By : Franyi Sarmiento, Ph.D., Inspenet, July 13, 2022
Improving the efficiency of mineral exploration and mining in Europe through the development of new technologies and models is the main objective of the Vector project, a European initiative with the participation of scientists from the Higher Council for Scientific Research (CSIC).
The researchers will create a new geological analysis tool, which uses machine learning, to make more sustainable and less invasive geological, geochemical and geophysical measurements.
“This workflow will be transferable and will be validated in three European sedimentary basins. The ultimate goal is for Europe to reduce its dependency when it comes to importing raw materials used in renewable energies and digital technologies”, highlights Ramón Carbonell, one of the researchers from the CSIC Geosciences Barcelona (GEO3BCN-CSIC) who are part of this project led by the Freiberg Helmholtz Institute for Resource Technology (HIF), of the Helmholtz Zentrum Dresden-Rossendorf (HZDR), in Germany.
Vector will promote knowledge based on accessibility and scientific evidence so that Europe is more dependent on its own deposits and deposits.
The project will develop a set of tools integrated into a single, distributed, multimodal, self-learning and interactive platform. Both the geological exploration potential and socioeconomic factors will be taken into account to obtain an assessment of the most suitable regions for exploration and, where appropriate, mining exploitation.
Specifically, the GEO3BCN-CSIC scientists will implement, test and validate a subsoil exploration methodology, up to depths of 2,000 to 3,000 metres, through the use of environmental seismic noise. “Another objective is the implementation of integrated interpretation and construction of three-dimensional models through the use of machine learning. This section consists of using data from different geophysical, geological and geochemical disciplines and integrating them into software to obtain three-dimensional geological models”, indicates the CSIC researcher.
Scientists from the Institute of Geosciences (IGEO-CSIC-UCM), led by CSIC researcher Fernando Tornos, will be in charge of this project with the geological and mineralogical characterization of the borehole samples, information that will be integrated with the observation data. hints from underground.
This DICYT portal material was edited for clarity, style, and length.
Dicyt Source : https://www.dicyt.com/noticias/machine-learning-para-mejorar-la-mineria-europea-en-materias-primas-estrategicas
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