Zircon is a widely-used heavy mineral in geochronological and geochemical research because it can extract important information to understand the history and genesis of rocks. Zircon has various types,and an accurate ...Zircon is a widely-used heavy mineral in geochronological and geochemical research because it can extract important information to understand the history and genesis of rocks. Zircon has various types,and an accurate examination of zircon type is a prerequisite procedure before further analysis.Cathodoluminescence(CL) imaging is one of the most reliable ways to classify zircons. However, current CL image examination is conducted by manual work, which is time-consuming, bias-prone, and requires expertise. An automated and bias-free method for zircon classification is absent but necessary. To this end, deep convolutional neural networks(DCNNs) and transfer learning are applied in this study to classify the common types of zircons, i.e., igneous, metamorphic, and hydrothermal zircons. An atlas with over 4000 CL images of these three types of zircons is created, and three DCNNs are trained using these images. The results of this study indicate that the DCNNs can distinguish hydrothermal zircons from other zircons, as indicated by the highest accuracy of 100%. Although similar textures in igneous and metamorphic zircons pose great challenges for zircon classification, the DCNNs successfully classify 95% igneous and 92% metamorphic zircons. This study demonstrates the high accuracy of DCNNs in zircon classification and presents the great potentiality of deep learning techniques in numerous geoscientific disciplines.展开更多
The Yangshan gold deposit is a super-large fine-grained disseminated gold deposit located in southern Gansu Province. Its metallogenic age has been determined by using the cathodoluminescence image and ion probe U-Pb ...The Yangshan gold deposit is a super-large fine-grained disseminated gold deposit located in southern Gansu Province. Its metallogenic age has been determined by using the cathodoluminescence image and ion probe U-Pb dating techniques. It is found that zircons from quartz veinlet of the fine-grained disseminated gold ore show characters of magmatic origin with prism idiomorphism, oscillatory zoning and dominant Th/U ratios of 0.5-1.5. Three main populations of zircons are obtained, giving average 206Pb/238U ages of 197.6±1.7 Ma, 126.9±3.2 Ma and 51.2±1.3 Ma respectively. The first age corresponds to the K-Ar age of the plagiogranite dike, while the latter two ages indicate that buried Cretaceous and Tertiary intrusives exist in the orefield, suggesting that the Yangshan gold deposit was genetically related to the three magmatic hydrothermal activities. By contrast, zircons from coarse gold-bearing quartz vein in the mining area are much older than the host rock, indicating that the vein was formed earlier and was not contaminated by later magmatic fluids. It is concluded that the coupling of multiperiodic hydrothermal activities in the mining area has contributed a lot to mineralization of the Yangshan gold deposit.展开更多
基金supported by the IUGS Deep-time Digitial Earth (DDE) Big Science ProgramNational Natural Science Foundation of China (Grant Nos. 42050104, 42172137, 41888101, and 42102092)+1 种基金Open Fund (Grant No. PLC20211102) of State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation of Chengdu University of Technologythe Everest Scientific Research Program of Chengdu University of Technology (Grant No. 2021ZF11402)。
文摘Zircon is a widely-used heavy mineral in geochronological and geochemical research because it can extract important information to understand the history and genesis of rocks. Zircon has various types,and an accurate examination of zircon type is a prerequisite procedure before further analysis.Cathodoluminescence(CL) imaging is one of the most reliable ways to classify zircons. However, current CL image examination is conducted by manual work, which is time-consuming, bias-prone, and requires expertise. An automated and bias-free method for zircon classification is absent but necessary. To this end, deep convolutional neural networks(DCNNs) and transfer learning are applied in this study to classify the common types of zircons, i.e., igneous, metamorphic, and hydrothermal zircons. An atlas with over 4000 CL images of these three types of zircons is created, and three DCNNs are trained using these images. The results of this study indicate that the DCNNs can distinguish hydrothermal zircons from other zircons, as indicated by the highest accuracy of 100%. Although similar textures in igneous and metamorphic zircons pose great challenges for zircon classification, the DCNNs successfully classify 95% igneous and 92% metamorphic zircons. This study demonstrates the high accuracy of DCNNs in zircon classification and presents the great potentiality of deep learning techniques in numerous geoscientific disciplines.
文摘The Yangshan gold deposit is a super-large fine-grained disseminated gold deposit located in southern Gansu Province. Its metallogenic age has been determined by using the cathodoluminescence image and ion probe U-Pb dating techniques. It is found that zircons from quartz veinlet of the fine-grained disseminated gold ore show characters of magmatic origin with prism idiomorphism, oscillatory zoning and dominant Th/U ratios of 0.5-1.5. Three main populations of zircons are obtained, giving average 206Pb/238U ages of 197.6±1.7 Ma, 126.9±3.2 Ma and 51.2±1.3 Ma respectively. The first age corresponds to the K-Ar age of the plagiogranite dike, while the latter two ages indicate that buried Cretaceous and Tertiary intrusives exist in the orefield, suggesting that the Yangshan gold deposit was genetically related to the three magmatic hydrothermal activities. By contrast, zircons from coarse gold-bearing quartz vein in the mining area are much older than the host rock, indicating that the vein was formed earlier and was not contaminated by later magmatic fluids. It is concluded that the coupling of multiperiodic hydrothermal activities in the mining area has contributed a lot to mineralization of the Yangshan gold deposit.
