Study of correlations between filtration and capacitance characteristics of carbonate reservoirs with complex void structure
https://doi.org/10.18599/grs.2025.3.16
Abstract
The present paper is devoted to the study of geological peculiarities of carbonate productive formations of oil fields and identification of correlations between filtration and capacitive properties of reservoirs with complex structure of void space. The dependence of reservoir permeability on its porosity, called petrophysical, is used in solving a wide range of problems, including geological and hydrodynamic modeling. Carbonate reservoirs have a complex void structure, which causes ambiguous petrophysical dependence and, consequently, insufficient reliability of calculations based on their application. Thus, with respect to the reservoir considered in this article, the standard petrophysical dependence is constructed differentially for pore and fracture type of reservoir voidness and is characterized by the values of the determination coefficient R2=0,81 and R2=0,16, respectively. An extended set of laboratory studies of carbonate core samples from one of the fields of the Perm region, including nuclear magnetic resonance, scanning electron microscopy, and X-ray computed tomography, allowed us to develop new dependencies that are valid for all types of voids and more closely link the filtration and capacitive characteristics of the reservoir (the coefficient of determination R2 exceeds 0,92). The feasibility of using the developed equations was confirmed by conducting a computational experiment using a geological and hydrodynamic model of the considered reservoir. Replacement of the standard petrophysical dependence with the dependences obtained in the article allowed to improve the prognostic ability of the model for both differential and integral development indicators (annual and cumulative oil production, respectively). The results of the study and the applied approaches can be used in solving the problems of designing and modeling the development of carbonate reservoirs to improve the quality of adaptation of historical data in geologic-hydrodynamic models, as well as increasing the degree of reliability of the performed calculations due to a more detailed consideration of the features of the structure of the void space of the rock relative to traditional methods.
About the Authors
Inna N. PonomarevaRussian Federation
Vladimir A. Novikov
Russian Federation
Dmitriy A. Martyushev
Alexandr V. Raznitsyn
Russian Federation
References
1. Alabere A.O., Jouini M.S., Alsuwaidi M., et al. (2025). Pore to core plug scale characterization of porosity and permeability heterogeneities in a Cretaceous carbonate reservoir using laboratory measurements and digital rock physics, Abu Dhabi, United Arab Emirates. Marine and Petroleum Geology, 172, p. 107214. https://doi.org/10.1016/j.marpetgeo.2024.107214
2. Alhindi H.S., Salisu A.M., Hussaini S.R., et al. (2025). Novel insights to unconventional carbonate mudstone reservoir with quantitative nanoporosity characterization and modeling of Tuwaiq Mountain Formation. Geoenergy Science and Engineering, 244, p. 213394. https://doi.org/10.1016/j.geoen.2024.213394
3. Ali N., Fu X., Chen J., Hussain J., Hussain W., Rahman N., Iqbal S.M., Altalbe A. (2024). Advancing Reservoir Evaluation: Machine Learning Approaches for Predicting Porosity Curves. Energies, 17, p. 3768. https://doi.org/10.3390/en17153768
4. Belov A.Yu., Belova A.A., Strakhov P.N. (2021). Geological aspects of the development of hydrocarbon deposits with hard-to-recover reserves. Neftyanoe Khozyaystvo = Oil industry, 3, pp. 50–53. (In Russ.). https://doi.org/10.24887/0028-2448-2021-3-50-53
5. Catinat M., Brigaud B., Fleury M., Thomas H., Antics M., Ungemach P. (2023). Characterizing facies and porosity-permeability heterogeneity in a geothermal carbonate reservoir with the use of NMR-wireline logging data. Geothermics, 115, p. 102821. https://doi.org/10.1016/j.geothermics.2023.102821
6. Chernyshov S., Popov S., Wang X., Derendyaev V., Yang Y., Liu H. (2024). Analysis of Changes in the Stress–Strain State and Permeability of a Terrigenous Reservoir Based on a Numerical Model of the Near-Well Zone with Casing and Perforation Channels. Applied Sciences, 14, p. 9993. https://doi.org/10.3390/app14219993
