We present a technique to automatically classify the wave type of seismic phases that are recorded on a single six-component recording station (measuring both three components of translational and rotational ground motion) at the earth's surface. We make use of the fact that each wave type leaves a unique 'fingerprint' in the six-component motion of the sensor. This fingerprint can be extracted by performing an eigenanalysis of the data covariance matrix, similar to conventional three-component polarization analysis. To assign a wave type to the fingerprint extracted from the data, we compare it to analytically derived six-component polarization models that are valid for pure-state plane wave arrivals. For efficient classification, we make use of the supervised machine learning method of support vector machines that is trained using data-independent, analytically-derived six-component polarization models. This enables the rapid classification of seismic phases in a fully automated fashion, even for large data volumes, such as encountered in land-seismic exploration or ambient noise seismology. Once the wave-type is known, additional wave parameters (velocity, directionality, and ellipticity) can be directly extracted from the six-component polarization states without the need to resort to expensive optimization algorithms.

We illustrate the benefits of our approach on various real and synthetic data examples for applications such as automated phase picking, aliased ground-roll suppression in land-seismic exploration, and the rapid close-to real time extraction of surface wave dispersion curves from single-station recordings of ambient noise. Additionally, we argue that an initial step of wave type classification is necessary in order to successfully apply the common technique of extracting phase velocities from combined measurements of rotational and translational motion.

How to cite: Sollberger, D., Bradley, N., Edme, P., and Robertsson, J. O. A.: Six-component wave type fingerprinting and filtering, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9312, https://doi.org/10.5194/egusphere-egu23-9312, 2023.

A new approach is proposed for measuring the local dispersion curves of surface waves in weakly anisotropic media using a single, multi-component station, which consists of translation and rotation or strain. We directly extract the local azimuth-dependent phase velocity of the Rayleigh wave from the 6C amplitude ratio using seismic arrays deployed in Southern California. The extracted dispersion curves match well with the theoretical 2φ azimuthal anisotropy term. And the estimated fast wave direction is also consistent well with results calculated from SKS and beamforming methods which demonstrates the feasibility of studying local seismic anisotropy directly from 6C amplitude observations.

How to cite: Tang, L., Igel, H., and Montagner, J.-P.: Seismic Anisotropy from 6C Observations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1069, https://doi.org/10.5194/egusphere-egu23-1069, 2023.

The increasing evidence of rotational motions due to earthquakes is now motivating civil engineers to investigate the effects of rotational ground motions on structures. With the advancement in instrumentation techniques, rotational sensors have been developed in the past few years, which can measure three components of rotational waves in addition to the translational waves. Conventionally, buildings are designed to withstand horizontal and vertical translational ground motions to minimize the damage to human life and financial losses during an earthquake. Damage to the structure is identified at two levels; (i) structural and (ii) material. The structural damage in reinforced concrete buildings is visible in the form of cracks and spalling concrete, which reduces the overall load-carrying capacity of the building. The damage at the material level is not visible to the human eye. This damage can be identified using coda wave interferometry techniques. In this method, a high cross-correlation between the coda of two waves passing a point on different days of experiment indicates a negligible change in the shear wave velocity of the material. In comparison, a lower cross-correlation signifies considerable change in the material properties.    

In order to understand how rotational motions affect reinforced concrete structures and how these can be simulated, the present work makes a novel attempt to use the newly developed rotation measuring sensors, BlueSeis 3A and IMU50, to understand the damage in a model concrete bridge structure (BLEIB). We employ advanced sensors in addition to conventional broadband and ultrasonic sensors on the 24m long two-span continuous reinforced concrete bridge equipped with various non-destructive sensing techniques and subjected to a variable pre-tension force of up to 450kN and various static loads. As an initial analysis, we first identify the bridge's first three fundamental frequencies and mode shapes from both recorded translational and rotational data. The analysis shows that the same fundamental frequencies are obtained from the recorded translational and rotational data. However, we expect to see a difference in the mode shapes. Theoretically, rotations are maximum at the bridge support and minimum at the centre of the bridge span. This behaviour is the reverse of what we observe from translational motions, where maximum translations are observed at the centre of the span while minimum at the supports. As the study plans to simulate rotational motions for reinforced concrete structures, a finite element model of the prototype bridge is also developed, and the fundamental frequencies and mode shapes of the model are validated with those obtained from the recorded data. This work shall be extended to applying coda wave interferometry to the rotational data recorded on the bridge to understanding the change observed in material properties when the bridge is subjected to active and passive forces.

How to cite: Dhabu, A., Bernauer, F., Liao, C.-M., Hadziioannou, C., Igel, H., and Niederleithinger, E.: Using Rotational Motions to understand material damage in Civil Engineering structure, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8851, https://doi.org/10.5194/egusphere-egu23-8851, 2023.

First announced at EGU2021, and said to be “released soon”, the 1C rotation seismometer which complements the blueSeis product line on the high performance segment, will be finally disclosed at EGU2023.

2019 and 2020 results have been shared about large mockup of giant Fiber-Optic Gyroscope from iXblue, having diameter as large as 1.2 meters, and the development road to reach an industrial product had been drawn. But several critical additional issues raised on the track.

Keeping in mind all the requirement of the instrument, the need for a transportable, and easily deployable instrument, the calibration capability, the possibility to push the performance pilling up the sensors, and the need for an optional orthogonal structure, we finally come to an instrumental solution with high versatility at expected performances.

The full development story will be shared, and the tests results of first production units of blueSeis-1C will be disclosed. Explanation about the various way to use it will be offered too.

Perspectives and applications using this long-awaited sensor will be presented, from ocean-bottom system tilt denoising to improved inversion of the seismic source.

How to cite: Guattari, F., Lenogue, G., Gautier, K., Frenois, A., and Couderette, A.: Long-awaited and delayed Transportable Highest grade of Fiber Optic Gyroscope for Seismology, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13600, https://doi.org/10.5194/egusphere-egu23-13600, 2023.

