煤矿井下随钻测量技术的现状与展望

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中图分类号：TD41 文献标志码：A 文章编号：1672-1098（2025）05-0049-13

Abstract：Objective To meet the escalating demands for informatization，automation，and intelligence in underground driling within the inteligent transformation of coal mines and to underpin smart driling， transparent geological modeling，and hazard early-warning.Methods The paper presents a systematic reviewof measurement-while-drilling （MWD） technologies for underground coal mines centering on three key functions—trajectory measurement， lithology identification，and communication-while-drilling—for trajectory measurement， the strapdown inertial navigation system based on inertial measurement units （IMUs）and advances in dynamic high-precision solutions for atitude and inclination parameters via Kalman filtering，eror modeling， and adaptivecompensation; for lithology identification，the limitations of conventional gamma-ray and electrical logging in real-time applications，the rise of multi-modal recognition that fuses bit-vibration characteristics，and the integration of neural networksand deep-learning frameworks for effcient lithology classification under complexdownhole conditions;and fordrilling communication，the development and application of acoustic， electromagnetic， mud-pulse， and magnetic-coupling technologies under constraints of highly conductive media， strong interference，and limited borehole diameters.Results Current research has achieved notable progress in improving dynamic atitude-solution accuracy，advancing real-time lithology identification based on vibration and inteligentalgorithms，and enhancing theadaptabilityof multiplecommunication techniquesincomplex environments，yet chalenges persist in sensor reliability，algorithm autonomy，model universality，and highspeed，high-reliabilitycommunication. Conclusion The paper projects future trends for MWD technologies in the intellgent transformation of coal mines，advocating prioritized breakthroughs in highly reliable sensors， autonomousatitude-resolutionalgorithms，data-driven lithology-identificationmodels，and high-speed，highreliability communication mechanisms to foster a new MWD system oriented toward transparent geology and intelligent drilling.

Key words： coal mine MWD；intellgent driling； trajectory measurement； lithology recognition; MWD communication

煤矿智能化是煤炭行业实现安全、绿色、智能、高效发展的核心技术支撑[1]。（剩余19747字）