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Textures, trace element compositions, and sulfur isotopes of pyrite from the Honghai volcanogenic massive sulfide deposit:Implications for ore genesis and mineral exploration
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作者 Zhiyuan SUN Xiaohua DENG Franco PIRAJNO 《Science China Earth Sciences》 SCIE EI CAS CSCD 2023年第4期738-764,共27页
In this paper, we present textures, trace element compositions, and sulfur isotope data for pyrite from the Honghai volcanogenic massive sulfide deposit to place new constraints on the source and evolution of the ore-... In this paper, we present textures, trace element compositions, and sulfur isotope data for pyrite from the Honghai volcanogenic massive sulfide deposit to place new constraints on the source and evolution of the ore-forming fluids and provide insights into the ore genesis with implications for future exploration. The Honghai deposit consists of upper lenticular ores comprising massive sulfides that are underlain by stockwork and disseminated sulfides. The textural and isotopic characteristics of the synsedimentary framboidal pyrite(Syn-Py) indicate its formation by biogenetic processes. Coarse-grained pyrite generations(M-Py1, M-Py2, and M-Py3) from the massive sulfides have high Au, Ag, Cu, Zn, Pb, Sb, and Tl concentrations and low Co, Se, Te, Ti, and Sn concentrations, indicating that they precipitated from metal-rich, low-to intermediate-temperature,oxidizing fluids. The high Te, Ti, and Sn concentrations and high Co/Ni ratios in the massive pyrite(M-Py4) associated with magnetite in the massive sulfide lenses, as well as the high Ti, V, Cr, and Ni concentrations and low Al, Mn, and Zn concentrations in the magnetite, suggest that the coexisting M-Py4 and magnetite precipitated under oxidizing and hightemperature(300℃ to 500℃) conditions. In contrast, pyrite grains from the underlying stockwork and veins(V-Py1, V-Py2, and V-Py3) are characterized by low Au, Ag, Cu, Zn, Pb, Sb, and Tl concentrations coupled with high Co, Se, Te, and Ti concentrations and high Co/Ni ratios, which are interpreted in terms of reducing and high-temperature ore-forming fluids. The large variations in δ^(34)S values from-6.4‰ to +29.9‰ suggest that the ore-forming fluids were derived from magmatic source that were significantly modified by seawater. The spatial variations of trace element assemblages of pyrite from different levels of the main massive orebodies can be used as an indicator for mineral exploration of Cu-Zn ores in the Honghai deposit.Although no significant difference in δ34S values is observed between the upper massive sulfide lenses and lower stockwork/vein zone, the spiky δ34S pattern noted in the massive pyrite can be used as a marker for the main massive orebodies. 展开更多
关键词 PYRITE Trace element compositions Sulfur isotopes Ore-forming fluids Honghai volcanogenic massive sulfide deposit
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Double Convective Hydrothermal System beneath Massive Sulfide Orebody in Gacun Deposit,Southwestern China 被引量:2
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作者 Hou ZengqianInstitute of Mineral Deposits, CAGS, Beijing 100037Mo Xuanxue Department of Geology and Mineral Resources, China University of Geosdences, Beijing 100083Urabe Tetsuro Geological Survey of Japan, Higash 1-1-3, Tsukuba, Ibaraki, 305, Japan 《Journal of Earth Science》 SCIE CAS CSCD 1995年第2期114-130,共17页
The Gacun Kuroko-type deposit, Southwestern China, is hosted in rhyolitic rocks associated with the underlying mafic rocks occurred in the - 1000 m deep fault - bounded basin within the intra -arc rifting zone which f... The Gacun Kuroko-type deposit, Southwestern China, is hosted in rhyolitic rocks associated with the underlying mafic rocks occurred in the - 1000 m deep fault - bounded basin within the intra -arc rifting zone which formed on the Triassic Yidun island - arc. Two vertically separated alteration systems are recognized: one is conformable or semiconformable alteration zone developed in - 150 m thick mafic unit 1-1.5 km below the massive sulfide ore body; the other is discordant alteration pipe directly surrounded around stockwork ore within rhyolitic unit. The lower conformable alteration zone extending for several kilometers along strike is characterized by silicification and epidotization which result in the development of quartz vein and quartz-epidote vein systems in mafic lava flows and replacement of primary minerals and groundmass in spilitized mafic volcanics and dikes by quartz, epidote - group minerals and sodic plagioclase. Sulfides often occur in the vein system and altered mafic volcanics. Quartz solubility relation indicates that silicification is a consequence of interaction of Si- saturated fluids with mafic rocks in a higher temperature system (T>340℃), intensifying by intrusion of mafic dike or high-level acidic magma chamber. The alteration pipe of diameter about 2 km shows a similar mineralogical zoning to Kuroko deposits of Japan. The sequence is quartz + hyalophane; sericite + chlorite + quartz and zeolite-like zones from core to margins of the pipe. The chlorite core only occurs in the root part of the alteration pipe and downwards transfers into epidote - chlorite and epidote - quartz vein swarm extending 500 m downwards. The felsic rocks away from the orebody and alteration pipe took place district-scale alteration, which has typical low-temperature mineral association: illite + albite + quartz + calcite. Whole -rock and quartz δ18O values indicate that district - scale alteration is a result of interaction of seawater with rocks at lower temperature (T<200℃)under water-dominated condition. However, the altered rocks from the pipe show remarkably δ18O enrichment, and bulk -rock δ18O values decreased gradually toward stockwork orebody from 15.1‰-l5. 