Mineral prospectivity mapping using machine learning tools

With the increasing demand for critical minerals and the strive for independent resources, Mineral Exploration has become a goal of the CRM strategy of the EU. Geophysics can play a decisive role in the exploration chain as one main input for mineral prospectivity mapping.

The workshop is a joined effort by experts from the Geological Survey of Finland (GTK) and Beak Consultants GmbH in the frame of the “DroneSOM” research project, co-funded by EIT Raw Materials. It will be held by Andreas Knobloch and Dr. Ina Storch (BEAK, Freiberg) as well as Dr. Johanna Torppa (GFK Finland) as a block course from September 1 to 5.

The workshop will showcase how (drone) geophysics and machine learning techniques can be effectively used for 2D and 3D data integration, mineral prospectivity mapping and exploration targeting. Firstly, an introduction to mineral prospectivity mapping with supervised and unsupervised methods will be presented with use cases and results from Europe and Africa. Secondly, a practical hands-on training on machine learning techniques such as self-organizing maps and artificial neural networks applied to 2D and 3D geospatial data will be provided including basic 2D data preprocessing in QGIS/ArcGIS and 3D data visualization in Skua Gocad.