High-Resolution Glacier Bed Imaging with Passive Seismology Using a Novel Dense Seismic Array at Isunnguata Sermia, West Greenland

SUMMARY A 2-D orthogonal distributed acoustic sensing (DAS) array designed for seismic experiments was buried horizontally beneath the Kafadar Commons Geophysical Laboratory on the Colorado School of Mines campus at Golden, Colorado. The DAS system using straight fibre-optic cables is a cost-efficient technology that enables dense seismic array deployment for long-term seismic monitoring, favouring both earthquake-based and ambient-noise-based surface wave analysis for subsurface characterization. In our study, the horizontally orthogonal DAS array records ambient noise data for a period of about two months from November 2018 to January 2019. During this time, the array also detected seismic signals from an ML3.6 earthquake at Glenwood Springs, Colorado, which exhibit opposite signal polarities in the orthogonal DAS section recordings. We derive the transformation matrix for DAS strain measurements in horizontally orthogonal cables to retrieve both Rayleigh and Love wave dispersion information from the single-component DAS signals using the 2-D multichannel analysis of surface waves method. In addition, ambient noise interferometry is applied to long-term DAS noise recordings. Our theoretical derivation demonstrates that Rayleigh and Love wave Green's functions are coupled in the noise cross-correlation functions (NCFs) of DAS receiver pairs. Stacking NCFs over the horizontally orthogonal DAS array can constructively recover the radial Rayleigh wave component but destructively suppress the Love wave component. The multimodal Monte Carlo inversion of the earthquake-based Rayleigh wave and Love wave dispersion measurements and the noise-based Rayleigh wave measurement reveals a 1-D layered structure that agrees qualitatively with geological surveys of the site. Our study demonstrates that although straight fibre-optic cables lack broadside sensitivity, using appropriate DAS array configuration and seismic array methods can extend the seismic acquisition ability of DAS and enable its application to a broad range of scenarios.

<p><span><span>Measurements of the seismic properties of Antarctic ice streams are critical for constraining glacier dynamics and future sea-level rise contributions. In 2020, passive seismic data were acquired at the Rutford Ice Stream, West Antarctica, with the aim of imaging the near-surface firn layer. A DAS (distributed acoustic sensing) interrogator and 1 km of optic fibre were supplemented by 3-component geophones. Taking advantage of transient seismic energy from a petrol generator and seismicity near the ice stream shear margin (10s of km away from the DAS array), which dominated the ambient seismic noise field,  we retrieve Rayleigh wave signals from 3 to 50 Hz. The extracted dispersion curve for a linear fibre array shows excellent agreement with an active seismic surface wave survey (Multichannel Analysis of Surface Waves) but with lower frequency content. We invert the dispersion curves for a 1D S-wave velocity profile through the firn layer, which shows good agreement with the previously acquired seismic refraction survey. Using a triangular-array geometry we repeat the procedure and find no evidence of seismic anisotropy at our study site. Our study presents challenges and solutions for processing noisy but densely sampled DAS data, for noise interferometry and imaging.</span></span><span><span> </span></span></p>

Ambient-noise-based seismic monitoring of the near surface often has limited spatiotemporal resolutions because dense seismic arrays are rarely sufficiently affordable for such applications. In recent years, however, distributed acoustic sensing (DAS) techniques have emerged to transform telecommunication fiber-optic cables into dense seismic arrays that are cost effective. With DAS enabling both high sensor counts (“large N”) and long-term operations (“large T”), time-lapse imaging of shear-wave velocity (VS) structures is now possible by combining ambient noise interferometry and multichannel analysis of surface waves (MASW). Here we report the first end-to-end study of time-lapse VS imaging that uses traffic noise continuously recorded on linear DAS arrays over a three-week period. Our results illustrate that for the top 20 meters the VS models that is well constrained by the data, we obtain time-lapse repeatability of about 2% in the model domain—a threshold that is low enough for observing subtle near-surface changes such as water content variations and permafrost alteration. This study demonstrates the efficacy of near-surface seismic monitoring using DAS-recorded ambient noise.

