In the context of the big data era, geological and mineral exploration and prospecting are encountering new opportunities and challenges. Characterized by massive volume, high variety, and rapid velocity, big data provides abundant information resources for geological and mineral exploration. Modern geological and mineral exploration workflows include regional geological surveys, geophysical and geochemical exploration, and drilling verification. Integrating big data into these processes is essential for improving prospecting efficiency and accuracy. This paper focuses on core big data-driven prospecting methods, including multi-source data integration, the construction of analytical and predictive models, and the development of intelligent decision-support systems. Meanwhile, challenges in the application of big data-such as data security and privacy issues, uneven data quality, and shortages of skilled professionalsare-analyzed. Corresponding countermeasures are proposed, including improving data-sharing mechanisms, strengthening technological research and development, enhancing talent cultivation, and introducing supportive policies, in order to promote the development of geological and mineral exploration and prospecting.
Sun Xiao-Dong (Wed,) studied this question.