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TECHNOLOGY AND CODE article

Front. Earth Sci.
Sec. Economic Geology
Volume 12 - 2024 | doi: 10.3389/feart.2024.1433662

Maximising the value of hyperspectral drill core scanning through real-time processing and analysis

Provisionally accepted
Samuel T. T Thiele Samuel T. T Thiele 1*Moritz Kirsch Moritz Kirsch 1Sandra Lorenz Sandra Lorenz 1Houda Saffi Houda Saffi 2Safia El Alami Safia El Alami 3Isabel C. Contreras Acosta Isabel C. Contreras Acosta 4Yuleika C. Madriz Diaz Yuleika C. Madriz Diaz 1Richard Gloaguen Richard Gloaguen 1
  • 1 Helmholtz Institute Freiberg for Resource Technology, Helmholtz Center Dresden-Rossendorf, Helmholtz Association of German Research Centres (HZ), Freiberg, Germany
  • 2 The International Artificial Intelligence Center of Morocco, Mohammed VI Polytechnic University, Rabat, Morocco
  • 3 Agronomic and Veterinary Institute Hassan II, Rabat, Morocco
  • 4 TheiaX GmbH, Freiberg, Germany

The final, formatted version of the article will be published soon.

    Hyperspectral imaging is gaining widespread use in the resource sector, with applications in mineral exploration, geometallurgy and mine mapping. However, the sheer size of many hyperspectral datasets (> 1 Tb) and associated correction, visualisation and analysis challenges can limit the integration of this technique into time-critical exploration and mining workflows. In this contribution, we propose and demonstrate a novel open-source workflow for rapidly processing hyperspectral data acquired on exploration drillcores. The resulting products are adaptable to the varied needs of geologists, geophysicists and geological engineers, facilitating better integration of hyperspectral data during decision making. These tools are applied to process hyperspectral data of 6.4 km of exploration drill cores from Stonepark (Ireland), Collinstown (Ireland) and Spremberg (Germany). The results are presented via an open-source web-viewing platform that we have developed to facilitate easy on and off-site access to hyperspectral data and its derivatives. We suggest that maximum value can be extracted from hyperspectral data if it is acquired shortly after drilling and processed on-site in real time, so that results can be quickly validated and used to inform time-critical decisions on sample selection, geological interpretation (logging) and drillhole continuation or termination. This timeliness and accessibility is key to ensure rapid data availability for decision makers during mineral exploration and exploitation. Finally, we discuss several remaining challenges that limit the real-time integration of hyperspectral drill core scanning data, and explore some opportunities that may arise as these rich datasets become more widely collected.

    Keywords: Hyperspectral (HS), big data & analytics, Visualisation & Interaction, Minerals exploration, Drillcore, Geology

    Received: 16 May 2024; Accepted: 25 Jul 2024.

    Copyright: © 2024 T Thiele, Kirsch, Lorenz, Saffi, El Alami, Contreras Acosta, Madriz Diaz and Gloaguen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Samuel T. T Thiele, Helmholtz Institute Freiberg for Resource Technology, Helmholtz Center Dresden-Rossendorf, Helmholtz Association of German Research Centres (HZ), Freiberg, Germany

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.