WITHDRAWN Using AIS Data to Determine the Location of Ocean Bottom Fiber Optic Cables
Description:
WITHDRAWN Undersea fiber-optic cables form the backbone of global telecommunication networks, facilitating rapid data transmission across continents. However, the correct location of telecom subsea cables is generally inaccurate, if not completely unknown, or even sometimes undisclosed for safety reasons, as fiber optic cables represent a crucial geopolitical asset. Unlike on land, where tap tests with precise GPS data can be performed, subsea cables are not easily and inexpensively accessible. This limits their potential for proper seismic and environmental monitoring of near-coastal regions using Distributed Acoustic Sensing (DAS).
This study presents an approach to enhance the geolocation of undersea fiber-optic cables using Automatic Identification System (AIS) data from ships and large vessels transiting above subsea cables. We use a 4-month dataset from a cable located offshore Florence, OR. The first 50 km of the cable were probed with a Febus A1R interrogator unit using a 20 m channel spacing, a 100 Hz sampling rate, and a 40 m gauge length. During this experiment, we identified 186 vessels of different types and sizes, many crossing the cable multiple times. We precisely determine the location of some channels using the noise generated by ships and correlate it with AIS data. This study allows us to provide additional constraints on the location of fiber-optic cables and DAS channels.
Session: Advancing Seismology with Distributed Fiber Optic Sensing [Poster Session]
Type: Poster
Date: 5/3/2024
Presentation Time: 08:00 AM (local time)
Presenting Author: Marcelle
Student Presenter: Yes
Invited Presentation:
Authors
Marcelle Collares Presenting Author Corresponding Author collares@umich.edu University of Michigan |
Zack Spica zspica@umich.edu University of Michigan |
Loïc Viens lviens@lanl.gov Los Alamos National Laboratory |
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WITHDRAWN Using AIS Data to Determine the Location of Ocean Bottom Fiber Optic Cables
Session
Advancing Seismology with Distributed Fiber Optic Sensing