SM2.2

The oceans present a major gap in geophysical instrumentation, hindering fundamental research on submarine earthquakes and the Earth’s interior structure, as well as effective earthquake and tsunami warning for offshore events. Emerging fiber-optic sensing technologies that can leverage submarine telecommunication cables present an new opportunity in filling the data gap. Marra et al. (2018) turned a 96 km long submarine cable into a sensitive seismic sensor using ultra-stable laser interferometry of a round-tripped signal. Another technology, Distributed Acoustic Sensing (DAS), interrogates intrinsic Rayleigh backscattering and converts tens of kilometers of dedicated fiber into thousands of seismic strainmeters on the seafloor (e.g., Lindsey et al., 2019; Sladen et al., 2019; Williams et al., 2019; Spica et al., 2020). Zhan et al. (2021) successfully sensed seismic and water waves over a 10,000 km long submarine cable connecting Los Angeles and Valparaiso, by monitoring the polarization of regular optical telecommunication channels. However, these new technologies have substantially different levels of sensitivity, coverage, spatial resolution, and scalability. In this talk, we advocate that strategic combinations of the different sensing techniques (including conventional geophysical networks) are necessary to provide the broadest coverage of the seafloor while making high-fidelity, physically interpretable measurements. Strategic collaborations between the geophysics community and telecommunication community without burdening the telecomm operation (e.g., by multiplexing or using regular telecom signals) will be critical to the long term success.

Marra, G., C. Clivati, R. Luckett, A. Tampellini, J. Kronjäger, L. Wright, A. Mura, F. Levi, S. Robinson, A. Xuereb, B. Baptie, D. Calonico, 2018. Ultrastable laser interferometry for earthquake detection with terrestrial and submarine cables. Science, eaat4458.

Lindsey, N.J., T. C. Dawe, J. B. Ajo-Franklin, 2019. Illuminating seafloor faults and ocean dynamics with dark fiber distributed acoustic sensing. Science. 366, 1103–1107.

Sladen, A., D. Rivet, J. P. Ampuero, L. De Barros, Y. Hello, G. Calbris, P. Lamare, 2019. Distributed sensing of earthquakes and ocean-solid Earth interactions on seafloor telecom cables. Nat Commun. 10, 5777.

Spica, Z.J., Nishida, K., Akuhara, T., Pétrélis, F., Shinohara, M. and Yamada, T., 2020. Marine Sediment Characterized by Ocean‐Bottom Fiber‐Optic Seismology. Geophysical Research Letters, 47(16), p.e2020GL088360.

Williams, E.F., M. R. Fernández-Ruiz, R. Magalhaes, R. Vanthillo, Z. Zhan, M. González-Herráez, H. F. Martins, 2019. Distributed sensing of microseisms and teleseisms with submarine dark fibers. Nat Commun. 10, 5778.

Zhan, Z., M. Cantono, V. Kamalov, A. Mecozzi, R. Muller, S. Yin, J.C. Castellanos, 2021. Optical polarization-based seismic and water wave sensing on transoceanic cables. Science, in press.

How to cite: Zhan, Z., Cantono, M., Castellanos, J., González Herráez, M., Jia, Z., Kamalov, V., Martins, H., Mecozzi, A., Müller, R., Shen, Z., Williams, E., and Yin, S.: Towards multi-method geophysical sensing on submarine cables, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6445, https://doi.org/10.5194/egusphere-egu21-6445, 2021.

