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Application of Big Data Analysis in Choosing Optimal Cross-plots Related to Dibenzofuran Compounds

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Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1303))

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Abstract

In this paper, the distribution of methyl dibenzofuran isomers (MDBFs) in petroleum hydrocarbon samples of different ages and sedimentary environments were analyzed by the GC-MS method and relevant software. Relevant parameters of MDBFs were put into several cross-plots that have been studied and can reflect the origin of petroleum hydrocarbon. The results show that the diagram of pristane/phytane (Pr/Ph) - dibenzothiophene/phenanthrene (DBT/P) and the diagram of Pr/Ph - alkyl dibenzothiophene/alkyl dibenzofuran (ADBT/ADBF) cannot distinguish shale derived from marine and lacustrine shale. Whereas the diagram of Pr/Ph - (1 + 4)-/(2 + 3)-MDBF can effectively distinguish. the sedimentary environments and lithologic characteristics of samples. The results show that the diagram of Pr/Ph versus (vs.) (1 + 4)-/(2 + 3)-MDBF are more suitable to reflect the sedimentary environment and lithologic characteristics of organic matters. The method of big data processing can effectively optimize geochemical information.

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Acknowledgments

This work was supported by National Natural Science Foundation of China (Project No.: 41802179), the Foundation for Projects of the Sichuan Science and Technology Program (Project No.: 2019YFH0037), and the Central Public-interest Scientific Institution Basal Research Fund of China (Project No.: 1610012018008, 2060302-022-20-010).

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Authors and Affiliations

  1. Key Laboratory of Development and Application of Rural Renewable Energy, Biogas Institute of Ministry of Agriculture and Rural Affairs, Chengdu, 610041, Sichuan, China

    Bingkun Meng, Lu Yang & Chunmiao Ma

  2. Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, Gansu, China

    Bingkun Meng

  3. State Key Laboratory of Petroleum Resources and Prospecting, College of Geosciences, China University of Petroleum, Beijing, 102249, China

    Chunmiao Ma

Authors
  1. Bingkun Meng
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  2. Lu Yang
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  3. Chunmiao Ma
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Corresponding author

Correspondence to Lu Yang .

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Editors and Affiliations

  1. School of Computer Science, University of Oklahoma, Norman, OK, USA

    Mohammed Atiquzzaman

  2. University of Aizu, Fukushima, Japan

    Neil Yen

  3. Shanghai University of Medicine and Health Sciences, Shanghai, China

    Zheng Xu

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Meng, B., Yang, L., Ma, C. (2021). Application of Big Data Analysis in Choosing Optimal Cross-plots Related to Dibenzofuran Compounds. In: Atiquzzaman, M., Yen, N., Xu, Z. (eds) Big Data Analytics for Cyber-Physical System in Smart City. BDCPS 2020. Advances in Intelligent Systems and Computing, vol 1303. Springer, Singapore. https://doi.org/10.1007/978-981-33-4572-0_57

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  • DOI: https://doi.org/10.1007/978-981-33-4572-0_57

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-33-4573-7

  • Online ISBN: 978-981-33-4572-0

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