Potash, as a critical strategic mineral resource, shares significant similarities with oil and gas exploration in its primary technical approaches. This paper systematically reviews the technological advances in potash reservoir prediction and the integrated oil- potassium exploration. The study indicates that: ① In terms of geophysical technologies, well logging has established a suite of identification markers for both solid and liquid potash deposits; seismic exploration characterizes the spatial distribution of reservoirs through impedance inversion; while gravity, magnetic, and electrical surveys delineate salt bodies based on physical property contrasts. ② Regarding artificial intelligence (AI) technologies, machine learning demonstrates good classification performance in data- sufficient areas, and deep learning shows potential in predicting complex reservoirs through feature extraction. ③ Geochemical methods, which integrate elemental and isotopic geochemistry along with the causative discrimination and comprehensive application of multiple geochemical parameters, effectively reveal potash- forming mechanisms and directly support exploration prediction. Based on practices in typical basins, this paper concludes that future technological development must focus on breakthroughs in three key directions: "deep exploration, intelligence, and integration". It aims to provide a systematic theoretical foundation and practical technical references for tackling key challenges such as deep detection and data fusion, thereby ensuring the security of potash resources in China.