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

Institutions

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

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

In Situ Gas Content Prediction of Deep Coal Seams Based on Logging in the Central Linxing–Shenfu Block

Guangui Zou, Yuyan Che, Ke Ren, Hu Zeng et al.
ACS Omega
Coal Properties and Utilization
article

In Situ Gas Content Prediction of Deep Coal Seams Based on Logging in the Central Linxing–Shenfu Block

Guangui Zou, Yuyan Che, Ke Ren, Hu Zeng, Jiasheng She, Suping Peng, Xiaodong Wang
article en

Abstract

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.

ACS Omega
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)
National Natural Science Foundation of China, National Key Research and Development Program of China, Science and Technology Program of Guizhou Province
Openalex Percentile: Top 15%
Coal Properties and Utilization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.