A comparative study of two modes for mapping felsic intrusions using geoinformatics |
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| Institution: | 1. Department of Mining Engineering, Faculty of Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran;2. Camborne School of Mines, University of Exeter, Penryn, UK;3. Young Researchers and Elite Club, South Tehran Branch, Islamic Azad University, Tehran, Iran;4. Department of Economic Geology, Tarbiat Modares University, Tehran, Iran;1. Geochemistry, Department of Mining Engineering, University of Gonabad, Gonabad, Iran;2. Geochemistry, Faculty of Mining, Petroleum and Geophysics, University of Shahrood, Shahrood, Iran;3. Geophysics, Faculty of Mining, Petroleum and Geophysics, University of Shahrood, Shahrood, Iran;1. School of Resources and Environmental Engineering, Hefei University of Technology, Hefei 230009, China;2. Centre for Exploration Targeting, University of Western Australia, Crawley 6008, Western Australia, Australia;3. School of Geosciences, Monash University, Clayton, VIC 3800, Australia;1. MLR Key Laboratory of Metallogeny and Mineral Assessment, Institute of Mineral Resources, Chinese Academy of Geological Sciences, Beijing 100037, China;2. Department of Earth and Space Science and Engineering, Department of Geography, York University, 4700 Keele Street, Toronto, ON M3J 1P3, Canada;3. State Key Lab of Geological Processes and Mineral Resources, China University of Geosciences, Beijing 100083, China;1. Faculty of Earth resources, China University of Geosciences, Wuhan 430074, China;2. State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan 430074, China |
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| Abstract: | Identifying felsic intrusions is an essential task in support of mineral exploration because the intrusions can be a source of energy and metals for magmatic-hydrothermal mineralization. In this paper, two models for mapping felsic intrusions are compared based on regional geochemical and geophysical data. Geochemical data as a type of compositional data which carry relative information should be preprocessed using log-ratio transformation. The first model, a factor ratio (F2/F1) model, was developed based on the chemical characteristics of the felsic intrusions, which are rich in K2O and high field strength elements (F2), but poor in Fe2O3 and compatible elements (F1). The second model, a hybrid model that combines principal component analysis and local singularity analysis, was based on the chemical and physical properties of the felsic intrusions. The results showed that (1) raw geochemical data should be processed using log-ratio transformation prior to multivariate data analysis to avoid spurious correlations between variables, and (2) the hybrid model performed better than the ratio of factors model for inferring felsic intrusions in the study area. The felsic intrusions mapped in this study provide information that can support further mineral exploration in the Dong Ujimqin Fe–Cu polymetallic district, Inner Mongolia, northern China. |
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| Keywords: | Compositional data Factor ratio Felsic intrusions Singularity Geoinformatics |
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