For the first time, a 6-km long fiber-optic strain cable was deployed across an active fault on the seafloor with the aim to monitor possible tectonic movement using laser reflectometry, 25 km offshore Catania Sicily (an urban area of 1 million people). Brillouin Optical Time Domain Reflectometry (BOTDR) is commonly used for structural health monitoring (bridges, dams, etc.) and under ideal conditions, can measure small strains (10^-6) along a fiber-optic cable, across very large distances (10 - 200 km), with a spatial resolution of 10 - 50 m. The FocusX1 expedition, (6-21 October 2020) onboard the R/V Pourquoi Pas? was the first experiment of the European funded FOCUS project (ERC Advanced Grant). We first performed micro-bathymetric mapping and a video camera survey using the ROV Victor6000 to select the best path for the cable track and for deployment sites for eight seafloor geodetic stations. Next we connected a custom designed 6-km long fiber-optic cable (manufactured by Nexans Norway) to the TSS (Test Site South) seafloor observatory in 2100 m water depth operated by INFN-LNS (Italian National Physics Institute) via a new Y-junction frame and cable-end module. Cable deployment was performed by means of a deep-water cable-laying system with an integrated plow (updated Deep Sea Net design Ifremer, Toulon) to bury the cable 20 cm in the soft sediments in order to increase coupling between the cable and the seafloor. The cable track crosses the North Alfeo Fault at four locations. Laser reflectometry measurements began on 18 October 2020 and are being calibrated by a 3 - 4 year deployment of eight seafloor geodetic instruments (Canopus acoustic beacons manufactured by iXblue) deployed on 15 October 2020. During a future marine expedition, tentatively scheduled for early 2022 (FocusX2) a passive seismological experiment is planned to record regional seismicity. This will involve deployment of a temporary network of Ocean Bottom Seismometers (OBS) on the seafloor and seismic stations on land, supplemented by INGV permanent land stations. The simultaneous use of laser reflectometry, seafloor geodetic stations as well as seismological land and sea stations will provide an integrated system for monitoring a wide range of slipping event types along the North Alfeo Fault (e.g. - creep, slow-slip, rupture). A long-term goal of the project is the development of dual-use telecom cables with industry partners.

How to cite: Gutscher, M.-A., Royer, J.-Y., Murphy, S., Klingelhoefer, F., Barreca, G., Gaillot, A., Quetel, L., Riccobene, G., Aurnia, S., Jousset, P., Poitou, C., and Ciausu, V.: First deployment of a 6-km long fiber-optic strain cable and a seafloor geodetic network, across an active submarine fault (offshore Catania, Sicily): The FOCUS experiment, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2498, https://doi.org/10.5194/egusphere-egu21-2498, 2021.

Distributed Acoustic Sensing (DAS) enables the use of existing underwater telecommunication cables as multi-sensor arrays, allowing for detailed study of the seismic wavefield. Since underwater telecommunication cables were not deployed for seismological investigations, the coupling between the cable and the seafloor varies, dramatically reducing the usefulness of poorly coupled cable segments for seismological research. In particular, underwater cables include segments that are suspended in the water column across seafloor valleys or other bathymetry irregularities. Here, we propose that ocean bottom currents may be studied by monitoring the vibrations of suspended cable segments. We analyze DAS-strain recordings on three dark fibers deployed in the Mediterranean Sea. Several cable segments, presumably suspended, feature high-amplitude signals with harmonic spectra as expected from a theoretical model of in-plane vibration of hanging cables. The spatial shape of the vibration modes are determined by filtering and stacking. Their comparison to theory allows constraining the attenuation of longitudinal waves propagating along the cable in the non-suspended sections. The vibration frequencies change over time scales of tens of minutes. Assuming that oscillations of suspended sections are driven by deep sea currents, the temporal fluctuations of the vibration frequencies are related to changes of the cables tension which, in turn, are related to the drag force induced on the suspended cable by the shedding of Karman vortex. On this basis, we propose a method to infer changes of deep sea current speeds from the changes of fundamental frequency of cable vibrations. Submarine optical reconnaissance campaigns and controlled smaller-scale experiments are planned to validate the approach. The work aims at demonstrating the potential of using suspended telecommunication cables to monitor and investigate marine currents in deep ocean environments.

How to cite: Mata Flores, D., Ampuero, J.-P., Mercerat, D., Sladen, A., and Rivet, D.: The Potential of DAS on Underwater Fiber Optic Cables for Deep-Sea Current Monitoring, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5042, https://doi.org/10.5194/egusphere-egu21-5042, 2021.

