Skip to main content

Advertisement

Log in

Geological structure identification of coalbed methane reservoir based on trend surface and curvature analysis algorithms

  • RESEARCH
  • Published:
Earth Science Informatics Aims and scope Submit manuscript

Abstract

The geological structure affects the occurrence of coalbed methane (CBM), and identifying its structural characteristic boundaries is significant for CBM development. Based on the 3# coal seam top elevation observation data of the South Shizhuang CBM district in Qinshui Basin, this study comprehensively used trend surface analysis, curvature analysis and multi-element overlay analysis to study the geological structure characteristics of this area and identify its geological structure boundaries. First of all, through the analysis of the fitting degree test and significance test, it was proved that the fourth-order trend surface can be better used to identify the geological structure characteristics in this area. On this basis, the geological structural units of the study area were identified on a regional scale, and the study area was divided into the northwest depression zone, the middle fold area and the eastern slope zone. Then, by using the contour curvature analysis method, the fold geological structure boundaries were identified on a local scale, and combined with the coal seam roof elevation model for optimization and adjustment, 73 fold structural boundaries were finally identified, including 37 anticlines and 36 synclines. The results showed that: (1) The fold structures of the 3# coal seam in the South Shizhuang CBM district are primarily wide and gentle secondary folds, with symmetrical wings and a roughly NNE trend. (2) The northwest depression zone is dominated by syncline structure. (3) In the middle fold zone, anticlines and synclines are evenly distributed. (4) The eastern slope zone is dominated by anticline structure and has small terrain fluctuations, making it a favourable area for CBM development. The identification results can provide a reference for the exploration, planning and development site selection of CBM resources in the study area.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Data availability

No datasets were generated or analysed during the current study.

References

Download references

Acknowledgements

The authors are grateful to the financial support for this project from the National Natural Science Foundation of China (Grant No. 41972304) & the National Science and Technology Major Project of China (Grant No. 2011ZX05060). We also thank the China United CBM Co. for providing the data and Dr. Qiyu Chen and two reviewers for their constructive advice and comments.

Funding

This work was financially supported by the National Natural Science Foundation of China (Grant No. 41972304) & the National Science and Technology Major Project of China (Grant No. 2011ZX05060).

Author information

Authors and Affiliations

Authors

Contributions

Guoxu Chen, Ruirui Li and Fang Lv conceived the manuscript; Guoxu Chen, Shengdong Liu and Zhongcheng Li provided funding support and ideas; Li Cao, Ruirui Li, Fang Lv, Jing Yuan and Panpan Li were responsible for researching methods, algorithms and model construction; Shengdong Liu and Zhongcheng Li provided the data used in this research; Guoxu Chen and Ruirui Li helped to improve the manuscript. All authors have read and agreed to the submitted version of the manuscript.

Corresponding author

Correspondence to Guoxu Chen.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Communicated by: G. Liu

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, G., Li, R., Cao, L. et al. Geological structure identification of coalbed methane reservoir based on trend surface and curvature analysis algorithms. Earth Sci Inform 17, 1345–1358 (2024). https://doi.org/10.1007/s12145-024-01232-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12145-024-01232-7

Keywords

Navigation