Artificial Intelligence, Machine Learning, and Autonomous Technologies in Mining Industry

Prospecting and Exploration

Prospecting is the first stage of looking for an economic mineral deposit and evaluating this deposit in terms of current economic and market conditions to ascertain if further investment is viable for the given prospect or not. Prospecting involves reconnaissance of the area of interest, collection of geophysical, geological, and economic data. Exploration involves sampling, laboratory work, borehole logging, and further investigation of prospect (Böhmer & Kucera, 2013). Both these stages involve extensive collection and use of data, and with the use of traditional methods involving human labor, site visits of remote areas, manual sampling and assaying, and primitive techniques can last a period of two years to twenty years before the actual worth of the deposit is established (Böhmer & Kucera, 2013).

Prospecting generally starts with finding an anomaly in the structure, lithology, geological features, and plantation and plant growth patterns using maps, aerial photographs, satellite images, and other available data. AI systems and data analysis software can be fed with geological, topographical, mineralogical, and mapping data and can be used to pinpoint the anomalies and variances in the data and to locate areas of potential interests. Some research in this field is already underway and one such system is being utilized on an experimental basis by Goldspot Discoveries Incorporated for gold discovery. Similarly, Goldcorp and IBM Watson are working together to sift through large geological data to improve the accuracy of targeting mineable prospects (Walker, 2017).