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Article

Experimental Study on the Alteration in Pore Structure of Chang 7 Shale Oil Reservoirs Treated with Carbon Dioxide

by
Can Shi
1,
Meng Yang
2,
Wei Liu
3 and
Wentong Zhang
4,*
1
College of Energy, Chengdu University of Technology, Chengdu 610059, China
2
Exploration and Development Technology Research Center of Yanchang Oilfield Co., Ltd., Xi’an 710075, China
3
The First Gas Production Plant, Changqing Oilfield Company, Petrochina, Yulin 718500, China
4
College of New Energy, Xi’an Shiyou University, Xi’an 710065, China
*
Author to whom correspondence should be addressed.
Processes 2025, 13(4), 1015; https://doi.org/10.3390/pr13041015
Submission received: 4 March 2025 / Revised: 24 March 2025 / Accepted: 26 March 2025 / Published: 28 March 2025
(This article belongs to the Special Issue Modeling, Control, and Optimization of Drilling Techniques)
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Abstract

:
Understanding the changes in the pore structure of reservoirs in the presence of CO2 is critical for carbon neutrality, especially for shale oil reservoirs with ultra-low permeability and porosity. However, studies examining the alteration in the pore structure of shale oil reservoirs that have been treated with CO2 remain limited. Thus, in this paper, nuclear magnetic resonance (NMR) and low-temperature nitrogen adsorption (LNA) technologies were employed to address this issue. The results show that the permeability and porosity of shale oil reservoirs increase after exposure to CO2. The permeability improves by 49.03%, and the porosity increases by 29.54%. The NMR results reveal that the pore structure of shale oil reservoirs is altered. Specifically, increases of 11.14%, 74.54%, and 990.02% in the presence of CO2 are observed for micropores, mesopores, and macropores, respectively. CO2 is more sensitive to macropores, followed by mesopores and micropores. Furthermore, the LNA results indicate that some small pores expand into larger pores, leading to a decrease in the number of small pores and an increase in the number of larger pores. Combining the results of NMR and LNA, it is found that the increase in big pores is the reason behind the enhancement in permeability and porosity. This paper sheds light on the change in the pore structure of shale oil reservoirs after exposure to CO2, further guiding the evaluation of CO2 storage capacity.

1. Introduction

With the growing threat of greenhouse gases to the global ecological system, the world has recognized the urgent need to reduce CO2 emissions. Based on this critical background, carbon neutrality is proposed [1,2]. Today, the concept of carbon neutrality has permeated various industries [3,4,5,6]. As for the oil and gas industry, carbon neutrality is embraced, because oil and gas production and geological CO2 storage can be achieved simultaneously [7,8,9,10]. Reservoirs are considered ideal targets for CO2 sequestration [11]. When choosing a CO2 geological site, unconventional reservoirs are regarded as ideal spaces due to their ultra-low physical properties [12,13], especially for shale reservoirs [14]. In this situation, CO2 can be safely and effectively sealed underground, as the CO2 is continuously injected into the shale reservoirs [15,16]. On the one hand, the oil and gas are replaced by CO2. On the other hand, CO2 is effectively trapped underground. During this process, CO2–water–rock interactions will essentially and necessarily happen, because shale reservoirs contain water [17]. Thus, research on the change in the shale reservoirs during CO2–water interaction is of paramount importance [18,19]. Recently, the oil and gas industry has increasingly focused on shale oil reservoirs due to their vast resource potential [20,21]. Therefore, investigating the change in shale oil reservoirs that have been exposed to CO2 is both scientifically intriguing and critically important.
The physical properties of shale oil reservoirs are essential for effectively enhancing oil and gas production [22]. The pore structure of shale oil reservoirs plays a critical role in controlling these physical properties [23,24,25,26]. Additionally, the change in the pore structure of shale oil reservoirs after exposure to CO2 has attracted much interest. The focus at this point is that people usually think that the change in the pore structure of shale oil reservoirs is due to CO2–water–rock interactions. Regarding the change in the pore structure of shale oil reservoirs in the presence of CO2, a consensus has yet to be reached due to paradoxical experimental results. For example, Zhou et al. investigated the change in the pore structure of shale reservoirs after exposure to CO2; the experimental results indicated that the average pore size of shale increases. Moreover, micropores and mesopores may expand into macropores [27]. Cheng et al. studied the pore structure of shale reservoirs under the influence of CO2; the experimental results demonstrated that the pore volume of reservoirs decreases after exposure to CO2 [28]. Tao et al. found that the porosity and permeability of shale decrease with the effect of CO2 [29]. Thus, our knowledge of the change in the pore structure of shale oil reservoirs after exposure to CO2 is still unclear. The reason for this conflict may be attributed to the different mineral compositions of shale reservoirs [30]. Therefore, more studies on the alterations in the pore structure of shale reservoirs with the impact of CO2 are urgently needed to resolve these discrepancies.
In light of the above, this paper investigates the change in the pore structure of shale oil reservoirs under the influence of CO2 in the southern Yanchang oilfield, Ordos Basin, in China. In this paper, nuclear magnetic resonance (NMR) and low-temperature nitrogen adsorption (LNA) technologies are combined to address this issue. NMR can nondestructively reveal the change in the pore structure, and LNA can clearly describe the alterations in nanopores of shale reservoirs. The findings from this paper elucidate the change in the pore structure of shale oil reservoirs after CO2 exposure, guiding schemes for CO2 geological storage because of the occurrence of inevitable CO2–water–rock interactions.

