In trial runs across the Qinling Mountains, Jiaodong Peninsula, and Wuyi Mountains metallogenic belts, the system delineated a series of gold, copper, iron, and lead-zinc exploration targets. Taking the Zhaishang-Liba mining district in the West Qinling as an example, the system completed data processing and prediction for 32 survey sheets at a 1:50,000 scale in just five days, newly delineating two exploration targets that were subsequently verified by drilling — work that would typically take months using traditional methods.

　　Wang said that trial applications across more than 100 projects in over 10 provincial-level regions have shown that the system can capture weak mineralization-related anomalies that are difficult for humans to detect, identifying new favorable exploration targets.

　　"The overall efficiency has improved by more than 60 percent, pushing mineral exploration toward being comprehensive, fast, and precise," he said, highlighting its particular value for deep mineral exploration.

　　The two systems come as China steps up efforts to apply AI to its new round of strategic mineral exploration, a campaign led by the Ministry of Natural Resources aimed at securing breakthroughs in domestic reserves of gold, copper, lithium, and other critical minerals. The goal is to identify a new batch of developable mineral sites by 2030 to ensure steady reserve growth at home and strengthen national energy and resource security.