Seismic interferometry facilitating the imaging of shallow shear‐wave reflections hidden beneath surface waves

Abstract

High‐resolution reflection seismics is a powerful tool that can provide the required resolution for subsurface imaging and monitoring in urban settings. Shallow seismic reflection data acquired in soil‐covered sites are often contaminated by source‐coherent surface waves and other linear moveout noises (LMON) that might be caused by, e.g., anthropogenic sources or harmonic distortion in vibroseis data. In the case of shear‐wave seismic reflection data, such noises are particularly problematic as they overlap the useful shallow reflections. We have developed new schemes for suppressing such surface‐wave noise and LMON while still preserving shallow reflections, which are of great interest to high‐resolution near‐surface imaging. We do this by making use of two techniques. First, we make use of seismic interferometry to retrieve predominantly source‐coherent surface waves and LMON. We then adaptively subtract these dominant source‐coherent surface waves and LMON from the seismic data in a separate step. We illustrate our proposed method using synthetic and field data. We compare results from our method with results from frequency–wave‐number (f‐k) filtering. Using synthetic data, we show that our schemes are robust in separating shallow reflections from source‐coherent surface waves and LMON even when they share very similar velocity and frequency contents, whereas f‐k filtering might cause undesirable artefacts. Using a field shear‐wave reflection dataset characterised by overwhelming LMON, we show that the reflectors at a very shallow depth can be imaged because of significant suppression of the LMON due to the application of the scheme that we have developed.

Ray‐based reflection traveltime tomography using approximate stationary points

“…SI is a method that generates seismic responses by cross‐correlating or convolving seismic data recorded at different receivers (e.g., Schuster ; Bakulin and Calvert ; Bakulin and Calvert ; Draganov, Wapenaar and Thorbecke ; Wapenaar and Fokkema ; Yu and Schuster ; Dong and Hanafy ; Hanafy and Schuster ; Liu, Draganov and Ghose ). In other words, SI can redatum sources (or receivers) as if virtual sources (or virtual receivers) were located at specific positions (i.e., actual source or receiver positions).…”

A 2D seismic reflection dataset of the Caosiyao giant porphyry Mo deposit in the shallow coverage area in Jining, Inner Mongolia, China

“…Although many geophysical survey methods (e.g., electrical, magnetic, gravity, seismic, remote sensing methods) exist, a general, effective, and feasible exploration technology system for use in any mineral exploration remains elusive. Among these geophysical methods, non‐seismic methods, including electromagnetic, induced‐polarization, and potential‐field techniques, have contributed considerably to mineral exploration at shallow depths for decades (Cameron et al, 2004; Eppinger et al, 2013; Liu et al, 2021; Meng et al, 2019; Yan et al, 2021). However, because of their underlying physical principles, these non‐seismic methods suffer inherent limitations with respect to their sensitivity and resolving power at deep depths.…”

Near-surface diffractor detection at archaeological sites based on an interferometric workflow

“…This workflow consists of three main steps. We first reveal masked diffractions by suppression of the dominant Love waves through a combination of SI and nonstationary adaptive subtraction (AS) (Dong et al, 2006;Halliday et al, 2007;Konstantaki et al, 2015;Liu et al, 2018). We then enhance the revealed weak diffraction signal through crosscoherence-based super-virtual interferometry (SVI) (Dai et al, 2011;Nakata et al, 2011;An and Hu, 2016;Place et al, 2019).…”