2. Experiments

2.1. Materials

The studied shale sample comes from Member 7 of the Donggou Block, Xiasiwan Oil Production Plant, in the southern Yanchang oilfield, Ordos Basin, China. Member 7 is a significant stratigraphic unit within the Triassic Yanchang Formation. Geologically, the Ordos Basin is a large intracratonic basin, characterized by stable tectonic settings and layered sedimentary sequences, with the Yanchang Formation representing a major hydrocarbon-bearing system, formed during the Late Triassic under lacustrine depositional environments. Member 7 is primarily composed of fine-grained sandstones that are interbedded with dark mudstones and organic-rich shales, which serve as both source rocks and reservoirs. A cylindrical core sample with a length of 7.570 cm and a diameter of 2.531 cm was selected for analysis. To minimize the impact of shale heterogeneity and anisotropy, the same sample was used for both nuclear magnetic resonance (NMR) and low-temperature nitrogen adsorption (LNA) tests. Moreover, MesoMR equipment for NMR from Suzhou Niumag Analytical Instrument Corporation and TriStar II3020 equipment for LNA from Micromeritics Instrument Corporation. The permeability and porosity of the sample were measured as 0.040 md and 9.619%, respectively, confirming the ultra-low physical properties that are typical of shale oil reservoirs. After measuring the permeability and porosity, the sample was divided into two sections. One section, 3.758 cm in length, was used for the NMR experiment, while the remaining section was crushed into 60–80-mesh powders for the LNA experiment. This approach ensures reliable and convincing experimental results by reducing the influence of shale heterogeneity. The experiments were conducted using formation water from the studied area, with the following ion concentrations: Na+ and K+ at 7734.748 mg/L, Ca2+ at 307.076 mg/L, Mg2+ at 120.356 mg/L, Ba2+ at 203.904 mg/L, Cl− at 10,587.296 mg/L, and SO42− at 69.348 mg/L. The total salinity of the formation water is 18,848.728 mg/L.

2.2. Experimental Scheme

The experiments included nuclear magnetic resonance (NMR) and low-temperature nitrogen adsorption (LNA). For the NMR experiments, the sample was prepared as a cylinder, while for LNA, it was crushed into particles. Thus, after cutting and crushing the single sample, a cylinder sample and particle sample were obtained. These samples were placed in a thermostat at 60° for 24 h to remove moisture. Subsequently, the cylindrical sample was analyzed using NMR. Both the cylindrical and particles samples were then transferred to a high-temperature and high-pressure reactor. The reactor was filled with formation water using a vacuum pump. CO2 molecules were injected into the reactor at 8 MPa and 30 °C to maintain a supercritical state for 6 h, allowing the sample to fully react with the CO2 and formation water. The reaction apparatus used for CO2 treatment during the experiment is shown in Figure 1. After the reaction, the sample were returned to the thermostat to dry [24]. Finally, the samples were analyzed using NMR and LNA. By comparing the NMR and LNA results before and after the CO2 treatment, the changes in the pore structure of the shale oil reservoirs were revealed. The whole experimental procedure is shown in Figure 2.