Summary In recent years, Distributed Acoustic Sensing (DAS) has found widespread applications in seismic imaging and monitoring at different scales. Due to inherent limitations in spatial resolution and signal-to-noise ratio at high frequencies, data acquisition with DAS is less commonly used in seismic exploration of the shallowest part (< 50 m) of the surface. We conducted a field experiment to compare the responses of six different buried DAS cables and conventional 14 Hz omnidirectional surface geophones. Our survey layout focuses on short offsets (< 50 m) and typical near-surface seismic sources (sledge hammer, shot gun). The directional sensitivity of the DAS cables prohibits the registration of steeply incident refracted waves, while diving waves and wide-angle reflections with oblique incidence as well as low-frequency surface waves can be recorded. The inherent cable noise partly overlaps with the frequency band of interest for shallow seismic imaging applications. The achievable geometrical accuracy of a DAS acquisition poses limitations when small station spacings are required. Overall, body-wave imaging via classic refraction or reflection methods faces significant challenges when compared to conventional geophone acquisition. Dispersion analysis of surface waves with advanced methods suggest that DAS data may find useful application for monitoring of the shallow subsurface.

Distributed acoustic sensing (DAS) is an emerging technology increasingly employed to monitor changes of formation properties, production noise and micro-seismic activity, and as an array of sensors in active seismic surveys. The data recorded with the DAS systems are very rich; some features observed in DAS records are often not well understood, and thus are underutilised. A systematic analysis of the data recorded passively with a DAS system in a 900-m deep well over a period of 12 weeks in the Perth metropolitan area, Western Australia, reveals the presence of several types of ambient energy in the subsurface, such as earthquakes, ocean swell and urban noise. In particular, over 85 days of the experiment, the analysis detected sixteen earthquakes, with epicentres ranging from 126 km to 900 km (for the local events) and from 2300 km to 6400 km (for the remote events). Signals with frequencies below 0.9 Hz are dominated by the oceanic swell. The recorded urban noise includes mine blasting, machinery and traffic. The experiment shows the ability of DAS to detect these events and as such is potentially useful for subsurface characterisation and monitoring.

Distributed acoustic sensing (DAS) is an emerging technology gaining acceptance in a variety of seismological applications. We systematically analyze the adaptability and usefulness of horizontal DAS deployments for near-surface geophysical applications, such as surface wave inversion, diving wave tomography, and passive subsurface source location. We find that, in accordance with previous studies, DAS data are generally similar to traditional sensors and can be successfully used independently. Nonetheless, DAS data suffer from inherent limitations due to the design of the optical measurement system. Among others, we identify the gauge length, measurement directivity, and saturation at near offsets as the primary limiting factors. When operating in low-velocity environments and a standard 10 m gauge length, surface wave analysis may be constrained to the usage of low frequencies due to the wavenumber filtering effect of the gauge length. The measurement directivity generally prohibits applications that are based on upgoing P-wave energy, such as near-offset diving wave tomography. In addition, saturation at near offsets prevents reliable diving wave traveltime picking. As a consequence of these limitations, the ultrashallow resolution achievable with DAS data is poor. Source directivity also strongly limits passive source location resolution. Whereas some of the limitations can be alleviated through an optimal choice of optical parameters at the interrogator level, we mostly rely on adapted field acquisition and data processing workflows that use the undisturbed portion of the recorded signal. Eventually, the spatiotemporal resolution and relative ease of long-term deployments turn DAS into a worthwhile option for monitoring and time-lapse scenarios, or when operating in urban environments over existing infrastructure.

With extensive development of urban underground space, ground collapses occasionally occur, resulting in property damage, injuries, or fatalities. Therefore, establishing an effective ground monitoring and collapse prevention system is necessary for reducing collapsing risk. Distributed Acoustic Sensing (DAS) technology has great potential for ground collapse monitoring around rail system for capacity of long-distance high-density monitoring and immunity to electromagnetic interference (EMI). In this study, experimental investigations were conducted using a high-performance DAS interrogator integrated with a 4 km-long distributed optical fiber to record background ambient noise inside a subway tunnel. Noise2Noise (N2N) unsupervised denoising model was employed to preprocess the DAS data across different time spans, thereby enhancing the signal-to-noise ratio (SNR). Additionally, noise tomography method in terms of passive multichannel analysis of surface waves (MASW) algorithm was utilized to extract the surface waves and calculate the dispersion curves containing soil layer information Stacking methods, including Phase-Weighted Stacks (PWS) and Generalized Average of Signals (GAS), were applied to further improve the SNR of the dispersion curves. Ultimately, a 2D S-wave velocity model to 45m depth was constructed, revealing low-velocity soil defects such as hollow and settlement. The result demonstrates that integrating DAS with tomographic imaging using urban ambient noise can provide a reliable basis for preventing ground collapse hazards.

