Vol. 337 No. 4 (2026)
DOI https://doi.org/10.18799/24131830/2026/4/5144
Analysis of the phase state of gas condensate fields in the presence of mineralized water
Relevance. Effective development of gas condensate fields is associated with retrograde processes and requires modeling the phase state of the reservoir hydrocarbon system. Currently, there is an algorithm for such calculation that considers water mineralization and finding all the roots of the material balance equation, but it has not been verified for correctness using field data. In addition, the analysis of the effect of the methods of combining into pseudo-components on the simulation result was not carried out. The error of the results in such a combination occurs due to the use of correlation dependencies of critical parameters. Aim. To analyse the effect of various methods of combining into pseudo-components on the results of calculating the phase state of a hydrocarbon system. Methods. A modified algorithm for calculating the phase state is used. It contains the definition of Sturm polynomials and the Euclidean method for sequentially dividing polynomials, the Sechenov coefficients to account for water mineralization. The pseudo-component parameters are calculated based on empirical correlations. The object of the study is the composition of the hydrocarbon system from the Sleipner Øst Ty Field. Results and conclusion. It was shown that pseudo-components should be isolated based on considerations of the predominant presence of hydrocarbon components in one aggregate state. The authors calculated the liquid phase molar fraction dependence on reservoir pressure. It was determined that the results of calculations of this parameter correspond to field data within 15% in the pressure range up to 80 atm. At high pressures, the relative error of deviation of calculated data from field data increases to 30%. This deviation is due to the inaccuracy of the description of the fluid behavior by the equation of state. It is shown that a small number of combined components more accurately describes the phase behavior of a multicomponent system.
For citation: Abdrazakova L.T., Gilmanov A.Ya., Shevelev A.P. Analysis of the phase state of gas condensate fields in the presence of mineralized water. Bulletin of the Tomsk Polytechnic University. Geo Assets Engineering, 2026, vol. 337, no. 4, pp. 26-33.
Keywords:
gas condensate fields, phase state, hydrocarbon system, pseudo-component, combination of components, molar fraction of liquid phase, validation, water mineralization
References:
1. Ishmuratov T.A., Khamidullina A.I., Islamov R.R., Khisamov A.A., Abdulmyanov A.R., Senina A.A., Andreev A.E., Opritov I.G., Abdullin A.F., Logashin A.M. Improvement of approaches for calculating the PVT properties of reservoir fluids of oil and gas, oil-gas-condensate and gas-condensate deposits on the territory of the activity of RN-Purneftegas LLC. Oil industry, 2021, no. 12, pp. 92–96. (In Russ.) DOI: 10.24887/0028-2448-2021-12-92-96
2. Varlamov D.I., Grishchenko E.N., Baranova S.V., Baranov A.A. Case record of dual completion develoyment in vietsovpetro wells. Oil industry, 2023, no. 7, pp. 58–64. (In Russ.) DOI: 10.24887/0028-2448-2023-7-58-64
3. Dmitrievsky N., Skibitskaya N.A., Gafarov N.A., Burkhanova I.O., Bolshakov M.N., Chernysheva E.A., Domanova E.G., Surnachev D.V., Marutyan O.O. Matrix oil and residual gas reserves of Orenburg oil-gas condensate field and prospects of their development. Geology, geophysics and development of oil and gas fields, 2023, no. 11 (383), pp. 24–31. (In Russ.) DOI: 10.33285/2413-5011-2023-11(383)-24-31.
4. Moog G.J., O'Sullivan T., Castellanos Diaz O., Verlaan M.A. Data integration process from oil characterization and PVT modeling to reservoir simulation for the East Cat Canyon Heavy Oil Field in California. SPE Reservoir Evaluation and Engineering, 2021, vol. 12, pp. 281–296. DOI: 10.2118/200810-MS
5. Eikeland K.M., Hansen H. Dry gas reinjection in a strong waterdrive gas/condensate field increases condensate recovery – case study: the Sleipner Øst Ty field, South Viking Graben, Norwegian North Sea. SPE Reservoir Evaluation and Engineering, 2009, vol. 12, pp. 281–296. DOI: 10.2118/110309-PA
6. Petrenko N.N., Bondarenko M.A., Petrenko V.I. Estimation of the scales of retrograde condensation in a giant gas-condensate deposit. Science. Innovations. Technologies, 2013, pp. 99–106. (In Russ.)
