Hybrid Fuzzy-Analytic Hierarchy Process (AHP) Model for Porphyry Copper Prospecting in Simorgh Area, Eastern Lut Block of Iran

Khosravi, Vahid; Ширази, Ареф; Shirazy, Adel; Hezarkhani, Ardeshir; Pour, Amin Beiranvand

doi:10.3390/mining2010001

Cited by 20 publications

(6 citation statements)

References 33 publications

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“…To achieve this goal, the importance of ore mineralization factors must be determined. All exploratory/information layers were weighted in this regard [6,45]. The types of layers and created classes, along with the weight of the classes, are presented in Table 2.…”

Section: Fusion Of Exploratory/information Layersmentioning

confidence: 99%

“…Such fusion requires the utilization of Geographic Information System (GIS) techniques. The GIS system is designed to collect, analyze, store, update, and display information in the finest possible way [4][5][6]. Various methods can be used to fuse the exploratory layers derived from different sources to identify the potential zones of mineralization.…”

Section: Introductionmentioning

confidence: 99%

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Fusion of Remote Sensing, Magnetometric, and Geological Data to Identify Polymetallic Mineral Potential Zones in Chakchak Region, Yazd, Iran

et al. 2022

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Exploration geologists are urged to develop new, robust, and low-cost approaches to identify high potential zones related to underground/unexplored mineral deposits because of increased depletion of ore deposits and high consumption of basic metal production industries. Fusing remote sensing, geophysical and geological data has great capability to provide a complete range of prerequisite data to accomplish this purpose. This investigation fuses remote sensing data, such as Sentinel-2 and Landsat 7, aerial magnetic geophysical data, and geological data for identifying polymetallic mineralization potential zones in the Chakchak region, Yazd province, Iran. Hydrothermal alteration mineral zones and surface and deep intrusive masses, hidden faults and lineaments, and lithological units were detected using remote sensing, aerial magnetic, and geological data, respectively. The exploratory/information layers were fused using fuzzy logic modeling and the multi-class index overlap method. Subsequently, mineral potential maps were generated for the study area. Some high potential zones of polymetallic mineralization were identified and verified through a detailed field campaign and drilling programs in the Chakchak region. In conclusion, the fusion of remote sensing, geophysical, and geological data using fuzzy logic modeling and the multi-class index overlap method is a robust, reliable, and low-cost approach for mining companies to explore the frontier areas with identical geologic conditions that are alleged to indicate polymetallic mineralization potential.

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Section: Fusion Of Exploratory/information Layersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fusion of Remote Sensing, Magnetometric, and Geological Data to Identify Polymetallic Mineral Potential Zones in Chakchak Region, Yazd, Iran

et al. 2022

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“…In an inversion, we always look for a model that meets the real conditions governing the environment [48,49]. In all of the inversion methods, the initial model alternates so that the difference between the response of the model [50] and the actual data is minimized [51].…”

Section: Inversion Of Two-dimensional Resistivity and Ip Datamentioning

confidence: 99%

Geophysical Explorations by Resistivity and Induced Polarization Methods for the Copper Deposit, South Khorasan, Iran

