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Coherence-based Earthquake Location Using Integrated Fiber-optic and Conventional Seismic Networks

Description: 

Distributed Fiber-Optic Sensing (DFOS) is an emerging technology able to provide detailed images of the seismic wavefield. Although standard (channel-wise) seismic data analysis procedures based on phase picks can be adapted for DFOS systems, their performances may be hindered by the effects of optical noise, cable coupling, and axial directivity. Furthermore, pick-based approaches do not fully exploit the primary advantage of DFOS, the high-density spatial sampling along the fiber.

Coherence-based approaches, which stack energy along theoretical travel-times, provide significant advantages for dense seismometer networks in constraining event locations on a 3D grid. However, DFOS systems have far more channels than conventional networks of seismometers, hence the direct use of coherence-based methods on DFOS data can be computationally demanding. Despite these challenges, the integration of DFOS and standard seismometers represents the next-generation paradigm for seismic monitoring. Possible solutions comprise a) improvements in computational efficiency and/or b) DFOS automatic data selection and decimation.

Here, we present preliminary tests of a coherence-based locator that better adapts to DFOS alongside standard seismometers. Efficiency of the method on DFOS data is achieved considering a cylindrical symmetry to compute 2D travel-time lookup tables (horizontal distance, depth), while retaining a 3D grid to sum the contributions of the individual DFOS waveforms (coherence map). We mitigate potential bias in event location when using DFOS and seismometers, arising from the different number of measurement sites, by assigning a balancing weight. Data sub-sampling is additionally considered for rectilinear cable sections.

Session: Fiber-optic Sensing Applications in Seismology - II

Type: Oral

Date: 4/15/2025

Presentation Time: 11:15 AM (local time)

Presenting Author: Emanuele

Student Presenter: No

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