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| Citation: |
Fichtner A, Walter F, Paitz P, Klaasen S, Bowden DC, Noe S, Müller N, Husmann D and Morel J (2025). An illustrated guide to: Distributed and integrated fibre-optic sensing in seismology. Earthq Sci 38(1): 67–77. DOI: 10.1016/j.eqs.2024.09.006
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The properties of laser signals are affected by deformation of the optical fibre through which they are transmitted. While this deformation dependence is undesirable in telecommunication, it can be exploited for the construction of novel seismic sensors that fill a niche in data acquisition where traditional seismometer arrays would be difficult to deploy. This includes densely populated urban centers, the oceans, volcanoes and the Earth’s polar regions. These notes complement a presentation on recent methodological developments and applications in fibre-optic seismology. The first part is focused on the use of distributed fibre-optic sensing in cryosphere research, and specifically the investigation of the internal structure and seismicity of glaciers and ice sheets. The second part is dedicated to recent advances in integrated fibre-optic sensing, with emphasis on novel measurement principles and sensitivity.
The use of the word ‘revolution’ to highlight the impact of scientific developments is often inflationary. However, looking back at the past decade, it is fair to say that fibre-optic sensing is in the process of revolutionising seismic data acquisition. While an exhaustive review that does justice to all developments is beyond the scope of this paper, we limit ourselves to a condensed overview that may serve as a hook for readers who wish to go into more detail. Early applications of a technology known as distributed acoustic sensing (DAS) can be found in the fields of perimeter and pipeline security (e.g., Taylor and Lee, 1993; Owen et al., 2012; Hill, 2015). Around the same time, DAS became widely used in seismic exploration and monitoring, often in boreholes where fibre-optic cables are pre-installed (Mateeva et al., 2013, 2014; Daley et al., 2013, 2014, 2016; Li M et al., 2015; Dean et al., 2016; Lellouch and Biondi, 2021). The dense channel spacing in the meter range, combined with the large frequency bandwidth from mHz to kHz (e.g., Lindsey et al., 2020; Paitz et al., 2021) soon turned DAS into an attractive tool for data acquisition in terrain where the installation and maintenance of dense seismometer arrays is difficult. This includes densely populated areas (e.g., Lindsey et al., 2017; Martin et al., 2017; Biondi et al., 2017; Ajo-Franklin et al., 2019; Spica et al., 2020; Yang Y et al., 2022), glaciers and ice sheets (e.g., Walter et al., 2020; Booth et al., 2020; Hudson et al., 2021; Brisbourne et al., 2021; Fichtner et al., 2022, 2023), volcanoes (e.g., Klaasen et al., 2021, 2022; Currenti et al., 2021, 2023), and avalanche-prone slopes (e.g., Paitz et al., 2023; Edme et al., 2023).
As DAS matured into an established element in the seismic data acquisition tool box, its disadvantages also became more apparent. In particular, the high cost of commercial interrogation units and the limited interrogation distance of typically several tens of kilometres, are frequently cited concerns. The latter prevents DAS from covering the oceans, which are arguably the largest blind spot in seismology. Alternative systems that exploit deformation-induced changes in the phase or polarisation of forward transmitted laser signals, have emerged more recently (e.g., Marra et al., 2018, 2022; Mecozzi et al., 2021; Zhan ZW et al., 2021; Bogris et al., 2022; Noe et al., 2023; Donadello et al., 2024). While their technical implementations differ, they all trade an increase of interrogation distance against spatial resolution along the fibre. The latter can be controlled, to some extent, by the fibre geometry (Fichtner et al., 2022) but does in any case not reach the metre-scale resolution of DAS.
The following notes complement a presentation on Fibre-optic seismology, given at Peking University on 9 January 2024. In the first half, we focus on applications of DAS for cryosphere research, e.g., to investigate the internal structure and seismicity of glaciers and ice sheets. The second half is dedicated to emerging integrated fibre-optic sensing technologies, with an emphasis on different measurement principles and theoretical background on the sensing characteristics of such systems. In an effort to address primarily non-experts in the field of fibre-optic seismology, the notes are written in a light and non-technical language, but provide numerous references to original research papers.