7. Reitblat E.A., Rozhina E.V., Komyagin A.I., Glumov D.N., Oparin I.A., Budyko A.I. Modeling properties of hydrocarbons in a reservoir with significant vertical differentiation of oil density and viscosity. Oil industry, 2022, no. 8, pp. 82–85. (In Russ.) DOI: 10.24887/0028-2448-2022-8-82-85
8. Varavva A.I., Apasov R.T., Apasov G.T., Vinogradov D.V., Polkovnikov F.I., Platonov D.V., Samolov D.A. Creating and maintenance of well's lift models at oil rim field's under-gas-cap zones – experience Novoport oil and gas-condensate field and Tazovskoe oil and gas-condensate field. SPE Russian Petroleum Technology Conference SPE-201962-RU. Moscow, October 26–29, 2020. pp. 1–13. (In Russ.)
9. Ogbeiwi P., Stephen K.D. Optimizing the value of a CO2 water-alternating-gas injection project under geological and economic uncertainties. SPE Journal, 2024, vol. 29, pp. 3348–3368. DOI: 10.2118/219458-PA
10. Fedorov K., Pospelova T., Kobyashev A., Guzhikov P., Vasiliev A., Shevelev A., Dmitriev I. Wag design: miscibility challenge, tools and techniques for analysis, efficiency assessment. SPE Russian Petroleum Technology Conference SPE-196758-RU. Moscow, October 15–17, 2020. pp. 1–16. (In Russ.)
11. Caldas P.F.B., Kirkman G., Ungar F., Yang T. Evaluation of PVT comparisons and GOR prediction based on advanced mud gas data: a case study from Snorre field. Petrophysics, 2024, vol. 65, pp. 532–547. DOI: 10.30632/PJV65N4-2024a8
12. Yushchenko T.S., Brusilovsky A.I. Modeling of PVT-properties of natural gas condensate mixtures adjusted for presence of residual water in collector. SPE Russian Petroleum Technology Conference SPE-176728-RU. Moscow, October 26–28, 2020. pp. 1–20. (In Russ.)
13. Trengove R.D., Hann J.H., Skates J.R. The impact of PVT data quality on hydrocarbon recovery predictions. SPE Conference Paper SPE-22988-MS, 1991, pp. 1–25.
14. Korotkov R.N., Ovcharenko D.M., Erofeev V.I. Setup of PVT-models. Modeling of injection wells. Configuring models of collection system and pipelines and reservoir pressure maintenance system. Bulletin of the Tomsk Polytechnic University. Geo Assets Engineering, 2024, vol. 335, no 6, pp. 37–45. (In Russ.) DOI: 10.18799/24131830/2024/6/4593
15. Garcia C.A., Villa J.R. Pressure and PVT Uncertainty in Material Balance Calculations. SPE Conference Paper SPE-107907-MS. Buenos Aires, Argentina, April 15, 2007. pp. 1–14.
16. Khan I.A., McAndrews K., Jose J.P., Jamaluddin A.K.M., Chetri H.B. Reservoir fluid analysis using PVT express. SPE Conference Paper SPE-101219-MS. Abu Dhabi, UAE, November, 2006. pp. 1–7.
17. Groot J. A., Chernetsky A., TeRiele P. M., Dindoruk B., Cui J., Wilson L. C., Ratnakar R. Representation of phase behavior and PVT workflow for DME enhanced water-flooding express. SPE Conference Paper SPE-179771-MS. Muscat, Oman, March, 2016. pp. 1–19.
18. Abdrazakova L.T., Gilmanov A., Shevelev A.P. Мethodology for calculation of phase behavior of a natural hydrocarbon system with account of formation water mineralization. Science. Innovations. Technologies, 2025, no. 1, pp. 117–136. (In Russ.) DOI:10.37493/2308-4758.2025.1.5
19. Brusilovsky A.I. Phase transformations in the development of oil and gas fields. Moscow, Graal Publ., 2002. 575 p.
20. Gimatudinov S.K. Physics of the oil and gas reservoir. Moscow, Nedra Publ., 1971. 312 p.
21. Varotsis N., Garanis V., Nighswander J. Quality assurance tool for PVT simulator predictions. SPE Conference Paper SPE-68235-MS. Al Manama, Bahrain, March 17–20, 2001. pp. 1–8.
