On the Detection Capabilities of Underwater Distributed Acoustic Sensing

Lior, Itzhak; Sladen, Anthony; Rivet, Diane; Ampuero, Jean‐Paul; Hello, Y.; Becerril, Carlos; Martins, Hugo F.; Lamare, P.; Jestin, Camille; Tsagkli, S.; Markou, C.

doi:10.1029/2020jb020925

Cited by 83 publications

(89 citation statements)

References 45 publications

(97 reference statements)

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“…On the other hand, one of the main promises of DAS is its versatility in deployment conditions, with interesting deployment targets including "heterogeneous" environments such as urban areas (Dou et al, 2017;Fang et al, 2020) and submarine basins (Lindsey et al, 2019;Sladen et al, 2019). For many civil monitoring applications, such as traffic density monitoring (Liu et al, 2018) and vehicle tracking (Wiesmeyr et al, 2020), some of the issues pointed out in the previous section do not apply, as the signals of interest arrive at the DAS fibre at a shallow (or zero) inclination. However, for the purpose of localising deep or distant sources, the inclination sensitivity of DAS starts to become directly relevant.…”

Section: Implications For Beamforming On Sparse and Dense Das Arraysmentioning

confidence: 99%

Evaluating seismic beamforming capabilities of distributed acoustic sensing arrays

Ende

Ampuero

2021

Solid Earth

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Abstract. The versatility and cost efficiency of fibre-optic distributed acoustic sensing (DAS) technologies facilitate geophysical monitoring in environments that were previously inaccessible for instrumentation. Moreover, the spatio-temporal data density permitted by DAS naturally appeals to seismic array processing techniques, such as beamforming for source location. However, the measurement principle of DAS is inherently different from that of conventional seismometers, providing measurements of ground strain rather than ground motion, and so the suitability of traditional seismological methods requires in-depth evaluation. In this study, we evaluate the performance of a DAS array in the task of seismic beamforming, in comparison with a co-located nodal seismometer array. We find that, even though the nodal array achieves excellent performance in localising a regional ML 4.3 earthquake, the DAS array exhibits poor waveform coherence and consequently produces inadequate beamforming results that are dominated by the signatures of shallow scattered waves. We demonstrate that this behaviour is likely inherent to the DAS measurement principle, and so new strategies need to be adopted to tailor array processing techniques to this emerging measurement technology. One strategy demonstrated here is to convert the DAS strain rates to particle velocities by spatial integration using the nodal seismometer recordings as a reference, which dramatically improves waveform coherence and beamforming performance and warrants new types of “hybrid” array design that combine dense DAS arrays with sparse seismometer arrays.

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Section: Implications For Beamforming On Sparse and Dense Das Arraysmentioning

confidence: 99%

Evaluating seismic beamforming capabilities of distributed acoustic sensing arrays

Ende

Ampuero

2021

Solid Earth

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“…The cables, earthquakes and seismometer locations are shown in the maps in this section. Appendix B Lior andZiv (2017, 2018) and Luco (1985) derived a set of ground motion RMS descriptions based on Eq. (3) (Eq.…”

Section: Appendix Amentioning

confidence: 99%

Strain to ground motion conversion of distributed acoustic sensing data for earthquake magnitude and stress drop determination

Lior

Sladen

Mercerat³

et al. 2021

Solid Earth

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Abstract. The use of distributed acoustic sensing (DAS) presents unique advantages for earthquake monitoring compared with standard seismic networks: spatially dense measurements adapted for harsh environments and designed for remote operation. However, the ability to determine earthquake source parameters using DAS is yet to be fully established. In particular, resolving the magnitude and stress drop is a fundamental objective for seismic monitoring and earthquake early warning. To apply existing methods for source parameter estimation to DAS signals, they must first be converted from strain to ground motions. This conversion can be achieved using the waves' apparent phase velocity, which varies for different seismic phases ranging from fast body waves to slow surface and scattered waves. To facilitate this conversion and improve its reliability, an algorithm for slowness determination is presented, based on the local slant-stack transform. This approach yields a unique slowness value at each time instance of a DAS time series. The ability to convert strain-rate signals to ground accelerations is validated using simulated data and applied to several earthquakes recorded by dark fibers of three ocean-bottom telecommunication cables in the Mediterranean Sea. The conversion emphasizes fast body waves compared to slow scattered waves and ambient noise and is robust even in the presence of correlated noise and varying wave propagation directions. Good agreement is found between source parameters determined using converted DAS waveforms and on-land seismometers for both P and S wave records. The demonstrated ability to resolve source parameters using P waves on horizontal ocean-bottom fibers is key for the implementation of DAS-based earthquake early warning, which will significantly improve hazard mitigation capabilities for offshore earthquakes, including those capable of generating tsunami.