We begin our tour with a brief summary of distributed acoustic sensing (DAS). The basic measurement principle, described in numerous books and review articles (e.g., Hartog, 2017; Lowrie and Fichtner, 2020; Zhan ZW, 2020; Lindsey and Martin, 2021), rests on the emission of laser pulses by an interrogation unit (IU) into a single optical fibre. Due to imperfect fabrication, the fibre contains defects that reflect small portions of the energy back to the IU. The time at which the back-scattered pulse arrives provides information on its distance from the emitter. As the fibre deforms, the defects move, thereby changing the time it takes the back-scattered pulse to arrive at the IU. This small change in arrival time can be measured by the IU and translated into an estimate of strain or strain rate as a function of position along the fibre.
The potential of DAS primarily lies in (1) the very dense channel spacing, typically on the order of few metres, (2) the resulting low cost per channel, compared to standard seismic sensors, (3) the possibility to use pre-existing telecommunication fibres, especially in urban areas or below the oceans, and (4) the rather easy deployment of fibre-optic cables in boreholes and in harsh environments, e.g., on glaciers, ice sheets, volcanoes or under water.
In the following paragraphs, we will illustrate the use of DAS for cryosphere research, which is arguably one of the scientific niches where this emerging technology is most beneficial.
The Rhône Glacier in the Swiss Alps is a temperate glacier at an elevation of 2,200–3,600 m. With a surface area of ~15.5 km2, it stretches around 8 km from the top of its accumulation zone to the bottom of its tongue. Being easily accessible, Rhône Glacier is a perfect natural laboratory to study the consequences of climate warming on alpine environments and to assess the potential of DAS in cryosphere research (Walter et al., 2020).
Slide 11: At the lower part of the glacier, at ca. 2,500 m elevation, we installed two kinds of instruments: a 1 km long fibre-optic cable in a triangular shape, and three seismometers, one in each corner of the triangle. The installation of both the fibre-optic cable and the seismometers took few hours. However, in this time, the fibre-optic cable provided 1,000 measurement points, and the seismometers only three.
Slides 12–14: Surface ice quakes, produced, for example, by the opening of crevasses, are among the most prominent signals in the DAS and seismometer recordings at frequencies up to 30 Hz. As a consequence of being produced near the surface, the wavefield is dominated by Rayleigh waves. The character of the DAS and the seismometer recordings is similar but not identical because they are different physical quantities.
Explosions fired close to the instruments are equally well visible, and in addition to Rayleigh waves, they cause clearly visible P waves in the 1–100 Hz frequency band. In this example it becomes apparent that the signal-to-noise ratio of the DAS recordings is lower than in the seismometer recordings. However, as we shall see later, the lower quality is compensated by the larger quantity of measurements.
Rock falls are a frequent phenomenon on most alpine glaciers, and their frequency can increase in response to climate warming. In contrast to surface ice quakes and explosions, they produce a complex time series, representing a longer-lasting process of rock masses falling off the slopes and hitting the glacier surface. Some of these events can be located with the help of the DAS array.
Slides 15 – 17: In this study, our main interest was on stick-slip ice quakes, i.e., events that occur at the interface between ice and bedrock. Generated at greater depth, they are distinguished by clearly visible P and S waves, with arrival times that can be picked easily.
The benefit of DAS becomes apparent when trying to locate stick-slip events. Using the three seismometers, positioned in the corners of the DAS array, produces a broad cloud of possible locations, shown in the form of green dots in the figure. With the help of the large number of DAS recordings, this broad cloud shrinks into the much smaller cloud of black points, thereby providing a much more accurate location estimate.
During the one-week deployment, we registered 48 additional stick-slip events with waveforms that are nearly identical to the ones just presented. (The average mutual correlation coefficient is ~0.98.) All of them could be identified as belonging to the same slip patch at the ice-bedrock interface.
Slide 18: In summary, we have seen that the deployment of kilometer-long fibre-optic cables on glaciers is logistically feasible. Good coupling and data quality can be achieved by simply covering the cable with snow, which provides protection against wind and temperature fluctuations. Compared to the few seismometers that could be installed, the DAS array provides substantially improved location accuracy, thereby enabling the inference that all recorded stick-slip events share the same source region at the glacier bed. This pilot experiment opens new opportunities to study the basal conditions of glaciers and their temporal variations, as well as the contribution of stick-slip motion to overall glacier dynamics.
