Exploration
Sepideh Ghasemi; Ali Imamalipur; Samaneh Barak
Abstract
This investigation centers on the Qarah Tappeh copper deposit, situated in the northern region of West Azerbaijan province, approximately 15 kilometers northeast of Maku city. The primary objective of the study is to comprehensively examine the study area through the analysis of 253 lithogeochemical ...
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This investigation centers on the Qarah Tappeh copper deposit, situated in the northern region of West Azerbaijan province, approximately 15 kilometers northeast of Maku city. The primary objective of the study is to comprehensively examine the study area through the analysis of 253 lithogeochemical samples, and assessing reserves utilizing ordinary kriging, guided by subsurface data obtained from 14 boreholes totaling 909.2 meters. The concentration–volume (C–V) multifractal modeling approach was employed to estimate the deposit's reserve. The findings of this research project indicate an estimated 988,604 tons of the deposit with an average grade of 0.14%. Through the analysis of log–log plots within the C–V relationship, threshold values signifying various copper (Cu) concentrations were identified. These plots revealed a pronounced power-law correlation between Cu concentrations and their corresponding volumes, with arrows denoting four specific threshold values. Utilizing this analytical methodology, mineralized zones were classified into five distinct categories: high (>0.42%), above-average (0.35-0.42%), average (0.27-0.35%), below-average (0.14-0.27%), and low (<0.14%) mineralized zones.
Exploration
Samaneh Barak; Ali Imamalipour; Maysam Abedi
Abstract
The Sonajil area is located in the east Azerbaijan province of Iran. According to studies on the geological structure, the region has experienced intrusive, subvolcanic, and extrusive magmatic activities, as well as subduction processes. As a result, the region is recognized for its high potential for ...
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The Sonajil area is located in the east Azerbaijan province of Iran. According to studies on the geological structure, the region has experienced intrusive, subvolcanic, and extrusive magmatic activities, as well as subduction processes. As a result, the region is recognized for its high potential for mineralization, particularly for Cu-Au porphyry types. The main objective of this research work is to utilize the fuzzy gamma operator integration approach to identify the areas with high potential for porphyry deposits. To carry out this exploratory approach, it is necessary to investigate several indicator layers including geological, remote sensing, geochemical, and geo-physical data. The analysis reveals that the northeastern and southwestern parts of the Sonajil region exhibit a greater potential for porphyry deposits. The accuracy of the resulting Mineral Potential Map (MPM) in the Sonajil region was evaluated based on data from 20 drilled boreholes, which showed an agreement percentage of 83.33%. Due to the high level of agreement, certain locations identified in the generated MPM were recommended for further exploration studies and drilling.
Sh. Rezaei; A. Imam Ali Pour
Abstract
In the recent years, according to the difficulty of accurately measuring parameters and demarcation of earth sciences, attempts have been made to simplify the natural events for better investigation using geo-modelling. Modeling with intelligent methods is one of the new methods that has been considered ...
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In the recent years, according to the difficulty of accurately measuring parameters and demarcation of earth sciences, attempts have been made to simplify the natural events for better investigation using geo-modelling. Modeling with intelligent methods is one of the new methods that has been considered in this field in the recent years. In this work, the intelligent method of adaptive neural-fuzzy inference system (ANFIS) is used to predict the elements of lead and zinc located in the Guard Kooh area, north of Yazd province in Iran. Descriptive statistics of data and correlation matrices of studied elements are obtained using the SPSS software. After the data is standardized, imported to the MATLAB software, and the lead and zinc elements are predicted using the ANFIS-SCM method. In this method, 70% of the data (175 samples) are set as the training data, and the rest (75 samples) are set as the test data, which are randomly selected. Using the obtained results, it is found that the grade of the estimated elements in the studied area has a good accuracy and a high correlation with the grade of the analyzed elements. As a result, the ANFIS-SCM intelligent method is a useful and accurate method for estimating the lead and zinc elements.
M. Esmailzadeh; A. Imamalipour; F. Aliyari
Abstract
The main aim of mineral exploration is to discover the ore deposits. The mineral prospectivity mapping (MPM) methods by employing multi-criteria decision-making (MCDM) integrate the exploration layers. This research work combines the geological, alteration, and geochemical data in order to generate ...
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The main aim of mineral exploration is to discover the ore deposits. The mineral prospectivity mapping (MPM) methods by employing multi-criteria decision-making (MCDM) integrate the exploration layers. This research work combines the geological, alteration, and geochemical data in order to generate MPM in the Kighal-Bourmolk Cu-Mo porphyry deposit. The overlaying of rock units and fault layers was used to prepare the geological layer. The remote sensing and geological studies were employed in order to create an alteration layer. For generating the geo-chemistry layer, the stream sediment and lithogeochemical data were utilized. The lithogeochemistry layer was categorized into 9 ones including Cu, Mo, Bi, Te, the alteration indices (e.g. potassic, phyllic, and propylitic), and the geochemical zonality indices (e.g. Vz1 and Vz2). In addition, the stream sediment layer was categorized into 6 layers including Cu, Mo, Bi, Te, and the geochemical zonality indices (e.g. Vz1 and Vz2). By examination of the created layers, the consistency of the potential areas was verified by field surveys. Afterward, the weights were assigned to each layer considering the conceptual model of porphyry copper systems. Consequently, the layers were integrated by the fuzzy gamma operator technique, and the final MPM was generated. Regarding the generated MPM, 0.86% of the studied area shows a high potential porphyry mineralization, and these areas are proposed for the subsequent exploration drilling locations.
