Spatial Overlay Analysis of Geochemical Singularity Index α-Value of Porphyry Cu Deposit in Gangdese Metallogenic Belt, Tibet, Western China
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Published:2023-09-08
Issue:18
Volume:13
Page:10123
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ISSN:2076-3417
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Container-title:Applied Sciences
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language:en
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Short-container-title:Applied Sciences
Author:
Zheng Shunli1, Jiang Xiaojia2, Gao Shunbao3
Affiliation:
1. School of Earth Resources, China University of Geosciences, Wuhan 430074, China 2. Collaborative Innovation Center for Exploration of Strategic Mineral Resources, School of Earth Resources, China University of Geosciences, Wuhan 430074, China 3. Institute of Geological Survey, China University of Geosciences, Wuhan 430074, China
Abstract
The statistical modeling with ILR-RPCA-back CLR has two problems when dealing with the closure effect of geochemical data. Firstly, after performing isometric logratio (ilr) transformation, robust principal component analysis (RPCA) is employed for processing. The double-plot diagram illustrates that the element sequence transformation occurs in the first and second principal components, while the unique principal component remains unattainable. Secondly, by transforming both the score and load into the centered logratio (CLR) space using the U matrix, it is possible to obtain a score result that corresponds to the original order of elements according to the CLR = ILR·U formula. However, for obtaining a load result that corresponds to the original order of elements, an alternative formula “CLR = UT·ILR” must be used instead. In order to determine the optimal element assemblage for porphyry copper deposits, this study conducted statistical analysis on mineral assemblages from discovered deposits in the Gangdese metallogenic belt and identified Cu, Mo, Au, Ag, W, and Bi as key elements associated with porphyry copper deposits. Subsequently, by analyzing the singularities of the composite elements, the spatial overlay of the combined element is carried out, and concentration-area (C-A) fractal filtering is applied to identify the anomaly and background areas. To facilitate comparison, we conducted an analysis of various mineral and ore deposit types, revealing the following findings: (1) Combination elements exhibit superior recognition capability than single elements in porphyry copper deposits; (2) Skarn-type copper deposits unrelated to porphyry show a high degree of dissimilarity compared to those related to porphyry; (3) this method offers advantages over the single element method in evaluating porphyry gold deposits by reducing anomaly levels and initial investment during the evaluation stage for porphyry copper anomalies; (4) However, this method has limited ability in distinguishing between porphyry copper and molybdenum deposits.
Funder
National Natural Science Foundation of China
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
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