75‰ in zeolite-like zone and 12. 05‰-14. 2‰ in sericite - quartz zone to 11.3 ‰ - 14. 4‰ in quartz - hyalophane zone. The filled temperatures of fluid inclusions in quartz and sphalerite lie in the ranges of 280 -320 ℃ for quartz - hyalophane zone and 250 ℃ to 297 ℃ for sericite-quartz zone. The estimated δ18O values of hydrothermal fluids are 7. 98‰ and3.2‰, respectively, based on quartz δ18O data in the deposit. The lower conformable alteration is considered to be approximately coeval with the alteration pipe, based on the SiO2 concentration in the fluids, which restrict the main fluid - rock reaction zone to be located in mafic horizon by quartz barometer, and metal element flux calculation and sulfide - epidote vein system developed both in alteration systems. High - salinity fluid inclusions in gangue quartz (>8% eq. NaCl) from stockwork ore and in quartz phenocryst (>40% eq. NaCl) in footwall rhyolite strongly suggest the existence of hot-saline brine to react with mafic complex and leach metal components, which probably originates mainly from magmatic fluid derived from high-level acidic magma chamber. The brine layer located in mafic unit possibly heats and drives the overlying single -pass convective seawater reacting with felsic rocks. The 'density window' may be expected to occur on the interface between seawater and brine layer, when the brine becomes to be gravitationally instability by the turbulent entrainment of seawater during magmatic and/or tectonic activities. The sulfide mineralization and alteration pipe is inter preted as an effect of the 'density window' through which the mixed fluids of brine with seawater adiabatically discharges upwards. 展开更多
关键词 hydrothermal alteration hot - saline brine fluid-rock reaction oxygenisotope Kuroto-type deposit volcanogenic massive sulfide (VMS) deposit Gacun deposit .
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Development and application of feature engineered geological layers for ranking magmatic,volcanogenic,and orogenic system components in Archean greenstone belts
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作者 R.M.Montsion S.Perrouty +2 位作者 M.D.Lindsay M.W.Jessell R.Sherlock 《Geoscience Frontiers》 SCIE CAS CSCD 2024年第2期251-273,共23页
Geologically representative feature engineering is a crucial component in geoscientific applications of machine learning.Many commonly applied feature engineering techniques used to produce input variables for machine... Geologically representative feature engineering is a crucial component in geoscientific applications of machine learning.Many commonly applied feature engineering techniques used to produce input variables for machine learning apply geological knowledge to generic data science techniques,which can lead to ambiguity,geological oversimplification,and/or compounding subjective bias.Workflows that utilize minimally processed input variables attempt to overcome these issues,but often lead to convoluted and uninterpretable results.To address these challenges,new and enhanced feature engineering methods were developed by combining geological knowledge,understanding of data limitations,and a variety of data science techniques.These include non-Euclidean fluid pre-deformation path distance,rheological and chemical contrast,geologically constrained interpolation of characteristic host rock geochemistry,interpolation of mobile element gain/loss,assemblages,magnetic intensity,structural complexity,host rock physical properties.These methods were applied to compiled open-source and new field observations from Archean greenstone terranes in the Abitibi and western Wabigoon sub-provinces of the Superior Province near Timmins and Dryden,Ontario,respectively.Resulting feature maps represent conceptually significant components in magmatic,volcanogenic,and orogenic mineral systems.A comparison of ranked feature importance from random forests to conceptual mineral system models show that the feature maps adequately represent system components,with a few exceptions attributed to biased training data or limited constraint data.The study also highlights the shared importance of several highly ranked features for the three mineral systems,indicating that spatially related mineral systems exploit the same features when available.Comparing feature importance when classifying orogenic Au mineralization in Timmins and Dryden provides insights into the possible cause of contrasting endowment being related to fluid source.The study demonstrates that integrative studies leveraging multidisciplinary data and methodology have the potential to advance geological understanding,maximize data utility,and generate robust exploration targets. 展开更多
关键词 Machine learning Random forests Mineral systems Magmatic Ni-Cu-PGE volcanogenic massive sulfide(VMS)Cu-Zn-Pb-Ag(-Au) Orogenic Au ABITIBI Wabigoon
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