We welcome contributions on developments in instrumental and theoretical advances, applications and processing with fibre optic point and/or distributed multi-sensing techniques, light polarization and transmission analyses, using standard telecommunication and/or engineered fibre cables. We seek studies on theoretical, observation and advanced processing across all solid earth fields, including seismology, volcanology, glaciology, geodesy, geophysics, natural hazards, oceanography, urban environment, geothermal applications, laboratory studies, large-scale field tests, planetary exploration, gravitational wave detection, fundamental physics. We encourage contributions on data analysis techniques, novel applications, machine learning, data management, instrumental performance and comparison as well as new experimental, field, laboratory, modelling studies in fibre optic sensing studies.
We are pleased to receive 2 invited speakers: Jiaxan Li (California Institute of Technology, USA) and Miguel González Herráez (University of Alcalá, UAH, Spain)
DAS (Distributed Acoustic Sensing) systems have become widely used tools in Geophysics and Seismology. While most DAS users are familiar with the basic principles of the technology and the typical performance of commercially available interrogators, there is often a limited understanding of the fundamental performance limits of DAS systems.
In this talk, I will review the foundational principles of DAS and will provide insight into the physical limitations of conventional technology. By exploring these constraints and strategies to overcome them, I will introduce two innovative systems currently under development in my lab that demonstrate significantly different capabilities compared to standard DAS systems.
The first system achieves centimeter-scale gauge lengths over a sensing range of approximately 1 km. The second system, while offering conventional performance (meter-scale resolution over tens of kilometers), eliminates 1/f instrumental noise entirely, making it well-suited for very long-term monitoring of processes with timescales ranging from days to months.
How to cite: Gonzalez-Herraez, M.: Beyond conventional DAS systems, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6942, https://doi.org/10.5194/egusphere-egu25-6942, 2025.
The interest in distributed acoustic sensing (DAS), using different implementations of Phase-Sensitive Optical Time-Domain Reflectometry (ΦOTDR), has dramatically increased in the last decade, particularly in the context of seismic signals, due to the possibility of high spatial coverages over >100km with a single fibre interrogator. However, while the possibility for high sensitivity measurements up to the vicinity of 1Hz regime have been extensively researched, potential of this technique for long-term (>24h) measurements has been so far largely unexplored.
In this paper Large Chirped-Pulse ΦOTDR (LCP-ΦOTDR) employing large chirps (8GHz) and assisted by distributed Raman amplification was used to extend traditional DAS bandwidth to day long high-sensitivity (mK) measurements over 50km of fibre.
With the use of large chirps in Chirped-Pulse ΦOTDR (extended almost one order of magnitude from the previously researched ≈1GHz to 8GHz, while retaining 10m spatial resolution), the stability of a fibre reference is greatly increased, allowing for long-term measurements without 1/f noise accumulation. Therefore, the intrinsic DAS sensitivity (sub-mK, sub-nε) observed over high frequencies (>1Hz) is maintained over much longer periods (>24h) even for several temperature variations of several ºC in the fibre.
Long range operation was achieved via distributed Raman amplification, which ensured high optical SNR over 50km of a standard single-mode fibre. The system’s nonlinearities were characterized both in the optical domain and in the dynamic strain sensing results thus ensuring an operation regime with sensor linearity and distortion free DAS measurements.
At the end of the 50km fibre (the worst point of optical SNR), calibrated dynamic strain signals (0.5Hz, 3000nε peak-to-peak) were applied to verify the system's response for traditional DAS operation. Then, temperature variations of several ºC were tracked over 72h, with an upper bound error of a few millikelvin. Coherency was maintained even after several hour-long measurement interruptions.
Finally, it should be noted that the LCP-ΦOTDR upper bound error of a few millikelvin over 72h is a conservative estimation, since an accurate assessment of the system’s noise floor was not experimentally possible (as the LCP-ΦOTDR sensitivity exceed our own experimental capability of applying or measuring mK temperature variations in the fibre).
How to cite: Canudo, J., Hernandez-Martín, L., Ania-Castañón, J. D., Preciado-Garbayo, J., and F. Martins, H.: Extending DAS operation bandwidth to LonG rAnge Millikelvin distriButed fIbre Thermometry, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10998, https://doi.org/10.5194/egusphere-egu25-10998, 2025.
We report preliminary results from a first-of-its-kind academic wireline deployment of a joint DAS-seismometer in an abandoned well. We designed a custom-made 1.5 km-long cable that includes both optical fibers and copper wires, and attached a seismometer at its bottom. The apparatus was lowered to a depth of approximately 750m in a vertical borehole, abandoned and plugged about 40 years ago. We also deployed broad-band seismometers near the wellhead. We show data from an active vertical seismic profiling (VSP) experiment in which we also had surface geophones, low-frequency DAS, and earthquake monitoring from the nearby Dead Sea Fault, including comparisons to surface stations. Coupling is obtained from the fluid filling the borehole below a depth of approximately 380 m. Despite very strong tube waves in the upper sections of the well and complicated phase behavior in the deeper parts, we were able to obtain useful data.
How to cite: Lellouch, A. and Wetzler, N.: Joint wireline DAS-seismometer deployment in an abandoned well: lessons and insights, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6458, https://doi.org/10.5194/egusphere-egu25-6458, 2025.
LOKI is an optical interrogator initially developed by ESEO and subsequently refined over several generations of prototypes. Over the past five years, these prototypes have been deployed worldwide in partnership with IPGP to investigate a wide range of sensor modalities (volcano monitoring, underwater seismicity, geothermal activity…), demonstrating robust field performance and highlighting new opportunities for high-precision measurements.
Technically, LOKI enables electronic-less point-based measurements at the end of long optical fibers (up to 30 km). This capability facilitates deployments under the sea or atop volcanoes, with LOKI situated onshore or in a distant safe area. Furthermore, it complements distributed acoustic sensing (DAS) systems that provide measurements along the fiber’s length. The combination of distributed (DAS) and pointwise (LOKI) approaches offers flexibility for complex experimental setups, enabling broad spatial coverage and locally detailed monitoring.
The presentation will outline various field campaigns and application scenarios where LOKI has been successfully deployed. Notably, LOKI can operate as part of an autonomous station in harsh outdoor environments, requiring only 6 W from a solar panel. The sensing elements employed in these deployments are fully optical and maintenance-free, including all-fiber strainmeters and seismometers, with additional modalities under development, including rotational seismometer. Retrofitting existing seismometers to operate them with optical readout will also be discussed, demonstrating how LOKI enables remote interrogation and broadened research possibilities.
From now on, LOKI is industrially manufactured by MAÅGM, ensuring consistent performance and readiness for extensive deployment, with dedicated support and maintenance services. This communication aims to share insights gained from diverse field tests and to inform the scientific community that these experiments are now reproducible and accessible, opening new avenues of research in seismic and structural monitoring.
How to cite: Guattari, F., Dupont, H., Menard, P., Bernard, P., Ferron, R., Feuilloy, M., Savaton, G., Plantier, G., and Metaxian, J.-P.: LOKI: A Field-Proven Optical Interrogator for High-Precision Remote Point Sensing of Electronics-Free Sensors, Now Available to the Geoscientific Community, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16037, https://doi.org/10.5194/egusphere-egu25-16037, 2025.
Long-term environmental monitoring of the deep ocean environment is crucial for better understanding the feedback processes between the oceans and Earth’s climate in the face of global warming. However, obtaining in-situ observations from the deep seafloor is difficult and costly. Use of laser reflectometry in optical fibers using existing submarine telecommunication cables can help bridge this knowledge gap. We performed distributed fiber-optic sensing using the BOTDR (Brillouin Optical Time Domain Reflectometry) technique, which is sensitive to mechanical strain (elongation/ shortening) and temperature changes, on a network of commercially operating telecom cables connecting the islands of the Guadeloupe archipelago in water depths of 10 - 700 m. Monitoring at regular 6 month intervals over the past 2.5 years reveals a seasonally adjusted two-year temperature change (delta T) of about +1.5°C between 2022 and 2024 on the shallow carbonate platform (10 - 40 m water depth) south of Grande-Terre (Saint François), Guadeloupe. These sea-floor measurements are corroborated by satellite observations of the Sea-Surface-Temperature (SST) during the past three years, which document an identical temperature increase at the sea surface, in the same location (offshore Saint François). CTD measurements performed in 5 locations along the cables reveal well-mixed waters and no temperature stratification. A smaller temperature increase (0.2 - 1.0°C) is observed in deeper waters (300 - 700 m) between the islands over the same period (2022 - 2024). A new measurement campaign is planned in mid-March 2025 with BOTDR on the submarine cables and XBT (eXpendable Bathy Thermograph) measurements at sea. Together with an additional field campaign performed (at a 3-month interval) in Sept. 2024 (during the maximum annual water temperature) the new campaign (performed during the minimum annual temperature and again at a 3-month interval) will fully constrain the seasonal variations in water temperature. These results can open the path for widespread use of submarine cables for long-term environmental monitoring of the seafloor.
How to cite: Gutscher, M.-A., Cappelli, G., Quetel, L., Philippon, M., LeBrun, J.-F., Nativelle, C., Quillin, J.-G., and Autret, E.: Monitoring long-term bottom water temperature changes using fiber-optic sensing in submarine telecommunication cables, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6368, https://doi.org/10.5194/egusphere-egu25-6368, 2025.
Distributed fiber-optic sensing is becoming increasingly topical because of its potential for recording a wide range of frequencies, at a high spatial sampling and over long distances. Distributed Acoustic Sensing (DAS) is one example of such an emerging technology. The lowest frequencies observed on marine DAS data are complex temperature signals at tidal periods (Ide et al, 2021). This presentation shows tidal period signals recorded on four DAS interrogators connecting Ny-Ålesund and Longyearbyen, Norway.
DAS records the phase changes in Rayleigh backscattered light from inherent impurities along the fiber to detect changes in the optical cable length. DAS data contain contributions from both temperature variation and elastic deformation. Interrogators normally record this as time-differentiated phase-change data which is linearly related to strain rate. At high frequencies (> 0.01 Hz, Sladen et al., 2019) the strain rate is dominated by elastic deformation, while at tidal frequencies (< 0.01 Hz) it is believed to primarily be generated from slow temperature variation, e.g., from internal tides (Williams et al., 2023). However, there are examples of strain measurements of tides (Roeloffs, 2010) and DAS signals that are proportional to the barotropic tidal pressure (Williams et al., 2023). Therefore, interplay between temperature and strain effects generated by tidal waves is not yet fully understood and remains a challenge.
During a field test in the summer of 2022 four interrogator units were installed in Svalbard, two in Ny-Ålesund and two in Longyearbyen. These recorded DAS data simultaneously for almost one month and covered two 260 km long fiber cables (see Rørstadbotnen et al., 2023, for more information). After the conclusion of the four-interrogator experiment, one of the interrogators was left recording in Ny-Ålesund. From this data, we have studied tidal period signals at selected channels over longer time periods (>14 days) and along the fibers for shorter periods (~4 days).
The results of the analyses will be presented, and we will demonstrate how the tidal signal varies along, and between, the two fiber cables. Additionally, the long-term signals will be compared to the water level data from Ny-Ålesund to validate the long-term trend in the data.
