A Leakage Safety Discrimination Model and Method for Saline Aquifer CCS Based on Pressure Dynamics

The saline aquifer CCS is a crucial site for carbon storage. Safety monitoring is a key technology for saline aquifer CCS. Current CO2 leakage detection methods include microseismic, electromagnetic, and well-logging techniques. However, these methods face challenges, such as difficulties in determining CO2 migration fronts and predicting potential leakage events; as a result, the formulation of test timing and methods for these safety monitoring techniques are somewhat arbitrary. This study establishes a gas–water two-phase seepage model and solves it using a semi-analytical method to obtain the injection pressure and the derivative curve characteristics of the injection well. The pressure derivative curve can reflect the physical properties of the reservoir through which CO2 flows underground, and it can also be used to determine whether CO2 leakage has occurred, as well as the timing and amount of leakage, based on boundary responses. This study conducted sensitivity analyses on eight parameters to determine the impact of each parameter on the bottom-hole pressure and its derivatives, thereby obtaining the influence of its parameters on different flow stages. The research indicates that, when a steady-state flow characteristic appears at the outer boundary, CO2 leakage will occur. Additionally, the leakage location can be determined by calculating the distance from the injection well. This can guide the placement and measurement of safety monitoring methods for saline aquifer CCS. The method proposed in this paper can effectively monitor the timing, location, and amount of leakage, providing a technical safeguard for promoting CCS technology.

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Journal
Processes
Published
2024-10-10
DOI
https://doi.org/10.3390/pr12102206
Citations
1
Primary Topic
Advanced Sensor and Control Systems
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article
Field-Weighted Citation Impact
0.33
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article

A Leakage Safety Discrimination Model and Method for Saline Aquifer CCS Based on Pressure Dynamics

Hailong Dang, Jun Ni, Xiaoliang Zhao, Chengjun Wang et al.
1 citations
Processes
Advanced Sensor and Control Systems
0.33
article

A Leakage Safety Discrimination Model and Method for Saline Aquifer CCS Based on Pressure Dynamics

Hailong Dang, Jun Ni, Xiaoliang Zhao, Chengjun Wang, Hongwei Jing
article en
1 citations

Abstract

The saline aquifer CCS is a crucial site for carbon storage. Safety monitoring is a key technology for saline aquifer CCS. Current CO2 leakage detection methods include microseismic, electromagnetic, and well-logging techniques. However, these methods face challenges, such as difficulties in determining CO2 migration fronts and predicting potential leakage events; as a result, the formulation of test timing and methods for these safety monitoring techniques are somewhat arbitrary. This study establishes a gas–water two-phase seepage model and solves it using a semi-analytical method to obtain the injection pressure and the derivative curve characteristics of the injection well. The pressure derivative curve can reflect the physical properties of the reservoir through which CO2 flows underground, and it can also be used to determine whether CO2 leakage has occurred, as well as the timing and amount of leakage, based on boundary responses. This study conducted sensitivity analyses on eight parameters to determine the impact of each parameter on the bottom-hole pressure and its derivatives, thereby obtaining the influence of its parameters on different flow stages. The research indicates that, when a steady-state flow characteristic appears at the outer boundary, CO2 leakage will occur. Additionally, the leakage location can be determined by calculating the distance from the injection well. This can guide the placement and measurement of safety monitoring methods for saline aquifer CCS. The method proposed in this paper can effectively monitor the timing, location, and amount of leakage, providing a technical safeguard for promoting CCS technology.

ProcessesVol. 12(10)
Xi'an Shiyou University (CN), China University of Petroleum, Beijing (CN), State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation (CN), Shaanxi Yanchang Petroleum (China) (CN)
Peace, Justice and strong institutions, Reduced inequalities
Openalex Percentile: Top 41%
Advanced Sensor and Control Systems
0.33
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