2.3. NMR and LNA Experiments

NMR is a nondestructive technology that can be applied to detect the pore structure of reservoirs. The principle of NMR is that once the sample is saturated with fluids, the signal of the T2 (transverse relaxation time) can indicate the pore size of the sample [31]. It is found that the higher the signal of T2 is, the bigger the pore size of the sample is. Due to its convenience and nondestructive nature, NMR technology is widely applied in petroleum fields [32]. The abscissa of NMR is the T2 relaxation time; the T2 values are needed and necessary to determine the to pore size [33]. In addition, the T2 relaxation time can be converted to the pore size distribution using a liner coefficient. The transformed coefficient of shale is 0.025 um/ms based on research on for the same reservoirs [28]. Thus, in this paper, the NMR curves were converted to the pore size distribution using this coefficient. Additionally, a MesoMR magnetic resonance instrument was employed to detect the pore structure of the shale sample.
LNA is performed to detect the pore structure of shale in the nanoscale range due to its high sensitivity in detecting nanopores [34]. The pore size information can be obtained from the adsorption–desorption isotherm. In the LNA experiment, a TriStar II3020 instrument was applied, with the pore size ranging from 0.35 to 500 nm. The N2 was adopted to analyze the pore size information. The bath temperature during the experiment was −195.8 °C. Before the experiment, a vacuum degassing treatment is needed to remove moisture in the sample. After the LNA experiments, the pore size distributions of shale before and after treatment with CO2 can be obtained by using the Barret–Joyner–Halenda (BJH) desorption curve [34]. The BJH method derives the pore size distribution by analyzing the nitrogen desorption isotherms. It applies the Kelvin equation to relate the capillary condensation pressure to the pore radius.

3. Results

3.1. Changes in Physical Parameters of Shale Oil Reservoirs After CO2 Treatment

As stated, the pore structure of shale oil reservoirs changes under the influence of CO2, further affecting the physical parameters of reservoirs. First, the changes in the physical parameters of shale oil reservoirs before and after CO2 treatment were measured using our experimental setup. The permeability and porosity of the shale oil reservoirs are shown in Figure 3.
Figure 3 shows that the permeability and porosity of shale oil reservoirs change in the presence of CO2. Specifically, the permeability and porosity increase with the effect of CO2. It can be observed in Figure 3a that the permeability of the shale sample before the CO2 reaction was 0.0467 Md, while the permeability changed to 0.0696 Md after reacting with CO2. The permeability value improved by 49.03%. As for the porosity, we can see in Figure 3b that the porosity of the shale rock before touching CO2 was 9.619%, while the porosity changed to 12.460% under the influence of CO2. The changed value in the porosity represents a 29.54% increase. It can be clearly observed that the permeability and porosity of shale oil reservoirs increase when they react with CO2.

