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Structural Modeling Based on Human–Computer Knowledge Interaction

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Abstract

Building structural models is a foundational step in the exploration of deep subsurface resources, such as oil and gas. However, in some complex surveys, expert cognition of the subsurface geological structures in the area is often incomplete, and the quality of seismic data rapidly deteriorates, which leads to poor structural interpretation and makes structural modeling a time-consuming and laborious task. To address this challenge, a structural modeling method based on human–computer knowledge interaction using knowledge graphs (KGs) is proposed. Initially, a KG of the structural model is established based on the original structural interpretation. Subsequently, it is gradually improved through iterative human–computer interaction to obtain a complete KG. Finally, the KG is used to guide the reconstruction of geological surfaces. In the process of improving the initial KG, humans can provide expertise to computers by editing the KG, and computers can cognize the data through the KG to help humans discover errors or new knowledge in the original structural interpretation. The method was tested on a field dataset and yielded robust and efficient results.

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Acknowledgments

This work has been supported by the National Natural Science Foundation of China (Grant nos. 42130812, 41974147 and 41804162).

Author information

Authors and Affiliations

  1. School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Xianglin Zhan & Cai Lu

  2. Central Sichuan Gas Field, Southwest Oil and Gas Company, PetroChina, Suining, 629000, China

    Shun Li, Song Tang & Minzhi Zhang

  3. School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Guangmin Hu

Authors
  1. Xianglin Zhan
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  2. Shun Li
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  3. Song Tang
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  4. Minzhi Zhang
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  5. Cai Lu
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  6. Guangmin Hu
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Corresponding author

Correspondence to Cai Lu.

Additional information

This work was supported by the National Natural Science Foundation of China (Grant nos. 42130812, 41974147 and 41804162).

Xianglin Zhang is a PhD student at the University of Electronic Science and Technology of China. Her major is Information and Communication Engineering, and her main research interests are intelligent geological modeling, knowledge graph construction and application, and artificial intelligence in geoscience. Email: xianglin_zhan@163.com

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Zhan, X., Li, S., Tang, S. et al. Structural Modeling Based on Human–Computer Knowledge Interaction. Appl. Geophys. (2023). https://doi.org/10.1007/s11770-023-1017-z

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  • DOI: https://doi.org/10.1007/s11770-023-1017-z

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