At the Mineral Prospectivity Conference by BRGM, which took place last week, Andreas Brosig from Beak Consultants GmbH won the 2017 Mineral Prospectivity Contest. The goal of the contest was to produce the most accurate predictive map for gold in the French Armorican Massif (Brittany). Each participant was allowed to create a predictive map using the provided dataset and using the methodology of his/her choice. The applied hybrid approach by Beak combines strengths of both data-driven and knowledge-based predictive mapping using Beak’s advangeo® Prediction Software. This success is the result of a 10-year-on-going development of the artificial neural network based software at Beak and the deep understanding of the respective exploration models by Beak’s geologists.
The conference was a full success, bringing together researchers from five continents. Mineral predictive maps have been discussed as important value-adding product that supports exploration targeting and land use management. Especially in traditional mining regions, they can substantially contribute to the identification of new opportunities.
At the conference, Dr Andreas Barth from Beak presented the keynote speech “Mineral Predictive Mapping – from Intuition to hybrid 3D Modelling”.
Furthermore, Andreas Brosig presented the poster “Mineral predictive mapping in 2D, 2.5D and 3D using Artificial Neural Networks – Case study of Sn and W deposits in the Erzgebirge, Germany”. It summarises three research projects funded by the Saxonian Government (ROHSA) and co-financed by the Federal Ministry of Economy (ZIM) and the Federal Ministry for Education and Research (r4).
The conference was a full success, bringing together researchers from five continents. Mineral predictive maps have been discussed as important value-adding product that supports exploration targeting and land use management. Especially in traditional mining regions, they can substantially contribute to the identification of new opportunities.
At the conference, Dr Andreas Barth from Beak presented the keynote speech “Mineral Predictive Mapping – from Intuition to hybrid 3D Modelling”.
Furthermore, Andreas Brosig presented the poster “Mineral predictive mapping in 2D, 2.5D and 3D using Artificial Neural Networks – Case study of Sn and W deposits in the Erzgebirge, Germany”. It summarises three research projects funded by the Saxonian Government (ROHSA) and co-financed by the Federal Ministry of Economy (ZIM) and the Federal Ministry for Education and Research (r4).
