Journal of Economic Geology (Nov 2017)
Geochemical and geophysical investigations, and fluid inclusion studies in the exploration area of Zafarghand (Northeast Isfahan, Iran)
Abstract
Introduction Urumieh-Dokhtar Magmatic Arc (UDMA) is a good prospective area for Cu, Cu-Mo and Cu-Au deposits (Fig. 1A and B). The Zafarghand district is located in the central part of the UDMA and the northeastern Isfahan. The present study concerns geological observations, alteration investigations, geochemical data and fluid inclusion studies. The purpose of the research is to identify geochemical anomalies and source of metals in this area. Geochemical anomalies for mineralizing elements and element associations were identified by using statistical analysis methods. Additionally, these results together suggest a site for exploration drilling in this study area. Materials and methods We collected 186 samples (rock) along multi-cross sections oriented perpendicular to the strike of the South -Ardestan fault (Fig. 2).Trace element concentrations were determined by the ICP-MS technique in Amdel laboratory (Australia). Thin sections and doubly polished sections (100–200 µm thick) from quartz veins were prepared from samples collected from the Zafarghand district in the University of Isfahan. Heating and freezing experiments on fluid inclusions were performed as defined (by Goldstein and Reynolds (1994) on a Linkam THM600 stage. Results Igneous rocks in the Zafarghand area are dominated by the Eocene and post Eocene acidic-intermediate rocks that include dacite, rhyodacite and andesite associated with diorite, quartz diorite and microdiorite intrusions. The present investigations indicate that all rocks of the Zafarghand district exhibit a variety of alterations. Hydrothermal alterations include phyllic, potassic, silicification, and argillic with widespread propylitic. The mineralization consists of malachite, azurite, hematite, and goethite, rare amounts of magnetite, pyrite, and chalcopyrite. Numerical traditional statistical analysis techniques have been applied to interpret the geochemical data of the study area. These methods are aimed at producing maps resulting from the detecting of anomaly or threshold values from the background (Aitchison, 1986; Sun et al., 2009). Anomalies of Cu, Mo, Au, Ag, Pb, Zn and Sb were determined by Mean + 2 standard deviation (Cheng, 2007; Zuo et al., 2009; Chen et al., 2016). Geochemical maps for these elements in rocks and soils (Fig. 4) show significant contrasts in haloes concentrations within the diorite and dacite rocks in the southeast of the study area. The addition of concentrations in rocks is suggested indicating that a district-scale geochemical present is confined to either base metals or precious metals. The obtained fluid inclusion results are compiled in Table 3. Primary fluid inclusions in quartz mostly consist of two-phases and rarely three phases. Homogenization temperatures (Th) in quartz samples represent wide variations from 123° to 550°C. They were classified according to the mode of homogenization into two immiscible types (Fig. 8): These are early inclusions stage with a high Th (between 328° and 550°C) and late stage inclusions with a low Th (between 123° and 390°C). The salinity measured using the equation of Bodnar (1993) for fluid inclusions varies from 1.15 to 43 eqv.wt% NaCl. It was divided into two groups including high salinity (32 to 43 eqv.wt% NaCl) and low salinity (1.15 to 5.16 eqv.wt% NaCl). Discussion The predictive results obtained by field observations, geochemical and micro thermometric studies are in good agreement with the known deposits. Geochemical anomalies are associated with phyllic and rare silicified altered rocks. The host rocks of anomalies are mainly dacite and diorite, respectively with an Eocene and younger age. District-scale geochemical patterns of several elements (Cu, Mo, Au, Pb, Ag, As, and Sb) in the surface coincide with the southeastern area and can be used to explore for epithermal and/or porphyry-type deposits. Anomalies of Cu and Mo are suitable for targeting Cu-Mo mineralization. Weak anomalies associated with Au concentration should also be combined with other exploration methods to identify mineralization in the Zafarghand district. Quartz veins are classified as V1 and V2 (Fig. 3G). Based on the properties of quartz hydrothermal fluids in the Zafarghand district, they are interpreted to have evolved in two-types of fluid fields (Fig. 7): - Stage 1 fluid inclusion: This inclusion included 32 to 43 wt percent NaCl eqv (high salinity) and homogenizing between 328° and 550°C. Primary quartz in stage 1 veins (V1) is poor inclusion and associated with sulfide minerals. It can be represented by fluids trapped during aporphyry- system episode. - Stage 2 fluid inclusion. This inclusion typically contains <5 wt percent NaCl eqv (low salinity) and homogenizing between 123° and 391°C. Quartz in stage 2 veins (V2) is characterized by milky color and inclusion rich. Low temperature, low salinity fluid inclusions demonstrate the last hydrothermal event. A possible origin for vapor-liquid inclusions in quartz veins (V2) could be explained by mixing of magma-related fluids with ground water. References Aitchison, J., 1986. The Statistical Analysis of Compositional Data. Chapman and Hall, London, 416 pp. Bodnar, R.J., 1993. Revised equation and table for determining the freezing point depression of H2O-NaCl solutions. Geochimica et Cosmochimica Acta, 57(3): 683–684. Chen, J., Chen, R., Mao, Z., Yang, H., Zhang, Ch. and Han, R., 2016. Regional mineral resources assessment based on rasterized geochemical. Ore Geology Reviews, 74: 15–25. Cheng, Q., 2007. Mapping singularities with stream sediment geochemical data for prediction of undiscovered mineral deposits in Gejiu, Yunnan Province, China. Ore Geology Reviews, 32(1-2): 314–324. Goldstein, R.H. and Reynolds, T.J., 1994. Systematics of fluid inclusions in diagenetic minerals: SEPM Short Course 31. Society for sedimentary geology, United states of America, 213 pp. Sun, X., Deng, J., Gong, Q., Wang, Q., Yang, L. and Zhao, Z., 2009. Kohonen neural network and factor analysis based approach to geochemical data pattern recognition. Journal of Geochemical Exploration, 103(1): 6–16. Zuo, R., Cheng, Q., Agterberg, F.P. Xia, Q., 2009. Application of singularity mapping technique to identification local anomalies using stream sediment geochemical data, a case study from Gangdese, Tibet, Western China. Journal of Geochemical Exploration, 101(3): 225–235.
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