With an elevation of 1,725 m and a caldera diameter on the order of 10 km, Grímsvötn is one of Iceland’s largest, and on a centennial time scale also most active volcanoes. It is covered by Europe’s largest ice cap, Vatnajökull and features a volcanically-heated subglacial lake of variable depth. The last major eruption of Grímsvötn occurred in 2011. In addition to the eruptions themselves, secondary effects such as subglacial floods (Jökulhlaup) and local climate variations are among the most significant natural hazards produced by Grímsvötn. The remoteness of the volcano and the harsh environment turn Grímsvötn into the perfect study object to explore the potentials and limitations of DAS (Klaasen et al., 2022).
Slides 20 – 22: In spring 2021, we deployed a 12.5 km long fibre-optic cable half-way around and into the caldera of Grímsvötn. The goal was blue-sky fundamental research: Is such an experiment logistically feasible? What are the kinds of environmental signals that could be recorded; if any at all? Is it possible to locate seismic events, and may some of the events only be detectable on the cable but not at the broadband seismic station on the caldera rim?
The deployment of the cable was possible only thanks to the construction of a purpose-built trenching sled. Towed by a snow cat, commonly used to prepare ski slopes, the sled featured a plough where the cable entered at the top and reappeared at ~50 cm depth below the surface. To prevent the sled from tipping over, two people and a filled oil barrel were needed as additional weights.
The DAS interrogator was installed in a research hut at the highest point of the caldera rim, where a combination of a diesel generator and batteries provided uninterrupted power for the nearly one month duration of the experiment.
Slides 23 & 24: Local earthquakes are among the most prominent signals recorded by the DAS array. During the experiment, we detected around 2,000 earthquakes, i.e., nearly two orders of magnitude more than the regional seismometer network.
Thanks to the good coverage provided by the DAS cable, many of the events could be located, thereby drawing a picture of Grímsvötn’s volcano-seismicity with unprecedented detail (Klaasen et al., 2023). A dyke-shaped structure outlined by the earthquake hypocentres, as well as several other event clusters are among the easily distinguishable features of the estimated source distribution.
Slides 25 – 30: A more subtle but still clearly visible component of the recordings is a nearly monochromatic background oscillation around 0.22 Hz between ~8 to 12 km distance along the cable, i.e., inside the caldera.
A simple spectral analysis reveals that the amplitude spectrum of the signal hardly varies over time, in stark contrast to the amplitude spectrum of ocean-generated microseismicity. Despite the complexity of the ice-covered volcanic system, the amplitude spectrum can be matched rather accurately by a simple one-dimensional harmonic oscillator with a quality factor of Q ≈ 10.
The minimum driving forces needed to sustain the ice sheet oscillations, i.e., the forces in addition to those provided by the ocean-related microseismic noise, can be estimated through the solution of a series of linear inverse problems. A time-frequency analysis of these forces reveals that they are required to act almost continuously, though with variable amplitude.
Most likely, the observed oscillation represents a standing flexural wave of the ice sheet floating on top of the sub-glacial lake. A plausible source is more or less continuously acting volcanic tremor that is being amplified by the ice sheet. In this sense, the floating ice sheet acts as a large natural loudspeaker (Fichtner et al., 2022).
Slide 31: As on Rhône Glacier, we have seen that the DAS deployment outperforms an array of conventional seismometers in terms of earthquake detection and location. This success has two important components: (1) The DAS array on Grímsvötn has a large number of receivers near the seismic sources. Hence, they could be detected despite their small local magnitude, sometimes as small as –3. (2) Snow and ice provide good coupling of the cable and shielding from wind and temperature fluctuations. In contrast to other environments, e.g., on bedrock or in urban areas, this coupling can be achieved rather easily.
A special feature of Grímsvötn is floating ice sheet resonance, which acts as an amplifier of low-amplitude tremor that would otherwise not be detectable. This phenomenon may offer new opportunities for the monitoring of subglacial volcanoes.
