Seismic imaging of mine tunnels by ambient noise along linear arrays

Seismic imaging using ambient noise has been widely used to image subsurface structures. The spatial auto correlation (SPAC) method using ambient noise recorded by seismic arrays can image subsurface velocity structures at various scales. In addition, an approximation of zero-offset reflection responses of the structure can be achieved by station autocorrelations of the ambient noise. In this study, to detect an abandoned mine tunnel that is expected to have low velocity anomalies, we jointly apply the SPAC method and station autocorrelation method along linear arrays on the surface above the tunnel. One hundred and thirty-six nodal seismometers were deployed linearly along three lines with station intervals of 1.5 and 5 m, respectively. The ambient seismic noise was continuously recorded for two hours by these stations. Through the SPAC analysis, the Rayleigh wave dispersion curves for the frequency band of 3 Hz to 15 Hz were extracted from the ambient noise, from which the 2D near-surface shear-wave velocity models were estimated. A low velocity zone is obvious at a depth of about 60-100 m in the velocity profile along line 2. In addition, clear diffraction signals can be seen at similar positions on station autocorrelation profile along line 3, which is very close to line 2. This anomalous area is interpreted to be the abandoned tunnel, which is further verified by drilling. Our study shows that the combination of SPAC and station autocorrelation methods can be effective in near surface exploration.

Automated summary

This study combines the SPAC method and station autocorrelation method to detect an abandoned mine tunnel using ambient noise recordings. The results show that the combination of these two methods can effectively image subsurface velocity structures and identify the location of the tunnel.