Accurate measurement of liquid flow velocity is crucial for pipeline management in the petroleum industry. Traditional flowmeters, such as ultrasonic, electromagnetic, and pressure-based devices, provide only point measurements and often require intrusive installation. Distributed Acoustic Sensing (DAS) offers a non-intrusive alternative by converting optical fibers into continuous acoustic sensors with meter-scale resolution. In this study, a High-Definition DAS system was applied in a laboratory flow loop to monitor single-phase liquid flow. The recorded signals were analyzed in both time and frequency domains. Results showed that the pump operating frequency dominated the spectral energy, accompanied by dispersive features. Power spectral density (PSD) increased linearly with flow rate, while Doppler-induced frequency shifts in the dominant component enabled velocity prediction. A regression model achieved a high coefficient of determination (R2 = 0.9928), confirming the strong predictive capability. These findings highlight DAS as a reliable and scalable solution for non-intrusive liquid flow monitoring in pipelines.

Firn densification profiles are an important parameter for ice‐sheet mass balance and palaeoclimate studies. One conventional method of investigating firn profiles is using seismic refraction surveys, but these are difficult to upscale to large‐area measurements. Distributed acoustic sensing (DAS) presents an opportunity for large‐scale seismic measurements of firn with dense spatial sampling and easy deployment, especially when seismic noise is used. We study the feasibility of seismic noise interferometry (SI) on DAS data for characterizing the firn layer at the Rutford Ice Stream, West Antarctica. Dominant seismic energy appears to come from anthropogenic noise and shear‐margin crevasses. The DAS cross‐correlation interferometry yields noisy Rayleigh wave signals. To overcome this, we present two strategies for cross‐correlations: (a) hybrid instruments—correlating a geophone with DAS, and (b) stacking of selected cross‐correlation panels picked in the tau‐p domain. These approaches are validated with results derived from an active survey. Using the retrieved Rayleigh wave dispersion curve, we inverted for a high‐resolution 1D S‐wave velocity profile down to a depth of 100 m. The profile shows a “kink” (velocity gradient inflection) at ∼12 m depth, resulting from a change of compaction mechanism. A triangular DAS array is used to investigate directional variation in velocity, which shows no evident variations thus suggesting a lack of azimuthal anisotropy in the firn. Our results demonstrate the potential of using DAS and SI to image the near‐surface and present a new approach to derive S‐velocity profiles from surface wave inversion in firn studies.

