Fusion of Lineament Factor (LF) Map Analysis and Multifractal Technique for Massive Sulfide Copper Exploration: The Sahlabad Area, East Iran

Ширази, Ареф; Hezarkhani, Ardeshir; Pour, Amin Beiranvand

doi:10.3390/min12050549

Cited by 17 publications

(9 citation statements)

References 47 publications

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“…Aeromagnetic geophysical data were utilized to investigate deep intrusive masses. Hidden fault systems in the area were also identified from the magnetic data [22]. The geophysical data used in this analysis provided information for potential mineralization in different levels (superficial, medium, and deep) in the study area.…”

Section: Methodsmentioning

confidence: 99%

“…For this purpose, two ETM+ scenes and two Sentinel-2 scenes were used, and the images from each dataset were mosaicked. Sentinel-2 and Landsat-7 data were successfully utilized to identify hydroxylbearing minerals, which are found in the alteration zones associated with ore mineralization in the metallogenic provinces [21,22]. Geological fieldwork was conducted in the study area during August 12th to 15th, the year 2021 and September 20th to 24th, the year 2022.…”

Section: Data Usedmentioning

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: Methodsmentioning

confidence: 99%

Section: Data Usedmentioning

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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“…The Inductively coupled plasma mass spectrometry (ICP-MS) method [64] was used to analyze geochemical samples collected from the study area. Zn, Cr, Ti, Mn, Sr, Ba, Au, As, Sb, Bi, Hg, W, Pb, Ni, Mo, Sn, Ag, Co, Fe and Cu were selected in this analysis.…”

Section: Geochemical Samplingmentioning

confidence: 99%

Geochemical Modeling of Copper Mineralization Using Geostatistical and Machine Learning Algorithms in the Sahlabad Area, Iran

Shirazi,

Hezarkhani,

Shirazy

et al. 2023

Minerals

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Analyzing geochemical data from stream sediment samples is one of the most proactive tools in the geochemical modeling of ore mineralization and mineral exploration. The main purpose of this study is to develop a geochemical model for prospecting copper mineralization anomalies in the Sahlabad area, South Khorasan province, East Iran. In this investigation, 709 stream sediment samples were analyzed using inductively coupled plasma mass spectrometry (ICP-MS), and geostatistical and machine learning techniques. Subsequently, hierarchical analysis (HA), Spearman’s rank correlation coefficient, concentration–area (C–A) fractal analysis, Kriging interpolation, and descriptive statistics studies were performed on the geochemical dataset. Machine learning algorithms, namely K-means clustering, factor analysis (FA), and linear discriminant analysis (LDA) were employed to deliver a comprehensive geochemical model of copper mineralization in the study area. The identification of trace elements and the predictor composition of copper mineralization, the separation of copper geochemical communities, and the investigation of the geochemical behavior of copper vs. its trace elements were targeted and accomplished. As a result, the elements Ag, Mo, Pb, Zn, and Sn were distinguished as trace elements and predictors of copper geochemical modeling in the study area. Additionally, geochemical anomalies of copper mineralization were identified based on trace elements. Conclusively, the nonlinear behavior of the copper element versus its trace elements was modeled. This study demonstrates that the integration and synchronous use of geostatistical and machine learning methods can specifically deliver a comprehensive geochemical modeling of ore mineralization for prospecting mineral anomalies in metallogenic provinces around the globe.

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“…They can be of economic significance because they frequently serve to concentrate ore deposits. Porphyry copper, Volcanic Massive Sulfide (VMS), Iron oxide-copper-gold (IOCG), skarn, hydrothermal and epithermal deposits are controlled by specific structural/lithological settings (e.g., [1][2][3][4][5][6][7]). Accordingly, the geological and geophysical (e.g., [8]) of a variety of ore deposits depends strongly on the analysis of geological structures at the regional and district scales.…”

Section: Introductionmentioning

confidence: 99%

Structural Analysis and Paleostress Evolution in the Imiter Silver Mining Region, Eastern Anti Atlas, Morocco: Implications for Mineral Exploration

et al. 2022

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Development and concentration of many ore deposits at the regional and district scales closely depend on structural geology, especially in polydeformed basements. The superposition of many deformation periods highlights the complexity of the structural context and expected potential location of mineralization zones. The formation and concentration of hydrothermal ore deposits is highly dependent on structural controls. On the NE flank of the Saghro massif (Eastern Anti-Atlas, Morocco), the Imiter silver mining region has been affected by multiple tectonic events since the Precambrian and throughout the Phanerozoic. In this investigation, a structural analysis of the different geological units revealed multi-stage deformation, beginning with the late Pan-African-Cadomian event, and ending with the last Cenozoic exhumation of the area. At least eight tectonic regimes have been identified. The Imiter basement, formed by the Cryogenian-early Ediacaran “flysch-like” Saghro Group, has been folded in low-grade metamorphic conditions, followed by an ENE-WSW brittle compressive event. These deformations occurred before to the early Ediacaran during the compressional and/or transpressional late Pan-African-Cadomian events (600–580 Ma). The unconformably overlaying deposition of the late Ediacaran Ouarzazate Group takes place in a WNW-ESE extensional setting and then involved in a NNW-SSE compressional event that occurred concurrently with a regional exhumation and erosion stages. A similar extensional event appears to have controlled the middle Cambrian sedimentation, the oldest Paleozoic deposits in this area. During the late Carboniferous, Variscan shortening was recorded by NW-SE transpressional deformation responsible for combined dextral strike-slip and southward thrusts. The Imiter silver mining region is part of the Moroccan Sub-Meseta Zone along with Paleozoic inliers of the Skoura and Tamlelt on the southern side of the High Atlas. The Mesozoic evolution began with the Late Triassic NNW-SSW transtensional tectonic regime with a northeast trending CAMP (Central Atlantic Magmatic Province) dyke during the Pangea breakup. Ultimately, the Imiter silver mining region experienced NNW-SSE Atlasic shortening during the uplift of the adjacent High Atlas. Over time, the direction of implemented tectonic stress and its effect on various geological units can elucidate the relationship between tectonism and hydrothermal silver mineralization in the Imiter region. In conclusion, structural analysis and investigation of paleostress development can be one of the most important factors for successful exploration plan and resource recovery in the Imiter region. An analysis of geological structures in determining feasible mineralization zones is crucial for future safe mining operation in the study area and can be extrapolated to other ore mining regions.

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Fusion of Lineament Factor (LF) Map Analysis and Multifractal Technique for Massive Sulfide Copper Exploration: The Sahlabad Area, East Iran

Cited by 17 publications

References 47 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

Geochemical Modeling of Copper Mineralization Using Geostatistical and Machine Learning Algorithms in the Sahlabad Area, Iran

Structural Analysis and Paleostress Evolution in the Imiter Silver Mining Region, Eastern Anti Atlas, Morocco: Implications for Mineral Exploration

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