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“…The low frequency regime may be critical regional scale landslide detection (i.e. Fan et al, 2020); hence this technique may be most appropriate for detecting relatively local low or far-field high frequency signals, but more studies are required that provide similar comparisons, to test the sensitivities of different cable configurations, interrogator units and analytical approaches (Lindsey and Martin, 2021;Lior et al, 2021).…”

Section: Opportunities Using Distributed Cable-based Sensingmentioning

confidence: 99%

“…It is also important to identify and differentiate landslide-related noise from ambient seismic and acoustic noise that arises from natural background processes and human activities in the ocean. In noisy marine environments, ambient noise may overprint or entirely obscure the records of submarine landslides; hence, an understanding of the levels, frequency and time windows of that background noise is important when designing monitoring strategies (Lior et al, 2021). Societal lockdowns in 2020 and 2021 associated with the COVID-19 pandemic have been identified as periods of significantly reduced seismic noise both on land and at sea (Lecocq et al, 2020;Ryan et al, 2020), and may therefore provide a rare window of reduced background noise to explore local to global datasets.…”

Section: Site-specific Effectsmentioning

confidence: 99%

Seismic and Acoustic Monitoring of Submarine Landslides: Ongoing Challenges, Recent Successes and Future Opportunities

Clare¹,

Lintern²,

Pope³

et al. 2021

Preprint

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Submarine landslides pose a hazard to coastal communities due to the tsunamis they can generate, and can damage critical seafloor infrastructure, such as the network of cables that underpin global data transfer and communications. These mass movements can be orders of magnitude larger than their onshore equivalents and are found on all of the world’s continental margins; from coastal zones to hadal trenches. Despite their prevalence, and importance to society, offshore monitoring studies have been limited by the largely unpredictable occurrence of submarine landslide and the need to cover large regions of extensive continental margins. Recent subsea monitoring has provided new insights into the preconditioning and run-out of submarine landslides using active geophysical techniques, but these tools only measure a very small spatial footprint, and are power and memory intensive, thus limiting long duration monitoring campaigns. Most landslide events therefore remain entirely unrecorded. Here we first show how passive acoustic and seismologic techniques can record acoustic emissions and ground motions created by terrestrial landslides. We then show how this terrestrial-focused research has catalysed advances in the detection and characterisation of submarine landslides, using both onshore and offshore networks of broadband seismometers, hydrophones and geophones. We then discuss some of the new insights into submarine landslide preconditioning, timing, location, velocity and their down-slope evolution that is arising from these advances. We finally outline some of the outstanding challenges, in particular emphasising the need for calibration of seismic and acoustic signals generated by submarine landslides and their run-out. Once confidence can be enhanced in submarine landslide signal detection and interpretation, passive seismic and acoustic sensing has strong potential to enable more complete hazard catalogues to be built, and opens the door to emerging techniques (such as fibre-optic sensing), to fill key, but outstanding, knowledge gaps concerning these important underwater phenomena.

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On the Detection Capabilities of Underwater Distributed Acoustic Sensing

Cited by 83 publications

References 45 publications

Evaluating seismic beamforming capabilities of distributed acoustic sensing arrays

Evaluating seismic beamforming capabilities of distributed acoustic sensing arrays

Strain to ground motion conversion of distributed acoustic sensing data for earthquake magnitude and stress drop determination

Seismic and Acoustic Monitoring of Submarine Landslides: Ongoing Challenges, Recent Successes and Future Opportunities

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