Enhancing Ambient Noise Interferometry for Das: Selective Stacking and Hybrid Seismic Receivers

Abstract

Summary Near-surface imaging is crucial for a broad range of studies, with seismic monitoring becoming an increasingly important tool due to recent developments in Distributed Acoustic Sensing (DAS) and ambient noise interferometry (ANI). Using a dataset acquired on the Rutford Ice Stream, West Antarctic, we develop ANI approach for DAS datasets which retrieves the Rayleigh wave response from the ambient seismic wavefield. We find that a conventional ANI approach, which uses a single DAS channel as a virtual source and the entire continuous dataset is stacked, produces unstable, poor quality interferograms. This is due to coherent instrument noise and an absence of continuous ambient seismic noise. To overcome these issues, we develop an approach based on selective-stacking and hybrid seismic receivers, which significantly improves the quality of the Rayleigh waves retrieved using DAS. Our findings highlight the impacts that coherent DAS instrument noise and the transient nature of seismic noise above 1Hz has on ambient seismic noise studies.