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SCEC2022 Plenary Talk, Seismology

Challenges, opportunities, and discoveries using large-scale distributed acoustic sensing arrays

Ettore Biondi, Yan Yang, Jiaqi Fang, Jiuxun Yin, Weiqiang Zhu, Jiaxuan Li, Ethan F. Williams, & Zhongwen Zhan

Oral Presentation

2022 SCEC Annual Meeting, SCEC Contribution #12029 VIEW SLIDES
In recent years, distributed acoustic sensing (DAS) is demonstrating to be an effective tool when applied for seismological purposes and the number of its applications is rapidly growing. DAS can turn ordinary telecommunication fibers into large-scale seismic arrays composed of thousands of channels with meter-scale spacing, which provide unprecedented data-rich observations to study natural and human-made seismic phenomena. In addition, the ever-increasing world fiber infrastructure would serve as the perfect framework to expand and enhance continuous monitoring by integrating DAS within existing seismic networks. However, the current data volumes recorded by DAS instruments (i.e., TBs/day)... represent a considerable challenge for processing systems. On the other hand, by leveraging modern computational architectures (e.g., general-purpose graphics processing units) and designing novel methodologies for data processing and analysis (e.g., machine-learning algorithms), it is possible to extract the plethora of information stored within DAS datasets. We highlight how we manage large DAS data volumes and employ them for various seismological applications: earthquake monitoring, subsurface characterization, and earthquake-early warning. Our database strategy of DAS data combined with the usage of state-of-art computational tools allows us to efficiently explore and exploit the recorded large datasets. The high-spatiotemporal resolution nature of DAS and its deployment simplicity on existing fibers will open new opportunities in seismic hazard assessment, noise and subsurface monitoring, and earthquake engineering.
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