With a total length of around 600 km, the Northeast Greenland Ice Stream (NEGIS) is Greenland’s largest active ice stream, discharging nearly ~12 % of its total ice mass into the North Atlantic (Rignot and Mouginot, 2012). It thereby makes a substantial contribution to the accelerated mass loss of the ice sheet and to current sea level rise. Located in the upstream part of NEGIS, the East Greenland Ice Core Project (EastGRIP), aims to retrieve a deep ice core that provides constraints on climate history, ice flow patterns and conditions at the ice-bedrock interface. At the EastGRIP site, ice thickness is around
Slides 33 & 34: The extensive infrastructure provided by the EastGRIP camp offers a unique opportunity for seismic studies, including conventional acquisition and fibre-optic sensing. Seismic data acquired over larger areas complement the single-point measurement of the ice core. Furthermore, recordings of surface waves deliver valuable constraints on the structure of the firn layer, which is the transition material between fresh snow at the surface and impermeable ice at greater depth.
An unusual source of surface waves was the landing of a C-130 Hercules plane on 26 July 2022. With a sinking speed around 1 m/s and an estimated weight of ~60,000 kg, the touch down injected an energy of ~30 kJ into the ice sheet. This corresponds to an earthquake of magnitude −0.2.
Prior to the landing, we trenched a 3 km long fibre-optic cable approximately 50 cm into the firn. The last ~2.6 km of the cable were perpendicular to the ski way, and the point where the plane landed made an angle of only 7° with the cable. Hence, observed apparent wave speeds are practically identical to actual wave speeds.
Slides 35 – 37: The raw time-domain recording of the landing shows signals that are clearly above the noise level. However, individual seismic phases are difficult to distinguish due to the complexity of the wavefield. Fortunately, the dense uniform sampling of the DAS channels enables a straightforward 2-D Fourier transform that can be used to translate the time-space domain data into the frequency-phase velocity domain.
The frequency-phase velocity amplitude spectrum reveals at least 15 easily distinguishable wave propagation modes, including the Rayleigh fundamental mode and numerous overtones, a leaky mode and several pseudo-acoustic modes caused by trapping of P waves in the firn layer.
Since significant lateral variations around the EastGRIP site only occur over length scales of tens of kilometres (Franke et al., 2022), the dispersion data can be conveniently inverted with the classical Backus-Gilbert method for 1-D media (Backus and Gilbert, 1968, 1970). This provides both estimates of S-wave speed averages at depth and uncertainty estimates. Within the upper ~100 m, S-wave speed increases nearly exponentially, which is typical for the firn layer (Kohnen and Bentley, 1973). Thanks to the exceptional data quality and quantity, uncertainties of the inferred wave speeds are on the order of few tens of m/s. Using well-established conversions from seismic wave speeds to density (Kohnen, 1972; Diez et al., 2014), the depth of the firn-ice transition, which occurs at a density of 830 kg/m3, can be estimated. It lies between 65 – 71 m, in accord with the results of firn core measurements (Vallelonga et al., 2014).
Slide 38: In summary, the combination of DAS with exotic seismic sources, an airplane landing in our case, can provide exceptional data quality. In our case, 15 wave propagation modes could be easily detected and identified over a frequency range from around 3–100 Hz. The approximate 1-D structure of ice sheets makes them ideally suited for Backus-Gilbert inversion, which provides resolution and uncertainty estimates without additional effort. In our case, resolution lengths below 100 m depth are on the order of few meters, and uncertainties are in the 10 m/s range (Fichtner et al., 2023). Such detailed information on firn structure is essential for various applications, including ice sheet mass balance estimates, ice core climatology, surface melt estimates, and seismic studies of deeper parts of the ice stream that require corrections for the shallow layer, similar to crustal corrections in seismology.
While DAS has become a mature technology, some of its weaknesses are also being better understood. Since back-scattered pulses are weak and further attenuated during propagation, the maximum interrogation distance in most DAS experiments is on the order of few tens of kilometres. Furthermore, DAS units that are currently commercially available are expensive, with a typical cost on the order of USD 100,000 or more. This motivates the development of alternative fibre-optic sensing systems that exploit deformation-induced phase delays of forward transmitted, instead of back-scattered, laser signals.
