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Geochemistry of sedimentary rocks from Permian–Triassic boundary sections of Tethys Himalaya: implications for paleo-weathering, provenance, and tectonic setting

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Acta Geochimica 2016年第4期35卷 428-436页

作者： Akhtar R.Mir V.Balaram Javid A.Ganai Shamim A.Dar A.Keshav Krishna Department of Earth Sciences University of KashmirSrinagar 190006India CSIR-National Geophysical Research Institute Hyderabad 500007India Department of Geology S.P.CollegeSrinagar 190008India

The geochemical characteristics of two sections—the Permian–Triassic boundary(PTB) Guryul Ravine section, Kashmir Valley, Jammu and Kashmir,India; and the Attargoo section, Spiti Valley, Himachal Pradesh, India—have been studied in the context of provenance, paleo-weathering, and plate tectonic *** sections represent the siliciclastic sedimentary sequence from the Tethys Himalaya. The PTB siliciclastic sedimentary sequence in these regions primarily consists of sandstones and shales with variable thickness. Present studied sandstones and shales of both sections had chemical index of alteration values between 65 and 74; such values reveal low-to-moderate degree of chemical weathering. The chemical index of weathering in studied samples ranged from 71 to 94, suggesting a minor K-metasomatism effect on these samples. Plagioclase index of alteration in studied sections ranged from 68 to 92, indicating a moderate degree of weathering of plagioclase feldspars. The provenance discriminant function diagram suggests that the detritus involved in the formation of present studied siliciclastic sedimentary rocks fall in quartzose sedimentary and felsic igneous provenances. These sediments were deposited in a passive continental margin plate tectonic setting according to their location on a Si_2 O versus K_2O/Na_2 O tectonic setting diagram.

关键词： Geochemistry Permian-Triassic boundary - Guryul Ravine tectonic settings

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Geochemistry of the ophiolite and oceanic island basalt in the Kangxian-Pipasi-Nanping tectonic mélange zone, South Qinling and their tectonic significance

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Science China Earth Sciences 2004年第2期47卷 128-137页

作者： LAI Shaocong ZHANG Guowei PEI Xianzhi YANG Haifeng Key Laboratory of Continental Dynamics Ministry of Education and Department of Geology Northwest University Xi'an 710069 China

Detailed studies indicate that Kangxian-Pipasi-Nanping tectonic zone is a complicated mélange zone which includes many tectonic slabs of different origins. Ophiolite (MORB-type basalt), oceanic island tholeiite and alkaline basalt have been identified. Moreover, this tectonic mélange zone is eastward connected with the Mianlüe suture zone. The deformation characteristics, consisting components and volcanic rock geochemical features for the Kangxian-Pipasi-Nanping tectonic mélange zone are much similar to those of the Mianlüe suture zone and Deerni ophiolite. Therefore, the Kangxian-Pipasi-Nanping tectonic mélange zone should be the westward extension part of the Mianlüe suture zone. It indicates that the Mianlüe suture zone had extended to the Nanping area.

关键词： ophiolite and volcanic rock geochemistry tectonic settings Kangxian-Pipasi-Nanping Mianlüe suture zone

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Machine learning and tectonic setting determination:Bridging the gap between Earth scientists and data scientists

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Geoscience Frontiers 2024年第1期15卷 339-353页

作者： Pratchaya Takaew Jianhong Cecilia Xia Luc S.Doucet Department of Spatial Sciences School of Earth and Planetary SciencesCurtin University6845 PerthWAAustralia Earth Dynamics Research Group School of Earth and Planetary SciencesCurtin University6845 PerthWAAustralia State Key Laboratory of Geological Processes and Mineral Resources China University of GeosciencesWuhanHubei 430074China

Technological progress and the rapid increase in geochemical data often create bottlenecks in many studies,because current methods are designed using limited number of data and cannot handle large *** geoscience,tectonic discrimination illustrates this issue,using geochemical analyses to define tectonic settings when most of the geological record is missing,which is the case for most of the older portion of the Earth’s *** are the primary target for tectonic discrimination because they are volcanic rocks found within all tectonic settings,and their chemical compositions can be an effective way to understand tectonics-related mantle ***,the classical geochemical discriminant methods have limitations as they are based on a limited number of 2 or 3-dimensional diagrams and need successive and subjective steps that often offers non-unique ***,weathering,erosion,and orogenic processes can modify the chemical composition of basalts and eliminate or obscure other complementary geotectonic *** address those limitations,supervised machine learning techniques(a part of artificial intelligence)are being utilized more often as a tool to analyze multidimensional datasets and statistically process data to tackle big data *** contribution starts by reviewing the current state of tectonic discrimination methods using supervised machine *** learning,especially Convolutional Neural Network(CNN)is the most accurate ***,it requires a large dataset and considerable processing time,and the gain of accuracy can be at the expense of ***,this study designed guidelines for data pre-processing,tectonic setting classification and objectively evaluating the model *** also identify research gaps and propose potential directions for the application of supervised machine learning to tectonic discrimination research,aimed at closing the divide between earth scientists and data scie

关键词： Machine learning Artificial intelligence Geochemistry Igneous petrology Basalts tectonic settings

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New discrimination diagrams for basalts based on big data research

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Big Earth Data 2019年第1期3卷 45-55页

作者： Qi Zhang Weidong Sun Yong Zhao Fanglin Yuan Shoutao Jiao Wanfeng Chen Institute of Geology and Geophysics Chinese Academy of ScienceBeijing 100029China Center of Deep Sea Research Institute of OceanographyChinese Academy of SciencesQingdaoChina Laboratory for Marine Mineral Resources Qingdao National Laboratory for Marine Science and TechnologyQingdaoChina CAS Center for Excellence in Tibetan Plateau Earth Sciences Chinese Academy of SciencesBeijingChina State Key Laboratory of Continental Dynamics Department of GeologyNorthwest UniversityXi’anChina School of Earth Sciences and Engineering SUN YAT-SEN UniversityGuangzhouChina Key Laboratory of Mineral Resources in Western China(Gansu Province) School of Earth SciencesLanzhou UniversityLanzhouChina

In recent days,discrimination diagrams have been widely used for tracing the tectonic settings and origins of basalts from orogenic ***,conventional discrimination diagrams are not accurate ***,we reported six new discrimination diagrams obtained from the global database using data mining *** most individual diagrams,island arc basalt can be nearly 100%was identified,whereas ocean island basalt and midocean ridge basalt can be discriminated from each other with less than 10%of overlap,under a confidence coefficient of 85%.Using the six new discrimination diagrams together,basalts of different origins can be efficiently identified.

关键词： Big data discrimination diagram tectonic settings SVM GEOROC

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