7. Chernyshov S.E., Ashikhmin S.G., Kashnikov Y.A., Ren S., Derendyaev V.V. (2024). Well perforation optimization using an abrasive jet technique to create oriented slotted channels in terrigenous reservoirs, Heliyon, 10(5), p. e27311. https://doi.org/10.1016/j.heliyon.2024.e27311
8. Chernyshov S.E., Popov S.N., Varushkin S.V., Melekhin A.A., Krivoshchekov S.N., Ren S. (2022). Scientific justification of the perforation methods for Famennian deposits in the southeast of the Perm Region based on geomechanical modelling. Journal of Mining Institute, 257, p. 732-743. https://doi.org/10.31897/PMI.2022.51
9. Dzublo A.D., Borozdin S.O. (2021). New data of a comprehensive geomechanical and petrophysical study of the Dolginskoe field reservoir properties. Bulletin of the Tomsk Polytechnic University. Geo Assets Engineering, 332 (10), pp. 105–115. (In Russ.). https://doi.org/10.18799/24131830/2021/10/3398
10. Florez J.J.A., Ulsen C., Ferrari J.V. (2024). Investigation of petrophysical properties of synthetic carbonate plugs: Adding a novel 3D printing approach to control pore networks. Petroleum Research, 9(4), p. 514-540. https://doi.org/10.1016/j.ptlrs.2024.06.006
11. Galkin S.V., Efimov A.A., Krivoshchekov S.N., Savitskiy Y.V., Cherepanov S.S. (2015). X-ray tomography in petrophysical studies of core samples from oil and gas fields. Russian Geology and Geophysics, 56 (5), pp. 782–792. https://doi.org/10.15372/GiG20150509
12. Gasanov A.B., Gurbanov V.Sh., Abbasova G.G. (2022). Variation in reservoir properties of productive strata in offshore fields of Azerbaijan. Gornyi Zhurnal , 12, pp. 10–15. (In Russ.). https://doi.org/10.17580/gzh.2022.12.02
13. Geng W., Wang J., Zhang X., Huang G, Li L., Guo Sh. (2023). Experimental study of pore structure and rock mechanical properties of tight sandstone after acid treatment. Acta Geotech, 18, pp. 6559–6571. https://doi.org/10.1007/s11440-023-02094-x
14. Gurbanov V.Sh., Sultanov L.A., Gulueva N.I. (2020). Analysis of petrophysical studies of deep-lying oil and gas reservoirs of onshore and offshore fields in Azerbaijan. Perm Journal of Petroleum and Mining Engineering, 20 (3), pp. 204–213. (In Russ.). https://doi.org/10.15593/2712-8008/2020.3.1
15. Ji C., Dong S., Dong S., Zeng L., Liu Y., Hao H., Yang Z. (2024). Fracture identification of carbonate reservoirs by deep forest model: An example from the D oilfield in Zagros Basin. Energy Geoscience, 5 (3), p. 100300. https://doi.org/10.1016/j.engeos.2024.100300
16. Katterbauer K., Arango S. Sun Sh., Hoteit I. (2015). Multi-data reservoir history matching for enhanced reservoir forecasting and uncertainty quantification. Journal of Petroleum Science and Engineering, 128, pp. 160–176. https://doi.org/10.1016/j.petrol.2015.02.016
17. Martyushev D.A. (2020). Improving the geological and hydrodynamic model a carbonate oil object by taking into account the permeability anisotropy parameter. Journal of Mining Institute, 243., pp. 313-318. https://doi.org/10.31897/PMI.2020.3.313
18. Martyushev D.A., Davoodi S., Kadkhodaie A., Riazi M., Kazemzadeh Y., Ma T. (2024). Multiscale and diverse spatial heterogeneity analysis of void structures in reef carbonate reservoirs. Geoenergy Science and Engineering, 233, p. 212569. https://doi.org/10.1016/j.geoen.2023.212569
19. Martyushev D.A., Ponomareva I.N., Chukhlov A.S., Davoodi S., Osovetsky B.M., Kazymov K.P., Yang Y. (2023). Study of void space structure and its influence on carbonate reservoir properties: X-ray microtomography, electron microscopy, and well testing. Marine and Petroleum Geology, 151, p. 106192. https://doi.org/10.1016/j.marpetgeo.2023.106192
20. Martyushev D.A., Ponomareva I.N., Davoodi S., Kazemzadeh Y., Kadkhodaie A., Tao Z. (2025). Deformation of the void space of pores and fractures of carbonates: comprehensive analysis of core and field data. Energy Geoscience, 6(1), p. 100364. https://doi.org/10.1016/j.engeos.2024.100364
21. Mason H.E., Smith M.M., Carroll, S.A. (2019). Calibration of NMR porosity to estimate permeability in carbonate reservoirs. International Journal of Greenhouse Gas Control, 87, pp. 19–26. https://doi.org/10.1016/j.ijggc.2019.05.008
