfields for polymer floods. Advances in Geo-Energy Research, 2024, vol. 12, Iss. 1, pp. 8–21. DOI: 10.46690/ager.2024.04.02.
27. Podoprigora D.G., Rogachev M.K., Byazrov R.R. Surfactant-polymer formulation for chemical flooding in oil reservoirs. Energies, 2025, vol. 18, Iss. 7, p. 1814. DOI: 10.3390/en18071814.
28. Raupov I.R., Rogachev M.K., Sytnik Ju.A. Overview of modern methods and technologies for the well production of high- and extra-high-viscous oil. Energies, 2025, vol. 18, iss. 6, p. 1498. DOI: 10.3390/en18061498.
29. Zhukov V.S., Kuzmin Yu.O. Experimental evaluation of the compressibility coefficients of fractures and intergranular pores of an oil and gas reservoir. Journal of Mining Institute, 2021, vol. 251, pp. 658–666. (In Russ.) DOI: 10.31897/PMI.2021.5.5.
30. Islamov Sh.R., Sagirova L.R., Bokov I.I., Shelukhova G.V. Application of cross-validation when choosing a variogram for modeling the porosity cube of a geological 3D model. Oil and Gas Territory, 2023, no. 11–12, pp. 14–23. (In Russ.)
31. Pollock D.W. Semianalytical computation of path lines for finite-difference models. Ground Water, 1988, vol. 26, no. 6, pp. 743–750.
32. Thiele M.R., Batycky R.P., Blunt M.J. A streamline-based 3D field-scale compositional reservoir simulator. SPE Annual Technical Conference and Exhibition. Denver, Colorado, 1996. SPE-38889-MS.
33. Forouzanfar F., Reynolds A.C. Joint optimization of number of wells, well locations and controls using a gradient-based algorithm. Chemical Engineering Research and Design, 2014, vol. 92, Iss. 7, pp. 1315–1328.
34. Sahni A., Horne R.N. Multivariate optimization of production strategies. SPE Journal, 2005, vol. 10, Iss. 01, pp. 91–101.
35. Emerick A.A. Well placement optimization using a genetic algorithm with nonlinear constraints. SPE Reservoir Simulation Symposium. The Woodlands, Texas, USA, 2009. SPE-118808-MS.
36. Alhuthali A.H., Datta-Gupta A., Yuen B. Optimizing smart well controls under geologic uncertainty. SPE Europec/EAGE Annual Conference and Exhibition. London, United Kingdom, 2007. SPE-107095-MS.