References:
Ide, S., Araki, E., Matsumoto, H., 2021, Very broadband strain-rate measurements along a submarine fiber-optic cable off Cape Muroto, Nankai subduction zone, Japan, Earth, Planets and Space, DOI: https://doi.org/10.1186/s40623-021-01385-5
Sladen, A., et al., 2019, Distributed sensing of earthquakes and ocean-solid Earth interactions on seafloor telecom cables, Nature Communications, https://doi.org/10.1038/s41467-019-13793-z
Williams, E. F., et al., 2023, Fiber-optic observations of internal waves and tides, Journal of Geophysical Research: Oceans, https://doi.org/10.1029/2023JC019980
Roeloffs, E., 2010, Tidal calibration of Plate Boundary Observatory borehole strainmeters: Roles of vertical and shear coupling. Journal of Geophysical Research: Solid Earth, https://doi.org/10.1029/2009JB006407
Rørstadbotnen, R. A., et al., 2023. Simultaneous tracking of multiple whales using two fiber-optic cables in the arctic, Frontiers in Marine Science, https://doi.org/10.3389/fmars.2023.1130898
How to cite: Rørstadbotnen, R. A. and Landrø, M.: Tidal period signals observed on DAS data from two 260 km fiber cables in Svalbard, Norway, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8409, https://doi.org/10.5194/egusphere-egu25-8409, 2025.
Fiber-optic sensing can be carried out in areas that are logistically challenging, especially in the offshore environment, and is therefore a valuable tool for detecting various oceanographic and geological processes such as earthquakes, volcanic eruptions, tides and currents. The use of telecommunication fibers, particularly those used for internet data traffic, enables extensive and far-reaching coverage, representing a relevant asset to investigate phenomena that are otherwise often under-sampled due to lack of in-situ monitoring. This infrastructure can be probed by analysing the phase of forward-transmitted optical signals using laser interferometry. Yet, the sensitivity of this technique to detect different oceanographic and geological processes needs to be fully understood.
Using a 260-km long optical fiber that is simultaneously used for internet traffic between Malta and Sicily (Italy), we recorded signatures of various offshore geological and oceanographic events along the Hyblean Plateau and the western Ionian Basin. Here, we present results spanning the period from September 2022, when data acquisition commenced, to March 2024, during which approximately 300 days of measurements were collected. This long-term analysis, which is still uncommon for offshore fiber sensing, has enabled us to study recurrent, long-period events affecting the fiber and investigate their correlation with environmental factors. Specifically, we observe earthquakes of magnitude ≥2.5 and microseism induced by wind-sea interaction. Additionally, we observe the signature of tides and internal gravity waves, as indicated through a 12 and 18 hour periodicity that is present throughout our recordings. The recordings further show a signal that we tentatively associate with sediment gravity flows, but further tests are needed to confirm its nature. Our experiment demonstrates that fiber sensing using laser interferometry provides an adequate sensitivity to monitor oceanographic and offshore geological processes, and its capability to produce small data volumes allows continued aquisition over long periods, which is needed for observations on seasonal timescales and to study rarely-occurring events such as sediment gravity flows.
Focusing on the Ionian Basin landscape, we anticipate that laser interferometry has the potential to complement the rich sensing equipment already installed by other research groups in the area, which includes permanent onshore seismometers and tide gauge stations, as well as ocean-bottom seismometers and fibers equipped with different sensing techniques.
The combination of various approaches offers a unique opportunity to assess and compare their sensitivity, improves the spatial coverage and completeness of observations and has the potential to enhance our understanding about offshore processes.
How to cite: Clivati, C., Schulten, I., Micallef, A., Donadello, S., Agius, M. R., Aiken, C., Mura, A., Levi, F., Calonico, D., and Xuereb, A.: Fiber sensing with internet cables: Monitoring offshore oceanographic and geological processes in the central Mediterranean Sea, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12354, https://doi.org/10.5194/egusphere-egu25-12354, 2025.
The oceans are a large part of our planet’s environment with highly diverse acoustic and seismic noise fields. These noise fields are made up of a plethora of natural (marine wildlife, ocean microseisms, earthquakes) and anthropogenic (ship traffic, seafloor construction) sources. It is very costly and time consuming to deploy and maintain offshore seismic and acoustic sensors to study this wide array of sources. Distributed acoustic sensing (DAS) applied on submarine fibre optic cables offers an unprecedented spatial resolution within the ocean environment for detailed analysis of seismic and acoustic noise at a relatively low cost.
Within this research project a 10 day long DAS dataset was acquired in June 2023 to characterise the submarine noise field of Galway Bay. The acquisition was performed using a Febus Optics interrogator on an optical fibre (5.56km length) connected to the Galway SmartBay offshore laboratory, located off the coast of Spiddal, Co. Galway, Ireland. In order to understand the cable sensitivity to a variety of different signals, both seismic and acoustic, present in the bay during the experiment, we compare the DAS data with data from other instruments such as seismometers (Irish National Seismic Network), hydrophones and wave buoys (both Galway SmartBay and Marine Institute Ireland).
The strain wavefield recorded with the DAS is being studied by isolating channels and treating them as stand alone sensors, and also utilising the densely spaced nature of DAS data to perform Frequency-Wavenumber (FK) analysis. Within the data there is a dominant signal between 0.1-0.3Hz, which is caused by the OSGW. Beamforming has been used to resolve the direction of propagation of these OSGW, which has been compared to the SmartBay wave buoy data. There is also a packet of ambient high frequency, 3.5-5.5Hz, Scholte waves present at intervals throughout the acquisition. Using FK analysis, a frequency vs phase velocity plot has been generated and shows a clear dispersion curve in the velocity range 300-1000m/s. There is also the presence of a, as of yet, undetermined signal in the 0.5-1.5Hz band. The presence of both of these waves (Scholte and 0.5-1.5Hz signal) aligns temporally with increases in the significant and maximum wave height recorded by the SmartBay wave buoy. The possibility of the increase in ambient seismic noise as a result of rougher sea conditions is being investigated further as such. Finally, during the acquisition there were several acoustic events picked up by the SmartBay hydrophone, these included ships passing overhead as well as North Atlantic minke whale calls. Unfortunately these signals were not observed on the DAS data despite the use of several techniques attempting to isolate them spatially and temporally (e.g. velocity filtering).
How to cite: Berry-Walshe, L., Tary, J.-B., Le Pape, F., Piana Agostinetti, N., Bean, C. J., Garcia Gomez, C., and MacCraith, E.: Using Distributed Acoustic Sensing with an Optical Fibre Cable in Galway Bay for Ocean Noise Monitoring, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13926, https://doi.org/10.5194/egusphere-egu25-13926, 2025.
About 70% of the Earth's surface is covered by ocean, making observations of seismic waves difficult and expensive in vast regions. Recently, seismic waves have been observed using transmission fiber-optic sensing on trans-oceanic subsea cables, making them an exciting potential addition to global seismic networks (f.ex. Marra 2018,2022; Zhan, 2021; Mazur 2024).
In this work we use a distributed fiber optic sensing (DFOS) prototype capable of measuring the integrated strain between each repeater (typically 100 km) along the entire cable length, with each span acting as an effective sensor. This division allows for a separation of signals from different parts of the cable, leading to higher S/N ratios on quiet deep-water segments and more easily interpreted waveforms. We show signals from several large earthquakes registered on 17 spans of the IRIS subsea telecommunications cable, that connects Iceland and Ireland. Multiple seismic body-wave phases, as well as longer period surface waves, can be tracked across the spans, or the array of effective sensors. Comparing the observed phase arrivals to those predicted by travel-time curves, we show how different phases are visible on different segments as expected by the varying orientation of individual segments relative to the seismic wave field. Furthermore, we simulate the observed waveforms using a spectral-element wave propagation software (SPECFEM3D_GLOBE), following the theoretical development of Fichtner et al 2022, and compare to the observed waveforms.
How to cite: Hjörleifsdóttir, V., Gunnarsson, A. I., Mazur, M., Kamalov, V., Karrenbach, M., Williams, E. F., Jonsson, O., Fontaine, N. K., Ryf, R., Dallachiesa, L., and Neilson, D. T.: Observations of earthquakes on multiple spans of the IRIS subsea fiber-optic cable connecting Iceland and Ireland, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18160, https://doi.org/10.5194/egusphere-egu25-18160, 2025.
Seismic surveys commonly use sensor arrays to record wave signals, with methods like noise cross-correlation function and spatial autocorrelation to analyze wave propagation features. However, these multi-station methods require many sensors, leading to high costs and deployment complexities. In contrast, single-station methods utilize constraints among different seismic components at a single location to extract dispersion curves and invert subsurface structures. However, these methods face theoretical limitations, including a lack of a generalized model to determine which components should be used, and problems related to the non-unique inversion of dispersion curves. To address these limitations, we propose the single-point interference method, using a six-component seismometer including an interferometric fiber-optic gyroscope to record rotational motions. This method models wave propagation as a two-port network system, and uses a transfer function to describe wave interference at the measurement point, where specific input-output pairs correspond to distinct subsurface structures. Assuming a single-source plane wave, when the transverse acceleration component serves as the input and the vertical rotation component as the output, the transfer function defines local parameters of Love waves: its amplitude represents the local phase velocity, and its phase represents the back azimuth of the incident wave. By adjusting input-output combinations, this method obtains the subsurface velocity structures for different wave types. For example, with the vertical acceleration component as the input and the transverse rotation component as the output, the local phase velocity of Rayleigh waves can be derived. This method provides an opportunity to cross-validate the inversion results. The term single-point emphasizes the locality of the method, rather than limiting its application to just one measurement point. By applying a six-component seismometer to obtain inversion results at multiple points along a line and interpolating these results, a continuous subsurface profile can be constructed. Expanding the line to a grid of points enables 3-D modeling of the subsurface structure within the grid area. Experiments demonstrate that this method can estimate velocity structures with a single-station seismometer, reducing the costs and deployment complexities of multi-station methods. Experimental seismic records and corresponding local velocity structure estimations will be presented to demonstrate this method’s advantages in seismic surveys.
How to cite: Zhou, Z., Chen, Y., and Li, Z.: A Single-Point Interference Method for Subsurface Structure Estimation Using a Six-Component Seismometer, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6645, https://doi.org/10.5194/egusphere-egu25-6645, 2025.
Ground motion signals acquired through Distributed Acoustic Sensing (DAS) provide unprecedented spatial resolution over kilometric distances, particularly in environments traditionally difficult to reach, such as the ocean bottom. Although this is a substantial upside on its own, DAS experiments come with data storage costs that translate into processing costs that have to be addressed. Whether we choose to adapt former tools or develop new tools, we often leverage computational infrastructures that may not be readily available or easily accessible to every researcher, and thus there is still a need for tools that can reliably run on the average workstation.
This presentation introduces a multiscale, kurtosis-based picking algorithm designed for detection on arbitrary-length traces. Using this newly developed picker, we propose pick scatter maps as a novel method for visualizing DAS data. These maps combine individual picks from traces to reveal patterns and facilitate the interpretation of signals recorded by DAS. It is infeasible to reliably plot a full-day 2D strain map due to resolution and memory issues, but it is possible to plot a full-day scatter map where overlapping points (picks) appear to form lines that correspond to individual signals, with their corresponding apparent velocities. Examples include extremely vertical lines (large apparent velocities) spanning the whole cable, which are expected for earthquakes, or localised lines with a visible slope (lower apparent velocities), which will usually correspond to vehicles. Scatter maps from some environments may feature signals of interest to other fields of research, such as marine life on ocean bottom cables.