Accurate monitoring of floating ice thickness is an important safety issue for northern countries where lakes, fjords, and coasts are covered with ice in winter, and used by people to travel. For example in Finland, 15-20 fatal accidents occur every year due to ice-related drowning. We have explored the potential of fiber optics to measure the propagation of seismic waves guided in the ice layer, in order to infer its thickness via the inversion of the dispersion curves. An optical fiber was deployed on a frozen lake at Lacs Roberts (2400m) above Grenoble and we measured with a DAS the signal generated by active sources (hammer) and ambient noise. We demonstrate that we can retrieve the ice thickness. This monitoring method could be of interest since the deployment of a fiber on ice is quite simple (e.g. using a drone) compared to other techniques for ice thickness estimation such as seismic survey or manual drilling.

How to cite: Coutant, O., Moreau, L., Boué, P., Larose, E., and Cimolino, A.: Measuring floating ice thickness with optical fibers and DAS, a test case study on a frozen moutain lake., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7404, https://doi.org/10.5194/egusphere-egu21-7404, 2021.

Fibre-optic Distributed Acoustic Sensing (DAS) is an emerging technology for vibration measurements with numerous applications in seismic signal analysis as well as in monitoring of urban and marine environments, including microseismicity detection, ambient noise tomography, traffic density monitoring, and maritime vessel tracking. A major advantage of DAS is its ability to turn fibre-optic cables into large and dense seismic arrays. As a cornerstone of seismic array analysis, beamforming relies on the relative arrival times of coherent signals along the optical fibre array to estimate the direction-of-arrival of the signals, and can hence be used to locate earthquakes as well as moving acoustic sources (e.g. maritime vessels). Naturally, this technique can only be applied to signals that are sufficiently coherent in space and time, and so beamforming benefits from signal processing methods that enhance the signal-to-noise ratio of the spatio-temporally coherent signal components. DAS measurements often suffer from waveform incoherence, and processing submarine DAS data is particularly challenging.

In this work, we adopt a self-supervised deep learning algorithm to extract locally-coherent signal components. Owing to the similarity of coherent signals along a DAS system, one can predict the coherent part of the signal at a given channel based on the signals recorded at other channels, referred to as "J-invariance". Following the recent approach proposed by Batson & Royer (2019), we leverage the J-invariant property of earthquake signals recorded by a submarine fibre-optic cable. A U-net auto-encoder is trained to reconstruct the earthquake waveforms recorded at one channel based on the waveforms recorded at neighbouring channels. Repeating this procedure for every measurement location along the cable yields a J-invariant reconstruction of the dataset that maximises the local coherence of the data. When we apply standard beamforming techniques to the output of the deep learning model, we indeed obtain higher-fidelity estimates of the direction-of-arrival of the seismic waves, and spurious solutions resulting from a lack of waveform coherence and local seismic scattering are suppressed.

While the present application focuses on earthquake signals, the deep learning method is completely general, self-supervised, and directly applicable to other DAS-recorded signals. This approach facilitates the analysis of signals with low signal-to-noise ratio that are spatio-temporally coherent, and can work in tandem with existing time-series analysis techniques.

References:
Batson J., Royer L. (2019), "Noise2Self: Blind Denoising by Self-Supervision", Proceedings of the 36th International Conference on Machine Learning (ICML), Long Beach, California

How to cite: van den Ende, M., Lior, I., Ampuero, J. P., Sladen, A., and Richard, C.: A self-supervised Deep Learning approach for improving signal coherence in Distributed Acoustic Sensing, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2502, https://doi.org/10.5194/egusphere-egu21-2502, 2021.

The need for submarine observatories to monitor offshore tectonic sources that can generate destructive earthquakes and tsunamis is widely recognized but the requirements of real-time communications and cost has hindered its Implementation. Only very few dedicated cables with sensors are in operation today. If the dozens of commercial telecommunication submarine cables that are deployed every year were instrumented, they could revolutionize the offshore earthquake monitoring. These cables, named as SMART (Science Monitoring And Reliable) have been advocated by the JTF of United Nations (Joint Task Force) for nearly a decade but none has been deployed today. However, there are several identified projects that should become the first pilots worldwide.

Fiber optic research have shown that the cable itself can be used as strain meters and useful for seismic monitoring.

