AI and data-driven methodologies are increasingly being used in mineral exploration to improve efficiency, accuracy, and reduce costs. Some applications include:
- Mineral deposit modeling: Machine learning algorithms are used to analyse geological, geochemical, and geophysical data to identify mineral deposit targets.
- Remote sensing: AI is used to process satellite and aerial imagery data to detect mineral occurrences and map geology.
- Drilling optimisation: AI algorithms are used to optimise drilling programs, reducing costs, and increasing the accuracy of mineral resource estimates.
- Mineral identification: AI is used to automatically classify mineral species and analyse mineral compositions using X-ray fluorescence (XRF) and other analytical techniques.
- Mineral processing optimisation: AI algorithms are used to optimise mineral processing operations, improving yields, and reducing costs.
Overall, AI and data-driven methodologies are helping the mineral exploration industry become more efficient and effective, enabling faster and more accurate discovery and development of new mineral resources.