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  1.  24
    Geologic Characterization of a Lower Cambrian Marine Shale: Implications for Shale Gas Potential in Northwestern Hunan, South China.Zhenghui Xiao, Jisong Liu, Jingqiang Tan, Rongfeng Yang, Jason Hilton, Ping Zhou, Zhaohui Wang & Yunjiang Cao - 2018 - Interpretation: SEG 6 (3):T635-T647.
    We have investigated the geologic features of the lower Cambrian-aged Niutitang Shale in the northwestern Hunan province of South China. Our results indicate that the Niutitang Shale has abundant and highly mature algal kerogen with total organic carbon content ranging from 0.6% to 18.2%. The equivalent vitrinite reflectance value is between 2.5% and 4.3%. Mineral constituents are dominated by quartz and clay. The average quartz content is much higher than that of clay minerals, and this suggests a high brittleness index. (...)
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    Quantitative Identification of Coal Texture Using the Support Vector Machine with Geophysical Logging Data: A Case Study Using Medium-Rank Coal From the Panjiang, Guizhou, China.Zhenghui Xiao, Wei Jiang, Bin Sun, Yunjiang Cao, Lei Jiang, Taotao Cao, Qing Yang, Cailun Huang, Xiansheng Yang & Xiangkuan Huang - 2020 - Interpretation 8 (4):T753-T762.
    Coal texture is important for predicting coal seam permeability and selecting favorable blocks for coalbed methane exploration. Drilled cores and mining seam observations are the most direct and effective methods of identifying coal texture; however, they are expensive and cannot be used in unexplored coal seams. Geophysical logging has become a common method of coal texture identification, particularly during the CBM mining stage. However, quantitative methods for identifying coal texture based on geophysical logging data require further study. The support vector (...)
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    Mathematical Modelling for TOC Content Prediction with Logging Parameters by Neural Networks: A Case Study of Shale Gas Well in South China.Yanran Huang, Zhenghui Xiao, Li Dong, Ye Yu & Taotao Cao - forthcoming - Interpretation:1-31.
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