Geophysical detection of clandestine tunnels is a complex problem that has met with limited success. Multiple methods have been applied, spanning several decades, but a reliable solution has yet to be found. We evaluated shallow seismic data collected at a tunnel test site representative of geologic settings found along the southwestern U.S. border. Our results demonstrated the capability of using P-wave diffraction and surface-wave backscatter techniques to detect a purpose-built subterranean tunnel. Near-surface seismic data were also collected at multiple sites in Afghanistan to detect and locate subsurface anomalies, including data collected over the escape tunnel discovered in 2011 at the Sarposa Prison in Kandahar, Afghanistan, which allowed more than 480 prisoners to escape, and data from another shallow tunnel recently discovered at an undisclosed location. The final example from Afghanistan was the first time surface-based geophysical methods have detected a tunnel whose presence and location was not previously known. Seismic results directly led to the discovery of the tunnel. Interpreted tunnel locations for all examples were within less than 2 m of the actual location. Seismic surface-wave backscatter and bodywave diffraction methods showed promise for efficient data acquisition and processing for locating purposefully hidden tunnels within unconsolidated sediments.
We have applied time-domain 3D elastic full-waveform inversion (FWI) to a known tunnel constructed 10 m below the surface with no distinguishing surface expressions. Multicomponent inversion experiments that use an initial model estimated from surface wave methods suggest that the vertical sources and the combination of vertical and longitudinal receivers result in the clearest image of the tunnel. We obtain an approximate 3D image of the tunnel using 24 vertical sources and 720 vertical and 720 longitudinal receivers. We find that increasing the number of vertical sources to 216 does not significantly improve the details of the tunnel. Further experimentation indicates that we can detect the tunnel using a reduced data set of 6–10 vertical sources and 216 vertical sensors. In addition, calculating the [Formula: see text] ratio helps remove artifacts from the inverted model and highlights the location of the tunnel. We compare the 3D inversion results with the 2D FWI results for the same tunnel that we previously evaluated. The variety of successful inversion experiments suggest that FWI is capable of imaging shallow tunnels in desert geologies.
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