Abstract: In view of China's coal-based energy structure, CO₂ geological storage can improve the resilience of the energy system, achieve low carbonization in the process of reducing the use of fossil energy, and is the backstop technology for China to achieve carbon neutrality. CO₂ migration monitoring is the key to grasp the storage status in time and ensure the safe and effective implementation of the project. In this paper, the multi-source, multi-field and multi-scale monitoring methods of CO₂ migration monitoring in recent years are reviewed in detail, and the key technologies of time-lapse seismic detection in CO₂ plume monitoring are introduced in detail. The future development direction of CO₂ migration monitoring technology is comprehensively considered. In the consistency processing of time-lapsed seismic data, the correlation recurrent attention network is built to ensure the consistency of time-lapsed seismic data. In terms of reservoir parameter prediction, a multi-scale and intelligent inversion process is developed by combining curvelet transformation and full convolutional neural network, and a multi-parameter simultaneous prediction process is established to realize efficient and high-precision prediction of CO₂ plumes. This study systematically sorted out the key technologies of CO₂ migration monitoring, pointed out the development direction of CO₂ migration monitoring, and provided a reference for the effective implementation of CO₂ geological storage.