One technology is DAS, Distributed Acoustic Sensing. DAS uses a single dedicated portion of (dark) fiber on a submarine cable, with a length about ~100 km. It can be modelled as a distributed strain sensor, with localization ability of a few meters. The DAS signal using OTDR (optical time domain reflectometry) and signal phase detection measures the fiber strain and record earthquakes with a resolution like broadband seismic sensors.

Another technology is LI (Laser Interferometry). LI may use a dark fiber or a single telecom wavelength channel in an optical fiber pair with commercial traffic, thousands km long. It relies on frequency stable laser sources and coherent detection. LI detects the changes of fiber optical transmission parameters over the whole cable. Using recording instruments on both ends, the arrival point of the first seismic waves is determined, and the azimuth to the epicenter estimated.

This work proposes and applies one methodology to assess the gain in earthquake source information using any of the three cable sensor technologies mentioned, against a background scenario that includes only land stations. We use a Monte-Carlo simulation to allow for picking uncertainties, local and regional variations of propagation velocity models. We parametrize the gain in information by measuring the epicenter uncertainty ellipse and the focal depth variability.

The proposed methodology is applied to the NE Atlantic domain, SW Iberia and the Azores archipelago, an area where the relative motion of the Nubia, Eurasia and North America plates can generate large and destructive earthquakes and tsunamis.

While the inclusion in the monitoring network of SMART observatories, placed inside cable repeaters, spaced every ±70 km, is straightforward, the use of DAS and LI is not. For DAS and LI we consider that observations can be decimated to virtual seismic stations every 5 km and 1 km respectively. To avoid using a set of very close stations, we implement different station selection algorithms.

The investigation presented in this work was conducted by LEA, Listening to the Earth under the Atlantic, a partnership between IT, IPMA and IDL. One of the main objectives of LEA is to promote research, development, training and outreach on geophysical and oceanographic phenomena using submarine cables, fostering its applications to Science and Civil Protection.

How to cite: Matias, L., Carrilho, F., Sá, V., Niehus, M., Corela, C., and Omar, Y.: Parameterizing the gains in earthquake monitoring using submarine optical fiber telecom cables, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7869, https://doi.org/10.5194/egusphere-egu21-7869, 2021.

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 and tsunami earthquakes.

How to cite: Lior, I., Sladen, A., Mercerat, D., Ampuero, J.-P., Rivet, D., and Sambolian, S.: Strain to Ground Motion Conversion of DAS Data for Earthquake Magnitude and Stress Drop Determination, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7601, https://doi.org/10.5194/egusphere-egu21-7601, 2021.

Ambient noise generated by the anthropological activities in the urban environments may contain both Rayleigh and Love waves. Due to the differences in the physics of Rayleigh and Love waves, a pre-knowledge of the wave modes in the cross-correlogram is essential for an accurate inversion of the subsurface velocity model. Several studies (Martin and Biondi, 2017; Martin et al., 2017; Luo et al., 2020) demonstrated that only Rayleigh waves can be extracted by cross-correlation if the virtual source is colinear with the DAS array based on the assumption that the ambient noise sources are random and uniformly distributed. However, in realistic cases, ambient noise sources may come from a certain direction (e.g., Dou et al., 2017; Zhang et al., 2019). Moreover, the source propagation direction should be resolved and used to correct the apparent dispersion curves. Zhao et al. (2020) and van den Ende et al. (2020) proposed that beamforming results are not always reliable due to the measurements of DAS.

Based on the synthetic DAS ambient noise data recorded by a near “L” shape array (Source-West corner of the Stanford DAS-1 array), we prove that beamforming can resolve the source direction when the ambient sources are mainly coming from one direction. Two important processing procedures are that: check the polarity in the data and apply polarity flip on one part of the data; apply amplitude normalization on the data if strong amplitude difference exits in the data. Based on the source direction, the coordinate of the DAS array, and amplitude ratio of the data recorded by the two segments of the DAS array, we propose an inversion method to calculate the amplitude ratio of the Rayleigh and Love waves generated by the ambient sources.

