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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  • [21] Alavi M(2016)High precision analysis modeling by backward elimination with attitude on interaction effects on Au (Ag)-polymetallic mineralization of Glojeh Ir J Afr Earth Sci 124 505-516
  • [22] Alavi M(2017)R- and Q-mode multivariate analysis to sense spatial mineralization rather than uni-elemental fractal modeling in polymetallic vein deposits Geosyst Eng 21 226-235
  • [23] Asadi HH(2018)Evaluation of elemental mineralization rank using fractal and multivariate techniques and improving the performance by log-ratio transformation J Geochem Explor 189 11-24
  • [24] Kianpouryan S(2018)Intensification of the polymetallic vein exploration by multivariate analysis and staged LINEST function at Glojeh deposit, NW Iran J Afr Earth Sci 147 190-198
  • [25] Lu Y-J(2017)Assessment of 226 Ra, 238 U, 232 Th, 137 Cs and 40 K activities from the northern coastline of Oman Sea (water and sediments) Mar Pollut Bull 118 197-205
  • [26] McCuaig TC(1974)Progresses in R-and Q-mode analysis: correspondence analysis and its application to the study of geological processes Can J Earth Sci 11 131-146
  • [27] Asghari O(2015)Chloritisation along the Thanewasna shear zone, Western Bastar Craton, Central India: Its genetic linkage to Cu–Au mineralisation Ore Geol Rev 70 151-172
  • [28] Hezarkhani A(2003)Isometric logratio transformations for compositional data analysis Math Geol 35 279-300
  • [29] Bahajroy M(2015)Centered log-ratio (clr) transformation and robust principal component analysis of long-term NDVI data reveal vegetation activity linked to climate processes Climate 3 135-149
  • [30] Taki S(2007)Chemical characterization and recent sedimentation rates in sediment cores from Rio Grande reservoir, SP, Brazil J Radioanal Nucl Chem 273 451-463