A work describes a deeply etched, long active length, high sensitivity short Fabry-Perot cavity nano-strain resolution sensor. The presented sensors exhibit high spectral sensitivity, low intrinsic temperature sensitivity which is for about 40 times lower than in case of FBG, small size and mounting comparable to conventional Fiber Bragg gratings. The sensor high potential is not only high sensitivity and low temperature intrinsic sensitivity, but also in short cavity length and its tunability, which can be simply accomplished in one production step. This brings versatility in interrogation with different general purpose and cost-efficient VIS-NIR widely available linear detector array-based spectrometers, while still providing strain sensing resolution within the range of few 10 nε. A strain resolution of 20 to 70 nε was demonstrated when using a cost-efficient VIS spectrometer. Furthermore, the sensor structure can be combined with multimode telecom lead-in fibers and low-cost broadband LEDs intended for automotive/lightning applications, which allow production of cost efficient solutions.

How to cite: Pevec, S. and Donlagic, D.: Nano-strain resolution fiber-optic Fabry-Perot sensors based measuring systems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3061, https://doi.org/10.5194/egusphere-egu23-3061, 2023.

Optical networks for data transmission have become a pervasive infrastructure in the last years in order to cope with the increasing bandwidth request, thus there is a huge potential to be employed as a wide fiber optic sensing network. In the terrestrial scenario such networks are usually arranged on meshed topologies densely covering large areas of hundreths or thousands of kilometers. On the network's nodes, dedicated hardware is used to routed the data traffic between the connections' endpoints. Such nodes are interconnected by optical fiber links of hundreds of kilometers long, repeated every tenths of kilometers using optical amplifiers.

To fulfill the modern traffic requirements, optical networks are evolving towards multi-service autonomous, flexible, software defined entities based on a centralized intelligence orchestrating the networking functions and communicating with the network elements using standardized interfaces. This trend opens the perspective of using the optical network for evironmental sensing, such as earthquake detection or anthropic activities monitoring. 

Indeed, distributed acoustic sensing (DAS) systems based on Rayleigh scattering have demonstrated that optical fibers are excellent sensors of mechanical stress. However, such systems are expensive and pose some limitations on the maximum reach, so they cannot be deployed extensively. In this context, re-using the already deployed optical data infrastructure to support and integrate dedicated system sensing may be highly beneficial. In this work, we propose an optical data network architecture exposing sensing functionalities with minimum or no additional hardware simply by exploiting the pervasiveness of the telecommunication infrastructure and getting data from the physical quantities already monitored for data transmission purposes. Such architecture on a typical terrestrial optical data network is outlined in figure.

Modern coherent transceivers based on digital signal processing already track the evolution of the transmitted optical signal phase and polarization to recover the transmitted data at the receiver side. As those quantities are strongly affected by external strain, they already contain environmental information. Furthermore, some polarization-based processing can be implemented on cheaper non-coherent transceivers available at each amplifier site as data-service channel, providing several sensing sources.

In addition, further optical devices such as add-drop multiplexer or optical amplifiers typically have several other sensors already embedded (power monitors, temperature sensors) or they can be equipped with some others which can provide environmental data from other physical quantities.

The set of all such environmental data streams produced by the network elements constitutes the streaming telemetry fed to a network controller. A post-process agent may be implemented by exploiting the computational power available in typical network elements to perform local data analysis and reduce the amount of data sent to the sensing controller. By cross-processing the data coming from the network elements, a sensing controller is able to detect and localize events making the network act as a smart grid by continuously monitoring large areas and providing early warning signals.

To support our proposal, in this work we show the results of an experimental activity aimed at detecting and localizing anthropic activities in the city of Turin using a deployed fiber ring.

How to cite: Virgillito, E., Straullu, S., Bratovich, R., M. Rodriguez, F., Awad, H., Castoldi, A., Proietti, R., D'Amico, A., Aquilino, F., Pastorelli, R., and Curri, V.: Exploiting Terrestrial Meshed Optical Data Networks as Environmental Sensing Smart Grids, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6998, https://doi.org/10.5194/egusphere-egu23-6998, 2023.

Optical fiber networks are being implemented in several countries aiming at dissemination of ultra-stable time and frequency references. This enables the comparison of optical clocks, which is a key part of the roadmap towards the future redefinition of the International System of Units (SI) second. Furthermore, this enables uses in chronometric geodesy, where the sensitivity of the optical clocks to the gravitation field enables measurements of height differences as low as 1 cm [1].
The frequency signals in the optical fibers are sensitive to acoustic vibrations which are present in the ground, which is the main source of noise to the disseminated signals.
In recent years, this has enabled studies in the use of optical fiber links for the detection of earthquakes [2]. In such an approach, the measurement is the integrated noise over the fiber path. This typically allows for one to several orders of magnitudes longer range as compare to DAS techniques, but with the loss of localization along the fiber. Such integrated approaches include measurements of the total polarization change of the light along the fiber [3], or the total phase change of a coherent ultra-stable laser signal, potentially including distributed sensing techniques in submarine fibers [2,4].

Here, we will present the first quantitative studies on the use of coherent optical fiber links for seismic detection. Using a the fiber network REFIMEVE in France (see Fig. 1), we present studies on the sensitivity of coherent optical fiber links to seismic events. We describe the dependence of the sensitivity to a number of parameters like incident angle, magnitude and distance, and compare the sensitivity of a fiber link with that of conventional seismometers. We show, for a first time to our knowledge, the detection of seismic waves by a coherent optical fiber network, and we study the prospects of using such a network for the localization of earthquakes. Lastly, we discuss the principles and results of a machine learning algorithm, which enables automatic detection of earthquakes in a coherent optical fiber link.