The basic concept of integrated, i.e., transmission-based, fibre-optic sensing rests on the emission of a laser signal at one end of an optical fibre that is received at the other end with some time delay. In response to deformation, the time delay changes. This is a consequence of both a change in length and a change in refractive index, known as the opto-elastic effect. Different sensing systems measure the time delay changes with different technological approaches, thereby extracting information about fibre deformation (e.g., Marra et al., 2018; Bogris et al., 2022; Noe et al., 2023).
The deformation-induced phase change of the transmitted signal can be shown to be proportional to the integral of strain along the fibre (Fichtner et al., 2022a, b); hence, the term integrated fibre-optic sensing. Unfortunately, the integration seems to eliminate the high spatial resolution, which is one of the main advantages of DAS. While integration is the price to pay for longer interrogation distances, it offers the opportunity to quantitatively compare DAS to an integrated sensor, because DAS delivers the integrand that we can use to synthesise the data produced by an actual integrated sensing system.
We performed the first quantitative comparison of DAS and an integrated fibre-optic sensor based on microwave frequency fibre interferometry (MFFI, Bogris et al., 2021, 2022). The concept of MFFI rests on the emission of a continuous laser signal modulated to microwave frequencies. At the end of the interrogation line, the fibre is looped back to the interrogator, which enables a real-time correlation of the original emitted signal and its delayed version that is received after some time.
Slide 44: To enable a fair comparison, we connected a DAS and an MFFI interrogator to fibres within the same ~30 km long telecommunication fibre, traversing the northern suburbs of the Greek capital Athens. Access to the fibre was provided by the Greek telecommunication company OTE, and the experiment was operational for around one month in October 2021.
Slides 45 & 46: A magnitude 6.3 earthquake that occurred on 21 October 2021 near Crete provided the data necessary to compare DAS and MFFI. The DAS recording shows clear P- and S-wave arrivals, as well as surface waves and long-lasting coda. Integrating, i.e., summing, the DAS data along the fibre, synthesises MFFI data that can be compared to the actual MFFI recordings. Though the MFFI prototype used in this experiment has a lower signal-to-noise ratio than DAS, individual oscillations can clearly be associated in a broad frequency range, thereby demonstrating that MFFI enables quantitative seismic wavefield measurements (Bowden et al., 2022).
Slide 48: The outstanding advantage of integrated fibre-optic sensing is its ability to overcome limitations of interrogation distance. In contrast to DAS, integrated sensors can measure deformation over thousands of kilometers, thus potentially crossing oceans. While DAS operates with phase delays of back-scattered pulses, integrated sensing exploits information in forward transmitted laser signals. The MFFI prototype, as a specific example of an integrated sensor, is capable of recording local and regional seismicity. Furthermore, it compares well to DAS recordings acquired along the same fibre line, thereby attesting to its ability to provide quantitative seismic wavefield measurements.
At first sight, the integration of strain along the fibre eliminates spatial resolution. In contrast to DAS, integrated sensing produces a single time series that cannot be directly associated to a certain position or some short interval along the fibre. It is therefore not immediately obvious that integrated sensors can be used for seismological tasks where spatial resolution is essential, e.g., the location of earthquakes or seismic tomography. In the following paragraphs we will see that integrated sensors do actually provide spatially distributed information, which can be extracted by a time-dependent analysis of the measurements.
Slides 49–51: Key to our analysis is a transformation of the equation that relates the deformation-induced phase change of transmitted laser signals to the integral of strain along the fibre. In fact, an integration by parts reveals that this can be rewritten as an integral over the product of local fibre curvature and the displacement of the fibre (Fichtner et al., 2022b).
We can illustrate the meaning of this equation with a small 2-D analytical example. It features a simple circular wave front incident on two different sine-shaped fibres. One of the fibres is shorter than the other but more strongly curved.
