Beak Consultants

How Much Ore is Still Left in the Erzgebirge Mountains?

How Much Ore is Still Left in the Erzgebirge Mountains?

Beak Consultants

Scientists from Beak Consultants are currently targeting this question in the frame of a research project. The Free State of Saxony possesses a unique, but in the last 21 years of limited use, treasure; the regional geological, geochemical and geophysical data.

This 'old' data and the empirical knowledge accumulated over centuries are now the basis of a complete new approach to data interpretation. Artificial neural networks will help to identify relationships between hundreds of data layers and the occurrence of mineral deposits.

The core component of the project is Beak`s Advangeo prediction software. By simulating the empirical-analytic way the human brain thinks, the software 'learns', by itself, from example. Reliably, it finds the 'footprints' of known mineral deposits in a huge amount of data. This 'knowledge' is then used to interpret data in large areas.

After a year-long period of review and preparation of selected regional data, now the real work begins. Step-by-step prospectivity maps for different commodities and different types of deposits will be created.

The Advangeo prediction software was developed by Beak Consultants after four years in a research project that was partly financed by the BMWi (Federal Ministry for Economy). Advangeo is part of a whole range of software products for the management of two-dimensional and three-dimensional geo-scientific data. Advangeo has already been applied successfully in the past in mineral resources prediction in Kosovo, Ghana, and in the Pacific. The regional geological data, which is used for the current research project, has been provided by the Saxon State Office for Environment, Agriculture and Geology as part of a co-operation project.

After the development and testing of the basic software and the successful development of a module for the prediction of geo-hazards in the past, a module tailored especially to applications in the field of mineral resources prediction is currently in development. By using the software to interpret the data from Saxony, not only the prediction methodology will be refined, but also a significant contribution to the prediction of the local mineral resources of Germany will be made.

With the expected medium-term availability of new and or more detailed data, further improvement and refinement of the validity of the method can be expected in the future, too, especially in individual mining districts as well as in 3D space.