3.2. Change in Pore Structure of Shale Oil Reservoir Based on NMR

The physical parameters were found to have a close relationship with the pore structure of reservoirs. We observed that the permeability and porosity of shale oil reservoirs increase the participation of CO2. Thus, investigating the pore structure of shale oil reservoirs in the presence of CO2 is necessary.
In this section, NMR technology was applied to investigate the change in the pore structure of shale oil reservoirs after treatment with CO2. The NMR curves during the entire experiment are displayed in Figure 4a, including the initial dry rock, initial saturated rock, CO2 reaction, dry rock after CO2, and saturated rock after CO2. As stated, the pore size distribution of shale oil reservoirs after CO2 treatment by NMR technology can be obtained through the transfer coefficient. The transformed pore size distribution curves are presented in Figure 4b.
Figure 4 shows the NMR curves under different conditions before and after treatment with CO2. The NMR curves exhibit various shapes, indicating that the pore structure of shale oil reservoirs changes in the presence of CO2. Figure 4a displays the NMR curves with the T2 relaxation time, while Figure 4b presents the NMR curves with the pore size. It can be observed that the CO2 reaction curve differs significantly from the other NMR curves. Additionally, the treated samples were dried and re-saturated. This experimental design is necessary, because CO2 can alter the pore structure of shale oil reservoirs. However, NMR technology detects hydrogen signals to describe pore information. When pores are filled with CO2, NMR cannot accurately characterize the pore structure. Therefore, the reacted sample was dried and re-saturated to expel CO2 from the pores. Thus, the NMR curves for the initial dry rock and dry rock after CO2, as well as the initial saturated rock and saturated rock after CO2, can be further employed to determine the change in the pore structure of shale oil reservoirs. The NMR curves for dry and saturated rock before and after treatment with CO2 treatment are shown in Figure 5.
Figure 5 shows that the intensity of NMR after CO2 treatment is higher than that of the sample before CO2 treatment. This indicates that CO2 changes the pore structure of shale oil reservoirs. It can be observed in Figure 5a that the peak value after treating with CO2 was higher than that of the sample before treating with CO2, between 0.01 and 0.1 μm; this shows that more hydrogen signals were detected near 0.05 μm (50 nm) after the sample was treated with CO2. The hydrogen signal increased for the dry rock samples, which may be due to the change in the clay minerals. It is accepted that the rock reacts with water and CO2, and the CO2–water–rock reaction induces clay mineral transfer [35,36]. Typically, more feldspars are transformed to kaolinite [37]. As a result, more hydrogen signals are detected after CO2 treatment. Furthermore, it can be seen in Figure 3b that the peak values of the sample at 50 nm and 5 μm increased after treatment with CO2, showing that more pores occurred at 50 nm and 5 μm. It should be noted that in Figure 5a, the intensity of the NMR curves shows the hydrogen signals of a dry rock sample, which further represents the change in the mineral composition. This is only due to the minerals of shale oil reservoirs containing hydrogen signals. However, when the sample was saturated with water, as in Figure 5b, the hydrogen signal in the water was higher than that in the minerals. The intensity of NMR can be used to determine the distribution of hydrogen signals in water, indicating the pore size of shale oil reservoirs. Thus, the pore size of shale oil reservoirs increases with the effect of CO2 based on the NMR curves in Figure 5b.
Based on the above analysis, the total NMR areas before and after CO2 treatment were collected and are shown in Figure 6a. Additionally, the intensity of the NMR curves in Figure 5b indicates the change in the pore structure of shale oil reservoirs. Thus, the different pore types for the sample before and after CO2 treatment were obtained according to the classification. It was noted that the standard in the classification is based on the peak shape in the NMR curves. Specifically, the pore size below 0.232 μm is attributed to micropores, the pore size between 0.232 and 23.208 μm is classified as mesopores, and the pore size above 23.208 μm is classified as macropores. The results for these pore types are shown in Figure 6b.
Figure 6a shows that the total NMR area of shale oil reservoirs, both for dry rock samples and saturated rock samples, increases after treatment with CO2. From the previous analysis, it can be concluded that CO2 can induce mineral change and increase the porosity of reservoirs. It is noted that the total NMR area for saturated rock samples reflects the pore structure of shale oil reservoirs before and after treatment with CO2. Thus, to further explore the changes in different pore types of shale oil reservoirs after treatment with CO2, the changes in the NMR area of various pore types are shown in Figure 6b.
Figure 6b indicates that the various pore types all exhibit an upward trend after treatment with CO2. Specifically, the total NMR area in the nanopores changed from 69,043.611 to 76,734.403, with an increase percentage of 11.14%. As for the mesopores, the total NMR area in the mesopores varied from 27,095.125 to 47,291.767, with a percentage increase of 74.54%. Regarding the macropores, the total NMR area in the micropores transformed from 52.820 to 575.746, with a percentage increase of 990.02%. Clearly, CO2 has a more significant impact on macropores and mesopores than on nanopores. In the case of CO2 changing the pore structure of shale oil reservoirs, CO2 is more sensitive to the macropores, followed by mesopores and micropores.

3.3. Changes in Pore Structure of Shale Oil Reservoir Based on LNA

LNA technology is highly effective for analyzing the nanopores of shale oil reservoirs. The change in the pore structure of shale oil reservoirs can be well described by LNA, which clearly identifies the alterations in the nanopores. The LNA curves, including the adsorption curve and desorption curve of shale oil reservoirs before and after CO2 treatment, are shown in Figure 7.
Figure 7 indicates that the adsorption quantity increases with the increase in relative pressure. When the relative pressure is lower than 0.45, the adsorption rate increases gradually. When the relative pressure is between 0.45 and 0.8, the adsorption rate increases rapidly. When the relative pressure is higher than 0.8, the adsorption rate shows a dramatic increase. The adsorption quantity amounts to its peak. After that, the occurrence of the hysteresis ring between the adsorption curve and the desorption curve indicates that capillary condensation happens in the process of nitrogen adsorption. That means that micropores and mesopores appear in the shale oil reservoirs. Specifically, the shape of the hysteresis ring can represent the pore structure of shale oil reservoirs. From the shape of the hysteresis ring of shale oil reservoirs before and after CO2 treatment, the hysteresis ring is attributed to the H3 type, indicating that lamellar slit pores exist.
The pore size distribution of shale oil reservoirs can be measured by the BJH of the desorption curve. Based on that, the pore size distributions of shale oil reservoirs before and after treatment with CO2 are displayed in Figure 8.
Figure 8 shows that the pore size distribution of shale oil reservoirs changes under the influence of CO2. A pore size lower than 128.54 nm is called a small pore, while a pore size higher than 128.54 nm is called a big pore. Regarding the reactions of small pores and big pores, the small pores decrease with treatment with CO2, while the big pores exhibit a contrary trend. To quantitively describe the alterations in the small pores and big pores of shale oil reservoirs after treatment with CO2, the cumulative contents in various pore types before and after treatment with CO2 are shown in Figure 9.
Figure 9 demonstrates that the small pores and big pores of shale oil reservoirs exhibit a difference after treatment with CO2. Specifically, the cumulative content of small pores changes from 0.191 to 0.170, representing a reduction of 11.045%, while the cumulative content of big pores increases from 0.014 to 0.016, representing an increase of 9.605%. The reason for the decrease in the small pores and the increase in the big pores is due to the impact of CO2. CO2 dissolves water to form carbonic acid, increasing the porosity of shale oil reservoirs. During this process, some small pores expand into big pores under the influence of CO2, with the result that the small pores decrease and the big pores increase. Furthermore, compared to the change in the micropores detected by NMR technology, these results show that micropores increase with the presence of CO2. Considering the change in the pore structure of shale oil reservoirs detected by LNA technology, it can be observed that the increase in big pores is the reason for the increase in micropores.

