Coal Geology & Exploration
Abstract
Background Intelligent coal mine construction represents an important measure to promote the high-quality development of the coal industry. Developing intelligent technologies and equipment for geological exploration is the key to both transparent geological guarantee and the efficient prevention and control of major disasters in coal mines. Advances This study presents a systematic analysis of the latest advances in intelligent technologies and equipment for underground geological exploration of coal mines in China, focusing on intelligent drilling and geophysical prospecting. In terms of intelligent drilling, this study introduces intelligent drilling rigs equipped with multiple functions, including adaptive control, remote monitoring, and fault diagnosis; intelligent drilling tools, including downhole motors with efficient power output, rotary steerable systems for precise trajectory control, intelligent drill rods with high-speed data transmission, and intelligent drill bits with self-sensing capability; and multi-parameter measurement-while-drilling (MWD) instruments for the real-time acquisition of trajectory, geological, and engineering parameters. The technologies and devices for intelligent drilling have significantly enhanced the automation and intelligence levels of the drilling process. Regarding intelligent geophysical prospecting, this study presents long-distance, dynamic, and high-precision detection technologies and instruments, such as seismic-while-mining (SWM) technology, seismic-while-tunneling (SWT) technology, and borehole geophysical prospecting. These technologies and instruments enable the effective identification of geological targets such as coal seam structures, faults, collapse columns, and water-bearing structures. Analysis reveals that intelligent equipment for underground geological exploration of coal mines faces a series of challenges. First, the limited intelligence level fails to support fully autonomous decision-making. Second, the detection accuracy and timeliness of the equipment are insufficient to satisfy the demand for real-time geological feedback. Third, the equipment exhibits weak adaptability to complex geological conditions and, in particular, demonstrates limited reliability in deep environments characterized by high gas content, high water pressure, high ground pressure, and complex structures. Fourth, the less complete standardization system restricts multi-equipment collaboration and large-scale application. Prospects A range of recommendations is proposed. First, it is necessary to promote the iterative upgrading of intelligent equipment and overcome technical bottlenecks in sensors and core components, as well as safe and efficient borehole formation under complex geological conditions. Second, cloud-edge collaborative data processing architectures should be established to improve the timeliness and accuracy of data interpretation. Third, it is recommended to expedite the integrated application of drilling and geophysical prospecting technologies for long-term, continuous, and dynamic perception of geological information on mines. Fourth, the standardization system for geological exploration should be developed rapidly to promote the widespread application of intelligent technologies and equipment. This measure will help build a full-chain intelligent technology and equipment system for geological exploration, thereby providing accurate and reliable geological guarantees for intelligent coal mining.
Keywords
intelligent coal mine construction, equipment for geological exploration, intelligent drilling, intelligent geophysical prospecting, deep mining, standardization, integrated drilling and geophysical prospecting
DOI
10.12363/issn.1001-1986.26.03.0161
Recommended Citation
ZHANG Jianming, LI Quanxin, LIU Fei,
et al.
(2026)
"Recent advances in research on intelligent technologies and equipment for underground geological exploration of coal mines in China,"
Coal Geology & Exploration: Vol. 54:
Iss.
6, Article 5.
DOI: 10.12363/issn.1001-1986.26.03.0161
Available at:
https://cge.researchcommons.org/journal/vol54/iss6/5
Reference
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