Bibliography:
1. M. Takamoto et al., Test of general relativity by a pair of transportable optical lattice clocks, Nat. Phot., 14 (7), 411–415. doi:30210.1038/s41566-020-0619-8
2. G. Marra et al. , Ultrastable laser interferometry for earthquake detection with terrestrial and submarine cables. Science, eaat4458. doi: 10.1126/science.aat4458279
3. J.C. Castellanos et al. ,Optical polarization-based sensing and localization of submarine earthquakes. In Optical fiber communication conference (OFC) 2022, doi:26210.1364/OFC.2022.M1H.4
4. G. Marra et al., Optical interferometry–based array of seafloor environmental sensors using a transoceanic submarine cable. Science, doi: 10.1126/science.abo193

Figure 1 : Map of the French REFIMEVE fiber network, shown in red lines. Dotted lines indicates indicate the full scale of the planned network, and continuous red lines indicate links used in these studies. Blue lines indicates the linear approximations of the links. All seismometers of the RESIF network is shown by small green triangles, and seismometers used in theses studies are shown by larger, turquoise triangles.

How to cite: Pottie, P.-E., Tonnes, M., Mazouth-Laurol, M., Montlavan-Leyva, H., Cantin, E., Pointard, B., Alvarez-Martinez, H., Le Targat, R., Lopez, O., Chardonnet, C., and Amy-Klein, A.: Low-frequency seismic wave sensing using coherent optical fiber networks for metrology, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15050, https://doi.org/10.5194/egusphere-egu23-15050, 2023.

In recent years, fiber-optic distributed acoustic sensing (DAS) has been gradually applied to seismology because of its long-distance and dense observation capability. It is a great challenge to effectively process the massive seismic data recorded by DAS. At present, the seismic data processing methods based on deep learning have achieved great success, especially in the tasks of seismic detection and arrival-time picking. However, due to the differences between DAS and geophone, such as sensing principles, spatial and temporal sampling rates, and noise intensity. The seismic arrival time picking model based on deep learning, which is trained by geophone seismic data with low spatial and temporal sampling rates and low noise intensity, severely degrades in performance on DAS seismic data with high spatial and temporal sampling rates and high noise intensity. In addition, a new seismic arrival time picking model is trained by fully supervised learning, which usually requires a large number of seismic data with accurate labels. However, the huge cost of manual picking and the lack of effective automatic picking models make it very difficult to build large-scale DAS seismic data sets with accurate labels. Therefore, it is very difficult to build an arrival time picking model based on fully supervised learning for DAS seismic data.

In this study, we propose a DAS seismic arrival time picking method based on fractional lower order statistics. Based on the difference of probability density function between noise and seismic signal, the proposed method uses alpha-stable distribution modeling noise (generally follow a Gaussian distribution) and seismic signal (generally follow a non-Gaussian distribution), and uses fractional lower order statistics under the assumption of alpha-stable distribution as the characteristic function to pick the arrival time.

Synthetic and actual DAS data tests show that the proposed method has better performance and robustness to random noise than other methods based on characteristic functions, such as STA/LTA, AR-AIC and kurtosis. Since the actual DAS seismic data has no ground truth of arrival time, we have further the performance of the proposed method on the geophone seismic data set. The proposed method provides better results on geophone seismic data and the data after up-sampling them to the typical time sampling rate of DAS.

How to cite: Wang, X., Wang, H., Wang, Y., Zeng, S., and Wang, Y.: Arrival Picking for Distributed Acoustic Sensing seismic based on fractional lower order statistics, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4769, https://doi.org/10.5194/egusphere-egu23-4769, 2023.

Seismic monitoring requires high temporal-spatial resolution and low deployment cost. Distributed acoustic sensing (DAS), as an emerging sensing technology for recording seismic data in recent years, can leverage communication cables for seismic monitoring, providing strong support for more intensive and real-time observation of geological activity. However, the traditional DAS phase unwrapping algorithms (PUAs) derived from Itoh requires the phase difference of adjacent pixels to be less than π, and thus make mistakes in the case of severe noise or large disturbance. In this paper, to the best of our knowledge, two-dimensional (2D) PUA is used to obtain seismograms in DAS for the first time. Satisfactory phase unwrapping is achieved by the 2D PUA method based on the transport of intensity equation (TIE), due to its robustness and noise immunity. Dynamic strain measurements in 80 m straight fiber-optic cable using homemade high-performance DAS, combined with TIE-based 2D PUA produce high-quality seismograms. Time Difference of Arrival (TDOA) Algorithm is applied based on the sensing signal of reliable channels in the seismograms, realizing the high-precision localization of the source. 2D PUAs apply to all phase-demodulation-based sensing techniques and are suitable for recovering spatially correlated objects such as seismic waves, thus having great potential in the field of seismic monitoring.

How to cite: Sun, J., Wang, Y., Zhang, J., Wan, A., Zhang, S., Ye, Z., Liu, F., Zhang, G., and Wang, Z.: Two-dimensional phase unwrapping algorithm aided high-precision source positioning with DAS, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5955, https://doi.org/10.5194/egusphere-egu23-5955, 2023.

We have used two seabed fibre optic cables connecting Ny Ålesund and Longyearbyen at Svalbard, North of Norway, to track several whales for several weeks. Exploiting that we have access to two fibres we demonstrate that it is possible to track several whales in a fairly large region. It is possible to create sound records of whales that can be used for identification and discrimination between various species. The localization method has also been tested by using a small air gun to confirm the localization method used for whales. Examples of earthquake recordings, ship traffic monitoring and distant storms will be shown.

Based on the rapid and promising developments within DAS technology, there is a growing interest for using fibre optic cables at the moon. Some challenges and possibilities related to Lunar DAS applications will be discussed.

How to cite: Landrø, M.: Using DAS-fibres at ocean floor and lunar surface, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2091, https://doi.org/10.5194/egusphere-egu23-2091, 2023.

