Compositional data analysis in the study of integrated geochemical anomalies associated with mineralization |
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| Institution: | 1. State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan 430074, China;2. Department of Earth and Oceans, James Cook University, Townsville, Queensland 4811, Australia;1. State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan 430074, China;2. Economic Geology Research Centre (EGRU), James Cook University, Townsville, Queensland, Australia;3. Institute of Geosciences, State University of Campinas (UniCamp), Campinas, São Paulo, Brazil;1. Department of Earth Sciences, University of Florence, Via G. La Pira 4, 50121 Firenze (I), Italy;2. CNR-IGG (Institute of Geosciences and Earth Resources), G. La Pira 4, 50121 Firenze, Italy;3. Department of Earth, Environment and Resources Sciences, University of Naples Federico II, Complesso Universitario Monte Sant''Angelo, Via Cintia snc, 80125 Napoli, Italy;4. Pegaso University, Piazza Trieste e Trento, 48, 80132 Napoli, Italy;5. Benecon Scarl, Dipartimento Ambiente e Territorio, Via S. Maria di Costantinopoli 104, 80138 Napoli, Italy |
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| Abstract: | Geochemical data are typical compositional data which should be opened prior to univariate and multivariate data analysis. In this study, a frequency-based method (robust principal component analysis, RPCA) and a frequency-space-based method (spectrum–area fractal model, S–A) are applied to explore the effects of the data closure problem and to study the integrated geochemical anomalies associated with polymetallic Cu mineralization using a stream sediment geochemical dataset collected from the Zhongteng district, Fujian Province (China). The results show that: (1) geochemical data should be opened prior to RPCA to avoid spurious correlation between variables; (2) geochemical pattern is a superimposition of multi-processes and should be decomposed; and (3) the S–A fractal model is a powerful tool for decomposing the mixed geochemical pattern. |
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