The aim of this study is geostatistical analysis and detection of anomalous elements in the Bardaskan area (in geological map of Bardaskan on scale 1:100,000 which is provided by the GSI organization). The study area is located in Khorasan province of Iran. Due to the availability of lithogeochemical regular data in the region as well as the importance of exploration of metal minerals in order to simplify and summarize the geochemical map, geostatistical methods were used to identify the mineralization potential of the region. Initially, using single-variable and multivariate statistical methods, anomalous elements were separated. Then, the thresholds (various communities) for the titanium element that was most likely to be anomalous were identified. Using these limits, the discriminant analysis was applied to the elements. Titanium, iron and magnesium elements were identified as the main mineral elements in the region. These elements indicate mineralization in the mafic bed rocks. Finally the map of the concentration of titanium element was mapped across the region with Kriging interpolation method. As a result, two anomalies of the titanium element in the region were identified.
One of the Iranian copper deposits that is located east of Iran and also known as a primeval one in that area is Mesgaran Field. Old mining works have been clearly seen in the area. Iran is located on global copper belt and as a result it has numerous potential areas as copper deposits. The purpose of this study is identifying possible potentialities of copper mining in less developed regions of Iran with basic modern technologies. In this study, laboratory investigations of this field were done on samples via leaching and the cementation method. According to the study purposes, acid concentration, temperature, time and pulp density were selected as the main factors that were tested in leaching studies. Moreover, pH, temperature, time and the amount of iron powder were factors which were tested for copper cementation. Optimum conditions of leaching studies with 99.11% recovery rate were obtained after 120 grams per liter of H 2 SO 4 , 80 degrees Celsius, 2 hours and 100 grams per liter of solid to liquid. On the other hand, optimum conditions of cementation by iron powder were resulted at more than 95% with a pH of 3, 45 degrees Celsius, 1 hour and 1.5 times more than the stoichiometric equation of required iron powder amount to precipitate copper.
The Kivi area in the East Azerbaijan Province of Iran is one of the country’s highest-potential regions for metal element exploration. The primary goal herein was to process the data obtained from geochemical, geostatistical, and remote sensing tools (in the form of stream sediment samples and satellite images) to identify metallic mineralization anomalies in the region. After correcting the raw stream sediment geochemical data, single-variable statistical processing was performed, and Ti and Zn were identified as the elements with the highest degree of contrast. The relationship among these elements was further investigated using correlation and hierarchical clustering analyses. Principal component analysis was then applied to determine the principal components related to these elements, which were subsequently plotted on a regional geological map. Elements related to Ti and Zn were identified using threshold limits of anomalous samples determined via linear discriminant analysis. Lithological units and alteration patterns were detected through remote sensing investigations on Landsat-8 images. Stream sediment geochemical and remote sensing survey results identified anomalous areas of Ti and Zn in the eastern part of the study region. Our results indicate that Ti and Zn are good pathfinder elements for further exploratory investigation in this area.
In general, the purpose of the mineralization modeling is the advancement of a mineral exploration project and ultimately, the extractive design of a deposit, which is one of the most important stages in mining engineering. Mineralization modeling is divided into two general categories, superficial and deep modeling. In surface modeling, the aim is finding abnormal locations in terms of mineralization at the study area, which is commonly used in the early stages of exploration as one of the means for locating exploratory boreholes. After drilling in the study area with the aim of identifying mineralization and reserve estimation it is necessary to obtain deep mineralization position and its geometric features, using statistical and modeling methods. Using mathematical, statistical and modeling methods, we can predict the position of iron mineralization in places where drilling is not done and eventually reach a three-dimensional model of the mineral materials underground. As a case study, the deep information about the boreholes of the sheytoor mining area in Yazd province of Iran was investigated. Iron mineralization was modeled as 2D cumulative model and 3D block model, and the results were presented. Finally the geochemical threshold and the anomalous limit of iron element are calculated by concentration-volume (C-V) fractal method in this deposit. Geochemical threshold and the anomalous limit for Fe in this deposit are 24.7% and 34.3% respectively.
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