Mining is a data-rich domain with decades worth of data from explorations across the globe. As economic conditions change and mining technologies evolve, valuable opportunities may be discovered if the data pointing to the opportunities is easily accessible and analyzable. While recently acquired data is maintained in modern GIS databases, a large portion of historical exploration data is still lying in scanned documents, photographs and images making information retrieval and analysis a tedious and inefficient process. AI can help change this situation without costing a fortune.
More broadly, with AI:
- Reduce the cost of human intensive processes, such as converting vast amount of data into digital assets. These tasks are out of reach for automation using non-AI techniques.
- Reduce needless, redundant measurements by combining geographical, geophysical and geological data from public sources, literature, and internal sources to create models that enable identification of potential sites for testing and mineral extraction.
- Augment the skills of experts, by creating digital twins of mining processes that mimic complex interactions between materials and mechanical processes to simulate scenarios and evaluate key metrics such as throughput, recovery etc.