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Session: Earthquake Characterization Using Fiber-optic Cables

Type: Oral

Date: 10/8/2024

Time: 11:45 AM

Room: Stanley Park Ballroom

Advancing Earthquake Characterization with Telecom Fiber Networks

The emerging distributed acoustic sensing (DAS) technology can convert a pre-existing telecommunication fiber cable of tens of kilometers in length into a dense seismic array of thousands of recording channels. Here, we present a workflow for leveraging DAS together with the conventional seismic network to analyze high-resolution earthquake source properties, including seismic phase picking, earthquake relocation, focal mechanism inversion, and high-resolution rupture imaging. We first introduce PhaseNet-DAS, a deep neural network model, for automated earthquake detection and seismic phase identification from DAS recordings. Following detection, our scalable cross-correlation framework, CCTorch, robustly measures differential phase traveltimes and relative polarities between detected seismic events. Furthermore, we have devised a matrix-free adjoint solver that performs double-difference relocation using data from thousands of DAS channels. We have also developed a data-driven method for reliably inverting absolute first-motion polarities on DAS, which are critical for tightly constraining the nodal plane orientations and accurately inverting high-resolution focal mechanisms. We have successfully applied these methods to several DAS arrays in California. Finally, we present the DAS-based high-resolution back-projection rupture imaging using the Mw6 crustal earthquake that occurred in Antelope Valley, CA in 2021 as an example. These successful research progresses underscore the potential of DAS as a next-generation seismic monitoring tool that can significantly enhance and complement existing seismic networks. With the extensive existing and proposed network of onshore and offshore telecommunication fiber cables, DAS could provide critical datasets for systematically investigating detailed seismic source properties.

Presenting Author: Jiaxuan

Additional Authors