4. Conclusions

Understanding the alterations in the pore structure of shale oil reservoirs is essential for a carbon-neutral target. Thus, in this paper, NMR and LNA technologies were combined to investigate the effect of CO2–water–rock interactions on the pore structure of shale oil reservoirs. After carefully analyzing the experimental data, the following conclusions can be drawn:
(1)
The permeability and porosity of shale oil reservoirs in Ordos Basin increase after CO2 treatment. The permeability increases by 49.03%, and the porosity increases by 29.54%.
(2)
CO2 has a more significant impact on the pore structure of shale oil reservoirs. Our NMR results show that the micropores, mesopores, and macropores of reservoirs all increase under the influence of CO2. Furthermore, CO2 is more sensitive to the macropores, followed by mesopores and micropores.
(3)
CO2 dissolves water to form carbonic acid, increasing the porosity of shale oil reservoirs. During this process, some small pores expand into big pores under the influence of CO2, resulting in a decrease in the number of small pores and an increase in the number of big pores. Moreover, it can be observed that the increase in big pores is the reason for the increase in micropores.

Author Contributions

Conceptualization, W.Z. and C.S.; methodology, W.Z. and C.S.; software, M.Y. and W.L.; formal analysis, C.S.; investigation, M.Y.; resources, W.Z.; data curation, M.Y. and W.L.; writing—original draft preparation, C.S.; writing—review and editing, W.Z.; visualization, W.L.; supervision, W.Z.; project administration, C.S. and W.Z.; funding acquisition, C.S. and W.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China, grant number 52404022, Shaanxi Provincial Science and Technology Department youth project (2024JC-YBQN-0601), Shaanxi Postdoctoral Foundation, grant number 2023BSHEDZZ322, and Shaanxi Provincial Department of Education, grant number 23JP135.

Data Availability Statement

The data supporting the findings of this study are available from the corresponding author upon reasonable request.

Conflicts of Interest

Author Meng Yang was employed by Exploration and Development Technology Research Center of Yanchang Oilfield Co., Ltd. Author Wei Liu was employed by The First Gas Production Plant, Changqing Oilfield Company. We affirm that PetroChina Changqing Oilfield Co. and Yanchang Oilfield Co. have not influenced the research, results, or conclusions presented in this study. We declare that there are no financial interests, such as patents, stock ownership, consultancies, or speaker’s fees, that could affect the objectivity of the work.

Abbreviations

The following abbreviations are used in this manuscript:
NMRNuclear magnetic resonance
LNALow-temperature nitrogen adsorption

