Multi-component surface-wave analysis for tunnel detection in the Sonoran Desert, AZ

Abstract

Subsurface void detection using seismic imaging is a challenging task that has been the subject of extensive research. In this thesis, I employ the novel multi-component backscatter analysis surface waves (BASW) methodology to detect a tunnel 1 m diameter and 10 m deep in the Sonoran desert, AZ. Vertical (V, Rayleigh wave), longitudinal (H1, Rayleigh wave), and transverse (H2, Love wave) surface-wave components were acquired and processed using multichannel analysis of surface waves (MASW) as input for backscatter analysis. BASW sections from all three data sets provided evidence of the tunnel and represented the first successful three-component BASW analysis. Backscatter from the tunnel was significantly enhanced while scatters from geologic heterogeneities were reduced by multiplying the H1 and H2 BASW sections. The location of the tunnel was identified with high confidence based on a joint interpretation of these different work flows. With the clarity of the tunnel signature observed on the multiplied H1-H2 BASW section and verification of that interpretation from numerical modeling, future tunnel detection studies using surface-wave methods would benefit from the combined use of the horizontal components. Joint interpretation of multiple results indicated that perturbations in the surface-wave wavefield can be indicative of a 1 m diameter and 10 m deep tunnel.