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为提升煤矿岩巷掘进过程中地质异常体识别的时效性与准确性，开展了基于随掘地震信号的面波频散分析研究。依托淮南谢桥煤矿瓦斯治理巷全断面掘进机(Tunnel Boring Machine, TBM)施工现场，布设16道高密度地震检波器，对随掘地震记录进行连续采集，并通过地震干涉与频散分析方法，获取随掘地震记录的面波频散能量图像。结果表明，所采集数据中面波能量连续性好，信噪比高，相位特征稳定，有效频率范围为2～42 Hz。采用遗传算法进行反演得到的剪切波速度模型在20～23 m范围内呈现明显低速异常，与掘进过程中实际揭露的破碎带位置高度一致。研究验证了随掘地震数据中蕴含的有效面波信息可用于高分辨率的近场地质探测，提出的方法具备工程现场快速部署与实时分析的可行性，为TBM掘进提供了可量化的地质预测手段。
Abstract：To improve the timeliness and accuracy of geological anomalies detection during coal mine roadway excavation, this study investigates surface wave dispersion analysis based on seismic signals acquired during excavation. At the fully mechanized tunnel boring machine(TBM) excavation site in the Xieqiao coal mine of Huainan, 16 high-density seismic geophones were deployed to continuously record seismic data during excavation. Through seismic interferometry and dispersion analysis, surface wave dispersion energy images of the excavation seismic records were obtained. The results show that the collected data exhibit good continuity of surface wave energy, high signal-to-noise ratio, and stable phase characteristics, with an effective frequency range of 2～42 Hz. Inversion using a genetic algorithm revealed a significant low-velocity anomaly in the shear wave velocity model at a depth of 20～23 meters, which corresponds closely to the fractured zone actually encountered during excavation. The study confirms that effective surface wave information contained in excavation seismic data can be used for high-resolution near-field geological detection. The proposed method is feasible for rapid deployment and real-time analysis in engineering applications, providing a quantifiable geological prediction tool for TBM tunneling.
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基本信息:
中图分类号:TD263.3;P631.4
引用信息:
[1]贺世芳,郭立全,秦广俊,等.煤矿岩巷TBM掘进随掘地震面波频散分析及其应用[J].工程地球物理学报,2025,22(06):607-614.
基金信息:
煤炭安全精准开采国家地方联合工程研究中心(安徽理工大学)开放基金项目(编号：EC2022010)