Scatter maps provide a way to highlight specific segments within month-long strain recordings. In the particular case of earthquakes, curve fitting in pick clusters produced by P- and S-wave arrivals lets us obtain phase picks by keeping those close enough to the fitting curve, discarding the rest to reduce delayed or consecutive triggers. These phase picks can be used for location purposes, sometimes combined with traditional stations to ensure proper azimuthal coverage. For other types of signals, each specific application will determine how its corresponding picks can be used. Speed tracking or near-cable activity monitoring are examples of such applications.
How to cite: Latorre, H., Ventosa, S., Ugalde, A., Cubas Armas, M., Rodríguez, T., Villaseñor, A., Martins, H. F., Vidal-Moreno, P., Bozzi, E., Bartolomé, R., and Ranero, C. R.: Efficient signal detection and visualisation for fibre-optic seismology: exploring multiple environments and applications, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6920, https://doi.org/10.5194/egusphere-egu25-6920, 2025.
Distributed fiber optic acoustic sensing (DAS) is a developing vibration observation technology recently. DAS has attracted widespread attention in the fields of structural monitoring, leakage detection, transportation, oil and gas exploration, and natural seismicity. Compared with conventional geophones, on the one hand, DAS has the advantages of low cost, high density, high sensitivity, efficient construction, and long-term monitoring. On the other hand, the signal-to-noise ratio of the DAS data is relatively low, so it is of great importance to suppress the DAS noise.
Most of traditional noise suppression methods rely on a prior information, which affects the final denoising effect. It also reduces the processing efficiency especially the amount of data is large. In recent years, the application of artificial intelligence methods in seismic data processing and interpretation has widespread gradually. Deep learning methods can dig deeper features of the data through multi-layer structure, so as to suppress the noise. To build the training dataset, we use fractional order Fourier Transform (FrFT) to construct a median filter to suppress the high (low) frequency noise. The soft-threshold curvelet transform is used to suppress random noise. The amplitude equalization f-k filtering is used to suppress the linear noise. In this way the denoised seismic record is obtained using three improved mathematical transform methods. In our U-net, the patching technique is used to generate many small-scale patches from the input data, together with their labels. The denoised data are reconstructed from the patches using the unpatching technique. This is helpful in reducing the computational cost and improve the ability to extract essential features from large-scale seismic data. And help to keep the same matrix dimension of input and output of the U-net. The Mish activation function is used instead of the traditional activation function (Sigmoid, ReLU or Tanh) in the U-net. The upper unbounded property of the Mish avoids the sharp drop of training speed. The lower bounded produces a strong regularization effect and can smooth the training model to get a better generalization ability. The non-monotonic property not only helps to keep little negative values that contribute to stabilizing the gradient of the network, but also avoiding the risk of gradient vanishing like the ReLU activation function.
After the calculation based on a real seismic data, three common noises mentioned above are suppressed by the U-net. The weakly hidden effective signals can be recovered from raw DAS data. Furthermore, our method does not involve the multiple waves suppressing. However, the curvelet transform can also achieve suppression of multiple waves. It can help form the training set for U-net. This is an aspect that needs to be further improved in the future.
How to cite: Wu, F., Wang, J., Li, Q., He, Y., and Luo, Z.: Distributed fiber optic sensing data noise suppression based on U-net, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12119, https://doi.org/10.5194/egusphere-egu25-12119, 2025.
The integration of Artificial Intelligence, particularly foundation models and modern Transformer-based architectures, opens up new frontiers for seismic monitoring. In this work, we propose a comprehensive AI-driven framework for detection and phase picking of seismic events. These models are designed to exploit the capabilities of advanced AI techniques to tackle the challenges posed by high-frequency, high-density data, and noisy environments typically associated with seismic monitoring technologies like Distributed Acoustic Sensing (DAS).
Our method combines the best of two worlds: U-Net's ability to capture high-resolution details and the power of Transformers to model global context. This combination helps the model achieve more accurate segmentation, identifying the phases' arrival times with high accuracy.
We validate our framework on DAS data acquired from the seismically active area of the Campi Flegrei caldera (Southern Italy), leveraging the dense temporal and spatial sampling offered by DAS technology. The results show that our approach effectively learns seismic wave characteristics: the arrival time picking model demonstrates a notable 5% enhancement in the average F1-score for P and S waves, achieving 90%, surpassing the current state-of-the-art performance.
This study highlights the huge potential of integrating AI-driven methodologies with DAS technology, paving the way for advanced automatic real-time seismic monitoring systems.
How to cite: Corsaro, M., Cannavò, F., Currenti, G., Palazzo, S., Allegra, M., Jousset, P., Prestifilippo, M., and Spampinato, C.: An Advanced Framework for Seismic Monitoring: Leveraging Transformer Models and Distributed Acoustic Sensing Technology for Earthquake Detection and Arrival Time Picking, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13670, https://doi.org/10.5194/egusphere-egu25-13670, 2025.
Distributed acoustic sensing (DAS) on submarine fibre optic cables complements seismic networks by providing real-time information from the seabed over long range. The seismology community has demonstrated impressive new capabilities and processing techniques with DAS seismic recordings, and collaborations have been established to systematically deploy the instrumentation. We focus on the integration with existing earthquake monitoring systems and show that edge computing and streaming from the DAS interrogation of submarine cables enhances rapid earthquake location when processed in conjunction with data from terrestrial seismometer stations.
The widely used SeedLink protocol enables data transfer in near real-time and has support for many acquisition and analysis systems. The protocol is optimized for applications in seismology and for use with standard seismometer sensors. Recently, SeedLink streaming for DAS systems has been developed in the SeisComP framework. Since the DAS instrument data rate can be orders of magnitude larger than a typical seismometer, we introduce the DAS virtual station concept to expose pre-processed data in a sampling compatible with that of traditional seismic networks. To benefit from the dense spatial sampling along the cable, we implement array processing as edge computing on the DAS instrument server. This enables noise suppression and wave analysis techniques that would not be possible if a sparse subset of the DAS single component channels were streamed directly. For example, a 150 km cable can be exposed as 15 virtual stations spaced 10 km apart, with each station representing the denoised and decomposed landward and seaward propagating wave phases in different velocity intervals. The associated data rate will be comparable to 15 seismometers and suitable for streaming even over low bandwidth connections from the cable landing station.
Streaming of DAS virtual stations via SeedLink seamlessly facilitates the use of any analysis tools and workflows using existing standard seismological formats and services; this also facilitates data handling and curation in seismological data centres. The integration with real-time data from seismic network stations of similar spatial sampling can also be conducted within standard frameworks. To understand the impact of the integration, we consider using the virtual stations in near real-time processing as a complement for rapid earthquake location. The location accuracy enhancement from incorporating the sparsely sampled virtual stations along the submarine cable can be significant due to the extended azimuthal coverage of stations in the ocean. For early detection and location this achieves the most important benefit of the DAS cable sensing, and with the noise suppression possible from the dense sampling operating as edge computing. Further details might be required in post event analysis, in which case the full DAS dataset can be transferred.
How to cite: Morten, J. P., Heinloo, A., Evangelidis, C., Strollo, A., and Tilmann, F.: Enhancing rapid earthquake location by integrating streaming DAS virtual stations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9133, https://doi.org/10.5194/egusphere-egu25-9133, 2025.
Distributed Acoustic Sensing (DAS) has become a standard tool in seismology, proving capable of replicating most measurements traditionally obtained with conventional sensors. Beyond this, DAS’s ability to provide spatially continuous recordings introduces a novel observational paradigm, revealing features that were previously difficult to detect.
One of the strengths of DAS lies in its capacity to track faint secondary phases, such as converted and reflected waves at the different interfaces of the medium. In this study, we focus on sedimentary regions where seismic waves split at the bedrock-sediment interface, producing double arrivals. Identifying and accurately picking these split phases is essential for precise event localization and leveraging DAS’s dense spatial coverage for high-resolution imaging of active geological structures.
We analyzed one year of data from three DAS arrays deployed onshore along the Chilean margin as part of the ABYSS project. Using a custom tool for efficient 2D phase picking, we manually identified several hundred events, creating a robust training dataset for a deep learning picker. This specialized picker successfully distinguishes closely spaced secondary arrivals, improving automatic detection and processing.
Our results demonstrate that automated picking of these phases enhances localization accuracy and facilitates earthquake processing in sedimentary environments. This methodology can be extended to other types of secondary phases, such as reflection from the Moho, paving the way for fully automated seismic data analysis in the context of complex arrivals pattern using DAS.
How to cite: Trabattoni, A., Rivet, D., Vernet, C., Baillet, M., Strumia, C., and van den Ende, M.: Automatic Picking of Secondary Phases with DAS: The Case of Sedimentary Split Waves, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16406, https://doi.org/10.5194/egusphere-egu25-16406, 2025.
Distributed Acoustic Sensing (DAS) has seen an increase in attention in the last decade, offering the ability to convert existing fibre optic cables into dense networks of passive sensors. These cables, which span vast areas of the globe, hold immense potential for diverse sensing applications. Oil dumping, whale hunting, trawling near the cables are all huge issues to our environment and biodiversity. DAS offers 24/7 real-time sensor capabilities, which can aid in protecting these areas, by detecting signals from various sources. However, the enormous data volumes generated by DAS systems present significant challenges in terms of manual analysis, highlighting the need for an adaptable and scalable approach, capable of identifying and classifying signals of interest.
This study introduces a new method, efficiently designed to address these challenges by detecting and classifying signals in DAS data. The proposed method enhances the detection of critical events such as earthquakes, marine mammal activity, and ship crossings, thereby expanding the scope of DAS applications.
The methodology should be cable-agnostic, and establishes a "normalcy model" that captures the typical data distribution over an extended period. Each channel along the fibre optic cable is modeled as a Gaussian distribution, representing its standard behavior. Incoming, unseen data is segmented and similarly treated as a Gaussian distribution. To detect deviations, the method uses the Kullback-Leibler (KL) divergence between the normalcy model and the observed data. A change is flagged when the divergence exceeds a threshold, which is determined empirically based on observed patterns in the data. By establishing a normalcy picture of the data, the model is not limited to only 1 specific fibre cable, but is adaptive to any. To classify signals, the method uses the spectral signatures unique to each event type, enabling automatic clustering based on the different signals. These clusters are validated using verified datasets. For example, ship signals are cross-referenced with Automatic Identification System (AIS) data and earthquake signals are compared against seismic databases. By incorporating these reference datasets, the system can reliably classify known signals and identify events of unknown origin for further analysis.
Our results show that it is possible to not only detect signals in DAS data fast and efficiently, but also cluster the signals, through the spectral signature, into different origins of the sources. We show that within the clusters is it possible to distinguish between different signals originating from the same source, e.g., differentiating between different ships, or earthquakes. This implies that we potentially are not only able to classify ships, but also identify which ship it is. This can tremendously enhance our capabilities in identifying and catching actors that dump oil or hunt whales in the ocean, so it can be stopped. The methodology can be used on any cable and has been shown to work on fibre cables in a very harsh arctic environment, with a lot of noise.
