Artificial Intelligence for Mineral Resource Estimation
Artificial intelligence (AI) is developing rapidly and has already been successfully used in geology and mining. Artificial intelligence application for mineral resource estimation is discussed by the example of the innovative Micromine Grade Copilot tool, which utilises neural networks and machine learning. The modelling is based on a database of samples or geological intervals by specified parameters, resulting in a categorical (geological) or numerical (resource) block model. Comparison of the results of the Micromine Grade Copilot simulation with the results of geologists showed the ability of artificial intelligence to summarise large amounts of professional experience information and reproduce it in similar tasks. Artificial intelligence enhances but does not replace human expertise, and its use has some risks of reducing the geologist’s involvement. The most successful is clearly the combination of human creativity and imagination with the ability of artificial intelligence to summarise huge amounts of information. Due to their complexity and multifactorial nature, the geological and mining industries have great prospects for the further development of artificial intelligence technologies.