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.
{"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}
Pub Date : 2024-05-01DOI: 10.1016/j.chemer.2024.126128
Nasreddine Tahar-Belkacem, Ouafi Ameur-zaimeche, R. Kechiched, Abdelhamid Ouladmansour, S. Heddam, David A. Wood, Roberto Buccione, Giovanni Mongelli
{"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}
Pub Date : 2024-05-01DOI: 10.1016/j.chemer.2024.126129
H. E. Çubukçu, E. Aydar, Lutfiye Akin, E. Şen
{"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}
Pub Date : 2024-04-26DOI: 10.1016/j.chemer.2024.126126
Zeynep Özbey, Namık Aysal, Şemsettin Caran, Fatma Şişman Tükel, Kıymet Deniz Yagcioglu, Mehmet Yesiltas, İsak Yılmaz
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.
门德斯地块是位于土耳其西部的一个大型变质结晶综合体。该山丘由新近纪晚期基底（核心）岩石和古生代-新生代覆盖层单元组成，经历了高、低级多相变质作用。地块东北边缘（西瓦斯利以东）的古生代至中生代覆盖层在构造上被上白垩世的元玢岩所覆盖。元闪长岩单元主要由偏闪长岩、辉长岩、辉绿岩和辉长闪长岩岩块组成，其基质为密集剪切的蛇纹岩。它还包括源自基性岩的闪长岩-阳起石-片岩和透闪石-阳起石-片岩岩块，以及源自超基性岩的绿泥石片岩岩块。钠钙闪石记录在大理岩-元青岩岩块边界的元青岩岩块样本中，即元青岩与底层大理岩层重叠的构造接触处。钠钙闪长岩分为绞长岩和铁闪长岩，其 Si 值（7.35-8.01 a.p.f.u.）和 X 值（0.69-0.80）相对均匀。根据钠钙闪长岩的矿物化学分析，P-T条件估计约为300-400 °C和5-6 kb。根据这些数值，门德列斯山丘的东北边缘一定是在中压（MP）绿泥石面下发生变质作用的。
{"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}
Pub Date : 2024-04-26DOI: 10.1016/j.chemer.2024.126125
Xiaohui Li, Yuheng Chen, Feng Yuan, Simon M. Jowitt, Mingming Zhang, Can Ge, Zhiqiang Wang, Yufeng Deng
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.
{"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}
Pub Date : 2024-02-23DOI: 10.1016/j.chemer.2024.126095
Ladislav Polák, Lukáš Ackerman, Tomáš Magna, Vladislav Rapprich, Michael Bizimis, R. Johannes Giebel, Sven Dahlgren, Shrinivas Viladkar
{"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}
Pub Date : 2024-02-06DOI: 10.1016/j.chemer.2024.126089
Gülcan Bozkaya, Ömer Bozkaya, Taylan Akın
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 (δ13CPDB ‰) and oxygen (δ18OPDB ‰) isotope compositions of hydrothermal calcites and dolomites and sulfur (δ34SCDT) and oxygen (δ18OSMOW) 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 δ34SCDT 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.
Kızıldere 地热区位于土耳其西部比尤克-门德列斯地堑东部，是最重要的地热储层，适合发电。当前和化石火成孔和蚀变带与中新世时期以来受 N-S 向延伸影响的构造带直接相关。与化石地热活动有关的碳酸盐（方解石、白云石）和硫酸盐（石膏、无水石膏）矿物以空隙/裂缝填充物和与新近纪碎屑岩和碳酸盐岩基底平行的带状/透镜状形式出现。首次分析了热液方解石和白云石的碳（δ13CPDB ‰）和氧（δ18OPDB ‰）同位素组成，以及石膏和无水石膏的硫（δ34SCDT）和氧（δ18OSMOW）同位素组成，并与当前的地热水组成相关。方解石和白云石的碳和氧同位素数据具有相似的碳同位素组成，但氧同位素组成不同，且沿地表方解石-钻屑方解石-钻屑白云石-地表白云石的方向递增。方解石和白云石矿物的同位素组成介于石灰岩和大理岩母岩组成之间，表明碳酸盐矿物形成流体源于热地热水循环过程中碳酸盐岩的溶解。根据 0-300 °C 温度范围内的方解石-CO2 和白云石-CO2 同位素分馏数据，化石同位素组成高于当前的 CO2 组成，反映了相对较低的温度条件。石膏和无水石膏矿物的同位素组成表明，热热水溶解了陆地蒸发岩，形成了富含硫的地热溶液，热液石膏和无水石膏就是从这种溶液中析出的。热液石膏和无水石膏的δ34SCDT成分与当前地热水成分相似。Kızıldere地热田中热液碳酸盐和硫酸盐矿物的稳定同位素地球化学数据表明，形成这些矿物的流体来源于主岩，而不是岩浆挥发物。
{"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 (δ<sup>13</sup>C<sub>PDB</sub> ‰) and oxygen (δ<sup>18</sup>O<sub>PDB</sub> ‰) isotope compositions of hydrothermal calcites and dolomites and sulfur (δ<sup>34</sup>S<sub>CDT</sub>) and oxygen (δ<sup>18</sup>O<sub>SMOW</sub>) 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-CO<sub>2</sub> and dolomite-CO<sub>2</sub> isotopic fractionation data for the 0–300 °C temperature range, the fossil isotope composition is higher than the composition of current CO<sub>2</sub> 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 δ<sup>34</sup>S<sub>CDT</sub> 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}
Pub Date : 2024-02-01DOI: 10.1016/j.chemer.2024.126087
N. Mohammadi, David R. Lentz, K. Thorne, Jim Walker, Neil Rogers, Brian L. Cousens, C. McFarlane
{"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}
Pub Date : 2024-02-01DOI: 10.1016/j.chemer.2024.126091
Lei Zhu, Bin Li, Angui Lu, De-Xian Zhang, Jun-Wei Xu
{"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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：