Prospecting of gold mineralization in Saqez area (NW Iran) using geochemical, geophysical and geological studies based on multifractal modelling and principal component analysis

Almasi, Alireza; Jafarirad, Alireza; Afzal, Peyman; Rahimi, Mana

doi:10.1007/s12517-014-1625-2

Cited by 24 publications

(6 citation statements)

References 51 publications

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“…Goldfarb et al, 2001;Nykänen et al, 2008b) to generate a metal deposition evidence layer for MPM. These elements have been used to study orogenic gold deposits and are associated with this type of mineralization worldwide and in the study area (Groves et al, 2000;Goldfarb et al, 2001;Aliyari et al, 2007Aliyari et al, , 2009Aliyari et al, , 2012Nykänen et al, 2008b;Almasi et al, 2015b). For modeling geochemical anomalies representing gold mineralization in the study area, concentration values of the selected elements were transformed into logistic space.…”

Section: Metal Deposition Evidence Mapmentioning

confidence: 99%

Prospectivity analysis of orogenic gold deposits in Saqez-Sardasht Goldfield, Zagros Orogen, Iran

Almasi

Yousefi

Carranza

2017

Ore Geology Reviews

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Diverse deposit-types or mineral systems form by diverse geological processes, so translation of knowledge about the controls of mineralization acquired from the 4D geological modeling into 2D spatial predictor maps is a major challenge for prospectivity analysis. In this regard, mathematical functions have been used to model the conceptual or perceived spatial relationships between geological variables and targeted type or system of mineralization. In this paper, due to the different models of spatial relationships between predictors and mineral deposits, we investigated the performance of different fuzzification functions to quantify the relationships. We demonstrated that various types of relationships between exploration features and a mineralization-type sought could be quantified using different fuzzification functions for prospectivity analysis. We illustrated the process of the prospectivity analysis by using a data set of orogenic gold deposits in Saqez-Sardasht Goldfield, Iran. Prospectivity modeling of orogenic gold mineralization in the study area showed that the NE-SW trending targets have priority for further prospecting of the deposits. Saqez-Sardasht Goldfield, Zagros Orogen, Iran (by A. Almasi, M. Yousefi, E. J.M. Carranza) Manuscript submitted to Ore Geology Reviews 2 Prospectivity analysis of orogenic gold deposits in IntroductionFor mineral prospectivity mapping (MPM) of a deposit-type sought in an area, mathematical functions have been used to model spatial relationships between geological variables system of mineralization (e.g., Bonham-Carter, 1994;Luo and Dimitrakopoulos, 2003; Porwal et al., 2003a,b,c;Carranza, 2008Carranza, , 2017. In MPM, mathematical functions, have been widely used to assign weights to discretized spatial evidence values as fuzzified evidential maps in the [0,1] range or to rank target areas as fuzzy prospectivity models (e.g., Bonham-Carter, 1994;Carranza and Hale, 2002;Luo and Dimitrakopoulos, 2003;Porwal et al., 2003c;Carranza, 2008Carranza, , 2009Carranza, , 2017Lisitsin et al., 2013;Mutele et al., 2017;Nykänen et al., 2017). The weights assigned to classes of discretized evidential values may be based on (a) expert judgment directly, (b) locations of known mineral occurrences (KMOs), (c) a combination of (a) and (b), or (d) subjectively-defined functions, so indirectly-assigned by analyst (e.g., Luo, 1990;Bonham-Carter, 1994;Cheng and Agterberg, 1999;Luo and Dimitrakopoulos, 2003;Porwal et al., 2003a Porwal et al., ,b,c, 2004Porwal et al., , 2006Carranza et al., 2005;Carranza, 2008Carranza, , 2014Porwal and Kreuzer, 2010;Mejía-Herrera et al., 2014;Carranza and Laborte, 2016;McKay and Harris, 2016). All these methods impart bias due to discretization of continuous spatial values, use of subjective expert judgments, and sparse or incomplete data on locations of KMOs in knowledge-and data-driven MPM (Coolbaugh et al., 2007;Lusty et al., 2012;Ford et al., 2016).To reduce bias in the assignment of weights to continuous-value spatial evidence, various re...