In this study we use distributed acoustic sensing (DAS) on a 41-km-long submarine optical fibre (OF) cable located offshore Toulon, France. We record both the amplitude and frequency of seafloor strains induced by ocean surface gravity waves, as well as secondary microseisms. Combining the analysis of the two types of waves, we identify and localize local sources of secondary microseisms that manifest as Scholte waves generated by the reflection of oceanic gravity waves on the coastline. During the experiment, these local sources represent the most energetic contribution to the seismic noise recorded along the OF and by an onshore broad-band station located near the DAS interrogator. As a result, the characteristics of this noise are closely related to local wave conditions. One major challenge in performing seismic imaging using ambient seismic noise correlations using DAS data is that we cannot solve for the true seismic velocity because the noise wave field is dominated by local sources. To address this, we measure the incident angle of the dominant local noise sources, correct the apparent velocity using the incident angle retrieve from beamforming analysis and generate a 2D model. We then quantify the errors that arise from picking the dispersion curves of the most energetic velocities without correcting from the incident angle. Our results show that there are significant differences in velocities, with differences reaching up to several hundred meters per second. This highlights the importance of correcting these velocities before generating a tomography. Finally we evaluate an alternative strategy for a linear DAS fiber that cannot be use to localized the dominant noise source. We measure the dispersion curve of the slowest Scholte waves recorded and compare it to the corrected dispersion curves of the dominant source. Although this strategy suffers from limitation, it minimizes the error in the velocity model.

How to cite: Guerin, G. and Rivet, D.: Using localized microseismic noise sources to perform high-resolution seismic Imaging of seafloor using Distributed Acoustic Sensing, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16640, https://doi.org/10.5194/egusphere-egu23-16640, 2023.

The application of distributed acoustic sensing (DAS) in seismology is rapidly expanding due to its ability to perform a large number of high-density measurements, i.e., distributed sensing, without using many point sensors, which is cost-effective. DAS application includes vertical seismic profiling, microseismic measurements, and hydraulic fracturing monitoring and mainly focuses on the event detection capability of  DAS data. 

Febus optics DAS interrogator (A1-R) is continuously running at German Black Forest Observatory (BFO) since May 2021, recording RAW data (selectively stored) or strain-rate data (continuously stored). Our study is in the experimental phase and focuses on testing basic concepts of DAS data, i.e., the effect of gauge-length on the amplitude of measurement and comparing the amplitude of DAS with other seismological sensors such as strain-meter array and a STS2 broadband sensor as well as synthetic simulations. Such comparison is performed using background noise characteristics (power spectral density) and examples of local and regional events that are detectable at the BFO site. 

In this study, we show examples of strain rate measurements related to local earthquakes recorded by horizontal fiber optic cables, employing two different DAS interrogators, cable types and coupling of the cables to the ground. We compared simultaneous recordings using Febus A1 DAS interrogator and OptoDAS by Febus optic and Alcatel Submarine Networks (ASN), respectively, and, concluded about the frequency and gauge-length dependent sensitivity of recordings in two cases. In addition, we compare the amplitude of DAS recordings, for example of local earthquakes, with the synthetic strain simulated  at lower frequency bands using the spectral-element method (Salvus) based on 3D media and analytic approach (Qseis) for 1D model. 

How to cite: Karamzadeh Toularoud, N., Gao, Y.-J., Azzola, J., Forbriger, T., Widmer-Schnidrig, R., Gaucher, E., and Rietbrock, A.: Local earthquake recordings using Distributed Acoustic Sensing (DAS) at BFO, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16307, https://doi.org/10.5194/egusphere-egu23-16307, 2023.

Identifying and monitoring the reactivation of faults and opening of fractures affecting low permeability, sealing formations in natural underground storage complexes such as Carbon Capture and Storage projects and Nuclear Waste repositories is essential to ensure storage integrity and containment. Although passive seismic monitoring can be effective for detecting induced failure, stress accumulation and fault reactivation can occur aseismically in clay-rich formations, preventing early failure to be recognized. Here, we investigate the potential of applying strain monitoring with fiber-optics sensing technologies to assess in-situ changing stress conditions at high spatial and temporal resolution.

We present results of fiber-optic sensing monitoring during the FS-B experiment, a controlled activation of a fault zone affecting the Opalinus Clay Formation in the Mont Terri underground Laboratory (Switzerland). Six constant flowrate water injections induced the hydraulic opening of the fault. A hydraulic connection between the injector and a monitoring borehole occurred, developing a flow path sub-parallel to the fault strike. A 2 km long fiber-optic cable looped through 10 monitoring boreholes surrounding and crossing the fault zone was used for distributed acoustic and strain sensing (DAS and DSS) before, during and after injection. Continuous low-frequency (< 1 Hz) DAS data reveals mechanical strain associated with fault reactivation. Increasing extensional strain is recorded near the point of injection and near the newly formed hydraulic flow path, reaching a value of ~150 μɛ. Post-activation residual strain of ~60 μɛ suggests irreversible fault zone deformation. Smaller strain changes are recorded above and below the high pressure flow path, suggesting a mechanically disturbed zone larger than the leakage zone. Low-frequency DAS data are consistent with co-located DSS strain data, local, 3D displacement measurements of fault movements and P-wave velocity anomalies derived from Continuous Active Source Seismic Monitoring (CASSM). Our results are promising and demonstrate the potential of fiber-optic sensing as a powerful tool for monitoring spatio-temporal evolution of fault reactivation processes and leakage in clay formations induced by fluid pressurization.

How to cite: Rodríguez Tribaldos, V., Hopp, C., Soom, F., Guglielmi, Y., Cook, P., Shadoan, T., Ajo-Franklin, J., Robertson, M., Wood, T., and Birkholzer, J.: Using Distributed Fiber-optic Sensing for Tracking Caprock Fault Activation Processes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9314, https://doi.org/10.5194/egusphere-egu23-9314, 2023.

