A numerical study of surface-wave-based tunnel detection at the Black Diamond Mines Regional Preserve, California

Abstract

Detecting underground voids, such as old mine workings, solution cavities in karst terrain, or unknown tunnels such as illicit cross-border tunnels, is a challenging problem for geophysics and an important concern for geotechnical design, public safety, and domestic security. Seismic surface-wave-based detection methods have become increasingly popular for detecting relatively shallow and small targets; however, the theoretical limitations of these methods have thus far remained unclear. We use a suite of 3D numerical simulations inspired by a tunnel detection experiment carried out at the Black Diamond Mines Regional Preserve (BDM) in northern California. The geophysical anomalies predicted by our numerical simulations at BDM agree with field observations, and our estimates for the location of the primary tunnel target agree with historical records in the area. Using our calibrated numerical model, we perform a parametric study to determine the effect of tunnel size, depth of burial, filling material, and source characteristics to determine the range over which surface-wave backscattering and attenuation-based methods are effective. In addition, we perform a regression analysis to determine a relationship for the maximum depth at which a tunnel may be detected via these approaches, given the target diameter, wavelength of interest, and the signal-to-noise ratio.