We apply the method to two 100-second DAS ambient noise data recorded by the Stanford DAS-1 array. We first resolve the source propagation direction from the two data. The results indicate that the ambient noise in the data were mainly generated by the motor vehicles running on the Campus Drive in the northwest of the array. Then we invert for the Rayleigh and Love waves amplitude ratio using the proposed method. The ratios for the two data are 0.2 and 0.13, respectively. The results suggest that the ambient noise generated by motor vehicles running on the northwest corner of the Campus Drive mainly contain Love waves.

How to cite: Zhao, Y. and Li, Y. E.: Beamforming Reliability of DAS Ambient Noise Data and Wave Modes Identification, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3858, https://doi.org/10.5194/egusphere-egu21-3858, 2021.

As fibre-optic DAS deployments become more common, researchers are turning to tried-and-true methods of locating or characterizing seismic sources such as beamforming. However, the strain measurement from DAS intrinsically carries its own sensitivities to both wave type and polarization (Martin et al. 2018, Paitz 2020 doctoral thesis). Additionally, a measurement along a conventional fibre-optic cable only provides one component of motion, and so certain azimuths may be blind to certain types of seismic sources, unless the cable layout can be designed to be oriented in multiple directions.

In this work, we explore the development and application of a beamforming algorithm that explicitly searches for multiple wavetypes. This builds on 3-component beamforming or Matched Field Processing (MFP) algorithms by Riahi et al. (2013), and Gal et al. (2018), where in addition to gridsearching over possible source azimuths, a distinct gridsearch is performed for each possible wavetype of interest. This does not solve the problem that a given cable orientation might be less sensitive to certain directions, but at least an array-response function can be robustly defined for each type of seismic excitation. This might help further distinguish whether beamforming observations are dominated by primary sources or by secondary scattering (van der Ende and Ampuero, 2020 preprint).

Much of this work uses analytic theory and synthetic examples. Time permitting, the enhanced algorithm will also be applied to data from the Mt. Meager experiment to explore its feasibility and efficacy with real data (EGU contribution from Klaasen et. al, 2021).

How to cite: Bowden, D. C., Klaasen, S., Martin, E., Paitz, P., and Fichtner, A.: Wave-selective beamforming with Distributed Acoustic Sensing, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12216, https://doi.org/10.5194/egusphere-egu21-12216, 2021.

We present an analysis and qualitative comparison between acoustic data recorded on a distributed acoustic sensing (DAS) instrument (Silixa iDAS, version 2) and a three-component geophone chain colocated in a 400 m deep ICDP borehole in the magmatically active Vogtland area, Germany. A tight buffer single-mode fiber optic cable with a structured surface was installed and cemented behind casing down to total depth of the well. Additionally, a vertical array of 10 Hz geophones is suspended within the borehole.At the surface, further geophones were installed to shape a permanent three-dimensional seismic array. For this experiment the DAS system sampled strain-rate data at 10 m gauge length and 1 m spacing, yielding a high-resolution image of the wave field. Both seismic systems recorded data for 24 hours at 1 kHz sampling rate.

Within these 24 hours of recording, we shot a vertical seismic profile (VSP) with a 300 kg heavy and 2.4 m tall drop weight source moving up to a distance of 400 m away from the wellhead. Furthermore, passive seismic events at local and regional distances were recorded.

We compare the signal quality between the DAS system and the calibrated three-component geophones using the active and passive signals, to determine the sensitivity, signal-to-noise ratios and frequency response. Further we investigate the noise characteristics of both systems in this natural and remote environment, and evaluate the feasibility of borehole DAS behind casing for micro-earthquake monitoring. We give an outlook how dense DAS data can be utilized for VSP experiments with the aim to develop methods for fault detection and characterisation for application in DAS data recorded at the surface.

How to cite: Isken, M. P., Dahm, T., Heimann, S., Wollin, C., Ohrnberger, M., Reinsch, T., and Krawczyk, C. M.: Signal analysis between DAS and geophones in a vertical borehole from active and passive sources, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10943, https://doi.org/10.5194/egusphere-egu21-10943, 2021.