Articles | Volume 15, issue 6
https://doi.org/10.5194/se-15-731-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/se-15-731-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Jun 2024
Research article |
| 28 Jun 2024
| 28 Jun 2024
Mapping geochemical anomalies by accounting for the uncertainty of mineralization-related elemental associations
Jian Wang
College of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China
State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan 430074, China
Renguang Zuo
CORRESPONDING AUTHOR
State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan 430074, China
Qinghai Liu
College of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China
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Ziye Wang and Renguang Zuo
EGUsphere, https://doi.org/10.5194/egusphere-2026-1293, https://doi.org/10.5194/egusphere-2026-1293, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
This study proposes a comprehensive uncertainty quantification framework that jointly evaluates data, model, and prediction uncertainties in deep learning-based mineral prospectivity mapping. By modelling and visualizing both data and model uncertainties, the framework transforms deep learning-based mineral prospectivity mapping from deterministic prediction to probabilistic decision-making, thereby enabling more reliable and trustworthy mineral exploration.
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Short summary
This study improves geochemical mapping by addressing the uncertainty in defining element associations. It clusters the study area by element similarity, recognizes elemental associations for each cluster, and then detects anomalies indicating underlying geological processes. This method is applied to a region in China, confirming its effectiveness and consistency with the geology. This study can enhance geochemical mapping for mineral exploration and improve geological-process understanding.
This study improves geochemical mapping by addressing the uncertainty in defining element...
