Finite difference modelling to evaluate seismic <i>P</i> wave and shear wave field data

Abstract

Abstract. High-resolution reflection seismic methods are an established non-destructive tool for engineering tasks. In the near surface, shear wave reflection seismic measurements usually offer a higher spatial resolution in the same effective signal frequency spectrum than P wave data, but data quality varies more strongly. To discuss the causes of these differences, we investigated a P wave and a SH wave reflection seismic profile measured at the same location on Föhr island, and applied reflection seismic processing to the field data as well as finite difference modelling of the seismic wavefield (SOFI FD-code). The simulations calculated were adapted to the acquisition field geometry, comprising 2 m receiver distance and 4 m shot distance along the 1.5 km long P wave and 800 m long SH wave profiles. A Ricker-Wavelet and the use of absorbing frames were first order model parameters. The petrophysical parameters to populate the structural models down to 400 m depth are taken from borehole data, VSP measurements and cross-plot relations. The first simulation of the P wave wavefield was based on a simplified hydrogeological model of the survey location containing six lithostratigraphic units. Single shot data were compared and seismic sections created. Major features like direct wave, refracted waves and reflections are imaged, but the reflectors describing a prominent till layer at ca. 80 m depth was missing. Therefore, the P wave input model was refined and 16 units assigned. These define a laterally more variable velocity model (vP = 1600–2300 m s−1) leading to a much better reproduction of the field data. The SH wave model was adapted accordingly but only led to minor correlation with the field data and produced a higher signal-to-noise ratio. Therefore, we suggest to consider for future simulations additional features like intrinsic damping, thin layering, or a near surface weathering layer. These may lead to a better understanding of key parameters determining the data quality of near-surface seismic measurements.