References

  1. Zhang, W.; Huang, H.; Li, M.; Ning, Z.; Cheng, Z.; Jia, Z.; Lyu, F.; Liu, F. Electric Field Control of CO2 Distribution in Kerogen Slit of Depleted Shale Gas Reservoirs: Implications for CO2 Sequestration. Energy Fuels 2024, 38, 20901–20912. [Google Scholar]
  2. Ahmadi, S.; Khormali, A. Development of an RSM-based predictive model for evaluation of corrosion efficiency of ATMP in one molar HCl for carbon steel samples. Pet. Sci. Technol. 2024, 42, 4537–4555. [Google Scholar]
  3. Shen, X.; Liu, H.; Zhang, Y.; You, L.; Guo, M.; Ma, L. An integrated model for carbon geo-sequestration considering gas leakage. J. Pet. Sci. Eng. 2022, 217, 110899. [Google Scholar]
  4. Hui, G.; Chen, Z.; Wang, Y.; Zhang, D.; Gu, F. An integrated machine learning-based approach to identifying controlling factors of unconventional shale productivity. Energy 2023, 266, 126512. [Google Scholar]
  5. Li, Q.; Han, Y.; Liu, X.; Ansari, U.; Cheng, Y.; Yan, C. Hydrate as a by-product in CO2 leakage during the long-term sub-seabed sequestration and its role in preventing further leakage. Environ. Sci. Pollut. Res. 2022, 29, 77737–77754. [Google Scholar]
  6. Li, Q.; Li, Q.; Cao, H.; Wu, J.; Wang, F.; Wang, Y. The Crack Propagation Behaviour of CO2 Fracturing Fluid in Unconventional Low Permeability Reservoirs: Factor Analysis and Mechanism Revelation. Processes 2025, 13, 159. [Google Scholar] [CrossRef]
  7. Lyu, F.; Ning, Z.; Kang, Y.; Jia, Z. Molecular dynamics simulations of shale wettability alteration and implications for CO2 sequestration: A comparative study. Colloids Surf. A Physicochem. Eng. Asp. 2024, 699, 134710. [Google Scholar] [CrossRef]
  8. Farajzadeh, R.; Eftekhari, A.A.; Dafnomilis, G.; Lake, L.; Bruining, J. On the sustainability of CO2 storage through CO2–Enhanced oil recovery. Appl. Energy 2020, 261, 114467. [Google Scholar]
  9. Hamza, A.; Hussein, I.A.; Al-Marri, M.J.; Mahmoud, M.; Shawabkeh, R.; Aparicio, S. CO2 enhanced gas recovery and sequestration in depleted gas reservoirs: A review. J. Pet. Sci. Eng. 2021, 196, 107685. [Google Scholar]
  10. Liu, Y.; Rui, Z. A storage-driven CO2 EOR for a net-zero emission target. Engineering 2022, 18, 79–87. [Google Scholar] [CrossRef]
  11. Shen, X.; Liu, H.; Mu, L.; Lyu, X.; Zhang, Y.; Zhang, W. A semi-analytical model for multi-well leakage in a depleted gas reservoir with irregular boundaries. Gas Sci. Eng. 2023, 114, 204979. [Google Scholar]
  12. Wang, Y.; Dai, Z.; Chen, L.; Shen, X.; Chen, F.; Soltanian, M.R. An integrated multi-scale model for CO2 transport and storage in shale reservoirs. Appl. Energy 2023, 331, 120444. [Google Scholar]
  13. Li, Y.; Chen, J.; Elsworth, D.; Pan, Z.; Ma, X. Nanoscale mechanical property variations concerning mineral composition and contact of marine shale. Geosci. Front. 2022, 13, 101405. [Google Scholar]
  14. Jia, Z.; Ning, Z.; Gao, X.; Wang, Q.; Zhang, W.; Cheng, Z. Experimental investigation on molecular-scale mechanism of wettability alteration induced by supercritical carbon dioxide-water-rock reaction. J. Pet. Sci. Eng. 2021, 205, 108798. [Google Scholar]
  15. Liu, S.; Liu, T.; Zheng, S.; Wang, R.; Sang, S. Evaluation of carbon dioxide geological sequestration potential in coal mining area. Int. J. Greenh. Gas Control 2023, 122, 103814. [Google Scholar]
  16. Zhang, L.; Nowak, W.; Oladyshkin, S.; Wang, Y.; Cai, J. Opportunities and challenges in CO2 geologic utilization and storage. Adv. Geo-Energy Res. 2023, 8, 141–145. [Google Scholar]
  17. Kang, Y.; Ning, Z.; Lyu, F.; Jia, Z. Changes in mechanical properties and surface microstructure of shale organic matter after coupling supercritical carbon dioxide with water. Appl. Geochem. 2024, 170, 106055. [Google Scholar]
  18. Kang, Y.; Ning, Z.; Lyu, F.; Jia, Z. Nanoscale profiling of the relationship between in-situ organic matter roughness, adhesion, and wettability under ScCO2 based on contact mechanics. Fuel 2024, 362, 130833. [Google Scholar]