We first consider the longer fibre. Though the wave consists of only one wave front, the computed phase change time series is composed of two distinguishable wave packets, each with multiple oscillations. This multiplication of wavelets is caused by the various high-curvature segments of the fibre. As the wave hits a high-curvature segment, i.e., the extrema of the sine curve, it produces a recorded phase change at that point in time. Hence, the earlier of the two wave packets is produced by the superposition of wavelets from high-curvature segments that are closer to the source, whereas the second wave packet is produced by more distance high-curvature segments.
For the shorter but more strongly curved fibre we also observe two wave packets. Their amplitude is approximately the same as for the longer fibre because the shorter length is compensated by the stronger curvature, in accord with the equation that we have seen before.
Slides 52 – 55: The previous toy example already hints at a procedure for the extraction of space-resolved information. In fact, different oscillations in the phase change recording may be associated to different high-curvature segments of the fibre. Hence, the time variable in the recordings relates to the space variable along the fibre.
We can formalise this relation with the help of adjoint techniques, which can be used to calculate the partial derivatives of (seismic) observables with respect to material properties, e.g., the P-wave speed in the medium considered in our example (e.g., Tarantola, 1988; Tromp et al., 2005; Fichtner et al., 2006; Plessix, 2006).
First, we choose a time window in the early part of the first wave packet. The application of adjoint techniques provides a sensitivity distribution or sensitivity kernel that outlines the regions where the arrival time of the wavelet in that window is sensitive to P-wave structure in the 2-D Earth model. As expected, the sensitivity kernel links the source location to the nearest high-curvature segment along the fibre (Fichtner et al., 2022).
Moving on to later time windows, produces different sensitivity kernels, all of which link the source location to one or several high-curvature segments. In accord with the intuitive explanation above, the later-arriving phase change oscillations correspond to more distant high-curvature segments, and vice versa.
Slides 56 & 57: It follows that spatially distributed information can be extracted from integrated sensing measurements with the help of a time-dependent analysis of the recordings. This is possible because integrated sensing sensitivity is proportional to local fibre curvature, meaning that high-curvature segments of the fibre located at different distances from the source, produce distinguishable wavelets in the phase change recording at different times. A quantitative analysis that produces space-resolution can be implemented with the help of adjoint techniques that attach a sensitivity distribution to each selected time window of the recording. Though real-world applications of this concept still need to be realised, it provides a theoretical foundation for seismic source inversion and tomography based on integrated sensing data.
While the MFFI system has been specifically constructed for the purpose of environmental sensing, one may also consider the direct exploitation of optical signals used for telecommunication in a broad sense. In fact, any telecom munication signal transmitted in the form of an electromagnetic wave through an optical fibre is affected by fibre deformation. This concerns, explained above, the phase of these signals (e.g., Marra et al., 2018; Bogris et al., 2022,) but also their polarisation (e.g., Mecozzi et al., 2021). Hence, deformation sensing for various applications may piggyback on fibre-optic telecommunication.
Slides 59 – 61: An example of such a co-use is fibre-optic sensing by active phase noise cancellation (Noe et al., 2023). The concept rests on the dissemination of highly accurate frequency signals, a method that has been established in the last decade by national metrology institutes to enable state-of-the-art comparison and distribution of atomic clocks signals (Husmann et al., 2021). Encoded in nearly monochromatic laser light, these signals are polluted by deformation of the optical fibre through which they are transmitted. To ensure that precise frequencies can be received by the user, the noisy frequency needs to be corrected in real time by a noise cancellation system.
While the opto-electronic details of such a system are beyond the scope of this presentation, it can be explained with a well-known acoustic analogue: noise-cancelling headphones. Such headphones are equipped with microphones that record the undesirable ambient acoustic noise. Electronics inside the headphones compute anti-sound that loudspeakers emit into the headphones, thereby cancelling the incoming noise almost exactly. In metrological applications, an anti-frequency takes the place of the anti-sound, and this anti-frequency can be shown to be proportional to the integral of strain along the fibre.
Slides 62 – 64: We were able to test the system using a 123 km long fibre loop between the Swiss cities of Bern and Basel. Located in the laboratories of the Swiss Federal Institute of Metrology (METAS), the noise cancellation system recorded a magnitude 4.3 earthquake that occurred 10 September 2022 near the French city of Mulhouse. A spectral-element simulation of the wavefield (Afanasiev et al., 2019), illustrates how the seismic waves emitted by the earthquake propagate along the fibre, thereby producing a time-dependent anti-frequency recording.
