Senior Geologist, Goldspot Discoveries Corp
The State of Technology in Mineral Exploration
Technology in mineral exploration has evolved significantly in the last few decades. The availability of local computational power, cloud-computing, mobile devices and portable analytical tools have enhanced our ability to collect and parse datasets for targeting and geological modelling. The application of machine learning techniques to conventional mineral exploration datasets emerged as computational power became accessible but early failures emphasize the requirement for geoscientific domain expertise to prepare datasets and evaluate results. Open source software has also significantly changed the industry. High quality mapping tools are now available with little up-front cost, deceasing the barrier to entry allowing more investment dollar to be spent on the ground. The advent of drill core scanning solution have promised a full multi-element, multi-spectral downhole solution for advanced geoscientific analysis. The only certainty is that technology will continue to evolve; we must determine how these advancements can be integrated to add value rather than complexity.
Matthew had been active in the mineral exploration and mining industry industry for 17 years from grass-roots targeting through to mature mining environments. He has an M.Sc. in applied exploration geochemistry as part of the Exploration Geochemistry Initiative (EGI) at the Mineral Deposit Research Unit (MDRU) at the University of British Columbia and a 1st Class Honours B.Sc. in geological sciences from the University of Manitoba. Prior to GoldSpot Matthew has worked with Anglo American, CSA Global Consultants and Impala Canada gaining significant experience in magmatic sulphide Ni-Cu-PGE deposits with additional experience in Sediment-Hosted Base Metals, Cu-Porphyry, Au, VMS, and Uranium deposit models. His current interests and specialties include greenfield data compilation and data integration, landscape geochemistry and terrain analysis, novel geochemical methods (biogeochemistry, passive soil hydrocarbon, etc.) portable field technology (XRF), open source GIS and geospatial technologies (GNSS and Drone photogrammetry) and machine learning tools to enhance mineral exploration workflows.
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