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Geological Journal of China Universities ›› 2023, Vol. 29 ›› Issue (3): 345-358.DOI: 10.16108/j.issn1006-7493.2023027

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Construction and Application of Lithofacies Paleogeography Knowledge Graphs

ZHANG Jiajia1,2,ZHANG Lei1,2,ZHONG Hanting1,2,3*,WANG Han1,2,3,CHEN Anqing1,2,3,LI Fengjie1,2,3,REN Qiang1,2,3,ZHENG Dongyu1,2,3,ZHAO Hongyi4,HOU Mingcai1,2,3*#br#   

  1. 1. Key Laboratory of Deep-time Geography & Environment Reconstruction and Applications of Ministry of Natural Resources, Chengdu University of Technology, Chengdu 610059, China;
    2. Institute of Sedimentary Geology of Chengdu University of Technology, Chengdu 610059, China;
    3. State key Laboratory of Oil and Gas Reservoir Geology and Exploitation (Chengdu University of Technology), Chengdu 610059, China;
    4. School of Earth Sciences and Resources, CUGB, Beijing 100083, China
  • Online:2023-06-20 Published:2023-06-20

Abstract: Big data has brought new ideas and challenges to lithofacies paleogeography research. However, due to the problems of complex data types, rich semantic relationships and unclear sharing mechanisms, it is difficult to conduct in-depth data mining, analysis, and effective utilization of lithofacies paleogeographic data, which makes making many advantages of big data not fully exploited in this field. The powerful semantic processing and open interconnection capabilities of knowledge graphs, make it plays an important role in solving the problems of big data text analysis and image understanding, which and haves broad application prospects. This paper summarizes the research background of lithofacies paleogeography knowledge graphs from the perspective of construction and application; by systematically investigates investigating the construction ideas, technologies and processes of lithofacies paleogeography knowledge graphs., and The paper also lists outlines the relevant applications of knowledge graphs in lithofacies paleogeography; and points out the main problems of lithofacies paleogeography knowledge graphs, prospects for future research directions.

Key words: big data, paleogeography, lithofacies paleogeography, knowledge graph

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