Advances in Geochemical Monitoring Technologies for CO2 Geological Storage

被引:0
|
作者
Ma, Jianhua [1 ,2 ,3 ]
Zhou, Yongzhang [1 ,2 ,3 ]
Zheng, Yijun [4 ]
He, Luhao [1 ,2 ,3 ]
Wang, Hanyu [1 ,2 ,3 ]
Niu, Lujia [1 ,2 ,3 ]
Yu, Xinhui [1 ,2 ,3 ]
Cao, Wei [1 ,2 ,3 ]
机构
[1] Sun Yat Sen Univ, Sch Earth Sci & Engn, Zhuhai 519000, Peoples R China
[2] Sun Yat Sen Univ, Ctr Earth Environm & Resources, Zhuhai 519000, Peoples R China
[3] Guangdong Prov Key Lab Geol Proc & Mineral Resourc, Zhuhai 519000, Peoples R China
[4] Chinese Acad Sci, Guangzhou Inst Geochem, Guangzhou 510640, Peoples R China
基金
中国国家自然科学基金;
关键词
CO2 geological sequestration; geochemical monitoring; IoT monitoring; machine learning; QUEST CARBON CAPTURE; RARE-EARTH-ELEMENTS; INJECTED CO2; BASE-LINE; RESERVOIR FLUIDS; STABLE-ISOTOPES; OXYGEN ISOTOPES; SHALLOW AQUIFER; NOBLE-GASES; LEAKAGE;
D O I
10.3390/su16166784
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
CO2 geological storage, as a large-scale, low-cost, carbon reduction technology, has garnered widespread attention due to its safety. Monitoring potential leaks is critical to ensuring the safety of the carbon storage system. Geochemical monitoring employs methods such as gas monitoring, groundwater monitoring, tracer monitoring, and isotope monitoring to analyze the reservoir's storage state and secondary changes after a CO2 injection. This paper summarizes the recent applications and limitations of geochemical monitoring technologies in CO2 geological storage. In gas monitoring, the combined monitoring of multiple surface gasses can analyze potential gas sources in the storage area. In water monitoring, pH and conductivity measurements are the most direct, while ion composition monitoring methods are emerging. In tracer monitoring, although artificial tracers are effective, the environmental compatibility of natural tracers provides them with greater development potential. In isotope monitoring, C and O isotopes can effectively reveal gas sources. Future CO2 geological storage project monitoring should integrate various monitoring methods to comprehensively assess the risk and sources of CO2 leakage. The incorporation of artificial intelligence, machine learning technologies, and IoT monitoring will significantly enhance the accuracy and intelligence of numerical simulations and baseline monitoring, ensuring the long-term safety and sustainability of CO2 geological storage projects.
引用
收藏
页数:24
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