Distributed Acoustic Sensing (DAS) has become a powerful technique for high-resolution, continuous monitoring of near- and subsurface earth phenomena, with increasing applications in geohazards, seismology, and industry applications such as CO₂ storage monitoring. However, the sensitivity of DAS measurements to atmospheric forcing, particularly during extreme weather events, remains poorly understood. In this study, we investigate the response of a permanent, 1.2 km long straight fibre-optic array installed at the Svelvik CO₂ Field Laboratory (Norway), to intense wind conditions associated with the Amy Storm, which hit Norway from October 3-6, 2025. As part of efforts to understand passive methods to monitor CO2 migration in the subsurface, an Alcatel Submarine Networks (ASN) DAS system continuously recorded strain-rate data along a buried fibre that includes both near surface-installed sections and borehole down- and up-going segments reaching depths of approximately 100 m. The near-surface sections were installed inside protective pipes and were therefore not directly coupled to the surrounding ground. To characterise wind-induced seismic signatures, we analyse downsampled recordings using band-limited root-mean-square (RMS) amplitudes and spectral methods across three frequency ranges (0.1–1 Hz, 1–3 Hz, and 3–10 Hz) and time averages over 1 hr intervals. Time–frequency characteristics are examined using group-averaged spectrograms, and a Spectral Energy Index (SEI) is derived by integrating power spectral density within each frequency band. These seismic metrics are compared with near located meteorological observations, including mean wind speed, maximum mean wind speed, and maximum wind gusts. The results reveal a pronounced increase in DAS energy coincident with the maximum speed gusts of storm Amy, with the strongest responses observed at frequencies below 3 Hz. Correlation and lag analyses show that seismic energy variations are closely associated with periods of enhanced wind activity, particularly wind gusts, indicating a strong coupling between transient atmospheric forcing and ground vibrations. Importantly, the response differs significantly between surface and depth segments of the fibre. Surface-installed channels exhibit broadband amplitude increases correlated with direct wind–ground interaction, while depth channels display coherent low-frequency spectral patterns, suggesting excitation by wind-generated surface waves or distant secondary sources (e.g., waves from neighbouring fjord) rather than direct aerodynamic loading. These findings demonstrate that DAS arrays deployed at wells (abandoned or active) are sensitive to extreme meteorological forcing, which can imprint distinct and depth-dependent seismic signatures. Quantifying and distinguishing wind-induced signals is therefore critical for the robust interpretation of DAS data in long-term passive monitoring applications, particularly when subtle subsurface signals related to CO₂ injection, migration, or leakage must be detected in the presence of strong environmental noise. At the same time, this sensitivity highlights an additional benefit of such fibre-optic installations: DAS infrastructure deployed in future abandoned wells in the context of Oil & Gas industry and their reutilization for CO2 capture and storage, can also provide valuable information for national seismic and environmental monitoring networks, extending their utility beyond site-specific applications.

SUMMARY Recent developments of distributed acoustic sensing (DAS) techniques and rotational seismometers enable us to record strain and rotational seismograms. This prompts us to adapt the methods used for traditional translational seismograms to strain and rotational seismograms. Recently, we extended the formulation of the spatial autocorrelation (SPAC) method to strain, rotation and tilt records. According to seismic interferometry for translation seismograms, cross correlations have clear connections to Green's functions under the isotropy and equipartition of noise wavefields. In this study, we clarify similar connections for strain and rotation seismograms. Because we extend the formulation in the frequency domain, we actually study the connection between the cross-spectral matrix of strain and rotation at two receivers and the Green's tensor. First, we provide a proof under a general framework by simply extending the proof for translation to that for strain and rotation. The proof shows the following results: (1) The cross-spectral matrix of (i, j)-component strains at two receivers is found to be proportional to the strain Green's tensor at one receiver for the sum of (i, j)- and (j, i)-components of the moment tensor source at the other receiver. (2) The cross-spectral matrix of (i, j)-component rotations at two receivers is found to be proportional to the rotation Green's tensor at one receiver for the difference of (i, j)- and (j, i)-components of the moment tensor source at the other receiver. Necessary assumptions for the proof are the isotropy and equipartition of the wavefield. We then check this proof with specific calculations for surface waves observed on the free surface. The proof is confirmed for the isotropic incidence of random-phase surface waves with a specific ratio between Rayleigh and Love wave energies. Seismic interferometry for strain and rotation was already studied. However, the connection of cross correlations to the Green's function for strain and rotation seismograms is discovered by this study for the first time. A specific proof for body waves that is assured by the general proof will be our next study.

