Removing source-side scattering for virtual deep seismic sounding (VDSS)

Abstract

We present a method that extends both the applicability and the quality of virtual deep seismic sounding (VDSS)—a technique for estimating crustal thickness that is robust even if the crust–mantle transition is complex or the crustal thickness is large. The results are important for studies of crustal contributions to isostasy and for understanding dynamic topography due to mantle convection. VDSS uses S-to-P conversions beneath seismic stations as virtual sources for large, post-critical reflections off the Moho, that is, the seismic phase SsPmp. Original applications of VDSS rely on deep earthquakes as sources of illumination to circumvent strong, near-source scattering (e.g. depth phases) and are, therefore, limited by the uneven distribution of deep seismicity. The method presented here effectively removes effects of the earthquake source wavelet (SW, including complexities arising from long, complicated source time functions and near-source scattering) and can be applied to signal from shallow and deep earthquakes. It involves two steps. First, based on analyses of particle motion, we separate ‘pseudo-P’ and ‘pseudo-S’ wave trains from the vertical and the radial component of ground motion. The latter is then used as the appropriate reference time-series for the deconvolution of the vertical and the radial component of ground motion. Since the reference time-series contains both the SW and S-type signals due to scattering near the receiver, the deconvolution also effectively removes S-type multiples, such as the phase SsPms and related reverberations. Applying this method to synthetic seismograms verifies that it is robust in removing complex SWs, even in the presence of random or signal-generated noise. The method is further validated using data recorded by the Hi-CLIMB array from both deep and shallow earthquakes. Impulsive signals are now routinely achieved, significantly improving both the quality and quantity of results from VDSS.