Study on Risk Assessment Methods for Geological Storage of Carbon Dioxide

Zidie Zhang; Xuegu Zhang; Yechao Niu; Xia Li; Fu Yang; Yujing Yue; Shi Li

doi:10.62051/ijnres.v5n1.07

Authors

Zidie Zhang
Xuegu Zhang
Yechao Niu
Xia Li
Fu Yang
Yujing Yue
Shi Li

DOI:

https://doi.org/10.62051/ijnres.v5n1.07

Keywords:

Carbon dioxide; Geological sequestration; Risk assessment.

Abstract

Carbon dioxide capture and storage (CCS) represents an effective approach for mitigating CO₂ emissions. However, the potential leakage of stored CO₂ poses significant risks to both the surrounding environment and human health, necessitating comprehensive risk assessment and management of CCS systems. This paper reviews the fundamental principles and applications of commonly employed methods for the risk assessment of CO₂ geological storage and provides insights into future development trends.

References

[1] S. Kumar, J. Foroozesh, K. Edlmann, M. G. Rezk, and C. Y. Lim, ‘A comprehensive review of value-added CO2 sequestration in subsurface saline aquifers’, Journal of Natural Gas Science and Engineering, vol. 81, p. 103437, Sep. 2020, doi: 10.1016/j.jngse.2020.103437.

[2] A. Peter, D. Yang, K. I.-I. I. Eshiet, and Y. Sheng, ‘A Review of the Studies on CO2–Brine–Rock Interaction in Geological Storage Process’, Geosciences, vol. 12, no. 4, p. 168, Apr. 2022, doi: 10.3390/geosciences12040168.

[3] P. Liu, T. Zhang, and S. Sun, ‘A tutorial review of reactive transport modeling and risk assessment for geologic CO 2 sequestration’, Computers & Geosciences, vol. 127, pp. 1–11, Jun. 2019, doi: 10.1016/j.cageo.2019.02.007.

[4] J.-M. Lemieux, ‘Review: The potential impact of underground geological storage of carbon dioxide in deep saline aquifers on shallow groundwater resources’, Hydrogeol J, vol. 19, no. 4, pp. 757–778, Jun. 2011, doi: 10.1007/s10040-011-0715-4.

[5] M. He, S. Luis, S. Rita, G. Ana, V. Euripedes, and N. Zhang, ‘Risk assessment of CO2 injection processes and storage in carboniferous formations: a review’, Journal of Rock Mechanics and Geotechnical Engineering, vol. 3, no. 1, pp. 39–56, Mar. 2011, doi: 10.3724/SP.J.1235.2011.00039.

[6] Q. Zhang et al., ‘A Hierarchical Analysis Method for Evaluating the Risk Factors of Pile Foundation Construction for Offshore Wind Power’, Sustainability, vol. 16, no. 18, p. 7906, Sep. 2024, doi: 10.3390/su16187906.

[7] P. Singh and A. S. Kalamdhad, ‘Unravelling barriers associated with dissemination of large-scale biogas plant with analytical hierarchical process and fuzzy analytical hierarchical process approach: Case study of India’, Bioresource Technology, vol. 413, p. 131543, Dec. 2024, doi: 10.1016/j.biortech.2024.131543.

[8] J. Wang et al., ‘Geological Conditions and Suitability Evaluation for CO2 Geological Storage in Deep Saline Aquifers of the Beibu Gulf Basin (South China)’, Energies, vol. 16, no. 5, p. 2360, Mar. 2023, doi: 10.3390/en16052360.

[9] S. Gao et al., ‘Study on Quantitative Assessment of CO2 Leakage Risk Along the Wellbore Under the Geological Storage of the Salt Water Layer’, Energies, vol. 17, no. 21, p. 5302, Oct. 2024, doi: 10.3390/en17215302.

[10] M. Tang, R. Li, R. Zhang, and S. Yang, ‘Research on New Electric Power System Risk Assessment Based on Cloud Model’, Sustainability, vol. 16, no. 5, p. 2014, Feb. 2024, doi: 10.3390/su16052014.

[11] X. Zou, ‘Research on Comprehensive Evaluation of CCS Project Based on Integrated Cloud Model and Entropy Weight’, International Journal of Nonlinear Science, vol. 18, pp. 53–59, Aug. 2014.

[12] V. Vasylkivska et al., ‘NRAP-open-IAM: A flexible open-source integrated-assessment-model for geologic carbon storage risk assessment and management’, Environmental Modelling & Software, vol. 143, p. 105114, Sep. 2021, doi: 10.1016/j.envsoft.2021.105114.

[13] G. Lackey, V. S. Vasylkivska, N. J. Huerta, S. King, and R. M. Dilmore, ‘Managing well leakage risks at a geologic carbon storage site with many wells’, International Journal of Greenhouse Gas Control, vol. 88, pp. 182–194, Sep. 2019, doi: 10.1016/j.ijggc.2019.06.011.

[14] Z. Wang, R. M. Dilmore, and W. Harbert, ‘Inferring CO2 saturation from synthetic surface seismic and downhole monitoring data using machine learning for leakage detection at CO2 sequestration sites’, International Journal of Greenhouse Gas Control, vol. 100, p. 103115, Sep. 2020, doi: 10.1016/j.ijggc.2020.103115.

[15] S. Harati et al., ‘Performance analysis of various machine learning algorithms for CO2 leak prediction and characterization in geo-sequestration injection wells’, Process Safety and Environmental Protection, vol. 183, pp. 99–110, Mar. 2024, doi: 10.1016/j.psep.2024.01.007.