Earthquake Early Warning (EEW) systems provide seconds to tens of seconds of warning time before potentially-damaging ground motions are felt. For optimal warning times, seismic sensors should be installed as close as possible to expected earthquake sources. However, while the most hazardous earthquakes on Earth occur underwater, most seismological stations are located on-land; precious seconds may go by before these earthquakes are detected. In this work, we harness available optical fiber infrastructure for EEW using the novel approach of Distributed Acoustic Sensing (DAS). DAS strain measurements of earthquakes from different regions are converted to ground motions using a real-time slant-stack approach, magnitudes are estimated using a theoretical earthquake source model, and ground shaking intensities are predicted via ground motion prediction equations. The results demonstrate the potential of DAS-based EEW and the significant time-gains that can be achieved compared to the use of standard sensors, in particular for offshore earthquakes.

How to cite: Lior, I., Rivet, D., Ampuero, J.-P., Sladen, A., Barrientos, S., Sánchez-Olavarría, R., Villarroel Opazo, G. A., and Bustamante Prado, J. A.: Magnitude Estimation and Ground Motion Prediction to Harness Fiber Optic Distributed Acoustic Sensing for Earthquake Early Warning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13803, https://doi.org/10.5194/egusphere-egu23-13803, 2023.

Volcano seismology is essential for understanding, monitoring, and forecasting eruptive events. The use of distributed acoustic sensing (DAS) technology can be particularly useful for this purpose because of its high temporal and spatial resolution, which may help to overcome the challenges of deploying and maintaining seismic arrays on volcanoes.

Between 2020 and 2022, we installed 4 km of optical fibre on Stromboli volcano, Italy, whose persistent activity is well-suited for investigating the related dynamic strain rate. The cable was buried at a depth of 30 cm and the layout geometry was designed to provide wide coverage while being constrained by natural obstacles and topographical features. Seismometers were also installed along the fibre. DAS data were collected using a Febus A1-R interrogator, and the acquisition period increased from one week in 2020 to over four months in 2022. We recorded volcanic tremor, ordinary explosions (several per hour), two major explosions in 2021 and 2022, and the entire sequence of a pyroclastic flow in 2022. 

DAS and seismic data show good agreement in both time and frequency domains after converting strain rate to velocity and vice versa using different methodologies. Beamforming of DAS data shows a dominant signal in the 3-5 Hz frequency band coming from the active craters. We will also present preliminary results of major explosions and pyroclastic flow. This experiment demonstrates that DAS can be used for monitoring volcanic activity.

How to cite: Biagioli, F., Métaxian, J.-P., Stutzmann, E., Ripepe, M., Trabattoni, A., Bernard, P., Longo, R., Diana, G., Innocenti, L., Capdeville, Y., Bouin, M.-P., and Lacanna, G.: Using Distributed Acoustic Sensing to Monitor and Investigate Eruptive Events at Stromboli Volcano, Italy, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3955, https://doi.org/10.5194/egusphere-egu23-3955, 2023.

Distributed Acoustic Sensing (DAS) has been successfully employed to monitor volcanic seismicity and to infer volcanic subsurface structures. Here, we analyse data recorded in September 2018 at Mount Etna by the 9N seismic network. The multi-instrument network includes a 1.3 km long fibre-optic cable that was buried 2-2.5 km away from the main craters. Additionally, 15 geophones were installed along the trajectory of the DAS cable, allowing for a comparison of strain-rate and ground velocity data.
During the acquisition period, tiny seismic events, likely caused by fluid movement and degassing, are visible with inter-event times in the range of 1 min. Volcanic explosions and volcano-tectonic earthquakes also occur frequently. We detect events over all frequency ranges by calculating the coherence matrix for very short time windows (stacking 15 windows of 5 seconds length). An eigendecomposition of the coherence matrices allows to extract the first eigenvectors, corresponding to the dominant source in the time window. The principal eigenvectors can be clustered to find groups of events with similar source properties. We also use the principal eigenvector of already known events as a matched filter to scan the whole dataset. The results of the DAS cable are compared to the observations of the geophone array. While largely obtaining similar findings, the DAS cable seems to better capture high-frequency features of certain events. We also explore the effects of stacking and downsampling of the DAS data prior to detection, which influences both resolution and computational efficiency of the algorithm.

How to cite: Grimm, J., Poli, P., and Jousset, P.: Detecting seismo-volcanic events based on inter-channel coherency of a DAS cable, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9089, https://doi.org/10.5194/egusphere-egu23-9089, 2023.

Distributed Dynamic Strain Sensing (DDSS), also known as Distributed Acoustic Sensing (DAS), is becoming a popular tool for volcano monitoring. The sensing method relies on sending coherent light pulses into an optical fibre and measuring the phase-shift of Rayleigh back-scattered light due to strain on the fibre. This provides distributed strain rate measurements at high temporal and spatial sampling rates. Standard telecom fibres have been conventionally used for this purpose, however engineered fibres are being developed to enhance the back-scattered light, providing up to 100 times improved sensitivity in contrast to the conventional standard fibre. Despite the technical advantages of engineered fibres, standard fibres already have extensive coverage around the Earth surface, and so there is an interest in using the existing telecommunication infrastructure. In this study we compare stack DDSS data from a fibre loops made of several fibres within the same optical fibre cable, with DDSS data measured on an engineered fibre. We analyse how stacking can improve the signal quality of the recorded DDSS data. In an area located 2.5 km NE from the craters of Mt. Etna, we spliced 9 standard fibres together from a 1.5 km long cable to create a single optical path and interrogated using an iDAS unit. At the same time, we interrogated with a Carina unit a 0.5 km engineered fibre installed parallel to the standard multi-fibre cable. Both fibres were interrogated in a common period of 5 days. We use a spatial cross-correlation function to find the channel equivalences between each fibre and then stack them to evaluate the changes in the DDSS data and compare with the engineered fibre data. Our results show that, despite engineered fibres have lower noise, a stack of 5 fibres can achieve a maximum noise reduction of 20% outside of the optical noise band, in comparison to the engineered fibre. We achieved this noise reduction for our specific configuration, and so we show how the stack improvement is dependent on the type of configuration in terms of fibres stacked and length of the fibres. Our findings motivate the exploitation of multi-fibre cables in existing infrastructures, so-called dark fibres, for monitoring volcano and applications to other environments.

