Exploration and Mining
Saeid Ghasemzadeh; Abbas Maghsoudi; Mahyar Yousefi
Abstract
The Baft district in Kerman province is located in the southeastern segment of the Urumieh-Dokhtar magmatic arc. This arc is characterized by thick accumulations of Cenozoic plutonic and volcanic rocks and provide favorable conditions to the development of hydrothermal systems and mineral deposition, ...
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The Baft district in Kerman province is located in the southeastern segment of the Urumieh-Dokhtar magmatic arc. This arc is characterized by thick accumulations of Cenozoic plutonic and volcanic rocks and provide favorable conditions to the development of hydrothermal systems and mineral deposition, in particular porphyry copper mineralization. For mineral prospectivity mapping (MPM) to delineate prospective areas some individual maps of evidence including distance to intrusive contacts, fault density, distance to hydrothermal alterations and multi-element geochemical signature were generated. Spatial evidence values in each map were transformed using a logistic function of unbounded values into the [0,1] range. Thus continuous maps of fuzzy evidence layers were integrated using geometric average function. To evaluate results of final potential map a data-driven prediction-area was used. The results showed that for the geometric average prospectivity model, 87% of the known mineral occurrences are predicted in 13% of the study area. Hence, this method can be utilized for mineral prospectivity mapping to delineate target areas for further exploration of a certain deposit-type.
S Kianpouryan; M Farahmandian; M Karimi; A Bahroudi
Abstract
Considering the existence of many copper deposits in Iran and the importance of their exploration, mineral potential mapping with high accuracy is an important tool. The process of mineral potential mapping is a cumbersome process which can be performed using different methods. The Hybrid Neuro-Fuzzy ...
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Considering the existence of many copper deposits in Iran and the importance of their exploration, mineral potential mapping with high accuracy is an important tool. The process of mineral potential mapping is a cumbersome process which can be performed using different methods. The Hybrid Neuro-Fuzzy approach is one of the powerful ones for mineral potential mapping in which both conceptual and empirical components of earth science information are employed, so using both components simultaneously increase the confidence interval. In this paper we were used Adaptive Neuro-Fuzzy Inference System (ANFIS) for mineral potential mapping in Chahar-Gonbad area 1:100000 sheet, Kerman province. The database consists of geology, geochemistry, airborne radiometric, regional faults, ETM+ data, and 22 deposit and occurrence locations. At first, the factor maps were provided in GIS environment in which each cell in the grid data represents a 100 m square on the ground, and then the outputs of this layer were used for training the network. As this technique requires some data for training the network, the occurrence locations were used for training and checking points. Since, the training points were not enough for this procedure, we assigned buffer from 100 to 1000 m for occurrence locations. The results showed that when the buffer is 500 m, the best classification which ANFIS identify about 80% of the known deposits and occurrence locations in high favorability zones.
S Alaei Moghadam; M Karimi; M Mesgari; N Saheb Zamani
Abstract
Due to the extensive areas of potential mineral reserves in the country, it seems necessary to have a systematic approach to identify and convert indices of mineral deposits into mines. Existing various conceptual models of mineral deposits, variety of both quantitative and qualitative data to explore ...
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Due to the extensive areas of potential mineral reserves in the country, it seems necessary to have a systematic approach to identify and convert indices of mineral deposits into mines. Existing various conceptual models of mineral deposits, variety of both quantitative and qualitative data to explore mineral deposits and the expertise and different interests, cause the mineral potential mapping process to be very complicated. So far, various methods such as the overlap index, fuzzy logic, neural networks and weights of evidence are used for modeling this complexity. Consideration the fuzzy nature of mineral exploration in the process of modeling exploratory data, applying expert knowledge and flexibility for all types of mineral deposits in the form of an integrated system is essential. Compared with other methods fuzzy inference system has stated characteristics. To verify this, in this study, a fuzzy inference system for modeling mineral potential was proposed and for the Chah Firoozeh copper deposit was implemented. The main stages of this research include fuzzifying factor maps using the appropriate membership functions and linguistic variables, combining factor maps using fuzzy inference (by creating if_then fuzzy rules database and using an appropriate decision-making model) and generating mineral potential map with defuzzification output.
In the resulted mineral potential map, porphyry copper mineralization prone area is located in the central regions with north-south extension. For evaluation, 24 exploration boreholes in the area are complying with the mineral potential map. Based on the four classification types of mineral potential map, the compliance rate was calculated as 63.64%, 75%, 63.95% and 80.23%. Obtained mineral potential map is more accurate in the very low potential areas and 81.52% of the holes with very low state are located properly. In addition, resulted mineral potential map was compared with the mineral potential map generated using only fuzzy operators and without fuzzifying factor maps. The comparison shows that the mineral potential map that was generated using fuzzy inference system, in four classifications used in this study has 6% greater compliance with the exploration boreholes in average.
Mahyar Yousefi; R. Gholami; A. Kamkarr-Ruhani; A. Moradzade
Abstract
In the systematic exploration plan for prospecting the mineral deposit, we can design an exploration algorithm using the modeling of known mineral occurrences. Such an algorithm is a key to recognize the area where is high probability of mineralization, reduce the risk of exploration and increases the ...
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In the systematic exploration plan for prospecting the mineral deposit, we can design an exploration algorithm using the modeling of known mineral occurrences. Such an algorithm is a key to recognize the area where is high probability of mineralization, reduce the risk of exploration and increases the probability of exploration success. In this paper, we introduce an algorithm for optimizing mineral potential model and target generation in the exploration operation with focus on the gold exploration. In this way, after descriptive and conceptual modeling of gold deposit, all of the characteristics that can be used as an exploration criterion have been identified and assembled as a target model. Then, various data layers have been used to generate significant evidential maps. Then all of the evidential maps should be combined to generate mineral potential model (map) of the mineralization type sought. Recent map shows the probability location of gold mineralization as target area. Finally an algorithm has been introduced in which all of the exploration stage and methods have been identified base on priority.