How to cite: Bülow Pedersen, H., Aalling Sørensen, K., Heiselberg, H., and Heiselberg, P.: Distributed Acoustic Sensing: A cable-agnostic method for detecting & classifying signals on fibre optic cables, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17386, https://doi.org/10.5194/egusphere-egu25-17386, 2025.
Distributed Acoustic Sensing (DAS) enables seismic monitoring by transforming fiber optic cables into dense, cost-effective sensor arrays. However, the vast data volume generated by DAS presents challenges for labeling, sometimes even making data labeling more time consuming than processing and research. Traditional supervised machine learning methods require extensive manual labeling for individual events, which is both time-consuming and susceptible to user bias.
To address these challenges, we propose a clustering-based approach to group similar data, allowing for cluster-level labeling rather than event-by-event annotation. Our method employs a two-step processing chain denoted (a) and (b). In the step (a), data is represented in a latent space defined by hundreds of features. Two approaches for constructing this latent space are explored: one using human-engineered features based on seismological signal processing, and the other leveraging self-supervised learning via the image-BYOL algorithm, which utilizes bidimensional representations of DAS data. The step (b) applies unsupervised clustering, initially reducing the dataset to 5000 clusters using K-Means partitioning algorithm, followed by hierarchical clustering to condense these into 500–700 interpretable clusters using an inconsistency criterion.
This method was applied to two DAS datasets collected in the Hautes-Pyrénées. The first dataset involved six weeks of continuous measurements along an 800-m cable in Viella, recorded with a temporal resolution of 400 Hz, a gauge length of 10 m, and a channel spacing of 2.4 m. The second dataset consisted of 19 ten-minute recordings along a 91-km cable, with a temporal resolution of 200 Hz, a gauge length of 10 m, and a channel spacing of 4.8 m. Using cluster-based labeling on the Viella dataset, we successfully detected 100% of earthquakes with a magnitude Mw>2.0 and identified the daily periodicity of anthropogenic events, such as those related to farming activities. Continuous and long-duration (>30 s) seismic signals, primarily generated by mechanical farming engines, demonstrated a clear periodicity, whereas impact-driven or impulsive events were less consistent in timing due to their diverse origins.
These findings highlight the potential of clustering techniques to analyze DAS data efficiently, reducing reliance on manual event labeling. Nevertheless, further improvements are necessary to minimize false positives, particularly for smaller seismic events.
How to cite: Huynh, C., Rimpot, J., Hibert, C., Turquet, A., Stangeland, T., Malet, J.-P., and Lanticq, V.: Unsupervised Learning for In-Depth Analysis of Continuous DAS Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19069, https://doi.org/10.5194/egusphere-egu25-19069, 2025.
Distributed optical fibre sensing (DOFS) has recently led to several international high impact publications e.g., 1,2 demonstrating its novel application for diverse environmental observations and hazards monitoring; e.g. for geological carbon dioxide/hydrogen storage for Net Zero, quantification of Arctic glacier and sea ice melting rates, ocean temperature, pressure and current speed measurements. DOFS sensing transforms a cable into an array of sensors, which can be used to detect and monitor multiple physical parameters such as temperature, vibration and strain, with fine spatial and temporal resolution over long distances (up to 100s of km). DOFS offers certain benefits over conventional seismic sensors such as ease and cost of deployment on the seafloor or downhole with restricted access, for a much higher number of equivalent point sensors. Although the equivalence between DOFS and seismometer signals remains uncertain. We are presenting results from a recently started project that will connect DOFS and geophysical data interpretation, using controlled laboratory environment to robustly interpret what is seen on field-scale measurements using DOFS.
DOFS measures the strain rate of vibrations in the ambient environment, but signal magnitude and characteristics depend on the nature of ambient noise and the surrounding substrate (water column, seafloor sediments, cable protective sheath, etc.). Here, we present results from cross-calibration of optical fibre and geophysical sensors in a controlled environment in rock physics lab. This involves equivalence testing on typical geological materials, from reservoir rocks to marine sediments, to accurately compare sensor measurements so we can relate them with certainty to future studies of seafloor seismo-acoustic wave propagation phenomena and their applications. This project has just started, and we have completed the comparison of ultrasonic velocity measurements using piezoelectric sensors and comparing that with DOFS measurements. The same experiment also looked the effect of increasing strain, wind speed and temperature. Over the next three months, we will also assess how DOFS and elastic wave measurements varies with a) sample type b) pressure and temperature c) pore fluid – air, CO2 and water. We will first measure metal samples (aluminium and brass) and then natural samples to assess the effect of heterogeneity. This will enable assessing novelty of DOFS for heterogeneity and fluid distribution mapping, providing an extra advantage compared to ultrasonic elastic wave measurement system. We will interrogate existing DOFS field data from Orkney and Eday in terms of spatiotemporal sensitivities obtained from lab testing. We will then explore the use of multi frequency measurements, which has not been done before. We will conduct experiments on ice formation to quantify ice thickness during the formation, especially from temperature and strain changes in vertically suspended optical fibre cable. The key question is ‘Can we detect the density variations in ice using DOFS?’. This project will provide the necessary proof of concept and key calibration results enabling greater credibility and de-risking of future proposals.
References:
1 Marra, G. et al. Science (2022), DOI:10.1126/science.abo1939
2 Spingys, C. P. et al. Scientific Reports (2024), DOI:10.1038/s41598-024-70720-z
How to cite: Sahoo, S., Falcon-Suarez, I., Spingys, C., Mangriotis, M.-D., Mohammad, B., North, L., Gregory, E., and Best, A.: Cross-calibration of optical fibre and geophysical sensors in a controlled environment , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13809, https://doi.org/10.5194/egusphere-egu25-13809, 2025.
Continuous geodetic measurements near volcanic systems have advanced our understanding of magma transport dynamics. However, capturing high spatio-temporal resolution dike intrusion dynamics remains challenging. In this study, we introduce fiber-optic geodesy, an approach that enabled us to track dike intrusions near Grindavík, Iceland, on a minute time scale. This approach utilizes low-frequency distributed acoustic sensing (LFDAS) along a telecommunication fiber cable to measure quasi-static signals during dike intrusions. We captured nine intrusive events over a one-year recording period, six resulting in fissure eruptions. Distinct LFDAS signals, characterized by consistent initial spatial strain response, emerged tens of minutes to several hours before eruptions. We used these signals to assist the Icelandic Meteorological Office (IMO) in issuing early warnings for volcanic eruptions. Moreover, LFDAS signals enable us to image dike intrusions on the minute time scale, revealing their evolution into eruptive lava fissures or their arrest at depth. Our results highlight the feasibility of using DAS for a dense array of strainmeters, enabling high-resolution, nearly real-time imaging of subsurface quasi-static deformations. In active volcanic regions, LFDAS recordings can offer critical insights into magmatic evolution, eruption forecasting, and volcanic hazard assessment.
How to cite: Li, J., Biondi, E., Heimisson, ., Puel, S., Zhai, Q., Zhang, S., Hjörleifsdóttir, V., Wei, X., Bird, E., Klesh, A., Kamalov, V., Gunnarsson, T., Geirsson, H., and Zhan, Z.: Minute-scale Dynamics of Repeated Dike Intrusion in Iceland with Fiber-Optic Geodesy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14458, https://doi.org/10.5194/egusphere-egu25-14458, 2025.
Distributed Acoustic Sensing (DAS) measures strain or strain rate along an optical fiber with a high spatial and temporal resolution. The typical channel distance is in the order of a few meters while the sampling frequency can reach 1 kHz or higher, which makes it possible to record a wide range of seismic signals.
The optical fibers used for DAS can be several kilometers long and measurements take place over days, weeks or months, resulting in very large datasets of up to several terabytes per day. However, due to this large amount of data, it is challenging to get a good impression of the different types of seismic signals present in the data, since a manual inspection can become immensely time-consuming.
In this study we aim to automatize this process by clustering the data to detect and categorize different types of seismic signals. A 2D continuous wavelet transform (CWT) is used to automatically extract features from the data. In contrast to many other approaches, this allows to not only use temporal information, but to also include the spatial dimension to further distinguish between different seismic sources and wave types.
The clustering is performed in two steps. First, a Gaussian Mixture Model (GMM) is used to cluster the features. Then, the final clusters are obtained by merging similar components of the GMM.
The application of the proposed procedure to different large DAS datasets provides valuable results. Identified clusters show different spatial and temporal patterns and correspond to seismic signals originating from various sources, such as car traffic, tramways or machinery.
How to cite: Bölt, O., Hammer, C., and Hadziioannou, C.: Towards the Clustering of Large Distributed Acoustic Sensing Datasets, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17842, https://doi.org/10.5194/egusphere-egu25-17842, 2025.
The Kefalonia Transform Fault (KTF), a 150-km long tectonic boundary connecting the Adriatic and Aegean plates, is characterized by slab tearing and significant seismic activity. Earthquake sequences in the region are clustered along the fault, yet the local earthquake catalog records remain sparse.
From April 23 to June 22, 2024, we conducted a two-month Distributed Acoustic Sensing (DAS) experiment on Kefalonia Island using a 15 km dark fiber network—7 km along a roadway and 8 km across the seafloor. By applying the STA/LTA method to marine DAS data, we detected ~10,000 high-frequency (5–20 Hz) events. Event clustering using pairwise correlations, combined with the local earthquake catalog, revealed six spatially distinct seismic clusters, each associated with specific fault segments.
Using these clusters as templates, we developed a new template matching workflow to expand the earthquake catalog to ~20,000 events, significantly increasing the detection of small-magnitude earthquakes. Each cluster highlights seismic activity on distinct fault segments and reveals foreshock and aftershock sequences for ML >2.5 events.
The refined catalog, with 100 times more events than the original local catalog, provides unprecedented temporal and spatial resolution of seismicity along the KTF. These results offer new insights into fault segment interactions and the processes of stress accumulation and release in the KTF system.
How to cite: Wang, Y. and Fichtner, A.: Mapping fault dynamics: Very high seismicity detected along the Kefalonia Transform Faul with DAS and template matching, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2886, https://doi.org/10.5194/egusphere-egu25-2886, 2025.
While several studies have shown the possibility to estimate earthquake magnitude from analysis of the S-phases recorded along fiber optic cables using Distributed Acoustic Sensing (DAS), understanding the source information hidden in the first seconds of these seismic recordings is still an open question requiring further investigation. In fact, in the case of submarine cables, with the fibers located closer to the epicenters, DAS could also be an asset for Early Warning of offshore earthquakes.
In this study, we explore the possibility of measuring the size of the earthquake from the first few seconds of the signal received by the DAS by relating measurements of peak amplitudes to earthquake magnitude. We analyze a dataset of over 100 events (2.5 < M < 7.4) recorded along three submarine dark fibers running parallel to the Chilean margin, between Concon and La Serena, forming an approximately 450-km-long linear array.
Unfortunately, this sensing technique suffers several limitations that complicate the recording of the first direct seismic arrivals. These include a lower signal-to-noise ratio (SNR) compared to traditional seismometers, and a high sensitivity of the measured parameters to local medium heterogeneities. Additionally, the longitudinal sensitivity of DAS makes it challenging to detect P-waves when using horizontally deployed cables, which are common when telecom fibers are utilized. Finally, modern DAS interrogators struggle to record strong ground motions due to phase wrapping of the backscattered light within the fixed interval [-π, π], resulting in the saturation of DAS recordings during intense shaking.