The comparison of observed and calculated anti-frequencies in different seismic period bands reveals a close correspondence between the two, thereby raising the question if metrological noise cancellation may be used to solve quantitative seismological inference problems.
Slides 65 & 66: In fact, the anti-frequency time series can be used to estimate the moment tensor of the Mulhouse earthquake. As reference, we use the moment tensor solution of the Swiss Seismological Service (SED), obtained from recordings of the regional seismometer network. Performing a moment tensor inversion with the anti-frequency information provides a solution that is identical to the references to within their mutual error bars.
Slide 67: In summary, we have seen that phase noise cancellation, despite being designed for a different application, enables long-range deformation sensing. No interruption of metrological services are needed, and the additional effort is limited to storing a time series of anti-frequencies that would otherwise be discarded. Spectral-element simulations of the anti-frequencies match the observations nearly ‘wiggle-by-wiggle’, suggesting that it may be used for quantitative seismology. In fact, a moment tensor inversion confirms that earthquake radiation patterns may be constrained with the help of metrological phase noise cancellation. While being in its infancy, this research direction opens new opportunities for seismology in sparsely covered areas, e.g., the oceans and the polar regions.
We presented applications of DAS in cryosphere research and various developments in integrated fibre-optic sensing. While being promising, it is important to note limitations of these methods in order to understand their range of applicability and possibly define future research directions.
Optical fibres are one-dimensional structures. This trivial statement has far-reaching implications for seismic data acquisition because two-dimensional arrays that are sometimes easy to design with seismometers may be difficult to realise with fibre-optic cables. Seismometers can be deployed independently of each other, whereas DAS channels are inevitably connected to their neighbours. Hence, the survey design problem becomes more challenging but not unsolvable (Fichtner and Hofstede, 2023).
In contrast to seismometers, standard fibre-optic sensors only provide one-component measurements of strain or strain rate. As a consequence, data analysis techniques that require polarisation information cannot be employed. This issue may compromise even standard tasks such as the identification of P- and S-wave phases. The development of helically-wound fibres (e.g., Kuvshinov, 2016) overcomes this issue to some extent, but has so far not found widespread use, possibly due to the cost and weight of such cables.
One of the frequently cited advantages of fibre-optic sensors is their ability to record under water and possibly cover the oceans by co-using telecommunication cables. While promising at first sight, it may in practice be challenging to fully exploit this potential. Underwater fibre-optic cables are typically deployed roughly along straight lines, and most of them follow nearly identical trajectories; for economic and geologic reasons. Therefore, the coverage provided by existing telecommunication cables is unlikely to improve seismic data coverage very much.
Closely related is the issue of geometry-dependent measurement sensitivity in integrated fibre-optic sensing. While this effect may be harnessed to produce spatially resolved measurements, seismologists’ ability to actually control the geometry of telecommunication cables is very limited.
In contrast to fibre-optic cables deployed for specific seismological applications, the geometry and coupling of telecommunication cables is often poorly known. To avoid vandalism, telecommunication companies may not want to disclose the precise trajectory of their cables. Due to water currents and undocumented ship tracks, the position of underwater cables may not be known to within hundreds of metres.
One of the main conclusions may be, at this point already, that major steps forward in seismic data coverage will require the dedicated deployment of fibre-optic cables with favourable geometry, especially in the oceans and urban areas.
The PowerPoint presentation with added notes is available in the Supplement.
A link to the presentation that this lecture note is based on can be found at
https://www.koushare.com/live/details/25403
The authors gratefully acknowledge phenomenal support from Silixa throughout all stages of this experiment. Invaluable advice on the selection of a suitable cable was provided by Andrea Fasciati at Solifos AG. This work was partially funded by the Real-time Earthquake Risk Reduction for a Resilient Europe project (RISE) under the European Union’s Horizon 2020 research and innovation programme (Grant Agreement Number
The authors affirm that they have no financial and personal relationships with any individuals or organization that could have potentially influenced the work presented in this paper.
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