Abstract: Core analysis can provide support for studying the history of hydrocarbon generation, reservoir formation, and petroleum accumulation, improving oil and gas recovery rates, and searching for large-scale high-quality reserves. With the hydrocarbon exploration and development shifting towards deep and unconventional fields, the reservoirs are highly heterogeneous, and so the previous single-point analysis based on core can no longer meet the needs. It is necessary to comprehensively analyze the multi-scale images and experimental data of cores. Moreover, core analysis has developed from conventional manual description to the current digital core technology, and further towards the intelligent recognition of cores. Firstly, the paper comprehensively summarizes the current research status of core image analysis at home and abroad, and then proposes the definition and connotation of intelligent recognition technology for cores; next, the intelligent recognition of cores has been elaborated based on the case study of how to reconstruct the high-resolution CT images of full-diameter pore structure using micro-nano CT images; finally, the application of intelligent recognition technology for cores in reservoir evaluation, fracturing scheme design, and micro-seepage mechanism research is prospected. The proposal of intelligent recognition technology for cores reflects that artificial intelligence technology has begun to upgrade and develop synchronously in the oil and gas field, i.e., from the primary stage of intelligentization and speed and efficiency improvement of single-point business to a higher stage of multi-scale and multi-modal data fusion, application of large model technology in vertical fields, as well as high-quality development.