Despite these challenges, we show that the P wave is poorly informative about the seismic source due to the influence of a shallow sedimentary layer, which generates a dominant PS-converted phase in the early DAS data. However, we demonstrate that this converted phase can be effectively used to robustly estimate earthquake sizes up to magnitude 7 within few seconds from the recording of an event. Furthermore, we derive amplitude attenuation laws as a function of distance and magnitude, overcoming the limitations of saturation by leveraging records from large events occurring hundreds of kilometers away from the array.
Overall, this work highlights the continued potential of DAS-based seismic monitoring infrastructures while providing valuable insights for the development of a new generation of DAS-based Earthquake Early Warning Systems.
How to cite: Strumia, C., Trabattoni, A., Scala, A., Rivet, D., and Festa, G.: Earthquake size from first seconds of DAS records , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12290, https://doi.org/10.5194/egusphere-egu25-12290, 2025.
Utilizing Distributed Acoustic Sensing (DAS) data recorded along three segments of an ocean bottom cable off the coast of Chile (~450 km in total), we have imaged the rupture process of an intermediate-depth earthquake of magnitude 6 , which occurred in Argentina on September 21, 2014. This earthquake is located approximately 400 km away from the cable. This marks a significant advancement in seismic monitoring: our approach fully exploits the high-density and wide-aperture capabilities of ocean bottom cables to provide low-cost, high-resolution observations of earthquake rupture processes across extensive geographic areas.
Our methodology integrates several key procedures to effectively address the challenges of imaging distant, moderate-size seismic events in environments with complex velocity structures using array techniques. The conversion from strain rate to velocity helps suppress scattering from sediment layers. Array processing based on cross-correlations between the mainshock and an empirical Green’s function (an aftershock) addresses the interference effect of multiple seismic phases, enhancing the coherence of waveforms along the entire cable length at high frequencies (1 to 4 Hz), and enabling a spatial resolution of approximately 1 km in the north-south direction. We further align the resultant data to correct travel time errors effectively, thereby improving the accuracy of our location estimates. Additionally, we average the results of 20 independently sampled subsets from the dense DAS sensors, significantly sharpening the imaging resolution and enhancing accuracy.
With these techniques, our analysis reveals three strong high-frequency radiation sub-sources, indicating a rupture propagation of 8 km over 6 seconds. These findings provide insights into the rupture directivity and nodal plane orientations, potentially indicating the mechanisms of strain localization on normal faults within the seismic slab at a depth of ~ 130 km. This application opens new pathways for further research in seismic monitoring and earthquake kinematics in previously unreachable oceanic environments. It also has the potential to accumulate a rich database of the kinematics of smaller, more frequent earthquakes, which require exceptionally high-resolution observations previously unattainable.
How to cite: Xie, Y., Ampuero, J.-P., van den Ende, M., Trabattoni, A., Baillet, M., and Rivet, D.: Advanced Imaging of a Magnitude 6 Earthquake Using Extended Ocean Bottom DAS Data off-shore Chile., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17308, https://doi.org/10.5194/egusphere-egu25-17308, 2025.
Distributed Acoustic Sensing (DAS) is a fiber-optic sensing technology that transforms optical fiber telecommunication cables into arrays of thousands of broadband strain meters. The emergence of DAS has spurred significant advancements across various scientific domains, including geophysics, seismology, hydrology, and engineering. Modern DAS systems offer spatial resolutions of several meters, ranges extending tens of kilometers, sensitivities below 1 nε, and sampling rates of up to several kHz.
Focusing on systems utilizing chirped pulse distributed acoustic sensing (as implemented by High-Fidelity Distributed Acoustic Sensing (HDAS) from Aragon Photonics Labs), these techniques demonstrate enhanced performance, achieving an optimal balance between range and sensitivity, particularly at low frequencies. In seismology, these capabilities enable the high-resolution detection of seismic waves originating from events such as local and teleseismic earthquakes, as well as micro-seismic vibrations induced by trains or vehicles.
DAS has proven effective in railway monitoring, enabling vehicle tracking and rail condition assessments. Its spatial and temporal density makes it especially promising for monitoring and control in high-speed railway systems. This work applies methods adapted from array seismology to visualize seismic surface waves generated by trains and other vehicles near a trackside dark fiber. These relatively simple methodologies efficiently extract and characterize surface waves propagating along the railway superstructure.
The DAS data collected from trackside fibers provide substantial information about terrain features and the condition of railroad superstructures. These findings highlight the potential of DAS systems for monitoring seismic surface waves and superstructure conditions using pre-installed fibers. Moreover, the evolution of this information over time can offer valuable insights for infrastructure owners, particularly in critical scenarios such as high-speed railway systems. Additionally, the local dispersion relation for surface waves reveals further details about the superstructure, which could support preventive maintenance efforts.
How to cite: Preciado-Garbayo, J., Canudo, J., Gonzalez-Herraez, M., F. Martins, H., Schaedler, M., Gaite-Castrillo, B., Bravo-Monge, J. B., de Maria, I., and Rodriguez-Plaza, M.: HDAS (High-Fidelity Distributed Acoustic Sensing) as a seismic surface wave monitoring tool along trackside dark fibers, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5267, https://doi.org/10.5194/egusphere-egu25-5267, 2025.
Extreme climate events and geological hazards have underscored the urgency of advancing multi-scale seismic imaging to accurately characterize the Earth system. Despite the widespread application of seismic surface wave methods based on dispersion analysis, which have been used for S-wave velocity imaging across scales from the critical zone (meter-scale) to the crust and mantle (kilometer-scale), high-resolution integrated imaging across different scales remains underexplored due to limitations in observational configurations and inversion techniques. In this study, we fully exploit the potetial of Distributed Acoustic Sensing (DAS) for cross-scale ultra-high-density observations and develop a compatible and pragmatic multi-scale surface wave imaging strategy based on Voronoi tessellation with grid cells adapted to dispersion data sensitivity kernels. A 2D dispersion curve inversion kernel and multigrid constrained update strategy are also integrated to this strategy to improve inversion accuracy and computational efficiency. More importantly, the strategy allows for the quantitative assessment of inversion result uncertainties and resolution, enhancing model reliability and guiding interpretation. The efficacy of this framework is validated through synthetic tests and applied to a seabed DAS field study in Monterey Bay, California. We demonstrate a refined S-wave velocity model with higher resolution and deeper illumination depth, offering new insights into the fault system and paleogeographic history of the region, especially paleochannel evolution. The results contribute to reconstructing past geological processes and understanding their influence on contemporary geohazards and subsurface dynamics. Our findings emphasize the necessity for multiscale imaging in large-scale geophysical studies.
How to cite: Guan, J., Cheng, F., and Xia, J.: Multi-Scale Surface-Wave Imaging Using Distributed Acoustic Sensing and Voronoi Tessellation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7809, https://doi.org/10.5194/egusphere-egu25-7809, 2025.
Understanding the structure, physical properties and dynamics of the shallow subsurface at high resolution is critical for evaluating geohazards and exposure. However, detailed characterization and monitoring of subsurface structures and processes remains a challenge, specially in urban environments and offshore areas where subsurface access is very limited. Fibre-optic sensing deployed on existing, unused (“dark”) telecommunication networks offers an unprecedented opportunity to investigate the subsurface at high resolution in an efficient and sustainable way. In particular, Distributed Acoustic Sensing (DAS) enables seismic measurements at a spatial resolution of a few meters over tens of kilometers and at a temporal resolution of a few milliseconds, which would be cost prohibitive and non-viable using conventional seismic sensors.
We explore the potential of using DAS deployed on onshore and offshore dark fibres for subsurface imaging and monitoring in the metropolitan area of Istanbul and the eastern Marmara Sea region (Turkey). Istanbul sits 20 km north of the North Anatolia Fault Zone (NAFZ), one of the World’s most active faults. The NAFZ presents complexities in fault geometry near the city, which are not well understood, and data are lacking on the presence and geometry of hidden faults underneath the urban area. Besides, many of the fast-growing districts of the metropolitan area are experiencing deformation processes, such as subsidence and landslides, and are prone to strong co-seismic shaking and liquefaction due to underlying soft sediments and shallow hydrological systems. To monitor seismicity and deformation processes in the eastern Marmara Sea, GFZ is operating the Geophysical Observatory of the Northern Anatolian Fault (GONAF) in collaboration with the Turkish Civil Disaster Emergency Authority (AFAD), consisting of seven boreholes equipped with seismometer strings and partly with strainmeters. With our study, we expand and strengthen the observatory by integrating fibre-optic sensing technologies and developing advanced approaches for DAS-based high-resolution imaging and process monitoring.
Since May 2024, two dark fibres have been interrogated by two DAS instruments deployed in a telecommunication facility in the Istanbul district of Kartal. One of the fibres is fully onshore; it is 17 km long and traverses part of this densely populated district, crossing almost perpendicularly the under-investigated Kartal Fault. The second fibre crosses the coastal portion of Kartal and runs on the ocean floor connecting four of the Princess Islands, which host GONAF stations. Ambient seismic noise from both natural (i.e. ocean waves) and anthropogenic (traffic) origin have been continuously recorded, and several local and regional earthquakes have been captured by both fibres. We are applying ambient seismic noise interferometry approaches and investigating the properties of earthquake wave propagation to obtain high-resolution images of the subsurface along the urban-coastal area, to illuminate potential hidden faults and retrieve detailed information on material properties and their relationship with site response and ground deformation. Ultimately, our study aims to provide approaches for leveraging dark fibre in densely populated coastal areas for efficient subsurface investigations for improved geohazard assessment.
How to cite: Rodríguez Tribaldos, V., Pinzón Rincón, L., Martínez-Garzón, P., Hillmann, L., Bohnhoff, M., Feyiz Kartal, R., Kılıç, T., and Krawczyk, C.: Distributed Fibre Optic Sensing for High-resolution Subsurface Investigation in Istanbul and the Marmara Sea , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12546, https://doi.org/10.5194/egusphere-egu25-12546, 2025.
Distributed Acoustic Sensing (DAS) has become very popular for recording seismic waves in recent years as it provides dense spatial sampling along an optical fiber with only one single interrogator unit (IU) needed for thousands of channels. Fibers can be several tens of kilometers long and in some applications so-called dark-fibers can be used, which were deployed for telecommunication purposes, but are currently not in use. This greatly reduces the necessary effort for field deployment.
Most applications rely only on the phase information in the recorded data. Use cases which rely on amplitude are less frequent, though DAS is very attractive in studies in which strain needs to be measured directly. While the IU is calibrated to record ’fiber strain’ or strain-rate, the properties of the cable and its coupling to the rock control the ’strain transfer rate’ and hence how much of ’rock strain’ is represented in the recorded signal. The ’strain transfer rate’ can be significantly smaller than 1, which also goes along with a reduction of signal to noise ratio, as instrumental noise levels do not depend on the coupling.
At Black Forest Observatory (BFO) we cemented eight optical fibers into a 250 m long groove in the concrete floor of the gallery. The fibers are made up of a 9 µm thick core, 116 µm thick cladding, 125 µm thick coating, and a 650 µm thick tight buffer adding up to a total thickness of 0.9 mm. This type of installation shall provide the best achievable coupling of the fiber to the rock.
