Details of the Abstract
| Title of paper | Enhancing prediction of deep-seated Cu-Mo porphyry deposit in Baohuashan: A comprehensive 2D inversion of AMT data |
| List of authors | K.A.W. Kouabena1, J. Zhou2*，R. Chen3*，L. Yin2，H. Cai1, Z. Lu2，J. Gu2，and W. Yu2 |
| Affiliation(s) |
1.School of Geosciences and Geomatics, China University of Geosciences, Wuhan 430074, China, 2.Third Geological Brigade of Jiangsu Provincial Bureau of Geology and Mineral Resources, Zhenjiang 212001, China, 3. School of Geosciences and Info-Physics, Central South University, Changsha 410083, China, |
| Summary |
The increasing global demand for copper and molybdenum, essential for modern industry and green energy solutions, necessitates the exploration of new mineral resources, particularly at deeper levels. This study focuses on the Baohuashan area in Jiangsu Province, China, leveraging Audio Magnetotelluric (AMT) technology to explore Cu-Mo porphyry deposits in a complex geological terrain at depths exceeding 500 meters. Utilizing one long survey line with 25 AMT sites, we aimed to enhance the detection and visualization of resistivity anomalies indicative of potential Cu-Mo deposits where traditional exploration methods have struggled with depths beyond 500 meters. Advanced data processing techniques, including machine learning tools for dimensionality analysis and OCCAM two-dimensional inversion, were employed. The results revealed distinct medium-resistivity (~2500 Ω.m) structures corresponding to granodiorite porphyry and porphyry diorite likely hosting the Cu-Mo deposits associated with regional faults. These findings, validated by two proposed and executed drillholes, suggest significant mineralization potential previously undetected by conventional methods. Keywords: Cu-Mo porphyry deposit, AMT, 2D inversion, data processing, mineralization prediction |
| Session Keyword | 3.0 EM methods for exploration (geothermal, mineral resources, etc.) |
| File upload |
3.0_enhancing_prediction_of_d_kouabena.pdf
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