How to cite: Diaz-Meza, S., Jousset, P., Currenti, G., David, A., Clarke, A., Stork, A., Chalari, A., and Krawzcyk, C.: Towards exploiting the advantages of a Standard telecom multi-fibre cable for volcano monitoring: an example from Mt. Etna, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15265, https://doi.org/10.5194/egusphere-egu23-15265, 2023.

Since September 2021, signs of unrest at Vulcano Island have been noticed after four years of quiescence, along with CO₂ degassing and the occurrence of long-period and very long-period events. With the intention of improving the monitoring activities, a submarine fiber optic telecommunications cable linking Vulcano Island to Sicily was interrogated from 15 January to 14 February 2022. Of particular interest has been the recording of 1488 events with wide range of waveforms made up of two main frequency bands (from 3 to 5 Hz and from 0.1 to 0.2 Hz).

With the aim of the automatic detection of seismic-volcanic events, different approaches were explored, particularly investigating whether the application of machine learning could provide the same performance as conventional techniques. Unlike many traditional algorithms, deep learning manages to guarantee a generalized approach by automatically and hierarchically extracting the relevant features from the raw data. Due to their spatio-temporal density, the data acquired by the DAS can be assimilated to a sequence of images; this property has been exploited by re-designing deep learning techniques for image processing, specifically employing Convolutional Neural Networks.

The results demonstrate that deep learning not only achives good performance but that it even outperforms classical algorithms. Despite providing a generalized approach, Convolutional Neural Networks have been shown to be more effective than traditional tecniques in expoiting the high spatial and temporal sampling of the acquired data. 

How to cite: Allegra, M., Currenti, G., Cannavò, F., Jousset, P., Prestifilippo, M., Napoli, R., Sciotto, M., Di Grazia, G., Privitera, E., Palazzo, S., and Krawczyk3, C.: Deep learning approach for detecting low frequency events on DAS data at Vulcano Island, Italy, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16459, https://doi.org/10.5194/egusphere-egu23-16459, 2023.

Since its first applications in the past decade, the use of fiber optic cables as ground motion sensors has become a central topic for seismologists, with successful applications of Distributed Acoustic Sensing (DAS) in various key fields such as seismic monitoring, structural imaging and source characterisation.

The instrument response of DAS cables however is largely unknown. Instrument response is a combination of instrument design, local site effects and ground coupling, and for DAS, the latter ones are believed to have a strong, spatially variable, but yet largely unquantified effect. This limits the application of a large number of staple seismological techniques (e.g. earthquake magnitude estimation, waveform tomography) that can require accurate knowledge of a signal’s amplitude and frequency content.

Here we present a method for accurately simulating a DAS cable and its response. The scheme is based on molecular dynamic-like particle-based numerical modelling, allowing the investigation of the effect of varying DAS-ground coupling scenarios. At first, we compute the full strain field directly, for each pair of neighbouring particles in the model. We then define a virtual DAS cable, embedded within the model and formed by a single string of interconnected particles. This allows us to control all aspects of the cable-ground coupling and their properties at an effective granular level through changing the bond strengths and bond types (e.g. nonlinearity) for both the cable and the surrounding medium. Arbitrary cable geometries and heterogeneous materials can be accommodated at the desired scale of investigation.

We observe that at the meter scale, realistic DAS materials, cable-ground coupling and the presence of unconsolidated trench materials around it dramatically affect wave propagation, each change affecting the synthetic DAS record, with differences exceeding at times the magnitude of the recorded signal. These differences show that cable coupling and local site effects have to be considered both when designing a DAS deployment and analysing its data when either true or along-cable relative amplitudes are considered.

How to cite: Celli, N. L., Bean, C. J., O'Brien, G., and Nooshiri, N.: Modelling of DAS cable and ground coupling response using Discrete Particle Schemes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14444, https://doi.org/10.5194/egusphere-egu23-14444, 2023.

Distributed Acoustic Sensing (DAS) is becoming a well-established technology in seismology. For historical and practical reasons, DAS manufacturers usually provide instruments that natively record strain (rate) as the principal measurement. While at first glance strain recordings appear similar to particle motion (displacement, velocity, acceleration) waveforms, not all of the seismological tools developed over the past century (e.g., magnitude estimation, seismic beamforming, etc.) can be readily applied to strain data. Notably, the directional sensitivity of DAS differs from conventional particle motion sensors, and DAS experiences an increased sensitivity to slow waves, often composed of highly scattered waves that are challenging to analyze. To address these issues, several strategies have been already proposed to convert strain rate measurements to particle velocity.

Based on a previously proposed mathematical formalism, we stress some fundamental differences between path-integrated strain and conventional displacement measurements. DAS inherently records arc length variation of the cable which is a relative motion measurement along a curvilinear path. We show that if the geometry of the DAS deployment is adapted to the wavefield of interest, path-integrated strain can be used to closely approximate the displacement wavefield without the need of additional instruments. We validate this theoretical result using collocated seismometers, discuss the limitations of this approach, and show two benefits: enhancing direct P-wave arrivals and simplifying the magnitude estimation of seismic events. While using path integrated strain is in some aspects more challenging, it achieves flat (hence lower) noise levels both in frequency and wavenumber. It also provides better sensitivity to high velocity phases, and permits the direct application of conventional seismological tools that are less effective when applied to the original strain data.

How to cite: Trabattoni, A., Biagioli, F., Strumia, C., Festa, G., van den Ende, M., Rivet, D., Sladen, A., Ampuero, J.-P., Metexian, J.-P., and Stutzmann, É.: Using path-integrated strain in Distributed Acoustic Sensing, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11842, https://doi.org/10.5194/egusphere-egu23-11842, 2023.