We use this installation as a test-bed for DAS IUs and show results from a huddle test run in spring 2024 with four types of IUs. The ’strain transfer rate’ becomes close to 1 for all IUs, making ’fiber strain’ almost equal ’rock strain’ as expected. A comparison with data recorded by the Invar-wire strainmeter at BFO and the intercomparison of IUs lets us further characterize the signal quality and coherent and incoherent background noise.
How to cite: Forbriger, T., Münch, F., Widmer-Schnidrig, R., Hillmann, L., Xiao, H., Rietbrock, A., Rodriguez Tribaldos, V., Strollo, A., and Jousset, P.: Cemented fibers as a test-bed for distributed acoustic sensing (DAS), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9229, https://doi.org/10.5194/egusphere-egu25-9229, 2025.
Understanding the full wave field is imperative for seismic data analysis, as the different components induce errors in the sensors. Recent development of rotational seismometers allows for detailed measurements of the wave field gradients. Providing additional information that was previously unattained. However, it is well-known from navigation solutions that rotational data requires proper processing to be physically meaningful. In this study, we focus on investigating and quantifying two errors affecting recording of rotations: 1) misorientation of sensor to local system called misorientation of rotations and 2) changing projection of the Earth’s spin in the recordings - Earth spin leakage. Using 6-component datasets, including 3C translation and 3C rotation, from near-field events at the Kīlauea Caldera in Hawai‘i and the Mw 7.4 Hualien event on 2024-04-02, we find that the Earth spin leakage is negligible, while the misorientation of the rotations increases with ground motion amplitude, potentially becoming significant for large earthquakes in the near-field. While these errors do not significantly affect acceleration corrections in our dataset, they may be relevant for high-amplitudes or in highly sensitive applications. This work offers the first quantification of these errors in seismology and provides guidance for assessing the need for corrections in future studies.
How to cite: Rossi, Y., Bernauer, F., Lin, C.-J., Guattari, F., and Pinot, B.: Quantifying Rotation-Induced Errors in Near-Field Seismic Recordings, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6411, https://doi.org/10.5194/egusphere-egu25-6411, 2025.
The Source Scanning Algorithm (SSA) was introduced (Kao and Shan, 2004; 2007) as an automated approach to detect and locate seismic events without the need for phase picking. This algorithm works by stacking observed waveforms based on theoretical arrival times derived from a velocity model, under the assumption of a potential point source. It conducts a grid search across multiple candidate source locations, identifying those that produce the highest stacking values (i.e., brightness) as the most probable hypocenters. Extensive use of this approach and its subsequent variations to continuous data streams has shown success even under challenging station geometries, noisy data, and complex seismic source conditions. Recently, Distributed Acoustic Sensing (DAS) has emerged as a powerful tool for seismic monitoring, employing standard fiber‐optic cables as dense arrays of virtual sensors. By measuring strain rate at meter‐scale intervals, DAS can offer continuous seismic coverage over large distances, including remote or hard‐to‐reach areas such as offshore regions, where deploying conventional seismometers can be impractical. With suitable processing, these strain rate measurements can be converted into particle motion, allowing the application of standard seismological methods. However, cable geometry and orientation may introduce azimuthal ambiguities, complicating the use of these methods. In this study, we evaluate the performance of the SSA for locating seismic events using exclusively DAS data. By analyzing both synthetic and real offshore datasets from diverse global regions (e.g., Chile, Greece), we systematically assess the effectiveness of SSA applied to continuous DAS measurements in accurately determining the locations of seismic events. This investigation raises new questions regarding the computational challenges involved—particularly the large volume of DAS data, the selection of appropriate characteristic functions, the integration of DAS data with local seismic networks, the velocity models used for travel-time calculations, and the necessary time corrections. Our results show that SSA can quickly and consistently detect seismic occurrences in DAS data without explicit phase picking, thereby offering a viable method for continuous monitoring even in the presence of the complicated geometries related with DAS installations. This study demonstrates the feasibility of combining DAS and SSA for high-resolution earthquake detection and highlights the potential for expanding its use in real-time seismic networks worldwide.
This research work was supported by the "SUBMarine cablEs for ReSearch and Exploration - SUBMERSE" EU-funded project (HORIZON-INFRA-2022-TECH-01, Grant Agreement No. 101095055).
How to cite: Fountoulakis, I. and Evangelidis, C.: Towards Rapid and Accurate Seismic Event Detection and Localization Using DAS Data: Exploring the Source-Scanning Algorithm Method., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7242, https://doi.org/10.5194/egusphere-egu25-7242, 2025.
The Swedish National Seismic Network (SNSN) in collaboration with the Swedish Transport Administration (STA) and Luleå University of Technology is currently studying how to incorporate DAS data from the railway system into the processing at the SNSN. A test data set consisting of both DAS and nodal data was collected in August 2024 along 15 km of railway passing the Kirunavaara underground iron mine in northernmost Sweden. During a three day period, the cable and instruments recorded blasts and induced events from the mine, as well as a more distant earthquake occurring along the Pärvie fault. Here we present analyses of the events using DAS data, a comparison of DAS and nodal data and various strategies to add DAS data to the SNSN processing. We will also discuss how data sharing between the Transport Administration and SNSN can be realized in future near real-time operations as the railway implements DAS technology.
How to cite: Lund, B., Papadopoulou, M., Kaslilar, A., and Rantatalo, M.: Incorporating Distributed Acoustic Sensing data in seismic network processing, an example from Sweden, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10198, https://doi.org/10.5194/egusphere-egu25-10198, 2025.
One of the major challenges in earthquake localization in the Aeolian Archipelago, particularly on Vulcano Island, arises from the significant coverage gap caused by the lack of seismic stations installed in marine areas, which are terrestrial zones where installation is challenging or impossible. Deploying stations offshore is logistically and financially demanding, limiting the spatial resolution of seismic monitoring networks in the region.
To address this gap, we explored the potential of using submarine fiber optic cables, traditionally deployed for telecommunication purposes, as seismic sensors. These cables were interrogated by a Distributed Acoustic Sensing (DAS) device, effectively creating a virtual seismic network in previously inaccessible areas. This innovative approach allows the DAS-derived signals to emulate conventional seismic recordings, enabling their integration into existing monitoring frameworks.
We processed the DAS data to generate seismic signals comparable to those obtained from traditional seismic stations. These signals were converted into SUDS files, which were subsequently analyzed using INGV-OE localization software, Seismpicker. Combining these DAS-derived seismic records with data from the permanent monitoring network, we re-evaluated the localization of several seismic events that occurred on Vulcano Island in January-February 2022. The inclusion of DAS data significantly enhanced the accuracy of hypocenter estimations, demonstrating its potential to fill critical observational gaps in the region.
Future work will focus on refining the DAS signal processing pipeline to improve the fidelity and reliability of seismic waveforms. Additionally, expanding the use of DAS technology across other submarine cables in the Aeolian Archipelago could further enhance seismic monitoring capabilities, providing a cost-effective solution to address the limitations of traditional networks. This approach underscores the transformative potential of leveraging existing telecommunication infrastructure to advance geophysical research and hazard mitigation efforts.
How to cite: Aliotta, M. A., Currenti, G., Prestifilippo, M., and Ferrari, F.: Improving earthquake localization in Vulcano island through DAS technology , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8248, https://doi.org/10.5194/egusphere-egu25-8248, 2025.
In urban environments, shallow geothermal heating and cooling systems can play a crucial role in the transition towards renewable energy sources. One such site (USquare) is a transformed military barracks in Brussels, where over one hundred boreholes were drilled (~120 m) and equipped with heat exchangers as part of a low-enthalpy geothermal heating network for a multi-use urban development project. Fourteen of these were equipped with fiber optic cables that can provide continuous temporal monitoring of downhole conditions during operation. This includes Fiber Bragg Grating sensors (FBGs), providing point measurements of temperature, and Distributed Acoustic Sensing (DAS) towards recording strain along the length of the fiber.
In this work, we present the experimental setup and initial results for subsurface monitoring at USquare. We compute the root mean square (RMS) amplitude of seismic noise across all channels, with promising results when compared with known hydro-geological logs. Consideration is also given to the impact of the urban environment on the stability of measurements due to variability in anthropogenic seismic sources. Finally, we show preliminary results applying seismic noise interferometry to downhole measurements. This includes computing auto-correlations from the individual channels and also cross-correlations with surface geophones. These findings highlight the potential of fiber optic sensing technologies for monitoring geothermal operations in urban environments, paving the way for more sustainable energy solutions.
How to cite: Yates, A., Pätzel, J., Caudron, C., Gerard, P., Govoorts, J., Fontaine, O., and Peremans, M.: Subsurface geothermal monitoring using fiber-optic technologies within an urban environment, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19285, https://doi.org/10.5194/egusphere-egu25-19285, 2025.
Distributed Acoustic Sensing (DAS) transforms optical fibers into extensive arrays of sensing points, making it particularly well-suited for seismic array processing techniques. Compared to arrays of seismometers, DAS has the potential for significantly higher spatial density of measurement points. A limitation of DAS is, however, its directional sensitivity, where the response of individual sensing points is influenced by the orientation of the fiber optic cable. In this study, we use a fiber optic cable that was installed by design with multiple cable orientations to record and analyze the seismic wavefield in three dimensions. This work investigates the capabilities of the DAS station, installed in the Munich region (Germany), for seismic monitoring of a nearby geothermal field. The DAS station consists of two controlled fiber-optic cable sections: a near-surface loop providing various azimuthal strain-rate measurements, which is extended into a 250-metre-deep vertical monitoring well for vertical sensing. The setup is complemented on the surface by a 3C-broadband seismometer for the validation of the results. In this study, we describe the design, installation and characterization of the DAS station, as well as the seismic event processing workflow. We demonstrate the ability of the 3D-DAS to analyze wavefield directionality, including back-azimuth, incidence and slowness components. In addition, we highlight the role of the vertical borehole in converting DAS strain-rate data into acceleration, which allows estimating source characteristics such as moment magnitude and stress drop estimation. These capabilities are demonstrated for a local seismic event relevant to the monitoring objective. Quality control procedures confirm the consistency and reliability of the DAS station measurements in comparison to 3C seismometer results. Extending the analysis to a broader event catalogue reveals spatial resolution limitations inherent to the station's array geometry. These results highlight the potential and challenges of using DAS for seismic monitoring in geothermal contexts.
How to cite: Azzola, J. and Gaucher, E.: Three-dimensional Distributed Acoustic Sensing to monitor geothermal fields in Munich, Germany, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6036, https://doi.org/10.5194/egusphere-egu25-6036, 2025.
Geothermal productivity strongly depends on reservoir performance, which is regularly monitored. This work presents the results from Distributed Dynamic Strain Sensing (DDSS or DAS) measurements during the restart of injection and production in deep geothermal wells. This technology's high spatiotemporal resolution enables monitoring relative strain and temperature changes along the entire sensing cable. We monitored 3.7 km of a producer and approximately 4.1 km of an injector. Both cables were installed post-borehole completion and reached up to 1 km into the reservoir. Distributed sensing was achieved using a commercial DDSS acquisition system sampling the boreholes at 1 m spatial interval and 2000 Hz.
