فصلنامه زمین شناسی اقتصادی
سال شانزدهم شماره 3 (پیاپی 42، پاییز 1403)

The Kalatehno prospecting area is located at 23 Km northwest of Gonabad, Khorasan Razavi province, and north of the Lut Block. The geology of the area includes subvolcanic units with monzonite, monzodiorite and diorite porphyry, volcanic units, pyroclastic and Quaternary units. Mineralization occurred epigenetically and as vein, in volcanic and pyroclastic units. The ore vein extends to 100-300 m along, and 1-3 m wide. The hypogene mineralization is characterized by chalcopyrite as the main ore mineral and minor amount of bornite, pyrite, galena with quartz as gangue minerals. Malachite, chrysocolla, chalcocite and secondary iron oxides (hematite, goethite) constitute the mineralization of oxidation and supergene zone. The main alteration in the area are silicification propylitic and argillic. According to geochemical study, the amount of copper is between 750 to 19500 ppm, Pb from 62.8 to 30400 ppm and Zn from 258 to 1800 ppm. Based on the structural control of mineralization, alteration types, mineralization and geology features, the Kalatehno deposit is similar to vein type copper deposits.

The Qeynarjah-Angouran district is located at the intersection of the Urumieh-Dokhtar and the Sanandaj-Sirjan structural zones in NW Iran. In this area, intrusive suites of Middle Triassic-Upper Jurassic age are exposed, including the Gharavol-Khane quartz diorite, the Kuh-e Belghais granite porphyry, and the Qeynarjeh granodiorites. Whole-rock geochemical data and crystal chemistry of apatite were analyzed to obtain the geochemical-metallogenic evolutions of magma and compare fertility using trace element interpolation. These intrusive suites with zircon saturation temperature (TZr) less than 900 °C and meta-aluminous to slightly peraluminous nature (A/CNK = 0.5-1.2) belong to the calc-alkaline series, which is evidence of I-type granitoids (Na2O/K2O = 0.8-2.0) in subduction zones (enrichment of LILE compared to HFSE along with P, Nb and Ti anomalies). ΣREE concentration, LREE/HREE ratio, and LILE content (including Rb, Ba, Th, U, K and Pb elements) in the Qeynarjeh granodiorites are determined to be twice as much as other intrusive suites, which are placed at a depth of 20 to 30 km of crust (Sr/Y=10-20), Rb/Sr ratio of whole-rock less than 0.4 and FeO content about 4 wt.% indicate characteristics of ore-bearing skarns. EPMA results show apatite crystals from Gharavol-Khane quartz diorite with high fluorine concentration (F = 2.2-2.7 wt.%) have been formed directly from the parent magma and Kuh-e Belghais granite porphyry apatites with high chlorine variation (Cl = 0.52-0.65 wt.%) is a result of large fluid-rock interactions between the granite porphyries and hydrothermal fluids. Overall, the Qeynarjeh granodiorites and the Gharavol-Khane quartz diorites show the most similarity with the petrogenesis-metallogenesis pattern of the iron skarn-causative intrusions.

Iran is considered one of the countries with a relative advantage in the field of mining and related industries due to its important mineral resources and reserves. This issue increases the importance and priority of development programs in the mining and mineral industries sector. Copper, after steel, ranks second among the major metals in terms of value-added production in the world. Iran, with a reserve of about 34 million tons of copper, owns 4% of the world's copper reserves. This article examines the analytical and comparative analysis of copper industry development programs in Iran and India. Although both countries have started their own development programs in the copper industry almost simultaneously, India was ranked among the top economic powers in Asia in 2018 compared to Iran. On the other hand, with some economic growth indicators surpassing China, some analysts believe that this trend may continue and India may achieve growth similar to China and even replace it. On this basis, India’s strategic plans in the field of copper can greatly help in formulating strategic plans in Iran’s copper industry. According to studies conducted in Iran, the most important challenges in the copper industry include increasing the amount of government salaries and export duties, non-entry of mining and industrial machinery, round-the-clock laws, and fluctuations in exchange rates and inflation. This research has examined the damage and analysis of the strengths and weaknesses of Iran’s copper industry program, reviewed the current situation and copper industry development programs, compared it with India, and addressed the challenges ahead. Finally, solutions have been proposed for the development of this important industry.

Middle Miocene igneous rocks are located in the Northeast of Joveinan, the middle part of the Urumieh-Dokhtar Magmatic Belt. The igneous rocks have intruded into the Eocene volcano-sedimentary units. The rocks consist of diorite, quartzdiorite, and monzodiorite. They contain plagioclase, hornblende, biotite, pyroxene, orthoclase, quartz, and opaque minerals, and have granular to porphyroid textures. Field and petrographic evidence such as a lack of thermal metamorphism and graphic texture suggests that the rocks crystallized at a shallow depth. The rocks exhibit characteristics of I-type granitoids and a calc-alkaline nature with metaluminous affinities. The enrichment of large ion lithophile elements (LILEs) and the negative anomaly of Ta, Nb, and Ti elements in the primary mantle normalized diagram demonstrate subduction-related magmatism in the continental arc setting. The chondrite normalized pattern of the rocks (Lan/Ybn= 3.68-5.64) suggests a low degree of partial melting and the absence of garnet as a permanent phase in the source region. Based on the petrological data, the parental magma has been produced in the subduction setting of the collisional zone. The primary magma resulting from the partial melting of the subducted lithospheric mantle intruded into the continental crust. The magma underwent numerous changes and evolution during ascent and created the intrusive rocks of Northeast Joveinan.

Identification of geochemical anomalies plays an essential role in mineral exploration. Recent research investigations have shown that Machine Learning (ML) algorithms can identify geochemical anomalies associated with mineralization that represent targets for mineral exploration. Machine Learning algorithms are widely used in various fields due to their strong capability to extract and display high-level features of training samples. Autoencoder networks show a high ability to identify geochemical anomalies. In this study, the combined method of autoencoder network with the fractal concentration-area method was used to identify geochemical anomalies. First, using multivariate factor analysis, the elements barium, lead, zinc, copper, gold, iron, gold and arsenic were selected as indicators. Subsequently, the uni-element geochemical maps of these elements were prepared, and to standardize the maps in terms of minimum and maximum values, all maps were fuzzified and scaled. Using the fuzzy gamma operator, uni-element geochemical maps were combined. Then the resulting map applied the deep autoencoder method with eight layers of encoder and decoder were reconstructed. Finally, a mineral prospectively map was prepared for the potential area using the concentration-area fractal method. The mixed model proposed in this study introduces the region with high mineralization potential northeast of the studied area.

In recent years, two-dimensional geoelectrical surveys have become one of the common and conventional methods in mineral exploration, groundwater resources investigations, engineering geophysics, archeology, etc. However, in some cases, these studies could not reach the targeted and expected results, and sometimes the geophysical results obtained have had a significant distance from the results obtained from direct studies such as drilling, etc. In this article, authors try to comprehensively analyze some factors that cause errors in two-dimensional geoelectrical studies, and on the other hand, state solution for minimizing the amount and severity of the discussed errors. Also, it has been tried to provide practical solution and approach for minimizing the error factors by a deep understanding of the source and mechanism of error factors. Finally, a case study in which geoelectrical data has been acquired by applying that new approach has been presented.