Greenland is particularly vulnerable to ongoing anthropogenic climate change and observational data document recent rapid mass loss of many of the Greenland Ice Sheet (GIS) glaciers. Mass loss of the GIS represents a major contributor to global sea level rise, but uncertainties in future projections are large. A recent acceleration in mass loss has been observed, with 2012 and 2018/19 record years documented by direct observations. However, estimates of melt variability and glacier runoff remain uncertain before the satellite era and the influence on surface ocean waters is unclear. In general, available observational records from high latitudes are sparse and short. Models require high-resolution data of past variability to resolve how fast the GIS reacts to warming.Past climate can be reconstructed from natural proxy archives. In high latitudes, however, most proxy time series utilised to date come from indirect land-based proxies. Calcified coralline algae are important shallow-marine calcifiers that grow attached to the seafloor and have emerged as subannual-resolution climate recorders for the extratropics. By analyzing long-lived coralline algae from Disko Bay, West-Greenland, in close proximity to Jakobshavn Glacier, we address this data gap. Jakobshavn Glacier is one of the largest glaciers in Greenland and the single largest source of mass loss from the GIS over the last 20 years. Sclerochronological analysis and ultra-high-resolution laser ablation ICP-MS data from calcified coralline algae (Clathromorphum compactum) provide seasonally-resolved records that capture the impact of surface temperature warming and glacier runoff on coastal Arctic environments. Algal Ba/Ca ratios track past glacier-derived meltwater input to the ocean surface layer and we report an unprecedented nonlinear increase in Jakobshavn glacier runoff into Disko Bay in the last 20 years. Our chronology from southern Disko Bay sites shows a distinct increasing trend from the early 2000s, recording the acceleration of GIS glacier mass loss and matching recent years of record amounts of ice loss in satellite data. The rate of increase in Ba/Ca (a runoff proxy) is unprecedented over at least the last 100 years, highlighting the rising influence of global warming on Arctic coastal ecosystems. The new algal chronology provides a long-term perspective on high-resolution variability in Jakobshavn Glacier runoff into Disko Bay, extending before observations, and confirming model data.

Distributed Acoustic Sensing (DAS) technology enables continuous monitoring of acoustic vibrations along fiber-optic cables, providing high-resolution spatial and temporal data for marine acoustic applications. This study investigates DAS’s capability for analyzing underwater radiated noise from ships, leveraging 4 days of DAS data collected in November 2021 using two cables from the Ocean Observatories Initiative Regional Cabled Array, extending offshore central Oregon. Data were collected using OptaSense and Silixa interrogators with gauge lengths of either 30 or 50 m and sampling rates ranging from 200 to 1000 Hz. Ship signals were identified in DAS data using Automatic Identification System (AIS) information and analyzed across different fibers and interrogators to assess system performance. Our results demonstrate that large ships are clearly visible in the DAS data within the 10–90 Hz frequency band at ranges exceeding 10 km. Low-frequency filtering extends the detection range, enhancing the ability to monitor ship signals. DAS-derived ship signals are compared with hydrophone data and a propagation model to assess the DAS system's detection capabilities. This study highlights the potential of DAS technology for maritime acoustic monitoring and its complementary role to traditional hydrophone systems in capturing underwater radiated noise by ships.

SUMMARY Recent developments in sensor technology have allowed for the low-cost deployment of dense seismic arrays which continuously record the seismic ambient noise field. Generally, the extraction of body waves from the seismic ambient noise field is more challenging than for surface waves, due to the dominant amplitude of the latter. In this study, we work with data from a dense seismic array deployment in the Dehdasht area, southwestern Iran. We show that by using the polarization properties of seismic waves, we can simultaneously retrieve both high frequency body waves and surface waves from the cross-correlated noise field. As a by-product of this study, we also observe high energy spurious artefacts, particularly those associated with the direct P-phases. Numerical simulations show that these artefacts are a consequence of an uneven distribution of noise sources, and are difficult to suppress during the simultaneous retrieval of body and surface waves.

In situ observations under typhoon conditions are sparse and limited. Distributed acoustic sensing (DAS) is an emerging technology that uses submarine optical-fiber (OF) cables to monitor the sea state. Here, we present DAS-based ocean current observations when a super typhoon passed overhead. The microseismic noise induced by ocean surface gravity waves (OSGWs) during Typhoon Muifa (2022) is observed in the ~0.08–0.38 Hz frequency band, with high-frequency (>0.3 Hz) component being tidally modulated. The OSGW propagation along the entire cable is successfully revealed via frequency–wavenumber analysis. Further, a method based on the current-induced Doppler shifts of DAS-recorded OSGW dispersions is proposed to calculate both speeds and directions of horizontal ocean currents. The measured current is consistent with the tidally induced sea-level fluctuations and sea-surface winds observed at a nearby ocean buoy. These observations demonstrate the feasibility of monitoring the ocean current under typhoon conditions using DAS-instrumented cables.