Here, we focus on the low-frequency subsurface dynamics captured during the restart phase. We extracted the low-frequency content (<0.1 Hz) by applying a cascading Finite Impulse Response (FIR) filter and a large decimation factor. As fiber optic strain measurements are sensitive to strain and temperature changes along the fiber optic cable, the low-frequency signal is influenced by subtle temperature changes induced by fluid motion.
The results provide unprecedented accuracy in determining deep geothermal inflow zones because we can detect flow velocities magnitudes lower than conventional flow meter measurements. Further, the activation time of the inflow from different depths can be distinguished. Fluid-flow velocity, strain, and their respective temporal derivatives can be used as a proxy for the heat contribution of different depths and the associated inflow zones.
These findings are part of the GFK-Monitor project (https://gfk-monitor.de/en/), demonstrating the ability of DDSS to detect and interpret complex reservoir processes in deep geothermal systems. This research advances downhole monitoring technologies, offers an improved understanding of subsurface processes, and informs strategies to optimize geothermal energy production.
How to cite: Hart, J., Wollin, C., Andy, A., Ledig, T., Reinsch, T., and Krawczyk, C.: Low Frequencies of Distributed Dynamic Strain Sensing enable unprecedented profiling of deep geothermal fluid production and injection, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5864, https://doi.org/10.5194/egusphere-egu25-5864, 2025.
Locating and monitoring groundwater flow is key to understand the health of aquifers, and identify possible pathways for groundwater flooding events that can affect citizens and infrastructures. Geophysical methods such as Electrical Resistivity Tomography have been widely used to image the location of water-saturated areas in the shallow underground (<<1 km), but are mostly limited to local, temporary deployments. Seismology has been successfully used to sense groundwater-related tremor, and seismic stations are well-suited to long-term deployments, but dense, local seismic networks are difficult and costly to deploy.
In this work, we are going to test the potential of Distributed Acoustic Sensing (DAS) on telecom fibres for monitoring groundwater flow. Telecom fibre cables are readily available in many areas where groundwater monitoring is key, such as densely populated cities and major roads, and DAS offers the possibility to achieve great spatial resolution (down to 1 m) with little deployment cost (provided access to the fibres).
Firstly we test the capabilities of DAS compared to traditional seismometers by converting seismic records to virtual DAS. We use records from a dense deployment over an underground, water-filled cave in County Roscommon, Ireland recorded in 2020 by DIAS. By rotating and differentiating the horizontal seismic velocities, we simulate the geometry, spatial averaging and strain rate from a virtual DAS cable that follows the seismometer profiles. Our results show that horizontal, axial strain can successfully sense the weak groundwater-related tremor picked up by the seismometers and identify its frequency content. Secondly, we use the Amplitude Source Location Method to track the source location of the tremor on both the seismometer and the simulated DAS data to assess DAS performance in locating subterranean groundwater flow.
Finally, we will present the results from a DAS survey on telecommunication fibres in Ireland to map groundwater flow we will perform in February 2025. The acquisition will target both well-known water bodies (rivers) along the fibre path for benchmarking as well as areas of past groundwater flooding along major roads in County Galway, Ireland. This experiment will be one of the earliest uses of DAS to locate and monitor groundwater flow, setting the stage for the use of optical fibre networks as a tool for high-resolution, long term aquifer and flood monitoring in urbanised areas.
How to cite: Celli, N. L., Bean, C. J., and Karbala Ali, H.: Monitoring groundwater flow using fibre optic sensing, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13022, https://doi.org/10.5194/egusphere-egu25-13022, 2025.
The ICDP Drilling the Ivrea-Verbano zonE (DIVE) project is focused on studying the lower continental crust (LCC) at key sites in the Ivrea-Verbano Zone of the Italian Alps. The stratigraphically placed research borehole 5071_1_A is drilled in the settlement of Megolo within the municipality of Pieve Vergonte, Val d’Ossola. It is deviated at an angle of c.a. 18 degrees from vertical and penetrates to a depth of 910m. The borehole was diamond drilled with 100% core recovery allowing for a very comprehensive rock characterisation program of the LCC lithologies penetrated.
As part of the wide-ranging geophysical research program, a field trial of a novel single-use borehole fibre optic sensing array, Fibre Line Intervention (FLI) tool, was conducted. The FLI tool is designed to rapidly deploy a continuous fibre optic sensor for distributed acoustic sensing (DAS) and temperature (DTS) measurements into open or cased boreholes. The FLI deploys a single-mode bare optical fibre via a single-use 50 cm long aluminium spool housing (shuttle). The bare fibre unspools from the shuttle as it falls into the borehole. The FLI shuttle tested fits in a borehole with a minimum diameter of 10 cm and a maximum length of 1000 m. After data acquisition, the bare fibre is cut and left to sink to the bottom of the borehole, where it remains along with the shuttle. Acoustic and thermo coupling of the fibre with the formations is achieved via the borehole fluid (water, mud, etc.). Several tests were conducted within the experiment’s program, including passive seismic recording and a multiple offset vertical seismic profile (VSP) survey. A 26,000 lb seismic source – EnviroVibe seismic truck – was used to acquire zero-offset and offset VSP data. The DAS data were collected using an iDAS-MG (Silixa) interrogator.
The trial successfully demonstrates the applicability of the Fibre Line Intervention (FLI) tool for carrying out borehole seismic surveys in scientific drilling projects. The experiment was the first test deployment of such a shuttle to collect downhole seismic data in ICDP projects. The trial has shown that such an approach for deploying distributed acoustic sensing is fast and can be handled by a minimum number of people. The probe is light (less than 5 kg and 1.5 m long).
Passive data revealed the nature of the seismic environment in the area within a wide frequency range and, if deployed for an extended period of time, would allow for the recording of teleseismic events such as earthquakes. Additionally, active water flow zones are identified, whilst the VSP data highlighted the locations of fracture zones intersected by the borehole. The results will be demonstrated in the presentation.
How to cite: Tertyshnikov, K., Greenwood, A., Collet, O., and Pevzner, R.: Field trial of DAS VSP with a single-use bare fibre optic probe during the ICDP-DIVE Phase 1 project, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14343, https://doi.org/10.5194/egusphere-egu25-14343, 2025.
Urban areas are very vulnerable to the effects of geohazards, with a high potential for human life and financial loss due to their high population density and advanced infrastructure. Obtaining high-resolution, subsurface information in urban areas is critical to understand and mitigate the effects of these hazards. In these densely populated centers, the shallow Earth is most stressed, as human activities continuously change their properties and interfere with natural processes. Geophysical surveys often face limitations in urban environments due to logistical constraints (anthropogenic activities, legal restrictions, and risks of equipment theft, among others). Repurposing unused, existing telecommunication optical fibers (so-called dark fibers) as sensing arrays offers a promising alternative to traditional geophysical methods, enabling subsurface imaging at high spatial and temporal resolution in densely populated areas.
The Megacity of Istanbul (Turkey), situated in one of the most tectonically active regions in the World, represents an ideal case for exploring the potential of using dark fibers for subsurface investigations in urban areas. Since May 2024, we have been using Distributed Acoustic Sensing (DAS) to continuously record passive seismic data along a 17 km-long dark fiber crossing the Kartal district in the metropolitan area of Istanbul with the aim to explore the potential of this technology for seismic hazard assessment. Our objective is to apply passive seismic interferometry approaches to DAS ambient seismic noise data to identify hidden faults and generate high-resolution urban-scale subsurface velocity models that can contribute to a better understanding of structures and material properties and their association with seismic risk. Using dark fibers in urban contexts presents multiple challenges, including vast data volumes, a complex noise environment, and unconventional geometries. To address these issues, we develop tools to maximize the potential of dark fibers by effectively utilizing opportunistic ambient noise sources. We evaluate valuable sources, such as train tremors and other traffic, and assess their effectiveness for DAS-based passive seismic interferometry in a complex array setting. Our final objective is to develop efficient approaches to achieve imaging at high spatial and temporal resolution, providing insights that could help mitigate geohazard risk in Istanbul and other similar urban areas.
How to cite: Pinzon-Rincon, L., Rodríguez Tribaldos, V., Martínez-Garzón, P., Hillmann, L., Bohnhoff, M., Kartal, R. F., Kılıç, T., and Krawczyk, C.: High-Resolution Subsurface Imaging for Hazard Assessment in Urban Areas Using Ambient Noise and Dark Fibers: a Case Study in Istanbul, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11688, https://doi.org/10.5194/egusphere-egu25-11688, 2025.
The Istanbul Natural Gas Distribution Company has started monitoring seismic activity within the Sea of Marmara using a fiber-optic (F/O) cable integrated with a Distributed Acoustic Sensing (DAS) system in order to mitigate secondary disasters that may occur after earthquakes and to protect critical infrastructures, such as pipelines. The monitored F/O cable, originally designed for telecommunications purposes, extends over a length of 60 kilometers beneath the Sea of Marmara. In 2022 October, this cable is integrated with a DAS system through an interrogator unit, installed at Tavşantepe Metro Station. The system consists of an analyzer that allows detection up to 40 kilometers, operates with a spatial channel spacing of 10 meters, in total 3910 channels, and a sampling rate of 200 Hz, enabling high-resolution seismic data acquisition. The cable’s route follows several critical regions: it enters the Sea of Marmara, traverses Büyükada, runs behind the Princes' Islands parallel to the Marmara Fault, intersects the fault at multiple locations, and ultimately terminates on land at Ambarlı. This strategic placement provides extensive coverage for monitoring seismic activity along this geologically active region.
Since the beginning of 2023, more than 500 earthquakes, with magnitudes ranging from 0.7 to 7.8, have been recorded using the F/O cable. Our analysis reveals that the quality of recorded seismic signals is strongly influenced by two factors: the incidence angle of wave on the cable and the cable's coupling with the ground. Poor coupling reduces the energy transfer from the ground to the cable, leading to weaker or distorted signals, while unfavorable incidence angles of wave, affect the strain response detected by the DAS system. These findings highlight the importance of optimizing cable placement and ensuring effective coupling for reliable seismic monitoring.
The developed algorithms have enabled the real-time automatic detection of earthquakes occurring within and around the Sea of Marmara using the F/O cable, and the initial results have been promising. The first real-time detection is accomplished for the M3.9 Çanakkale earthquake occurred on 19 November 2024 at 07:46:15 UTC. The F/O cable detects the earthquake 33 seconds following its occurrence, and the system sent an automatic detection notification approximately 1 second later after detection.
As part of our project, at the beginning of January 2025, a vessel-based survey is conducted to determine the submarine position of the F/O cable passing beneath the Sea of Marmara. This study contributes to improving the application of DAS in submarine seismic observation and highlights potential challenges in data acquisition from F/O cables.
How to cite: Coşkun, Z., Koç, B., Özgür, H. G., Aslan, K., Özkan, E., Şahin, R. C., Erkorkmaz, T., Tunç, S., Pınar, A., and Özener, H.: Observations of Seismic Activity Using Fiber Optic DAS in the Sea of Marmara , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10070, https://doi.org/10.5194/egusphere-egu25-10070, 2025.
Distributed acoustic sensing (DAS) is an instrumental approach that allows fiber optic cables to be turned into dense arrays of acoustic sensors. This technology, based on an optical time-domain reflectometer (OTDR) technique, is attractive in marine environments where instrumentation is difficult to implement. Its main applications lie in seismology, oceanography, and bioacoustics.
