【目的】传统巷道地震超前探技术受限于炸药使用、停掘需求、预报速度、探测范围及能力等方面的不足，难以满足智能掘进工作面的高精度地质构造探测需求。【方法】随掘地震以掘进机截割煤壁的震动为震源，采用数据实时上传、自动处理及动态成像的工作模式，充分利用信息技术和软件支撑，借助于海量数据支撑下的实时连续超饱和叠加，大幅提升了对掘进工作面前方地质异常体的成像精细度。以山西王坡煤矿为研究对象，在2条掘进巷道中部署了随掘地震监测系统，开展地质构造精细探査。【结果和结论】实际工作中，利用监测作业开展后48 h内积累的数据，即可对掘进工作面前方200 m范围内地质异常体成像。在3217工作面回风巷中，成功揭示了掘进工作面前方97 m的矸石挤压带反射异常，预报误差1 m；在3303工作面运输巷中，揭示了掘进工作面前方39 m的陷落柱，预报误差2 m；在3303工作面运输巷中，揭示了2处煤层破碎带异常区，其中，一处位于掘进工作前方148 m，预报误差1 m，另一处位于掘进工作面前方211 m外，在前序陷落柱和煤层破碎带遮挡下，依然足以形成较强的成像结果，预报误差3 m。结果表明：该技术施工作业便捷，探测精度高、探测距离远且探测能力强，可为瓦斯灾害的防治提供技术支持，为煤矿智能掘进巷道安全高效掘进提供可靠的地质保障。

【Objective】Traditional coalmine tunnel seismic advance detection technology is limited by factors such as the use of explosives, mining stoppage requirements, prediction speed, detection range, and capabilities, making it difficult to meet the high-precision geophysical exploration needs of intelligent tunnel excavation faces. Method】Seismic-while-tunneling monitoring uses the vibration of the roadheader cutting the coal wall as the seismic source and adopts a working mode of real-time data upload, automatic processing, and dynamic imaging. It fully utilizes information technology and software technology, significantly enhancing the imaging precision of geological anomalies ahead of the mining face through real-time continuous super-saturation stacking supported by massive data. Taking Wangpo Coal Mine in Shanxi as the research object, a seismic-while-tunneling monitoring system was deployed in two driving tunnels to conduct detailed exploration of geological structures. 【Results and Conclusion】In practical operations, data accumulated within 48 hours after monitoring operations can image geological anomalies within a 200 m range ahead of the mining face. In the return airway of the 3217 working face, a reflected anomaly of a squeezing gangue zone 97 m ahead of the mining face was successfully detected with a prediction error of 1m; in the transport tunnel of the 3303 working face, a collapse pillar 39 m ahead of the mining face was identified with a prediction error of 2 m; in the same transport tunnel of the 3303 working face, two abnormal areas of fractured coal zones were detected. One located 148 m ahead of the mining face had a prediction error of 1 m, while the other located beyond 211 m ahead, despite being obstructed by a collapse pillars and a fractured coal zone, still produced relatively strong imaging results with a prediction error of 3 m. This indicates that the detection capabilities of seismic-while-tunneling monitoring during mining can provide technical support for the prevention of gas disasters. The application results demonstrate that this technology is convenient for construction operations, with high detection accuracy, long detection distance, and strong detection capability, providing reliable geological support for intelligent and safe tunnel excavation in coal mines.