  19. Fatah, A.; Mahmud, H.B.; Bennour, Z.; Gholami, R.; Hossain, M. The impact of supercritical CO2 on the pore structure and storage capacity of shales. J. Nat. Gas Sci. Eng. 2022, 98, 104394. [Google Scholar]
  20. Jia, B.; Tsau, J.-S.; Barati, R. A review of the current progress of CO2 injection EOR and carbon storage in shale oil reservoirs. Fuel 2019, 236, 404–427. [Google Scholar]
  21. Yu, H.; Xu, H.; Fu, W.; Lu, X.; Chen, Z.; Qi, S.; Wang, Y.; Yang, W.; Lu, J. Extraction of shale oil with supercritical CO2: Effects of number of fractures and injection pressure. Fuel 2021, 285, 118977. [Google Scholar] [CrossRef]
  22. Shi, C.; Lin, B.; Yu, H.; Shi, S.; Zhang, J. Characterization of hydraulic fracture configuration based on complex in situ stress field of a tight oil reservoir in Junggar Basin, Northwest China. Acta Geotech. 2023, 18, 757–775. [Google Scholar] [CrossRef]
  23. Zhang, W.; Ning, Z.; Wang, Q.; Cheng, Z.; Lyu, C.; Wang, Y.; Liu, Z.; Wang, H. Experimental study on the effects of an electric field on the pore characterization in anode, middle and cathode regions of tight sandstone samples. Geoenergy Sci. Eng. 2023, 223, 211500. [Google Scholar] [CrossRef]
  24. Zhang, W.; Ning, Z.; Wang, B. Experimental investigation of the variations in the pore structure of tight sandstones subjected to an electric field. J. Pet. Sci. Eng. 2021, 204, 108690. [Google Scholar] [CrossRef]
  25. Zhang, W.; Ning, Z.; Gai, S.; Zhu, J.; Fan, F.; Liu, Z.; Wang, H. Fast and effective observations of the pore structure of tight sandstones at the same location by utilizing AFM and CF-SEM. J. Pet. Sci. Eng. 2022, 208, 109554. [Google Scholar] [CrossRef]
  26. Wentong, Z.; Qing, W.; Zhengfu, N.; Rui, Z.; Liang, H.; Zhilin, C. Relationship between the stress sensitivity and pore structure of shale. J. Nat. Gas Sci. Eng. 2018, 59, 440–451. [Google Scholar] [CrossRef]
  27. Zhou, J.; Yang, K.; Tian, S.; Zhou, L.; Xian, X.; Jiang, Y.; Liu, M.; Cai, J. CO2-water-shale interaction induced shale microstructural alteration. Fuel 2020, 263, 116642. [Google Scholar] [CrossRef]
  28. Cheng, Q.; Tang, J.; Liu, Y.; Jia, Y.; Lu, Y.; Sun, X.; Zhao, G.; Liu, Y. Pore alteration of Yanchang shale after CO2-brine-rock interaction: Influence on the integrity of caprock in CO2 geological sequestration. Fuel 2024, 363, 130952. [Google Scholar] [CrossRef]
  29. Tao, J.; Meng, S.; Li, D.; Rui, Z.; Liu, H.; Xu, J. Analysis of CO2 effects on porosity and permeability of shale reservoirs under different water content conditions. Geoenergy Sci. Eng. 2023, 226, 211774. [Google Scholar] [CrossRef]
  30. Pan, Y.; Hui, D.; Luo, P.; Zhang, Y.; Zhang, L.; Sun, L. Influences of subcritical and supercritical CO2 treatment on the pore structure characteristics of marine and terrestrial shales. J. CO2 Util. 2018, 28, 152–167. [Google Scholar] [CrossRef]
  31. Fan, L.; Chen, J.; Zhu, J.; Nie, X.; Li, B.; Shi, Z. Experimental study on enhanced shale oil recovery and remaining oil distribution by CO2 flooding with nuclear magnetic resonance technology. Energy Fuels 2022, 36, 1973–1985. [Google Scholar]
  32. Zhang, W.; Huang, H.; Ning, Z.; Cao, J.; Ni, J.; Jia, Z.; Yang, B.; Cheng, Z.; Lyu, F. Multiscale evolution observation of the pore structures of porous media under an electrokinetic treatment. J. Appl. Geophys. 2023, 219, 105247. [Google Scholar] [CrossRef]
  33. Wang, H.; Lun, Z.; Lv, C.; Lang, D.; Luo, M.; Zhao, Q.; Zhao, C. Nuclear-magnetic-resonance study on oil mobilization in shale exposed to CO2. SPE J. 2020, 25, 432–439. [Google Scholar]
  34. Liu, X.; Xiong, J.; Liang, L. Investigation of pore structure and fractal characteristics of organic-rich Yanchang formation shale in central China by nitrogen adsorption/desorption analysis. J. Nat. Gas Sci. Eng. 2015, 22, 62–72. [Google Scholar]
  35. Chen, K.; Liu, X.; Nie, B.; Zhang, C.; Song, D.; Wang, L.; Yang, T. Mineral dissolution and pore alteration of coal induced by interactions with supercritical CO2. Energy 2022, 248, 123627. [Google Scholar] [CrossRef]
