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Wavefield Reconstruction Using Mixed DAS and Point-Sensor Networks

Session: Fiber-Optic Seismology II [Poster]

Type: Poster

Date: 4/23/2021

Presentation Time: 03:45 PM Pacific

Description: 

Distributed Acoustic Sensing (DAS) networks promise to revolutionize observational seismology by providing cost-effective, highly dense spatial sampling of the seismic wavefield, especially by utilizing pre-deployed telecomm fiber in urban settings for which dense seismic network deployments are difficult to construct. However, each DAS channel is sensitive only to one projection of the horizontal strain tensor and therefore gives an incomplete picture of the horizontal seismic wavefield. We utilize compressive sensing to develop a framework within which a DAS deployment, or mixed DAS and point-seismic deployment, generates a representation of the horizontal seismic wavefield as a signle unified data product. We illustrate this method using the Porotomo seismic deployment at Brady, Nevada, and find that the DAS network can successfully recover both components of the horizontal P wavefield for the regional ML4.3 Hawthorne NV earthquake. We also find that the inclusion of a small number of point sensors significantly improves overall recovery, and reaches similar levels of performance to much denser point sensor arrays.

Presenting Author: Jack Muir

Student Presenter: Yes

Authors