Objective and Method Densely distributed sub-seismic faults have emerged as a major hidden disaster-causing geological factor, heavily influencing both the production efficiency and operational safety of coal mines. To achieve precise advance detection of underground sub-seismic faults in coal mines, this study designed a geological model. Using seismic-while-tunneling (SWT) advance detection technology for roadways of coal mines, this study investigated the geological situation of sub-seismic faults through forward modeling. Furthermore, it explored the seismic image characteristics of these faults obtained using the SWT observation system under varying survey line lengths and geophone spacing values.

Results and Conclusions The forward modeling results indicate that the layout of the SWT observation system significantly influenced both the positioning accuracy and azimuth distribution of sub-seismic faults. Specifically, with increases in the survey line length and the density of seismic traces, the detection precision increased significantly. In contrast, larger geophone spacing corresponded to a lower signal-to-noise ratio (SNR) and more pronounced pseudomorphs in seismic migration imaging. Concurrently, a shorter survey line was associated with more dispersed diffracted wave energy, higher pseudomorph amplitude, and lower-quality seismic images with lower SNRs. Based on simulation results, the parameters of the SWT observation system were optimized and were then validated through a field application in two roadways of mining face WII02040503 in the Tunbao Coal Mine, Xinjiang. Specifically, survey lines with a total length of 2 780 m and 558 receiver points were arranged along both roadways, with a cumulative monitoring length of over 2 558 m. As a result, the SWT observation system yielded advance prediction of 37 fault anomalies, including 29 verified and six predicted on the side walls of roadways yet to be verified. The predicted fault anomalies had an average planar positional error of 5.68 m and advance detection accuracy of 93.5% for sub-seismic faults. Both numerical simulations and the field application demonstrate that, by optimizing key parameters of the SWT observation system based on the characteristics of faults in mines, the SWT advance detection technology can effectively identify densely distributed sub-seismic faults. Accurate advance detection enables the timely optimization of the tunneling technique and support parameters, thereby enhancing the production efficiency of mines and reducing tunneling costs.