Delineating mineralized phases based on lithogeochemical data using multifractal model in Touzlar epithermal Au–Ag (Cu) deposit, NW Iran

Heidari, Seyed Mehran; Ghaderi, Majid; Afzal, Peyman

doi:10.1016/j.apgeochem.2012.12.014

Cited by 45 publications

(8 citation statements)

References 55 publications

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“…Clustering is the classification of objects into different groups, or more precisely, the partitioning of a data set into subsets (clusters), so that the data in each subset could share some common similarity according to some defined distance measure [3,4,12,31]. Factor analysis takes as input a large number of variables and describes them with small number of factors in order to reduce the data dimension [1,2,18,20]. Appropriate factors should provide an easy interpretation of the data to make geological sense.…”

Section: Hierarchical Clustering and R-mode Analysismentioning

confidence: 99%

Classification of rock types using multivariate analysis in the Dezak area, SW Iran

et al. 2020

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The geochemical multivariate techniques were applied to recognize different geological units and categorized rock types which accompanied by different penalties. Knowing changes and classification of raw materials with macroscopic and microscopic quantification have direct effect on economic and efficiency in a precipitated calcium carbonate plant. Based on lithological changes, the Darian Formation was divided into four rock units based on a total of 492 chip samples collected from the study area. The main aim objective of this study was to classify the rock types in this area using a multivariate analysis combining the R-mode factor analysis and K-Means method. Due to the opposite vector orientation of SiO

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Section: Hierarchical Clustering and R-mode Analysismentioning

confidence: 99%

Classification of rock types using multivariate analysis in the Dezak area, SW Iran

et al. 2020

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“…The superiority of the fractal modelling technique is proven because of using all the available data and considering their spatial relations with each other (Afzal et al 2010;Carranza, 2008;Cheng et al, 1994;Hassanpour and Afzal, 2013;Li et al, 2003;Wang et al, 2008;Heidari et al, 2013;Afzal et al, 2011;2016;2017a,b;Sadeghi et al, 2012;Rahmati et al, 2015;Meigoony et al, 2014;Nazarpour et al, 2015;Cheng 2007;Hosseini et al, 2015).…”

Section: Concentration-number (C-n) Fractal Modelling Techniquementioning

confidence: 99%

Characterization of Ar-Rassafeh Badyieh area (Area-2), Syria by using the airborne gamma-ray spectrometric and fractal modelling techniques

Asfahani

2019

Contributions to Geophysics and Geodesy

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The available aerial gamma-ray spectrometric data of Ar-Rassafeh Badyieh area (Area-2) are used herein for geological interpretations and mapping purposes. Those data are interpreted by the concentration-number (C-N) fractal modelling technique, with the use of log-log graphs. According to C-N model, different radioactive ranges of TC, eU, eTh, and K have been isolated. Those ranges are thereafter used to characterize the lithological outcrops in the study area. The radioactive signatures of all the outcrops in Area-2 have been discussed and documented through establishing the C-N maps of TC, eU, eTh, and K, and benefiting of the available geological map. The C-N fractal modelling technique proves its efficacy, where radioactive and lithological boundaries of outcrops are in concordance. The case study presented in this paper shows the importance and the role of airborne gamma-ray spectrometric and fractal modelling techniques to support the geological mapping and the interpretations in geological context, particularly when the study region is rugged and difficult to be accessed.

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“…Fractal/multifractal modeling established by Mandelbrot (1983) has been widely applied in different geoscience branches especially in the spatial modeling of different mineralized zones and geochemical anomalies (e.g., Afzal et al, 2011Afzal et al, , 2012Agterberg et al, 1993;Carranza, 2008;Cheng et al, 1994;Cheng, 1999Cheng, , 2007Heidari et al, 2013;Li et al, 2002Li et al, , 2003Li et al, , 2004Lima et al, 2003;Ma et al, 2014;Zuo et al, 2009Zuo et al, , 2012Zuo et al, , 2013Zuo and Wang, 2015). The Concentration-Volume (C-V) fractal model proposed by Afzal et al (2011) can be utilized to distinguish various mineralized zones with respect to the threshold values (breakpoints).…”

Section: Introductionmentioning

confidence: 98%

Multi-Gaussian kriging: a practice to enhance delineation of mineralized zones by Concentration–Volume fractal model in Dardevey iron ore deposit, SE Iran

Afzal

Madani

Shahbeik

et al. 2015

Journal of Geochemical Exploration

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Delineating mineralized phases based on lithogeochemical data using multifractal model in Touzlar epithermal Au–Ag (Cu) deposit, NW Iran

Cited by 45 publications

References 55 publications

Classification of rock types using multivariate analysis in the Dezak area, SW Iran

Classification of rock types using multivariate analysis in the Dezak area, SW Iran

Characterization of Ar-Rassafeh Badyieh area (Area-2), Syria by using the airborne gamma-ray spectrometric and fractal modelling techniques

Multi-Gaussian kriging: a practice to enhance delineation of mineralized zones by Concentration–Volume fractal model in Dardevey iron ore deposit, SE Iran

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