Distributed Acoustic Sensing for Seismic Monitoring of The Near Surface: A Traffic-Noise Interferometry Case Study

Shan Dou,John Peterson,Thomas M Daley,Eileen R Martin,Michelle Robertson,Craig Ulrich,Anna M Wagner,Nate Lindsey,Jonathan B Ajo-Franklin,Barry Freifeld

doi:10.1038/s41598-017-11986-4

Abstract

Ambient-noise-based seismic monitoring of the near surface often has limited spatiotemporal resolutions because dense seismic arrays are rarely sufficiently affordable for such applications. In recent years, however, distributed acoustic sensing (DAS) techniques have emerged to transform telecommunication fiber-optic cables into dense seismic arrays that are cost effective. With DAS enabling both high sensor counts (“large N”) and long-term operations (“large T”), time-lapse imaging of shear-wave velocity (VS) structures is now possible by combining ambient noise interferometry and multichannel analysis of surface waves (MASW). Here we report the first end-to-end study of time-lapse VS imaging that uses traffic noise continuously recorded on linear DAS arrays over a three-week period. Our results illustrate that for the top 20 meters the VS models that is well constrained by the data, we obtain time-lapse repeatability of about 2% in the model domain—a threshold that is low enough for observing subtle near-surface changes such as water content variations and permafrost alteration. This study demonstrates the efficacy of near-surface seismic monitoring using DAS-recorded ambient noise.

Highlights

In order to provide warnings before failures occur, an effective near-surface seismic monitoring system needs to utilize measurements that have sufficient resolution and extent, both spatially and temporally
To balance the trade-off between data quality and temporal resolution, we use phase-weighted stacking (PWS) to achieve high signal-to-noise ratio (SNR) with fewer records than what would be needed with a mean stack (Fig. 4); we look for the shortest epoch duration sufficient for stabilizing the data stacks
With a 110-meter-long distributed acoustic sensing (DAS) array deployed perpendicular to a nearby road, we were able to acquire multichannel recordings of surface waves via ambient-noise interferometry

Summary

Introduction

In order to provide warnings before failures occur, an effective near-surface seismic monitoring system needs to utilize measurements that have sufficient resolution and extent, both spatially and temporally This in turn requires deployment and continuous operation of dense sensor arrays, which is rarely feasible with conventional sensors (e.g., geophone) because long-term costs are prohibitively high. DAS generates digital waveforms that are familiar to seismic practitioners, but because DAS is a distributed sensor, waveforms obtained at each channel are not a point measurement but are strains measured over a spatial distance This distance is commonly referred to as gauge length, and one must not confuse gauge length with channel spacing: whereas channel spacing can be as small as 25 cm (as it only needs to be longer than the spatial duration of the laser pulse2), gauge length needs to be long enough (typically ≥8 meters3) to ensure optimal signal-to-noise ratio (SNR). With DAS, multichannel recordings of surface waves can be continuously retrieved with ambient-noise interferometry, making noise-based approach applicable to time-lapse VS imaging

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Conclusion