- The new AI system shortens mineral prediction timelines to one week.
- AI-GeoMapping integrates big data and artificial intelligence for mapmaking.
- AI-OreSeeking automates traditional mineral exploration workflows.
- The systems have been trialed in several international regions with notable results.
A new artificial intelligence system launched by the China Geological Survey has cut mineral prediction and assessment work that previously took six months down to just one week. The bureau unveiled two systems, named AI-GeoMapping and AI-OreSeeking, at the 28th China Mining Congress and Expo held in Tianjin, marking their global debut. The systems are designed to accelerate geological survey and mineral exploration work while reducing reliance on human expert analysis.
AI-GeoMapping's innovative mapping approach
AI-GeoMapping offers a new approach to regional geological surveys by directly integrating big data and artificial intelligence into the mapping process. The system intelligently consolidates and analyzes data collected from space, airborne and ground-based sources, embedding AI-generated maps at every stage of the survey. It covers the entire mapping workflow, from preliminary research and data collection to final map generation and compilation, and can identify geological bodies with an overall accuracy exceeding 90%. It also improves the efficiency of data processing, integrated analysis and map compilation by more than 50%.
Developers have trialed the system on nearly 100 maps at a 1:50,000 scale in Qinghai, Tibet, Xinjiang and Fujian. It has also been applied internationally in Morocco, Saudi Arabia and Laos.
AI-OreSeeking's automated workflow
Traditional mineral exploration work has relied primarily on human experts to analyze data from multiple independent sources, but AI-OreSeeking automates this workflow by integrating geoscience data, geological knowledge, exploration models and more than 200 data processing algorithms for mineral exploration. The system draws on millions of entries in a geological knowledge graph covering mineralization patterns, mineral deposit models and geological settings, paired with algorithms that process gravity, magnetic, electrical, geochemical and remote sensing data. It can collect and consolidate data from multiple sources, identify exploration targets, generate three-dimensional geological structure models, and produce resource prediction assessments along with full evaluation reports.
Users can select expert-led, fully automated or human-machine collaborative modes depending on project requirements.
In a demonstration in the West Qinling region, the system processed data and completed prediction assessments for 32 maps in just five days, successfully identifying two gold exploration targets and four other areas with potential. The system supports exploration and assessment of a range of solid minerals, including gold, iron, copper, aluminum, lithium, cobalt, nickel, lead, zinc, chromium, potash and uranium. According to an official surnamed Qu at the China Geological Survey, the system has been trialed in more than 100 projects spanning over 10 provincial-level regions. Both systems were independently developed by the China Geological Survey. Bureau official Ren Xiaomei said the technology is expected to provide a technical reference for the intelligent transformation of mineral exploration worldwide.
How AI is reshaping mineral exploration
The artificial intelligence systems launched by the China Geological Survey underscore the importance of technology in mineral exploration. The combination of AI-GeoMapping and AI-OreSeeking has not only boosted exploration efficiency but also reduced reliance on human experts, with positive implications for resource management and environmental protection. As global demand for mineral resources grows, advances in such technologies could reshape how the industry operates, driving more intelligent mineral exploration and opening up new possibilities for future resource development.