Geochemistry最新文献

{"title":"Targeting porphyry Cu deposits in the Chahargonbad region of Iran: A joint application of deep belief networks and random forest techniques","authors":"Majid Keykhay-Hosseinpoor, Alok Porwal, Kalimuthu Rajendran","doi":"10.1016/j.chemer.2024.126155","DOIUrl":"https://doi.org/10.1016/j.chemer.2024.126155","url":null,"abstract":"Mineral prospectivity modeling (MPM) is a valid and progressively accepted predictive tool for mapping reproducible potential mineral exploration targets. In this study, a hybrid approach combining unsupervised deep belief networks with supervised random forest (DBN-RF) is performed to delineate potential exploration targets for porphyry Cu deposits in the Chahargonbad region of Iran. Firstly, a mineral system model for porphyry Cu deposits is established, and relevant targeting criteria are delineated based on comprehensive exploration datasets. Subsequently, within this hybrid framework, the DBN extracts deep implicit feature information, which is then utilized as input for the RF. The comparative results on the performance of the hybrid model and the RF model trained by the primary targeting criteria, in terms of the improved prediction-area plot, demonstrate that the DBN-RF prospectivity model outperformed the RF-generated model with an overall efficiency of 0.53. This hybrid model accurately identified 81.97 % of known Cu deposits within an investigation area of 18.03 %, with primary trends aligned with the primary faults and volcanic units of the region. This study demonstrates effective performance of DBN-RF in identifying exploration targets for porphyry Cu deposits at regional scale and also highlights the potential of deep learning-based methods for successful MPM.","PeriodicalId":12522,"journal":{"name":"Geochemistry","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning models to predict rare earth elements distribution in Tethyan phosphate ore deposits: Geochemical and depositional environment implications","authors":"Nasreddine Tahar-Belkacem, Ouafi Ameur-zaimeche, R. Kechiched, Abdelhamid Ouladmansour, S. Heddam, David A. Wood, Roberto Buccione, Giovanni Mongelli","doi":"10.1016/j.chemer.2024.126128","DOIUrl":"https://doi.org/10.1016/j.chemer.2024.126128","url":null,"abstract":"","PeriodicalId":12522,"journal":{"name":"Geochemistry","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141048440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temporal constraints on magmatic evolution of Acıgöl Bimodal Volcanic Field (Nevşehir, Türkiye)","authors":"H. E. Çubukçu, E. Aydar, Lutfiye Akin, E. Şen","doi":"10.1016/j.chemer.2024.126129","DOIUrl":"https://doi.org/10.1016/j.chemer.2024.126129","url":null,"abstract":"","PeriodicalId":12522,"journal":{"name":"Geochemistry","volume":"1986 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141027620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mineral chemistry and P–T conditions of the winchite-bearing metabasic rocks in the NE edge of the Menderes Massif (Western Türkiye)","authors":"Zeynep Özbey, Namık Aysal, Şemsettin Caran, Fatma Şişman Tükel, Kıymet Deniz Yagcioglu, Mehmet Yesiltas, İsak Yılmaz","doi":"10.1016/j.chemer.2024.126126","DOIUrl":"https://doi.org/10.1016/j.chemer.2024.126126","url":null,"abstract":"The Menderes massif is a large metamorphic crystalline complex located in western Turkey. The massif consists of late Neoproterozoic basement (core) rocks and Palaeozoic - Cenozoic cover units that have undergone by high- and low-grade polyphase metamorphisms. Palaeozoic to Mesozoic cover units cropped out in the NE edge of the massif (east of Sivaslı) are overlaid tectonically by upper Cretaceous meta-ophiolitic rocks. The meta-ophiolitic unit comprises blocks mainly of metabasalt, metagabbro, metadiorite and metaultramafite within an intensively sheared serpentinite matrix. It also includes blocks of epidote-actinolite-schist and tremolite-actinolite-schist, which originated from basic rocks, as well as chlorite schist blocks, which originated from ultramafic rocks. Sodic-calcic amphiboles recorded in the samples of metabasalt block taken from the marble-metabasalt block boundary, at the tectonic contact where the meta-ophiolitic rocks overlap the underlying marble sequence. Sodic-calcic amphiboles were classified into winchite and ferri-winchite with relatively homogeneous Si (7.35–8.01 a.p.f.u.), and X (0.69–0.80) values. P-T conditions were estimated to be around 300–400 °C and 5–6 kb based on the mineral chemical analyses of the sodic-calcic amphiboles. According to these values, the NE edge of the Menderes Massif must have undergone metamorphism under a medium-pressure (MP) greenschist facies.","PeriodicalId":12522,"journal":{"name":"Geochemistry","volume":"66 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141059908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"3D mineral prospectivity modeling using multi-scale 3D convolution neural network and spatial attention approaches","authors":"Xiaohui Li, Yuheng Chen, Feng Yuan, Simon M. Jowitt, Mingming Zhang, Can Ge, Zhiqiang Wang, Yufeng Deng","doi":"10.1016/j.chemer.2024.126125","DOIUrl":"https://doi.org/10.1016/j.chemer.2024.126125","url":null,"abstract":"A significant proportion of recent mineral exploration has increasingly focused on the targeting of deep-seated orebodies. Mineral prospectivity modeling is one of the more important approaches that facilitates exploration targeting and the mitigation of risks associated with mineral exploration, particularly under cover. Recent advances in 3D mineral prospectivity modeling enable the effective extraction of predictive information from three-dimensional geological models, enabling more accurate exploration targeting of deep-seated orebodies. These advancements have synergized with deep learning approaches to improve the efficiency of mineral exploration based on nonlinear and multi-layer sensing attributes, effectively enabling the identification and extraction of key relationships between 3D predictive maps and mineralization. The main deep learning method used for 3D mineral prospectivity modeling is convolutional neural network (CNN) modeling. However, this research typically does not consider the multiscale features of geological structures, meaning further improvements can be made to this modeling approach. This paper introduces a multi-scale 3D convolutional neural network model (3D CNN) incorporating a spatial attention mechanism and an Inception module (MSAM-CNN) for 3D mineral prospectivity modeling. By integrating Inception modules and spatial attention mechanisms, the network's capability to identify multi-scale geological features and delineate key predictive areas is significantly enhanced compared to typical CNN approaches. This new approach provides further improvement in the accuracy and generalization capability of 3D mineral prospectivity modeling. To evaluate the effectiveness of this model, we undertook 3D mineral prospectivity modeling within the area of the Baixiangshan iron deposit, in the Ningwu Basin of the Middle-Lower Yangtze River Metallogenic Belt, China. The results show that the multi-scale 3D convolutional neural network model is remarkably robust and has good generalization capabilities. The approach can also can effectively delineate targets within the deep and peripheral areas of the deposit, providing targets for future exploration. The addition, performance indicators, ROC curve, and Capture-Efficiency curve generated during this modeling consistently demonstrate that the MSAM-CNN model outperforms Inception-enhanced CNN (M-CNN), CNN, Random Forest (RF), and Support Vector Machine (SVM) models. All of this indicates that MSAM-CNN approaches can effectively extract 3D spatial features within 3D predictive maps during 3D mineral prospectivity modeling better than other approaches that are commonly used, indicating that thius approach represents a promising tool for the accurate and precise identification of targets during future exploration for deep-seated mineralization.","PeriodicalId":12522,"journal":{"name":"Geochemistry","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140927553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lithium exploration targeting through robust variable selection and deep anomaly detection: An integrated application of sparse principal component analysis and stacked autoencoders","authors":"Saeid Esmaeiloghli, Alexandre Lima, Behnam Sadeghi","doi":"10.1016/j.chemer.2024.126111","DOIUrl":"https://doi.org/10.1016/j.chemer.2024.126111","url":null,"abstract":"","PeriodicalId":12522,"journal":{"name":"Geochemistry","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140205247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Significance