Abstract: In-situ leaching of uranium is an important technical means for sandstone-type uranium mining. Acid in-situ leaching of uranium is widely used because of its low cost and good leaching effect. However，the phenomenon of pore blockage in the leaching process seriously restricts the leaching efficien⁃ cy and becomes the core bottleneck of the development of this technology. According to the cause of block⁃ age，the blockage can be divided into chemical blockage and physical blockage. Chemical blockage is mainly caused by insoluble precipitates such as calcium sulfate formed by the reaction of leaching agent and mineral layer. Physical blockage is divided into two types of solid phase particle migration deposition and gas phase accumulation plugging. On the basis of clarifying the formation mechanism，influence law and core characteristics of various types of blockages，the existing blockage removal technologies are sum⁃ marized into three categories of chemical blockage removal，material understanding blockage removal and source prevention blockage removal. The application effects，applicable scenarios and limitations of vari⁃ ous measures are analyzed. Furthermore，the idea of intelligent regulation and deblocking of production process parameters based on real-time monitoring and artificial intelligence algorithm is proposed. The ap⁃ plication prospects of machine learning agent model，physical information neural network and digital twin technology in in-situ leaching are discussed，which provides a reference for blocking prevention and con⁃ trol，deblocking process optimization and efficient mining in the process of in-situ leaching of sandstone�type uranium deposits.

Key words: acid in-situ leaching of uranium, blockage mechanisms, deblocking measures, intelligent control