In Situ Gas Content Prediction of Deep Coal Seams Based on Logging in the Central Linxing–Shenfu Block
Abstract Deep coalbed methane, a key strategic resource for unconventional natural gas supply, is abundant in the Ordos Basin, China. However, limited systematic research on the state of gas occurrence and critical depth, combined with sparse gas content and in situ stress measurements, has severely restricted the optimization of developmental strategies. Focusing on the 8+9# coal seam of the Taiyuan Formation in the central Linxing–Shenfu Block, Ordos Basin, an improved gas content prediction model is established, which comprehensively accounts for matrix compression, thermal expansion, adsorption-induced swelling, and the pore volume occupied by adsorbed gas. The adsorbed gas content trend was exhibited by logging data. Continuous in situ stress profiles were predicted using logging data combined with the Eaton method and Huang Rongzun’s in situ stress model. Critical depth was determined using the gas content evolution and in situ stress regime transition. The minimum horizontal stress of the 8+9# coal seam exhibited a “higher in the south and lower in the north” distribution pattern. The gas content critical depth is 1076–1704 m, the in situ stress critical depth is 1138–1727 m, and the integrated critical depth is 1076–1727 m, showing a “deeper in the south and shallower in the north” distribution. Based on the three-stage variation pattern of gas content and stress regime, a layered development strategy was proposed. This study supports location optimization and drilling and fracturing parameter design, contributing to safe, efficient, and economical deep coalbed methane development under similar geological conditions.
Authors
- Guangui Zou (ORCID: https://orcid.org/0000-0002-4423-2335)
- Yuyan Che (ORCID: https://orcid.org/0009-0001-0839-7650)
- Ke Ren (ORCID: https://orcid.org/0000-0002-3672-7848)
- Hu Zeng
- Jiasheng She
- Suping Peng
- Xiaodong Wang (ORCID: https://orcid.org/0009-0000-7492-030X)
Institutions
- China University of Mining and Technology (CN)
- University Of Information Technology (MM)
- China Academy of Railway Sciences (CN)
- China Coal Technology and Engineering Group Corp (China) (CN)
- Intelligent Health (United Kingdom) (GB)
Publication Details
- Journal
- ACS Omega
- Published
- 2026-09-13
- DOI
- https://doi.org/10.1021/acsomega.6c08674
- Primary Topic
- Coal Properties and Utilization
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China
- Science and Technology Program of Guizhou Province