Spurious signals attenuation using SVD-based Wiener filter for near-surface ambient noise surface wave imaging

Abstract

In recent years, high-frequency passive surface wave methods based on seismic interferometry have been applied to estimate near-surface shear wave velocity structure in urban geophysical investigations. One of key steps of using surface-wave methods is to image the dispersion energy and identify different modes of surface waves. In the dispersion image generated by multichannel analysis of passive surface waves method, however, a type of “crossed” artifacts usually overlaps and smears the true dispersion energy in a high frequency range. The “crossed” artifacts are spatial aliasing of a reverse-directional propagating wave with a directional velocity scan. In urban areas, the coherent noise signals could be repetitively induced by traffic in a short time segment, which will produce repetitive signals in the cross-correlation function, leading to spurious reverse-directional propagating waves in the causal or acausal part. We propose to use the Wiener filter based on singular value decomposition (SVD) to attenuate the spurious signals in the cross-correlation functions so as to reduce “crossed” artifacts in the dispersion image. A synthetic example demonstrates that the “crossed” artifacts related to spurious signals in the dispersion image can be well attenuated by applying the SVD-based Wiener filter (SVDWF) to cross-correlation functions. Two field examples suggest that high-mode dispersion energy in the dispersion images generated from the SVDWF denoised cross-correlation functions becomes more continuous and clearer in high frequency bands, which benefits from the advantages of both SVD and Wiener filters.