Distributed Acoustic Sensing (DAS) is an acoustic sensor instrument that turns a single optical fiber into a dense array of thousands of equally spaced seismometers. Geoscientists and companies have an interest in investing in DAS technologies for better understanding the Earth by observing natural and anthropogenic seismic events or assisting in large infrastructure monitoring with low installation and maintenance costs. However, this type of instrument generates a significantly larger amount of data than conventional seismometers, data that can be complex to store, exploit and interpret.

Several strategies for classifying seismic events from fiber-optics DAS data exist in the scientific literature. Conventional approaches rely on the use of features that describe the waveforms and frequency content of signals recorded individually at virtual stations along the fiber; they do not integrate the spatial density of information permitted by DAS. Several studies on dense seismological arrays have introduced similarity measures between the different time series data such as cross-correlations, dynamic time warping (DTW) or compression-based dissimilarity.

This study aims to quantify the contribution of spatial features for DAS data streams classification. We have chosen to explore spatial features related to both standard statistical measures (e.g., spatial mean, median, skewness, kurtosis), and advanced signal processing measures (e.g., auto-correlations, cross-correlations, DTW). This set of measures allows enriching a list of already used time series features which includes waveform, spectrum and spectrogram. A Random Forest (RF) classifier is then trained, and a Random Markov Field (RMF) algorithm is used after classification to account for redundant spatial and temporal information.

The evaluation of the spatial feature contribution is based on the output of the RF-RMF processing chain. Anthropogenically-triggered seismic data were acquired at the FEBUS Optics test bench. We consider five seismic sources: footsteps, impacts, excavators, compactor and fluid leaks. A class of noise is added as the RF-RMF algorithm is developed for processing DAS streams inherently affected by  noise.  Accurate  classification results can be obtained using only time features, and ongoing tests show a 2% increase in the correct classification rate with the use of both time and spatial features. The improvement allowed by the addition of spatial features is tangible but limited on our test dataset, but we think it should have a much greater impact on natural sources and we will discuss this perspective.

How to cite: Huynh, C., Hibert, C., Jestin, C., Malet, J.-P., and Lanticq, V.: Contribution of spatial features for classifying seismic events from Distributed Acoustic Sensing (DAS) data streams, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6189, https://doi.org/10.5194/egusphere-egu23-6189, 2023.

We present a novel seismic acquisition and processing technique to efficiently evaluate the local dispersion curves of Rayleigh waves for subsequent inversion of shear velocities and near-surface characterization.

The proposed approach consists of computing the ratio between the (time derivated) horizontal spectra H(f)=(∂_tV_x(f)²+∂_tV_y(f)²)^1/2  and the pseudo-divergence spectra D(f), with D being the sum of the horizontal gradients of the horizontal components (i.e. D=∂_xV_x+∂_yV_y).

The processing method itself is comparable to the commonly used H/V approach, except that the H/D spectral ratio provides a direct estimate of the frequency-dependent phase velocities c_R(f)  instead of the site frequency amplification(s). This is demonstrated using synthetic data.

We describe how the D component can be obtained in practice, i.e. by finite-differencing closely spaced horizontal phones or potentially using Distributed-Acoustic-Sensing (DAS) and fibre-optic deployed at the surface. Some limitations about wavelength dependency and impact of Love waves are discussed, as well as potential mitigation measures.

A field test on several hours of ambient noise data collected in Germany with multi-component geophones results in realistic values of Rayleigh wave velocities ranging from ~770 m/s at 10 Hz to ~500 m/ at 30 Hz. Thanks to the local and omni-directional nature of the estimation, the minimal number of required channels and the applicability to ambient noise, we believe that the proposed H/D method can be an attractive alternative to expensive array-based techniques.

How to cite: Edme, P., Sollberger, D., Kiers, T., Schmelzbach, C., Bernauer, F., and Robertsson, J.: Divergence-based estimation of Rayleigh wave dispersion curves, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2814, https://doi.org/10.5194/egusphere-egu23-2814, 2023.

Maintenance of infrastructure is costly and difficult to implement systematically when it spreads over wide areas, such as road or pipeline networks. In the monitoring of road ways, conventional methods to control the road integrity rely on discrete measurements in space and time. There is a large demand for innovative technologies that are able to assess the structural integrity as a whole and in regular intervals or even continuously. Distributed fiber-optic sensing opens the opportunity to measure numerous physical quantities such as temperature and strain with high spatial and temporal resolution over tens of kilometers. In addition, it is easily deployable at reasonable cost.

In order to address the issue of asphalt aging due to exposure to heavy traffic loads, we installed a fiber-optic cable into a reworked road interval and recorded fiber-optic data in a controlled experiment with numerous test vehicles of different sizes and weights. The recorded data suggests that elastic properties of the asphalt can be retrieved from the bypassing traffic. Vehicles can be characterized by the number of axes and load on the asphalt composite. In the next phase, we will monitor the aging of the test field to deduce how varying matrial properties can be better identified for geotechnical and geoscience applications.

How to cite: Krawczyk, C. M., Lipus, M. P., Hart, J., Wollin, C., Cunow, C., and Jousset, P.: Monitoring of elastic properties using DAS and DTS in a controlled experiment during road construction, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15841, https://doi.org/10.5194/egusphere-egu23-15841, 2023.

At a local scale, e.g. in urban settlements, seismic subsurface characterization requires implementing experiments at high spatial resolution. Distributed acoustic sensing (DAS) provides the opportunity of using pre-existing fiber optic cables as dense receiver arrays, thus potentially reducing the effort for active seismic surveying in urban areas. Due to their small footprint, passive experiments appear particularly appealing. However, extracting coherent signals in an urban environment, i.e. in the presence of anthropogenic activity in the receivers' vicinity, remains a challenge.