Ширази¹,

Хезархани²,

Ширази³

et al. 2022

IZVESTIYA

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Link for citation: Adel Shirazy, Ardeshir Hezarkhani, Aref Shirazi, Timkin T.V., Voroshilov V.G. Geophysical explorations by resistivity and induced polarization methods for the copper deposit, South Khorasan, Iran. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2022, vol. 333, no. 3, рр. 99-110. In Rus The relevance. These are the first geophysics studies in the Mesgaran exploration area. Based on geological studies in the mineral zone, copper mineralization was proven. The mineralization type in this area was identified as Cyprus-type massive sulfide. The complexity of the geological structure determines the need to use geophysical research and forecasting methods for planning mining and drilling operations. The main aim of this study is the application of geophysical methods in the search for mineral deposits and modeling of the geological environment. Object: Mesgaran exploration area, South Khorasan province, Iran. Methods. In order to obtain more subsurface information, geophysical methods IP and Rs were used. Five profiles were designed and implemented for geoelectric surveys. Overall, five profiles (P1 to P5) were read as dipole-dipole arrays with 784 points. The profiles were taken east-west and north-south along parallel to the mineralization zones. The dipole-dipole array is designed with the parameters AB=MN=20 m, jump=20 m and up to 6 jumps for MN. Results. In general, four types of anomalies were identified in these investigations. Which to some extent revealed the association of anomalies with the types of rocks and mineralization of the study area: 1) anomalies with low electrical resistivity, as well as low polarity, often correspond to quaternary alluvial deposits; 2) abnormalities with high electrical resistance, and low polarity, which are consistent with limestone’s and are often superficial; 3) anomalies with high polarity and high resistance, which in the south of the profiles form altitude and correspond to the agglomerates; 4) anomalies with high polarity and higher relative resistance are associated with igneous masses, which are often composed of andesitic-basaltic rocks. Based on the position of the identified anomalies in the 5 profiles, the optimal location of the drills was determined.

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“…The most important discussion in the analysis of geochemical data is to determine the background threshold for each element in the region and to separate the background threshold from the anomaly of the relevant element (Cheng et al 1996, Khosravi et al 2022c,d, Shirazi et al 2018a, c, Shirazy et al 2022. Using statistical methods, the threshold concentration of geochemical elements is identified.…”

Section: Copper Threshold Limit Investigationmentioning

confidence: 99%

Geochemical relations among elements in stream sediment samples from Siojan Prospecting Area, Iran using geostatistical methods

Shirazi,

Shirazy,

Hosseini

et al. 2022

Ruhuna J. Sci.

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Stream sediment samples play an important role in identifying potential areas of metallic and non-metallic mineralization in mineral exploration studies. The relationship of geochemical elements with each other shows how the elements are distributed in the area. Also, by identifying related elements, sampling and targeted chemical analysis can be used in the next stages of exploration. The purpose of this study is to investigate the elements related to the copper element in the Siojan prospecting area, which is located in South-Khorasan province and 30 km northwest of Birjand city of Iran. In Siojan area, 120 stream sediment samples of a 60 square kilometer area were collected to detect geochemical anomalies and were consequently analyzed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS) for 45 elements. Preliminary geological studies showed that the studied area has copper mineralization potential, and therefore, copper was selected as the target element in this study. Copper trace elements were identified in the area and the results were used to identify copper mineralized anomalies. For the elemental analysis data, methods of Principal Component Analysis (PCA), Factor Analysis (FA), Hierarchical Cluster Analysis (HCA) and K-Means Clustering were performed to identify the relevant elements and relationships among them. Statistical analysis of the concentration of geochemical elements in the region revealed that copper and cobalt elements were identified as two elements of the same family in terms of geochemical genetics. The average value for copper and cobalt elements in the analyzed samples was 27.2 ppm and 15.5 ppm, respectively. Finally, the relationship between copper and cobalt elements was modeled as an equation using the K-Means Clustering algorithm.

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Hybrid Fuzzy-Analytic Hierarchy Process (AHP) Model for Porphyry Copper Prospecting in Simorgh Area, Eastern Lut Block of Iran

Cited by 20 publications

References 33 publications

Fusion of Remote Sensing, Magnetometric, and Geological Data to Identify Polymetallic Mineral Potential Zones in Chakchak Region, Yazd, Iran

Fusion of Remote Sensing, Magnetometric, and Geological Data to Identify Polymetallic Mineral Potential Zones in Chakchak Region, Yazd, Iran

Geophysical Explorations by Resistivity and Induced Polarization Methods for the Copper Deposit, South Khorasan, Iran

Geochemical relations among elements in stream sediment samples from Siojan Prospecting Area, Iran using geostatistical methods

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