Current technology limits the range of DAS to ca. 150 km making it very useful in the Azores, where seismic stations only exist on the Islands with a strong E-W alignment, as shown by Matias et al. (2021). The Azores have been suffering an increase in extreme wave conditions that affect navigation and coastal infrastructures. DAS can provide proxies for significant wave height, period, and surface currents on the shallow sections of the cable, complementing existing monitoring networks.
The Azores region is part of the migration routes for fin and blue whales, which are known to produce acoustic signals during certain parts of the year. These vocalizations provide crucial data for Passive Acoustic Monitoring that can be used to support the establishment and update of mitigation measures addressing their preservation. DAS has already demonstrated its usefulness in detecting and tracking baleen whales using acoustic records.
One issue that needs to be addressed in using DAS data is calibration. It is well demonstrated that strain or strain rate as measured by DAS can be converted to ground motion along the direction of the submarine cable section, if the apparent phase velocity is known. Similarity between DAS converted signals and co-located seismograms is well demonstrated but the absolute value is likely to vary with the cable coupling to the seafloor.
This work reports on the recent operation of a DAS interrogator deployed at the Faial landing site to monitor the first 50 km of the telecommunication cable between Faial and Flores islands operated by Fibroglobal. The instrument used, HDAS developed by the IO-CSIC, recorded at 50 Hz for 11 months starting on the 15th of December 2023 with 10 m gauge length. For calibration purposes two 4C OBS were deployed close to the cable at ~10 km and ~30 km distance from the landing point. The OBSs were deployed in July 2024 and recovered in November 2024, providing 5 months of simultaneous recordings with the DAS.
As expected, both earthquakes and whale vocalizations were identified on the DAS and OBS. We show that DAS can contribute to an improved localization of local offshore earthquake parameters due to its high density of sensors, particularly for the events occurring NW of Faial Island, with locations North of the cable. Clear landward and seaward oceanic waves are identified on the cable's shallow section. In all the applications the main question to address is the variable coupling of the cable to the seafloor in the Azores plateau of volcanic origin.
This work is supported by the Portuguese Fundação para a Ciência e Tecnologia, FCT, I.P./MCTES through national funds (PIDDAC): UID/50019/2025 and LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020), by the MODAS project 2022.02359.PTDC, and by EC project SUBMERSE project HORIZON-INFRA-2022-TECH-01-101095055.
How to cite: Matias, L., Corela, C., Gonçalves, S., Loureiro, A., Schlaphorst, D., Carrilho, F., Custódio, S., Martins, H., Silva, S., Frazão, O., Niehus, M., and Pereira, A.: Monitoring the oceans with DAS in the Azores, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12240, https://doi.org/10.5194/egusphere-egu25-12240, 2025.
This study investigates the use of subsea communication cables as seismic monitoring instruments. We simulate the waveforms observed on 17 spans of the Iceland-Ireland subsea telecommunications cable, following the framework presented in Fichtner et al., 2022. We use an open source spectral-element wave propagation code (SPECFEM3D GLOBE) to simulate strain rate at a dense set of points along the cable. The simulations incorporate realistic physical conditions, including the effects of topography, gravity, crustal structure, ocean load and cable geometry, and are executed on the Elja HPC platform, using 150 CPUs.
A Python-based pipeline processes and visualizes simulated strain data, supporting comparisons with real-world observations. This pipeline lays a foundation for a software library for analysis of seismic subsea cable data.Preliminary results indicate alignment between simulations and observations, with ongoing refinements addressing discrepancies caused by environmental noise and measurement uncertainties. The ability to model the observed strain response on the fiber optic cable, enables the incorporation of this dataset into traditional seismological applications, expanding observational coverage and contributing to the understanding of seismic processes in areas not accessible to traditional seismic networks.
How to cite: Gunnarsson, A. I., Mazur, M., Kamalov, V., Karrenbach, M., Williams, E. F., Jonsson, O., Fontaine, N. K., Ryf, R., Dallachiesa, L., Neilson, D. T., and Hjorleifsdottir, V.: Simulations of seismic waveforms observed on the IRIS subsea cable, connecting Iceland and Ireland, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19609, https://doi.org/10.5194/egusphere-egu25-19609, 2025.
Understanding volcanic processes is fundamental for anticipating impacts of eruptive activity on human activities and environment. Deformation and seismicity often precede and accompany volcanic eruptions. Models of magma emplacement and ground deformation associated with eruptions are obtained from GNSS and InSAR observations and associated seismic source mechanisms from seismic observations. While satellite sensing techniques benefit from a large spatial coverage but coarse temporal resolution and accuracy (mm range), seismometer networks acquire dense temporal data but are sparsely distributed and suffer from spatial aliasing. Dynamic models of sources during the event at the minute scale are challenging to obtain because they are in most cases too small or too slow to be observed accurately with conventional instrumentation. Here, we demonstrate that distributed fibre optic sensing using phase optical time domain reflectometry (Φ-OTDR) allows us to retrieve dynamic and static deformation processes associated to diking events prior to volcanic eruptions, at the minute time scale. Since November 2023, we are continuously monitoring an existing telecom fibre optic cable with a conventional iDAS interrogator, set-up on western Reykjanes Peninsula, SW Iceland. Reykjanes Peninsula is the onshore expression of the Atlantic mid-oceanic ridge, where a series of magmatic intrusions and eruptions have occurred since 2020. The used cable spans across locations from a large inflation/deflation area near dyke outbreaks at its eastern end, to a remote area where little signatures from eruptions are observed at its western end. In-situ down-sampled strain-rate data from 1000 Hz to 200 Hz is transferred continuously via internet to our computing center at the GFZ in Germany. We further down-sample data to 2 minutes and perform time integration in order to analyse long period strain signals both spatially and temporally. Here we present resulting distributed dynamic strain observations and their source inversions associated with a series of several eruptions and intrusions (18.12.2023 22:17; 14.01.2024 07:57; 08.02.2024 06:03; 16.03.2024 23:14; 22.08.2024 21:26; 20.11.2024 23:14 – all times UTM). Our inversions comprise a Mogi source and an Okada model, and we test several inversion methods. For each recorded eruption, we invert the distributed spatial strain taken every 2 minutes, allowing us to follow magma progression prior to each eruption with time. Inverted dimensions and dyke locations match rather well with observed eruption locations. We also analyse links between seismic velocity changes from distributed dynamic strain ambient noise records and the eruptions. These results show that fibre optic distributed sensing is capable of simultaneous seismological and geodetic observations in a volcanic context opening the path for a better understanding and potentially improved real-time monitoring of volcanic processes.
How to cite: Jousset, P., Gudnason, E. Á., Currenti, G., Wollin, C., Holstein, L., Maaß, R., Diaz-Meza, S., Hersir, G. P., Sigurðarson, D., and Krawczyk, C.: Sources of Ultra-Slow Dynamic and Static Deformation of dyke eruptive events revealed by telecom fibre optic cable sensing on western Reykjanes Peninsula, SW Iceland., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5200, https://doi.org/10.5194/egusphere-egu25-5200, 2025.
Etna volcano (Italy) is one of the most active volcanoes in the world with a great variety of events leading to effusive and/or explosive eruptions. The eruptive events are usually preceded and accompanied by ground deformation, that is often so tiny that only high-precision borehole strainmeters are capable to capture. So far, the analysis of more than 10 years of records from the Etna strainmeter network has shown the importance of continuous strain monitoring both for surveillance purposes and research advancements. Despite their valuable contribution, the number of deployable borehole high-precision strainmeters is limited by costs, logistics and challenges in the installation. Here, we demonstrate that fiber optic sensing is a valid alternative for measuring ultra-small slow volcano deformation.
In 2024 an innovative Distributed Fiber Optic Sensing prototype has been set up to interrogate a fiber optic cable installed behind casing in a 200-m deep borehole in Serra La Nave (on the southern Etna flank at ca. 5 km away from the summit craters). The new interrogator uses a reference-based Rayleigh backscatter correlation method which allows for precise long-term strain measurement. The quality of the fiber optic data is assessed by comparing the signals against well-known rock deformation responses and against strain time series recorded by the Etna strainmeter network. Thanks to the accuracy better than few nanostrain in the low frequency range, we clearly observe Earth tidal components in the fiber optic strain data. Peaks in the M2 (period 12.42 h) and O1 (period 25.82 h) tidal constituents emerge well above the background noise. The reliable detection and extraction of tidal components provide the opportunity to characterize and quantify the coupling between the fiber and the rock formation. Moreover, strong correlations with atmospheric pressure changes and rainfall events are observed. These evidences demonstrate a good coupling between the fiber optic cable and the surrounding rocks, although the degree of coupling is highly variable along the cable. The analyses show a long-term stability of the interrogator capable to record volcano deformation.
On the morning of 10th November 2024 Etna experienced a weak lava fountain preceded by a short and small seismic swarm. Despite the tiny deformation induced by the volcano activity, the fiber optic interrogator was able to discern strain variations on the order of 125 nanostrain over 2 h (0.02 nanostrain/s). The first analyses and interpretation of the signal related to the volcano activity will be presented.
How to cite: Currenti, G., Jousset, P., Liehr, S., Carleo, L., Pulvirenti, M., Pellegrino, D., Kirchner, J., Hahn, M., Bonaccorso, A., and Krawcyz, C.: Ultra-small volcano deformation recorded at Etna by fiber optic sensing, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11343, https://doi.org/10.5194/egusphere-egu25-11343, 2025.
The LUNA Moon analogue facility, jointly operated by DLR and ESA in Cologne, Germany, provides a simulated lunar environment for instrument and experiment tests and operations training for both robotic and crewed missions. At the heart of LUNA is a 700 m2 regolith testbed, filled to 60 cm depth with EAC-1A Mare simulant, which also contains a deep-floor area with of to 3 m depth. Before filling the hall with the regolith simulant, a 500 m long fiber-optic cable containing single- and multi-mode fibers, as well as an engineered fiber, was deployed in a spatial grid to support future tests of DAS and DTS applications for the Moon.
The first user campaign after inauguration of LUNA collected 4 days of DAS data in November 2024, partly overlapping with a test of vertical-component geophones for a possible Artemis IV deployed instrument. Besides, a preliminary set-up of the LUNA broad-band station (Trillium Compact 120 s) was recording continuously at the same time. In this presentation, we show results for geolocating and mapping the fiber in LUNA (using tap test, weight drops, and QGIS) and compare the characteristics of signals recorded by the different instruments. We investigated and describe hammer shots for geophone-based refraction seismics, signals from cars, airplane take-offs (from nearby CGN airport), a helicopter overfly (with characteristic Doppler shift), the crane within LUNA, and a small, 3U-cubesat sized rover driving in LUNA. We also recorded a teleseismic earthquake with the DAS. Our results provide a comprehensive baseline characterization of anthropogenic noise at our facility, offering a valuable reference for identifying external events at LUNA during future user campaigns and mission preparations.
How to cite: Knapmeyer-Endrun, B., Fantinati, C., Hart, J., Pinzon Rincon, L. A., Jousset, P., Krawczyk, C., Garcia, R., Calosci, L., Spichal, C., Hallinger, M., Küchemann, O., and Maibaum, M.: To the Moon: DAS measurements of anthropogenic signals in LUNA, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15804, https://doi.org/10.5194/egusphere-egu25-15804, 2025.
