Migration imaging quality can be improved and the disaster source ahead of the tunnel face can be detected efficiently by quickly and effectively removing the noise associated with random broadband and intense energy characteristics from tunnel advance seismic wave detection data. In this study, a denoising method for tunnel advance seismic wave detection is established by introducing the advantages of the spectral subtraction method in suppressing random noise into tunnel seismic wave detection data processing. The denoising method can effectively remove random noise and has high computational efficiency that meets the fast construction requirements of the tunnel. An numerical simulation analysis of typical adverse geological models shows that spectral subtraction can effectively suppress the random noise interference in the tunnel environment, increase the signaltonoise ratio of reflected wave signals in the seismic record, and reduce the artifactual interference in the offset imaging results, effectively improving the detection accuracy. Accordingly, the method was applied to a case project, and the location and extent of the rock fracture zone in front of the tunnel face were successfully detected, proving the effectiveness and practicality of the method for future applications.