3D/4D Geological Modeling for Mineral Exploration, 2nd Edition

A special issue of Minerals (ISSN 2075-163X). This special issue belongs to the section "Mineral Exploration Methods and Applications".

Deadline for manuscript submissions: 31 October 2024 | Viewed by 68

Special Issue Editors


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Guest Editor
School of Geosciences and Resources, China University of Geosciences, Beijing 100083, China
Interests: big data of geoscience; mineral exploration; remote sensening mapping; artificial intelligence; machine learning; deep learning; 3D/4D geological modeling; geostatistics; numerical Simulation; hyperspectrum
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Guest Editor
Research Institute in Mines and the Environment (IRME), University of Québec in Abitibi-Témiscamingue, Rouyn-Noranda, QC J9X 5E4, Canada
Interests: 3D geophysics modeling for geosciences
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Guest Editor
Institute of Mineral Resources, Chinese Academy of Geological Sciences, Beijing 100037, China
Interests: 3D/4D modeling; prospectivity mapping
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Guest Editor
School of Earth Sciences and Engineering, Sun Yat-sen University, Guangzhou 510000, China
Interests: 3D geological modeling and its applications
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Special Issue Information

Dear Colleagues,

Three-dimensional and four-dimensional (3D/4D) geological modeling is a key technology and methodology for geologists to understand geological events and quantitatively analyze multiscale metallogenic models for mineral exploration. The geological concept model and metallogenic digital model can be quantitatively analyzed and 3D/4D models can be built, simulated, and integrated via multisource geoscience datasets or big data of geosciences using AI-driven technologies. It is a challenge to construct 3D/4D certainty models for mineral exploration using multiscale and multisource datasets (big data); mineral resource assessment and environment protection are associated with regional mining development and strategic planning. This Special Issue aims to improve decision-making processes using 3D/4D geological modeling for mineral exploration, and multiple innovative methodologies and technologies (e.g., conventional explicit and implicit 3D modeling, real-time mining of 4D management and decision making, and 5G+ information technology, artificial intelligence decision making, 3D/4D simulation, and digital twin, etc.).

Prof. Dr. Gongwen Wang
Prof. Dr. Lizhen Cheng
Prof. Dr. Nan Li
Dr. Weisheng Hou
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Minerals is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • 3D/4D geological modeling
  • 3D/4D simulation
  • big data
  • knowledge discovery
  • artificial intelligence
  • uncertainty analysis
  • metallogenic systems and mineral systems
  • mineral resource assessment
  • deep 3D targeting
  • big data of geosciences
  • data-driven, knowledge-driven, AI-driven

Published Papers

This special issue is now open for submission.
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