In this study, we present results from combining the well known technique of Multichannel Analysis of Surface Waves (MASW) with the coherency-based enhancement of wavefields. The investigation is based on a DAS dataset acquired along a major road in Berlin, Germany. We analyse a 4.5 km long straight subsegment of a dark fiber that was sampled at 8 m intervals with 1000 Hz over a period of 15 days. After temporal decimation and the interferometric analysis, clear causal and a-causal branches of Rayleigh-surface waves emerge in the virtual shot gathers.

In the further processing, we employ coherence-based enhancement of wavefields to amplify the Signal to Noise Ratio of the virtual shot gathers. Compared to the traditional workflow of ambient-noise tomography the modified one yields improved dispersion curves particularly in the low-frequency part of the signal. This leads to an increased investigation depth along with lower uncertainties in the inversion result. The final velocity model reaches depths down to 300 m. We show that the application of coherence-based enhancement of the virtual shot gathers in the MASW-workflow may significantly relax the necessity of collecting long baselines for passive tomography in urban environments.

How to cite: Ehsaninezhad, L., Wollin, C., Schwarz, B., and Krawczyk, C.: Coherence-based Amplification of Rayleigh Waves from Urban Anthropogenic Noise recorded with Distributed Acoustic Sensing, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12740, https://doi.org/10.5194/egusphere-egu23-12740, 2023.

Efficient, safe and sustainable utilization of geothermal reservoirs depends on reliable well completion and monitoring technologies. Conventional borehole measurement methods can only be used after the completion process and usually show snapshots of the borehole conditions at discrete points in time. Therefore, the successful borehole completion is a risky process and mainly relies on the experience of the driller. By using distributed fiber-optic sensing technologies, it is possible to monitor all along the cable with dense spatial sampling and continuous in real-time.

In this presentation, we give insights into our newest case study in Berlin. A 450 m deep exploration well for an Aquifer Thermal Energy Storage was completed. We installed a fiber optic sensor cable along the whole production tubing, that contained several single-mode and multi-mode fibers in loose tube and tight buffered configuration. This cable allows to simultaneously measure distributed temperature (DTS), distributed acoustics (DAS) and distributed strain (DSS/DTSS) for the entire completion process.

Particularly with a combined analysis and interpretation of the different fiber-optic technologies, conventionally untraceable processes can be visualized. We are able to show changes of subsurface flow paths due to blockages. Processes to be prevented, like caving or bridging can be detected and the proper rise of gravel or cement can be surveyed. Provided to the driller in real time, subsurface uncertainties can be significantly reduced.

Monitoring geothermal wells with a fiber-optic sensing infrastructure is not only a powerful tool to reduce risks during well completion, which can lead to compromised well integrity. The installed equipment and technology can also be used to assess the well integrity over the whole cycle of the well, to ensure a longest possible lifespan.

How to cite: Hart, J., Lipus, M. P., Wollin, C., and Krawzcyk, C.: Supporting the completion process of boreholes using combined fiber-optic monitoring technologies, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15291, https://doi.org/10.5194/egusphere-egu23-15291, 2023.

Understanding fault zone dynamics in multi-scale is important to embrace the complexity of the earthquake behavior and its natural system. However, the opportunity to map and observe the fault zone behavior at depth with high spatial resolution are rare as also the challenge itself on targeting and identifying the fault zone at depth. We placed a 3D cross-fault fiber array with a downhole loop from surface to depth of 700m for Hole-A (Hanging wall site, crossing fault at depth), after drilling and coring to a frequent slip fault, Milun fault in a plate boundary zone, which ruptured during the 6 February 2018 Mw6.4 Hualien earthquake, and resulted in severe damage to several tall buildings with tens of casualties and injuries. Then, the surface segment crosses the surface fault rupture zone using commercial fiber, and to another downhole loop of 500m fiber for Hole-B (Footwall site). The high spatial resolution from distributed acoustic sensing (DAS) allows us to characterize the fault zone feature together with the retrieved core and geophysical logs after drilling through this frequent slip zone. This 3D route includes the experiment of using commercial fiber to the future application of surface rupture zone identification for seismic hazard mitigation. The project successfully retrieved the fault core associated with Milun fault zone, which could be also seen in geophysical logs with low velocity and resistivity, and mapped using Optical Fiber Sensing technique of the downhole fiber. Within the Milun fault zone, while a 20m thick fault core with grey and black gouge was discovered, a distinct seismic feature associated with this 20m fault gouge was found by its amplification of the strain records from DAS. This amplification ratio is about 2.5-3 when compared to the channels at deeper depth related to a consolidated rock material.  This amplification factor was frequency and azimuth independently, as genuinely observed from all events (e.g. local, and teleseismic earthquakes) with similar amplification factor. Our study shows that the amplification from this 20m fault gouge zone is mainly from the nature of the heterogeneous medium in elastic constant while crossing the fault zone, especially the fault core. Similar feature at surface but with wider surface rupture zone (~ 200m) was found in DAS data as well although less evidence using commercial fiber, while could be validated from the densely deployed geophones crossing the surface rupture of the 2018 Hualien earthquake. Through the depth, a high-resolution asymmetric feature of this active fault was evidenced from the downhole optical fiber and cores. This fault zone behavior would be hardly seen or confirmed without continuous viewing of the wavefields to this high spatial resolution to meter scale. Although the narrow fault gouge, the nature of its amplification in strain due to its strong material contrast from fault gouge was intriguing, and requires intensive attention to consider the contribution of the fault zone heterogeneity in the medium. This might give hints on the understanding of the observation of earthquake dynamics triggering reported worldwide after the occurrence of a mega-earthquake.

How to cite: Ma, K.-F., Kuo, L.-W., Huang, H.-H., von Specht, S., Lin, C.-J., Ku, J.-S., Lin, C.-R., Wu, E.-S., Wang, C.-Y., and Chang, W.-Y.: Why high spatial resolution matters: narrow fault zone, but big effects observed by Taiwan Milun-fault Drilling and All-inclusive Sensing (Taiwan MiDAS) project, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17585, https://doi.org/10.5194/egusphere-egu23-17585, 2023.