Urban Near-surface Seismic Monitoring using Distributed Acoustic Sensing

Abstract

Urban subsurface monitoring requires high temporal-spatial resolution, low maintenance cost, and minimal intrusion to nearby life. Distributed acoustic sensing (DAS), in contrast to conventional station-based sensing technology, has the potential to provide a passive seismic solution to urban monitoring requirements. Based on data recorded by the Stanford Fiber Optic Seismic Observatory, we demonstrate that near-surface velocity changes induced by the excavation of a basement construction can be monitored using existing fiber optic infrastructure in a noisy urban environment. To achieve the satisfactory results, careful signal processing comprising of noise removal and source signature normalization are applied to raw DAS recordings. Repeated blast signals from quarry sites provide free, unidirectional, and near-impulsive sources for periodic urban seismic monitoring, which are essential for increasing the temporal resolution of passive seismic methods. Our study suggests that DAS will likely play an important role in urban subsurface monitoring.

City‐Scale Dark Fiber DAS Measurements of Infrastructure Use During the COVID‐19 Pandemic

“…Therefore, this type of experiment can be rapidly deployed in a few hours and continue to record for years without major operations costs. In urban areas, DAS measurements have already been used for near surface geological imaging (Dou et al, 2017; Fang et al, 2020; Martin, 2018; Spica et al, 2020) and earthquake recording (Lindsey et al, 2017; Martins et al, 2019).…”

Sensing earth and environment dynamics by telecommunication fiber-optic sensors: An urban experiment in Pennsylvania USA

“…In 2019 there are more than hundreds repeatable blast events cataloged from these sites, which could allow yearly near-surface monitoring of geotechnical engineering activities (Fang et al, 2020) and/or hydrological systems owing to a significant ground water level variation. One strong event, shown in Figure 14, was recorded on May 14 2019 from the site 4 (Pleasant Gap, PA).…”

“…This series of experiments have shown that signal quality is often good enough for earthquake detection and imaging even though loose cables in underground conduits only couple to the surrounding soils through friction and gravity (Lindsey et al, 2017;Jousset et al, 2018;Martin et al, 2019;Yu et al, 2019;Ajo-Franklin et al, 2019). At the Stanford Fiber Optic Seismic Observatory, Rayleigh wave dispersion showed significant spatial variability at scales relevant to earthquake ground motion prediction (Martin, 2018;Spica et al, 2020), and time-lapse changes through a building excavation (Fang et al, 2020). However, investigation of near-surface time-lapse changes due to seasonal precipitation variation yielded no significant velocity variation when investigated with time-lapse ambient noise interferometry (Martin, 2018).…”

A Self-Supervised Deep Learning Approach for Blind Denoising and Waveform Coherence Enhancement in Distributed Acoustic Sensing Data

“…By connecting a DAS interrogator at one end of a (potentially) tens-of-kilometres-long optical fibre, time-series measurements of ground deformation can be made at metre-spaced intervals along the cable. This emerging technology has massively extended our range of capabilities for seismic monitoring, enabling the deployment of dense seismic arrays in areas that were previously inaccessible, such as urban [2], [3] or submarine [4], [5] locations. Fibreoptic cables can be deployed on rugged terrain on land or underwater, are temperature-robust, and they are sensed ex-situ (i.e.…”