22. Mondal, I., Singh, K.H. (2024). Petrophysical insights into pore structure in complex carbonate reservoirs using NMR data. Petroleum Research Petroleum Research, 2024, 9(3), 439-450. https://doi.org/10.1016/j.ptlrs.2024.03.004
23. Mukhametshin V.Sh., Kulesova L.S., Safiullina A.R. (2021). Grouping and determining oil reservoirs in carbonate reservoirs by their productivity at the stage of geological exploration. Bulletin of the Tomsk Polytechnic University. Geo Assets Engineering, 332 (12), pp. 43–51. (In Russ.). https://doi.org/10.18799/24131830/2021/12/2982
24. Ponomarev A.I., Merkulov A.V., Sopnev T.V., Murzalimov Z.U., Kushch I.I., Kozhukhar R.L. (2021). Accuracy of porosity, when performing three-dimensional geological images. Bulletin of the Tomsk Polytechnic University. Geo Assets Engineering, 332 (4), pp. 97–106. (In Russ.). https://doi.org/10.18799/24131830/2021/4/3152
25. Raznitsyn A.V, Popov N.A. (2020). Comprehensive determination of petrophysical properties of the productive deposits using the NMR method. Bulletin of Perm University. Geology, 19 (2), pp. 132–139. (In Russ.). https://doi.org/10.17072/psu.geol.19.2.132
26. Raznitsyn A.V. (2022). Interpretation of NMR data in the complex of laboratory work on the study of core (on the example of terrigenous deposits of the Timano-Pechora oil and gas province). Perm Journal of Petroleum and Mining Engineering, 22 (3), pp. 109–115. (In Russ.). https://doi.org/10.15593/2712-8008/2022.3.2
27. Repina V.A., Galkin V.I., Galkin S.V. (2018). Complex petrophysical correction in the adaptation of geological hydrodynamic models (on the example of Visean pool of Gondyrev oil field). Journal of Mining Institute, 231, pp. 268–274. (In Russ.). https://doi.org/10.25515/PMI.2018.3.268
28. Shams M., El-Banbi A., Sayyouh H. (2020). Harmony search optimization applied to reservoir engineering assisted history matching. Petroleum Exploration and Development, 47 (1), pp. 154–160. https://doi.org/10.1016/S1876-3804(20)60014-3
29. Sidorov S.V., Rizvanova Z.M. (2023). Justification of the boundary values of open porosity and gas permeability using data from flow studies for porous carbonate reservoirs. Georesursy = Georesources, 25 (4), pp. 115–120. https://doi.org/10.18599/grs.2023.4.8
30. Stepanov A.N., Gabdrahmanova A.R., Galiahmetov I.F., Samohvalov N.I., Anisimovich O.S., Kurelenkov C.Kh. (2023). Vug porosity consider methods to increase forecast ability of carbonate reservoir simulation model. Neftyanoe Khozyaystvo = Oil industry, 2, pp. 20–23. (In Russ.). https://doi.org/10.24887/0028-2448-2023-2-20-23
31. Sun Z., Wang J. (2024). Analysis of reservoir damage and microscopic seepage simulation in low permeability oil and gas reservoirs based on pore topology structure. Journal of Engineering Research (in Press). https://doi.org/10.1016/j.jer.2024.05.032
32. Wang H., Zhou Q., Sheng J., Luo Y., Liu J., Liu X. (2023). Effect of long-term infiltration on porosity-permeability evolution in carbonate rocks: An online NMR coupling penetration test. Journal of Hydrology, 617, p. 129029. https://doi.org/10.1016/j.jhydrol.2022.129029
33. Xie L., You Q., Wang E., Li T., Song Ya. (2022). Quantitative characterization of pore size and structural features in ultra-low permeability reservoirs based on X-ray computed tomography. Journal of Petroleum Science and Engineering, 208, p. 109733. https://doi.org/10.1016/j.petrol.2021.109733
34. Zhang R., Lu G., Peng X., Li l., Hu Y., Zhao Y., Zhang L. (2024). Study on the mechanism of gas-water two-phase flow in carbonate reservoirs at pore scale. Petroleum, 10(4), p. 631-645. https://doi.org/10.1016/j.petlm.2023.09.008
35. Zhao Yu., Luo R., Li L., Zhang R., Zhang D., Zhang T., Xie Z., Luo Sh., Zhang L. (2024). A review on optimization algorithms and surrogate models for reservoir automatic history matching. Geoenergy Science and Engineering, 233, p. 212554. https://doi.org/10.1016/j.geoen.2023.212554
36.
Review
For citations:
Ponomareva I.N., Novikov V.A., Martyushev D.A., Raznitsyn A.V. Study of correlations between filtration and capacitance characteristics of carbonate reservoirs with complex void structure. Georesursy = Georesources. https://doi.org/10.18599/grs.2025.3.16