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| Multi-layer DEM-based metallogenic characteristics analysis and optimization algorithm for prospecting targets in polymetallic deposits |
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Received:October 10, 2024
Revised:February 17, 2025
Accepted:April 01, 2025
Published Online:April 30, 2026
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| DOI：10.3969/j.issn.1005-7854.2025.06.010 |
| KeyWord:DEM;polymetallic deposits;metallogenic regularity;geological characteristics;prospecting target;ore genesis;prospecting potential |
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| The Fourth Geological Exploration Institute of Henan Province Co Ltd, Zhengzhou 450001, China |
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| Abstract: |
| The metallogenic process of metals is highly complex, involving multiple geological processes such as magmatic activities, tectonic movements, and fluid migration. The interplay of these factors forms polymetallic deposits, which complicates prospecting and subsequently affects the performance of optimization algorithms. To address this, a multi-layer Digital Elevation Model (DEM)-based algorithm for analyzing metallogenic geological characteristics and optimizing prospecting targets in polymetallic deposits is proposed. First, the metallogenic geological characteristics of multi-layer DEM polymetallic deposits are analyzed. The collected DEM data undergo interpolation to improve data quality, and all data are superimposed onto the DEM to identify anomalous areas of polymetallic deposit geological features, enabling preliminary delineation of prospecting targets. A polymetallic deposit DEM dataset is constructed, and the slope and aspect of multiple sampling points in the mining area are extracted to establish an elevation model for analyzing the geological characteristics of the mining area. Based on this, the anomaly values of element content and gravity values in the polymetallic mining area are calculated, the similarity between different target areas is compared, and the types of target areas are classified to preliminarily delineate prospecting targets. By calculating the enrichment coefficient, the degree of element enrichment in the prospecting targets is evaluated, and the priority of the prospecting targets is determined, thereby achieving the optimization of prospecting targets. Experimental results show that extracting metallogenic geological characteristics from multi-layer DEM polymetallic deposits comprehensively reflects the influence of various factors on changes in sediment element content. The selected prospecting targets exhibit high and stable ore discovery rates, with an average value of 67.42%. The optimization performance is superior to other comparative algorithms. The multi-layer DEM-based algorithm for analyzing metallogenic geological characteristics and optimizing prospecting targets in polymetallic deposits not only improves prospecting efficiency and reduces exploration costs but also significantly enhances the targeting and success rate of prospecting, laying a solid foundation for the sustainable development and utilization of mineral resources. |
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