Distributed Acoustic Sensing (DAS) for Continuous Monitoring of Near-Surface Properties Using Coda Wave Interferometry

Date: 4/24/2019

Time: 09:15 AM

Room: Grand Crescent

Distributed Acoustic Sensing (DAS) re-purposes telecommunication optical fibers as multichannel seismic arrays. This rapidly developing technology enables acquisition of seismic data for long periods of time across long distances (10’s of km) at unprecedented spatial (~1 m) and temporal resolutions, defining it as an ideal tool for monitoring variations in near-surface seismic properties.

Measuring changes in relative seismic velocity (dv/v) in the subsurface using ambient seismic noise interferometry is increasingly being used in environmental and geohazard monitoring. Here, we follow this approach and explore the utilization of DAS-based seismic observations for tracking temporal changes in dv/v through the analysis of coda waves in ambient noise recordings. The continuous recording of ambient seismic noise at frequencies from mHz to kHz at very high spatial density provided by DAS enables a thorough investigation of hypothesized spatial and temporal variations in seismic velocities and how they relate to changes in subsurface properties. We calculate cross-correlation function estimates between inline DAS sensors for consecutive time periods and apply coda wave analysis techniques to estimate traveltime shifts between waveforms. Issues related to the repeatability of DAS observations and the significance/interpretability of measured changes for monitoring near-surface properties will be addressed. This approach is applied to a variety of monitoring DAS datasets recorded over several months using both built-for-purpose fiber-optic installations and so-called ‘dark fiber’ networks, i.e. fiber-optic lines installed for telecommunication purposes but not currently utilized for data transmission (unlit). Applications range from detection of water-level fluctuations to permafrost thaw. Our observations will shed light into the potential for using DAS-based seismic networks as a tool for continuous monitoring of environmental and critical processes at a regional scale.

Presenting Author: Verónica Rodríguez Tribaldos

Authors