AP09058419 – Prediction of the characteristics of a porous medium, taking into account the modes of rock dissolution on a pore scale based on machine learning

Objective of the project: The aim of the project is to characterize the porous media (absolute and relative phase permeability, capillary pressure) under different dissolution regimes (injection rate and acid concentration) at the pore scale using machine learning.

Relevance: The relevance of the project is that within the framework of the research work, for the first time, machine learning will be used to determine the characteristics of the porous medium of carbonate core samples (absolute and relative phase permeability, capillary pressure) under various dissolution modes (injection rate and acid concentration).

Scientific supervisor: Ph.D., Assilbekov Bakhytzhan

Results obtained: Within the project, carbonate rock dissolution was experimentally studied using X-ray micro-computed tomography, revealing changes in porosity and permeability. The effects of acid concentration and injection rate, as well as different dissolution mechanisms, were identified. Machine learning methods were applied to predict absolute permeability, with the Extra Trees model showing the highest accuracy. Relationships between pore structure characteristics and transport properties, including the impact of natural fractures, were analyzed. The influence of dissolution on two-phase flow was investigated, showing significant changes in relative permeability and reduced residual oil saturation. The results are valuable for optimizing acid treatment processes in reservoirs. All project objectives were fully accomplished with strong practical relevance.

List of publications with links to them

1. Akasheva Zh.K., Assilbekov B.K., Soltanbekova K.A., Kudaikulov A.A. Numerical simulation of carbonate rocks dissolution near the wellbore // Journal of Mathematics, Mechanics and Computer Science. – 2021. – Vol. 112, No. 4. – P. 78–93. – DOI: https://doi.org/10.26577/JMMCS.2021.v112.i4.07
2. Bolysbek D.A., Assilbekov B.K., Akasheva Zh.K., Soltanbekova K.A. Analysis of the heterogeneity influence on main parameters of porous media at the pore scale // Journal of Mathematics, Mechanics and Computer Science. – 2021. – Vol. 112, No. 4. – P. 69–77. – DOI: https://doi.org/10.26577/JMMCS.2021.v112.i4.06
3. Болысбек Д.А., Асилбеков Б.К., Кульджабеков А.Б. Численное изучение влияния растворения породы на поровую структуру карбонатных образцов на основе экспериментальных данных // Вестник КазНПУ. Серия «Физико-математические науки». – 2023. – Т. 82, № 2. – URL: https://bulletin-phmath.kaznpu.kz/index.php/ped/article/view/1249
4. Асилбеков Б.К., Акашева Ж.К., Болысбек Д.А., Кульджабеков А.Б. Численное исследование растворения карбонатной породы: влияние масштаба области // Вестник КазНПУ. Серия «Физико-математические науки». – 2022. – Т. 79, № 3. – С. 63–72. – DOI: https://doi.org/10.51889/3035.2022.74.92.008
5. Soltanbekova K.A., Assilbekov B.K., Zolotukhin A.B. Study of the horizontal sidetracking efficiency using hydrodynamic modeling (on the example of a Kazakhstani field) // Complex Use of Mineral Resources. – 2022. – Vol. 320, No. 1. – P. 42–50. – DOI: https://doi.org/10.31643/2022/6445.05
6. Akasheva Zh.K., Bolysbek D.A., Assilbekov B.K. Study of carbonate rock dissolution using X-ray microcomputed tomography: impact of acid flow rate // News of the National Academy of Sciences of the Republic of Kazakhstan. Series of Geology and Technical Sciences. – 2023. – Vol. 1, No. 457. – P. 20–32. – DOI: https://doi.org/10.32014/2023.2518-170X.256
7. Асилбеков Б.К., Калжанов Н.Е., Болысбек Д.А., Узбекалиев К.Ш., Бекбау Б.Е., Кульджабеков А.Б. Исследование эффективности алгоритмов машинного обучения на основе данных различных горных пород // Вестник нефтегазовой отрасли Казахстана. – 2023. – Т. 5, № 3. – С. 5–19. – DOI: https://doi.org/10.54859/kjogi108649
8. Болысбек Д.А., Кульджабеков А.Б., Бекбау Б.Е., Узбекалиев К.Ш. Изучение поровой структуры и расчет макроскопических характеристик горных пород на основе изображений рентгеновской микрокомпьютерной томографии // Вестник нефтегазовой отрасли Казахстана. – 2023. – Т. 5, № 2. – С. 17–30. – DOI: https://doi.org/10.54859/kjogi108647
9. Assilbekov B.K., Bolysbek D.A., Kalzhanov N.E., Uzbekaliyev K.Sh. Study of the efficiency of machine learning algorithms based on data of various rocks // News of the National Academy of Sciences of the Republic of Kazakhstan. Series of Geology and Technical Sciences. – 2023. – Vol. 5, No. 461. – P. 58–75. – DOI: https://doi.org/10.32014/2023.2518-170X.331
10. Bolysbek D.A., Kuljabekov A.B., Issayev G.I., Uzbekaliyev K.Sh. Experimental study of dissolution of carbonate samples using X-ray microcomputed tomography // News of the National Academy of Sciences of the Republic of Kazakhstan. Series of Geology and Technical Sciences. – 2023. – Vol. 5, No. 461. – P. 89–99. – DOI: https://doi.org/10.32014/2023.2518-170X.333
11. Bolysbek D.A., Kuljabekov A.B., Uzbekaliyev K.S., Assilbekov B.K. Effect of rock dissolution on two-phase relative permeabilities: pore-scale simulations based on experimental data // Applied Sciences. – 2023. – Vol. 13. – Article 11385. – DOI: https://doi.org/10.3390/app132011385
12. Soltanbekova K.A., Assilbekov B.K., Zolotukhin A.B., Akasheva Zh.K., Bolysbek D.A. Results of laboratory studies of acid treatment of low-permeability rock cores // News of the National Academy of Sciences of the Republic of Kazakhstan. Series of Geology and Technical Sciences. – 2021. – Vol. 5, No. 449. – P. 113–123. – DOI: https://doi.org/10.32014/2021.2518-170X.105
13. Bolysbek D.A., Akasheva Zh.K., Assilbekov B.K., Uzbekaliyev K.Sh., Bekbau B.E., Issayev G.I. Permeability evaluation for heterogeneous and naturally fractured carbonate samples before and after HCl injection: experiments and pore-scale simulations // Geofluids. – (Web of Science, Q2).
14. Болысбек Д.А., Кульджабеков А.Б., Бекбау Б.Е. Экспериментальное изучение растворения карбонатных образцов с применением рентгеновской микрокомпьютерной томографии // Вестник нефтегазовой отрасли Казахстана. – 2023. – Т. 5, № 4.
15. Асилбеков Б.К., Калжанов Н.Е., Бекбау Б.Е., Болысбек Д.А. Обзор по расчету характеристик образцов горных пород на основе их изображений с применением алгоритмов глубокого машинного обучения // Вестник нефтегазовой отрасли Казахстана. – 2023. – Т. 5, № 4.
16. Асилбеков Б.К. Экспериментальное изучение процесса растворения карбонатных образцов и расчет их основных характеристик на основе томографических снимков: монография. – Алматы: Satbayev University, 2023. – 69 с. – ISBN 978-601-323-404-5.