Seismic Monitoring of Machinery through Noise Interferometry of Distributed Acoustic Sensing
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Abstract
Abstract Application of distributed acoustic sensing (DAS) in seismic studies has benefited from its high-density acquisition, environmental adaptation, and low-cost deployment. Nevertheless, the great potential of such observations in seismic research across scales is far from explicit. To test the feasibility of DAS for small-scale seismic monitoring in the urban city, we conducted a one-week field experiment with three ∼72 m long fiber-optic cables, and eight seismometers at the campus of southern marine science and engineering Guangdong laboratory (Guangzhou). Stable high-frequency (2–8 Hz) noise correlation functions (NCFs) were successfully retrieved between DAS channels from continuous in situ noise recording. The observed NCFs are highly asymmetrical, indicating the nonuniform distribution of the noise sources. Beamforming analysis of the seismic data demonstrates that the noise sources are stable daily with consistent direction and slowness. Temporal variation of the NCFs shows that the observed stable signals emerge simultaneously with the machinery operating time of the campus. NCF modeling with spatially varying source spectra reveals that a localized source in the nearby office building fitted the observations well. Accordingly, ground vibration of operating machinery is suggested to account for the temporal and spatial features retrieved from the observed NCFs. Our study demonstrates that DAS has great potential in high-resolution source localization and characterization, as well as temporal monitoring (∼hours) using urban anthropogenic seismic sources.
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