The geochemistry of gossans associated with Sarcheshmeh porphyry copper deposit, Rafsanjan, Kerman, Iran: Implications for exploration and the environment

Atapour, Habibeh; Aftabi, Alijan

doi:10.1016/j.gexplo.2006.07.007

Cited by 100 publications

(50 citation statements)

References 17 publications

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“…The Sar Cheshmeh porphyry system has central phyllic/potassic alteration zones surrounded by a propylitic zone. The porphyry Cu mineralization is associated with potassic, biotitized and phyllic alteration zones (Waterman & Hamilton, ; Atapour & Aftabi, ).…”

Section: Geological Setting Of the Study Areamentioning

confidence: 99%

Selection of Less Biased Threshold Angles for SAM Classification Using the Real Value–Area Fractal Technique

et al. 2014

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The accuracy of classification of the Spectral Angle Mapping (SAM) is warranted by choosing the appropriate threshold angles, which are normally defined by the user. Trial-and-error and statistical methods are commonly applied to determine threshold angles. In this paper, we discuss a real value-area (RV-A) technique based on the established concentration-area (C-A) fractal model to determine less biased threshold angles for SAM classification of multispectral images. Short wave infrared (SWIR) bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images were used over and around the Sar Cheshmeh porphyry Cu deposit and Seridune porphyry Cu prospect. Reference spectra from the known hydrothermal alteration zones in each study area were chosen for producing respective rule images. Segmentation of each rule image resulted in a RV-A curve. Hydrothermal alteration mapping based on threshold values of each RV-A curve showed that the first break in each curve is practical for selection of optimum threshold angles. The hydrothermal alteration maps of the study areas were evaluated by field and laboratory studies including X-ray diffraction analysis, spectral analysis, and thin section study of rock samples. The accuracy of the SAM classification was evaluated by using an error matrix. Overall accuracies of 80.62% and 75.45% were acquired in the Sar Cheshmeh and Seridune areas, respectively. We also used different threshold angles obtained by some statistical techniques to evaluate the efficiency of the proposed RV-A technique. Threshold angles provided by statistical techniques could not enhance the hydrothermal alteration zones around the known deposits, as good as threshold angles obtained by the RV-A technique. Since no arbitrary parameter is defined by the user in the application of the RV-A technique, its application prevents introduction of human bias to the selection of optimum threshold angle for SAM classification.

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Section: Geological Setting Of the Study Areamentioning

confidence: 99%

Selection of Less Biased Threshold Angles for SAM Classification Using the Real Value–Area Fractal Technique

et al. 2014

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“…Map of Iran showing the volcano–plutonic magmatic arc and copper belt. Some important porphyry copper deposits (

1 = Kader

2 = Gode‐Kolvari

3 = Ijo

4 = Miduk

5 = Sar Cheshmeh

6 = Deh Siahan

7 = Darrehzar

8 = Chahar gonbad

) (Atapour and Aftabi ).…”

Section: Application To Real Datamentioning

confidence: 99%

A new stable downward continuation of airborne magnetic data based on Wavelet deconvolution

Abedi

Gholami

Norouzi

2014

Near Surface Geophysics

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This paper describes an efficient wavelet‐based deconvolution method for the downward continuation of airborne potential (magnetic and gravity) field data. We formulate the downward continuation process as a linear ill‐posed deconvolution problem. To obtain a reasonable downward continued field data, it is stabilized in a wavelet domain by minimizing the L1‐norm of the coefficients subject to the constraint that is the agreement of the upward response with the original observed data up to a white Gaussian noise level. The resulting convex constrained problem is then solved very fast and efficiently via the split Bregman iterations method. The generalized cross‐validation (GCV) criterion as a plotted curve versus the iteration count with new formulation is used to determine the optimum number of Bregman iterations without prior knowledge about noise properties. A synthetic magnetic field data embedded in a Gaussian noise is constructed from isolated multi‐source anomalies, whose results show that the airborne magnetic data can be continued stably downward by the proposed automatic sparse deconvolution method in a few iterations. When compared with conventional methods such as Tikhonov and Edge‐preserving with the proposed method, similar results were obtained. To test the performance on real data, we chose to use the airborne magnetic data of the central Iranian volcanic‐sedimentary belt. The enhanced downward continued data to a depth level of 200 m beneath the ground surface indicates adequate matching of high potential zones with previous working mines and copper deposits. Obtained results from both synthetic and real data confirm that the performance of the proposed technique is as good as the classical deconvolution ones.

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“…The rock types of this belt are composed of voluminous tholeiitic, calc-alkaline, and K-rich alkaline intrusive and extrusive rocks with associated pyroclastic and volcanoclastic successions, along the active margin of the Iranian plates (Berberian and King, 1981;Dargahi et al, 2010). This belt hosts the famous Iranian porphyry deposits, such as Sarcheshmeh, Sungun, Meiduk, Kahang and Darehzar (Shahabpour, 1994;Atapour and Aftabi, 2007;Boomeri et al, 2009;. Based on Yugoslavian geologists exploration in 1972, there is an Eocene volcano-sedimentary complex consisting of granite, diorite-granodiorite and tuff rocks, as depicted in Fig.…”

Section: Geological Setting Of Case Studymentioning

confidence: 99%

Application of concentration-volume fractal method in induced polarization and resistivity data interpretation for Cu-Mo porphyry deposits exploration, case study: Nowchun Cu-Mo deposit, SE Iran

Saein

Rasa

Omran

et al. 2012

Nonlin. Processes Geophys.

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Abstract. The aim of this study is the utilization of the concentration-volume (C-V ) fractal method based on geoelectrical data including induced polarization (IP) and resistivity (RS) in targeting areas hosting different sulfidic mineralization zones in Nowchun Cu-Mo porphyry deposit, SE Iran. The C-V fractal model employed in this research in order to separate high and moderate sulfidic zones from low sulfidic zone and barren wall rocks in the deposit is corresponding to chargeability and resistivity. Results obtained from the C-V method indicate that there is a positive correlation between subsurface mineralization and sulfide mineralized zones; additionally, use of the C-V method based on geophysical data is recognized as an accurate approach for delineation of various mineralization zones in the depth for optimization of mineral exploration operation, particularly in porphyry deposits.

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The geochemistry of gossans associated with Sarcheshmeh porphyry copper deposit, Rafsanjan, Kerman, Iran: Implications for exploration and the environment

Cited by 100 publications

References 17 publications

Selection of Less Biased Threshold Angles for SAM Classification Using the Real Value–Area Fractal Technique

Selection of Less Biased Threshold Angles for SAM Classification Using the Real Value–Area Fractal Technique

A new stable downward continuation of airborne magnetic data based on Wavelet deconvolution

Application of concentration-volume fractal method in induced polarization and resistivity data interpretation for Cu-Mo porphyry deposits exploration, case study: Nowchun Cu-Mo deposit, SE Iran

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