Near-surface characterization using urban traffic noise recorded by fiber-optic distributed acoustic sensing

Abstract

The recently developed fiber-optic distributed acoustic sensing (DAS) technology has attracted widespread attention in engineering applications, oil exploration, and seismological research. Compared with the conventional geophones, DAS can acquire high-resolution data due to a dense sampling and can be deployed conveniently in the complex acquisition environment. These advantages of DAS make it promising for near-surface characterization in the urban city. In this study, a DAS line was utilized to record traffic noise seismic data in the urban city and to investigate the near-surface characterization. Seismic surface waves were reconstructed from the acquired traffic noises using seismic interferometry. Thereafter, we obtain the near-surface shear wave velocity profile below the DAS line by surface wave dispersion curve inversion using a Bayesian Markov Chain Monte Carlo method. The results demonstrate the effectiveness of DAS-based urban traffic noise in near-surface characterization.