Quality and quantity assessment using multivariate compositional and univariate analysis in the Glojeh polymetallic vein mineralization

被引:0
作者
Farshad Darabi-Golestan
Ardeshir Hezarkhani
机构
[1] Amirkabir University of Technology,Department of Mining and Metallurgical Engineering
来源
Carbonates and Evaporites | 2020年 / 35卷
关键词
Spatial patterns; Single-element fractal modeling; Multivariate analysis; Isometric log-ratio transformed; Pathfinder elements; Glojeh Au deposit;
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摘要
Background separation from anomalous concentration is a fundamental process in exploration geochemistry for polymetallic ore deposits. Therefore, fractal modeling and multivariate analysis have been applied to vein identification in the Glojeh polymetallic deposit, Tarom zone, northwestern Iran. The C-N fractal modeling demonstrated that the threshold value is equal to 103.34 ≈ 2000 ppb, and the total number of 100.89 ≈ 8 samples are anomalous for Au. Anomalous and background populations may do not represent major differences using the frequency distribution, but they possibly could be different in spatial patterns. Therefore, the application of single element fractal modeling would not be able to determine polymetallic veins and veinlet samples. Accordingly, a better anomaly identification may be approached using the multivariate analysis and compositional isometric log-ratio (Ilr) transformed data. It revealed that sample ID’s of 33, 29, 30, 28, 32, 35, 47, 81, 80, 31, 34 and 36 are concentrated from (Ag, Pb, As, Au) > (Te, Mo) > (Zn, S) > (W, Cu) > (Be and Cd). The factor analysis based on Ilr-transformed data indicated Au, As, Mo, W, Ag, Pb, Te, Be, and Zn are enriched and can be considered as pathfinder elements for tracing a polymetallic mineralization, while Al, K, Ba, Ce, La, Na, Zr, Rb, Y and Th have been depleted. These findings will complement and improve the results of fractal modeling to the determination of several ore-related elements, and they were quantitatively and qualitatively assessed. Finally, the mineralization type could be classified in a high sulfidation epithermal deposit.
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[71]  
Faith MK(2011)Mapping complexity of spatial distribution of faults using fractal and multifractal models: vectoring towards exploration targets Comput Geosci 37 1958-30
[72]  
Fávaro D(2014)Analysis of stream sediment data for exploring the Zhunuo porphyry Cu deposit, southern Tibet J Geochem Explor 143 19-43
[73]  
Damatto S(2009)Application of fractal models to characterization of vertical distribution of geochemical element concentration J Geochem Explor 102 37-41
[74]  
Moreira E(2016)Fractal/multifractal modeling of geochemical data: a review J Geochem Explor 164 33-211
[75]  
Mazzilli B(2013)Compositional data analysis in the study of integrated geochemical anomalies associated with mineralization Appl Geochem 28 202-undefined
[76]  
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[80]  
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