  36. Wang, Z.; Ding, K.; Liu, T.; Yao, J.; Sun, H.; Yang, Y.; Zhang, L.; Song, W.; Zhang, K.; Zhong, J. Minireview of microscopic CO2 interactions with fluids and minerals in shale: Advances and outlook. Energy Fuels 2023, 37, 9895–9913. [Google Scholar]
  37. Turkson, J.N.; Md Yusof, M.A.; Fjelde, I.; Sokama-Neuyam, Y.A.; Darkwah-Owusu, V.; Tackie-Otoo, B.N.; Adenutsi, C.D.; Amoyaw, B.; Hyun, L.J.; Kwon, S. Carbonated Water Injection for Enhanced Oil Recovery and CO2 Geosequestration in Different CO2 Repositories: A Review of Physicochemical Processes and Recent Advances. Energy Fuels 2024, 38, 6579–6612. [Google Scholar] [CrossRef]
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Figure 1. A schematic diagram of the whole experimental process.
Figure 1. A schematic diagram of the whole experimental process.
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Figure 2. The schematic diagram of the whole experimental process.
Figure 2. The schematic diagram of the whole experimental process.
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Figure 3. Changes in the physical parameters of shale oil reservoirs. (a) Permeability; (b) porosity.
Figure 3. Changes in the physical parameters of shale oil reservoirs. (a) Permeability; (b) porosity.
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Figure 4. The NMR curves during the whole experiments. (a) T2 curves; (b) pore size distribution.
Figure 4. The NMR curves during the whole experiments. (a) T2 curves; (b) pore size distribution.
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Figure 5. The NMR curves before and after treatment with CO2. (a) Dry rock sample; (b) saturated rock sample.
Figure 5. The NMR curves before and after treatment with CO2. (a) Dry rock sample; (b) saturated rock sample.
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Figure 6. The NMR results before and after treatment with CO2. (a) Different dry and saturated states; (b) various pore types in saturated states.
Figure 6. The NMR results before and after treatment with CO2. (a) Different dry and saturated states; (b) various pore types in saturated states.
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Figure 7. The LNA curves before and after treatment with CO2.
Figure 7. The LNA curves before and after treatment with CO2.
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Figure 8. The pore size distributions before and after treatment with CO2, determined by LNA experiments.
Figure 8. The pore size distributions before and after treatment with CO2, determined by LNA experiments.
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Figure 9. The cumulative contents in various pore types before and after treatment with CO2.
Figure 9. The cumulative contents in various pore types before and after treatment with CO2.
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Shi, C.; Yang, M.; Liu, W.; Zhang, W. Experimental Study on the Alteration in Pore Structure of Chang 7 Shale Oil Reservoirs Treated with Carbon Dioxide. Processes 2025, 13, 1015. https://doi.org/10.3390/pr13041015

AMA Style

Shi C, Yang M, Liu W, Zhang W. Experimental Study on the Alteration in Pore Structure of Chang 7 Shale Oil Reservoirs Treated with Carbon Dioxide. Processes. 2025; 13(4):1015. https://doi.org/10.3390/pr13041015

Chicago/Turabian Style

Shi, Can, Meng Yang, Wei Liu, and Wentong Zhang. 2025. "Experimental Study on the Alteration in Pore Structure of Chang 7 Shale Oil Reservoirs Treated with Carbon Dioxide" Processes 13, no. 4: 1015. https://doi.org/10.3390/pr13041015

APA Style

Shi, C., Yang, M., Liu, W., & Zhang, W. (2025). Experimental Study on the Alteration in Pore Structure of Chang 7 Shale Oil Reservoirs Treated with Carbon Dioxide. Processes, 13(4), 1015. https://doi.org/10.3390/pr13041015

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