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The aim of this study was to identify various mineralization zones especially supergene enrichment and hypogene zones in Kahang Cu porphyry deposit by higher than 60 million tonnes of sulfide ore with an average grade of 0.6% Cu and 70 ppm Mo, which is situated in central Iran, based on analyzing the subsurface data using a proposed power spectrum–volume (P–V) fractal method. P–V method is used in frequency domain provided by application of Fourier series transformation on assay data. Straight lines fitted through log–log plots, showing P–V relations for Cu, were employed to separate supergene enrichment and hypogene zones from leached zone and barren host rock in the deposit. In the proposed P–V fractal method, the identification of mineralization zones is based on power–law relationship within power spectrum field (S) and the rock volume hosting Cu mineralization at different grades by applying a V(≥ S) ∝ S− 2/β multifractal model. The subsurface data from deposit was analyzed by P–V fractal method and the results have been compared with geological models which included alteration and mineralogical models. The comparison shows that the interpreted zones based on the P–V fractal method have noticeable consistency to the geological models. The proposed P–V method is its either new approach to define zones in a mineral deposit and there was no professional software available to perform the relevant calculations; therefore, Fractal Power Spectrum–Volume (FPSV) software was programmed by the authors to achieve this goal.

In regional exploration programs, the distribution of elements in known mineral deposits can be used as a guide for the classification of deposits, search for new prospects and modeling ore deposit patterns. The Sanandaj–Sirjan Zone (SSZ) is a major metallogenic zone in Iran, containing lead and zinc, iron, gold, copper deposits. In the central part of the SSZ, lead and zinc mineralization is widespread and hitherto exploration has been based on geological criteria. In this study, we used clustering techniques applied to element distribution for classification lead and zinc deposits in the central part of the SSZ. The hierarchical clustering technique was used to characterize the elemental pattern. Elements associated with lead and zinc deposits were separated into four clusters, encompassing both ore elements and their host rock-forming elements. It is shown that lead and zinc deposits in the central SSZ belong to two genetic groups: a MVT type hosted by limestone and dolomites and a SEDEX type hosted by shale, volcanic rocks and sandstone. The results of elemental clustering were used for pattern recognition by the K-means method and the respective deposits were classified into four distinct categories. K-means clustering also reveals that the elemental associations and spatial distribution of the lead and zinc deposits exhibit zoning in the central part of the SSZ. The ratios of ore-forming elements (Sb, Cd, and Zn) vs. (Pb and Ag) show zoning along an E–W trend, while host rock-forming elements (Mn, Ca, and Mg) vs. (Ba and Sr) show a zoning along a SE–NW trend. Large and medium deposits occur mainly in the center of the studied area, which justify further exploration around occurrences and abandoned mines in this area. The application of a pattern recognition method based on geochemical data from known mineralization in the central SSZ, and the classification derived from it, uncover elemental zoning, identify key elemental associations for further geochemical exploration and the potential to discover possible target areas for large to medium size ore deposits. This methodology can be applied in a similar way to search for new ore deposits in a wide range of known metallogenic zones.

The purpose of this study was to identify the various mineralization zones especially supergene enrichment and hypogene in two different Iranian porphyry Cu deposits, based on subsurface data and by using the proposed concentration–volume (C–V) fractal method. The Sungun and Chah-Firuzeh porphyry Cu deposits, which are situated in NW and SE Iran, respectively, were selected for this study. Straight lines fitted through log–log plots showing C–V relations for Cu were employed to separate supergene enrichment and hypogene zones from oxidation zones and barren host rocks in the two deposits and to distinguish a skarn mineralized zone from the hypogene zone in Sungun deposit. In the proposed C–V fractal method, the identification of mineralization zones is based on power–law relationships between Cu concentrations and the volume of rocks hosting porphyry Cu mineralization. Separate subsurface data from the two deposits were analyzed by C–V fractal method and the results have been compared with geological models which included alteration and mineralogical models. The comparison shows that the interpreted zones based on the C–V fractal method are consistent with the geological models. The proposed C–V method is a new approach to defining zones in a mineral deposit and there was no commercial software available to perform the relevant calculations; therefore, a fractal concentration–volume (FCV) software was designed by the authors to achieve this goal.

Geochemical anomaly separation using the concentration-area (C-A) method at Kahang (Gor Gor) porphyry system in Central Iran is studied in this work. Lithogeochemical data sets were used in this geochemical survey which was conducted for the exploration for Cu mineralization in dioritic and andesitic units at Kahang Cu-Mo porphyry system. Similar surveys were also carried out for Mo and Au exploration in these rock units. The obtained results have been interpreted using rather extensive set of information available for each mineralized area, consists of detailed geological mapping, structural interpretation and alteration data. Anomalous threshold values for the mineralized zone were computed and compared with the statistical methods based on the data obtained from chemical analysis of samples for the lithological units. Several anomalies at a local scale were identified for Cu (224 ppm), Mo (63 ppm), and Au (31 ppb), and the obtained results suggests existence of local Cu anomalies whose magnitude generally is above 1000 ppm. The correlation between these threshold values and ore grades is clearly interpreted in this investigation. Also, the log-log plots show existence of three stages of Cu enrichment, and two enrichment stages for Mo and Au. The third and most important mineralization event is responsible for the presence of Cu at grades above 1995 ppm. The identified anomalies in Kahang porphyry system, and distribution of the rock types, are mainly monzodiorite and andesitic units, do have special correlation with Cu and monzonitic and dioritic rocks, especially monzodioritic type, which is of considerable emphasis. The threshold values obtained for each element are always lower than their mean content in the rocks. The study shows threshold values for Cu is clearly above the mean rock content, being a consequence of the occurrence of anomalous accumulations of phyllic, argillic and propyllitic alterations within the monzonitic and dioritic rocks especially in monzodioritic type. The obtained results were compared with fault distribution patterns which reveal a positive direct correlation between mineralization in anomalous areas and the faults present in the mineralized system. © 2009 Elsevier B.V.