TIAN Shaoguo, LI Xiangrong, HUANG Tao, et al. Application and prospects of artificial intelligence technology in coalbed methane companiesJ. Shaanxi Coal, 2026, 45(9): 231-235. DOI: 10.20120/j.cnki.issn.1671-749x.2026.0935
Citation: TIAN Shaoguo, LI Xiangrong, HUANG Tao, et al. Application and prospects of artificial intelligence technology in coalbed methane companiesJ. Shaanxi Coal, 2026, 45(9): 231-235. DOI: 10.20120/j.cnki.issn.1671-749x.2026.0935

Application and prospects of artificial intelligence technology in coalbed methane companies

  • Based on the engineering practice of Shaanxi Coalbed Methane Development and Utilization Co., Ltd. (hereinafter referred to as "the Coalbed Methane Company"),we elaborate on the innovative applications of AI in geological exploration and development, safety production control, intelligent equipment operation and maintenance, and management decision-making optimization. In the field of exploration and development, a geological knowledge graph was constructed to integrate multi-source heterogeneous data; the innovative application of CGAN-driven intelligent fault generation technology and CUDA-based parallel modeling, improving the efficiency of 3D geological modeling by 400%, with surface reconstruction errors ≤ 0.3 m. The water inrush early warning accuracy based on the random forest algorithm reached 89%. In the field of safety production, an AM-LSTM multi-modal fusion early warning model (F1-score=0.93) was developed, and a three-tier architecture of "equipment – edge – cloud" was constructed to achieve a risk response latency of < 50 ms, a predictive accuracy of 91% for equipment failures, and a 30% reduction in accident rates. In the field of business management, the Prophet-random forest ensemble model controlled material demand forecasting errors within 8%, and the inventory turnover rate was increased to 4.6 times per year. Through the "Holographic One-Map" decision-making center integrating data from six major domains, management response efficiency improved by 80%. Practice shows that the application of AI has significantly increased the average daily gas production per well by 22.5% and the unmanned rate of fixed sites (50%). In the future, key efforts will focus on digital twin drilling and large-model technologies to promote the unmanned rate of fixed sites to 80%.
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