- Joined
- Mar 3, 2021
Highlights
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We developed a migration-based source location method to locate vessels on Distributed Acoustic Sensing data.- •
The algorithm was applied on two DAS datasets acquired from seabed infrastructure.- •
The method showed excellent performance with DAS-derived locations validated by GPS, both for the considered deep- and shallow water case.
Conclusions
We successfully applied a processing method to automatically detect and locate vessel-induced acoustic events using two DAS datasets from two types of pre-existing seabed infrastructure, each with different field conditions. The location method consists of a migration-based source location approach and subsequent k-means clustering, and results show a clear correlation between DAS derived vessel locations with the locations from independently reported AIS data.
So, everything in our on the ocean can be monitored and tracked using the vast arrays of fiber optic cables on the seabed now!The method makes effective use of the high spatial-temporal density of DAS data through constructive summation of coherent waveforms over space and time. The track, speed and course of the considered vessels could be derived from the analyzed DAS data in the vicinity of the fiber-optic cable and showed consistent agreement with the AIS data. This demonstrates the potential of using DAS measurements to monitor acoustic sources, such as from vessels, in the vicinity of seabed infrastructure. Finally, the method allows for first optimizing the velocity model and then inverting for the acoustic source location in a sequential manner. This highlights the complimentary value of the method for subsurface studies.