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Section: Metal Deposition Evidence Mapmentioning

confidence: 99%

Prospectivity analysis of orogenic gold deposits in Saqez-Sardasht Goldfield, Zagros Orogen, Iran

Almasi

Yousefi

Carranza

2017

Ore Geology Reviews

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“…These shear zones in the earth crust provide a high permeability fractured zone, and facilitated the circulation of hydrothermal fluid that mostly accompanied with the mineralization. High concentration of Au in the ductile shear zone directly related to the deformation intensity in the study area (Aliyari et al, 2009;Alizadeh-Dinabad et al, 2013;Almasi et al, 2015;Almasi et al, 2017). Strain ellipsoid geometry provides important data about deformation history in the shear zone (Mookerjee and Nickleach, 2011).…”

Section: Discussionmentioning

confidence: 99%

“…Mesozoic rocks in the study area deposited after a long interval with older units; this contains a complex of volcanic-sedimentary. These units have widespread exposure, high thickness and metamorphosed to greenschist facies (Aliyari et al, 2009;Alizadeh-Dinabad et al, 2013;Almasi et al, 2015;Almasi et al, 2017) (Fig. 1b).…”

Section: D1 Dynamo-thermal Regional Deformationmentioning

confidence: 99%

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Constraining of strain ellipsoid shape from sectional data in the Au bearing shear zone west of Iran

Behyari¹

2019

Acta Geodynamica Et Geomaterialia

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Ductile shear zone recorded valuable data about the progressive deformation and geodynamic setting of the earth crust. Analysis of the strain ratio on the deformed quartz grains in the samples of the Zagros orogenic shear zone indicated generally most of the strain ellipsoids shape are prolate and developed under constructional strain regime. Principal axes of the strain ellipticity ratio varied in the range between 2.04 to 3.12, shear strain magnitude analysis indicated ε s are between 0.6 to 1.3. Strain ellipsoid shape also revealed the propagation of the shear zone could not be coeval with the continental collision because in the collision region expected the ellipsoid shape to be oblate. Flattening strain regime in the Zagros Orogeny contemporaneous with the collisional event (D1 phase) and widespread in the Sanandaj-Sirjan Metamorphic Zone. Constructional conditions and prolate strain ellipsoid could be related to the post-collisional deformation phase (D2 phase). In this event stretching and shearing localized in the ductile shear zone and transtension structures superimposed on the former transpression structures. The deformation followed by third phase and brittle event (D3 phase) and caused to the propagation of veins. These veins somewhere cut the foliation and in the other place are parallel to foliation plane.

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“…For the complicated mineralization system, West and Shlesinger's [15] study suggests that the sampled data from them varies from normal to logarithmic normal distribution and then to pareto distribution along with the system becoming more complex, showing strong characteristic of fractal and multi-fractal, the traditional method of data processing is unreasonable because of the unmeet of stationary [1,6] …”

Section: Discussionmentioning

confidence: 99%

Multi-Fractal Model of Coal Resources Distribution and Its Application in Spatial Distribution Law of Coal thickness

Liu¹,

Baolin²,

Songmei³

2017

IJSIP

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Prospecting of gold mineralization in Saqez area (NW Iran) using geochemical, geophysical and geological studies based on multifractal modelling and principal component analysis

Cited by 24 publications

References 51 publications

Prospectivity analysis of orogenic gold deposits in Saqez-Sardasht Goldfield, Zagros Orogen, Iran

Prospectivity analysis of orogenic gold deposits in Saqez-Sardasht Goldfield, Zagros Orogen, Iran

Constraining of strain ellipsoid shape from sectional data in the Au bearing shear zone west of Iran

Multi-Fractal Model of Coal Resources Distribution and Its Application in Spatial Distribution Law of Coal thickness

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