of highly siderophile element and Re–Os isotope systematics in global carbonatites","authors":"Ladislav Polák, Lukáš Ackerman, Tomáš Magna, Vladislav Rapprich, Michael Bizimis, R. Johannes Giebel, Sven Dahlgren, Shrinivas Viladkar","doi":"10.1016/j.chemer.2024.126095","DOIUrl":"https://doi.org/10.1016/j.chemer.2024.126095","url":null,"abstract":"","PeriodicalId":12522,"journal":{"name":"Geochemistry","volume":"44 1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139948729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stable isotope geochemistry evidences from fossil carbonate and sulfur minerals on the origin of geothermal water, Kızıldere Geothermal Field, Western Turkey","authors":"Gülcan Bozkaya, Ömer Bozkaya, Taylan Akın","doi":"10.1016/j.chemer.2024.126089","DOIUrl":"https://doi.org/10.1016/j.chemer.2024.126089","url":null,"abstract":"<p>The Kızıldere geothermal field, located at the eastern part of the Büyük Menderes graben in Western Turkey, is the most important geothermal reservoir suitable for electricity generation. Current and fossil fumaroles and alteration zones are directly related to the tectonic zones influenced by N-S directional extension since Miocene period. Associated to fossil geothermal activities carbonate (calcite, dolomite) and sulfate (gypsum, anhydrite) minerals were occurred in the form of void/crack fill and bands/lenses parallel to bedding of Neogene clastic and carbonate rocks. The carbon (δ¹³C_PDB ‰) and oxygen (δ¹⁸O_PDB ‰) isotope compositions of hydrothermal calcites and dolomites and sulfur (δ³⁴S_CDT) and oxygen (δ¹⁸O_SMOW) isotope compositions of gypsum and anhydrites are analyzed first time and correlated current geothermal water composition. The carbon and oxygen isotope data of calcites and dolomites have similar carbon but different oxygen isotope composition which increases in the direction of surface calcite – drill cuttings calcite – drill cuttings dolomite – surface dolomite. The isotope compositions of calcite and dolomite minerals range between limestone and marble host rock compositions and indicate the carbonate mineral-forming fluids originated from dissolution of carbonate rocks during the circulation of hot geothermal waters. According to the calcite-CO₂ and dolomite-CO₂ isotopic fractionation data for the 0–300 °C temperature range, the fossil isotope composition is higher than the composition of current CO₂ and reflects relatively lower temperature conditions. The isotope compositions of gypsum and anhydrite minerals indicate that hot thermal waters dissolved terrestrial evaporites and formed a sulfur-rich geothermal solution, and hydrothermal gypsum and anhydrite precipitated from this solution. The δ³⁴S_CDT compositions of hydrothermal gypsum and anhydrites are similar to the current geothermal water compositions. Stable isotope geochemistry data of hydrothermal carbonate and sulfate minerals in the Kızıldere geothermal field have shown that the fluids forming these minerals were originated from host rocks instead of magmatic volatiles.</p>","PeriodicalId":12522,"journal":{"name":"Geochemistry","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139755129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"U-Pb and Re-Os geochronology and lithogeochemistry of granitoid rocks from the Burnthill Brook area in central New Brunswick, Canada: Implications for critical mineral exploration","authors":"N. Mohammadi, David R. Lentz, K. Thorne, Jim Walker, Neil Rogers, Brian L. Cousens, C. McFarlane","doi":"10.1016/j.chemer.2024.126087","DOIUrl":"https://doi.org/10.1016/j.chemer.2024.126087","url":null,"abstract":"","PeriodicalId":12522,"journal":{"name":"Geochemistry","volume":"60 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139873134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monazite and zircon U Pb and muscovite 40Ar/39Ar geochronology constraints on the timing of magmatism and mineralization in the Huxingshan tungsten deposit, South China","authors":"Lei Zhu, Bin Li, Angui Lu, De-Xian Zhang, Jun-Wei Xu","doi":"10.1016/j.chemer.2024.126091","DOIUrl":"https://doi.org/10.1016/j.chemer.2024.126091","url":null,"abstract":"","PeriodicalId":12522,"journal":{"name":"Geochemistry","volume":"32 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139890695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}