A scalable algorithm for cross-correlations of compressed ambient seismic noise

Abstract

Companies and academic geophysicists are increasingly collecting continuous seismic data on denser arrays, and are looking to a variety of lossy compression methods to store and quickly access this data. Some researchers turn to ambient noise interferometry for low-cost near-surface imaging to avoid to cost and permitting required for active source experiments, but the computation can be very expensive. For each window of time, typical ambient noise interferometry scales as the product of the number of time samples per window and the number of sensors squared. This paper proposes a new algorithm for data stored in a low-rank matrix factorized form, performing interferometry in compressed form, and separating scalability in sensors from time samples. Application to real data shows nearly identical results at orders of magnitude lower cost. The algorithm can be extended to tensor compressions, averaging cross-correlations over many time windows.

Sensing Earth and environment dynamics by telecommunication fiber-optic sensors: an urban experiment in Pennsylvania, USA

“…By using existing telecommunication infrastructure, particularly by plugging into "dark" or unused fiber that is already installed underground, these experiments greatly reduce the experimental cost and setup time as an interrogator simply needs to be plugged into one end of a stretch of fiber to begin data acquisition. This series of experiments has 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).…”

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

“…By using existing telecommunications infrastructure, particularly by plugging into "dark" or unused fiber that is already installed underground, these experiments greatly reduce the experimental cost and setup time as an interrogator simply needs to be plugged into one end of a stretch of fiber to being data acquisition. 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).…”

“…The ultimate goal of this project is to understand the response of DAS fiber sensing arrays to particular events and use repeating signals to continuously monitoring environment and subsurface physical/chemical/biological changes. Similar to the Stanford array (Martin et al, 2019) and recent Pasadena array (Zhan, 2020), the Penn State FORESEE array continuously records DAS data along 5 km of dark underground telecommunication fibers for over one year since April 2019 (Zhu and Stensrud, 2019). This is the first deployment of a DAS dark fiber array in the Eastern US.…”

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

“…By using existing telecommunications infrastructure, particularly by plugging into "dark" or unused fiber that is already installed underground, these experiments greatly reduce the experimental cost and setup time as an interrogator simply needs to be plugged into one end of a stretch of fiber to being data acquisition. 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).…”