scholarly journals Ground motion response to an ML 4.3 earthquake using co-located distributed acoustic sensing and seismometer arrays

2018 ◽  
Vol 213 (3) ◽  
pp. 2020-2036 ◽  
Author(s):  
Herbert F Wang ◽  
Xiangfang Zeng ◽  
Douglas E Miller ◽  
Dante Fratta ◽  
Kurt L Feigl ◽  
...  
Keyword(s):  
Ground Motion ◽  
Acoustic Sensing ◽  
Motion Response ◽  
Distributed Acoustic Sensing

scholarly journals Corrigendum: Ground motion response to anML 4.3 earthquake using co-located distributed acoustic sensing and seismometer arrays

2018 ◽  
Vol 214 (1) ◽  
pp. 704-704
Author(s):  
Herbert F Wang ◽  
Xiangfang Zeng ◽  
Douglas E Miller ◽  
Dante Fratta ◽  
Kurt L Feigl ◽  
...  
Keyword(s):  
Ground Motion ◽  
Acoustic Sensing ◽  
Motion Response ◽  
Distributed Acoustic Sensing

Empirical Investigations of the Instrument Response for Distributed Acoustic Sensing (DAS) across 17 Octaves

2020 ◽  
Author(s):  
Patrick Paitz ◽  
Pascal Edme ◽  
Dominik Gräff ◽  
Fabian Walter ◽  
Joseph Doetsch ◽  
...  
Keyword(s):  
Ground Motion ◽  
Urban Areas ◽  
Waveform Inversion ◽  
Acoustic Sensing ◽  
Full Waveform ◽  
Environmental Properties ◽  
Instrument Response ◽  
Distributed Acoustic Sensing ◽  
Reference Measurements ◽  
Seismic Networks

ABSTRACT With the potential of high temporal and spatial sampling and the capability of utilizing existing fiber-optic infrastructure, distributed acoustic sensing (DAS) is in the process of revolutionizing geophysical ground-motion measurements, especially in remote and urban areas, where conventional seismic networks may be difficult to deploy. Yet, for DAS to become an established method, we must ensure that accurate amplitude and phase information can be obtained. Furthermore, as DAS is spreading into many different application domains, we need to understand the extent to which the instrument response depends on the local environmental properties. Based on recent DAS response research, we present a general workflow to empirically quantify the quality of DAS measurements based on the transfer function between true ground motion and observed DAS waveforms. With a variety of DAS data and reference measurements, we adapt existing instrument-response workflows typically in the frequency band from 0.01 to 10 Hz to different experiments, with signal frequencies ranging from 1/3000 to 60 Hz. These experiments include earthquake recordings in an underground rock laboratory, hydraulic injection experiments in granite, active seismics in agricultural soil, and icequake recordings in snow on a glacier. The results show that the average standard deviations of both amplitude and phase responses within the analyzed frequency ranges are in the order of 4 dB and 0.167π radians, respectively, among all experiments. Possible explanations for variations in the instrument responses include the violation of the assumption of constant phase velocities within the workflow due to dispersion and incorrect ground-motion observations from reference measurements. The results encourage further integration of DAS-based strain measurements into methods that exploit complete waveforms and not merely travel times, such as full-waveform inversion. Ultimately, our developments are intended to provide a quantitative assessment of site- and frequency-dependent DAS data that may help establish best practices for upcoming DAS surveys.

Near-field spectral analysis of data-integrative dynamic rupture earthquake simulations of the 1992 Landers earthquake

2020 ◽  
Author(s):  
Nico Schliwa ◽  
Alice-Agnes Gabriel
Keyword(s):  
Spectral Analysis ◽  
Ground Motion ◽  
Near Field ◽  
Slip Distribution ◽  
Corner Frequency ◽  
Dynamic Rupture ◽  
Geophysical Research ◽  
Acoustic Sensing ◽  
Distributed Acoustic Sensing ◽  
Large Earthquakes

<p>The rise of observations from Distributed Acoustic Sensing (e.g., Zhan 2020) and high-rate GNSS networks (e.g., Madariaga et al., 2019) highlight the potential of dense ground motion observations in the near-field of large earthquakes. Here, spectral analysis of >100,000 synthetic near-field strong motion waveforms (up to 2 Hz) is presented in terms of directivity, corner frequency, fall-off rate, moment estimates and static displacements.</p><p>The waveforms are generated in 3‐D large-scale dynamic rupture simulations which incorporate the interplay of complex fault geometry, topography, 3‐D rheology and viscoelastic attenuation (Wollherr et al., 2019). A preferred scenario accounts for off-fault deformation and reproduces a broad range of observations, including final slip distribution, shallow slip deficits, and spontaneous rupture termination and transfers between fault segments. We examine the effects of variations in modeling parameterization within a suite of scenarios including purely elastic setups and models neglecting viscoelastic attenuation. </p><p>First, near-field corner frequency mapping implementing a novel spectral seismological misfit criterion reveals rays of elevated corner frequencies radiating from each slipping fault at 45 degree to rupture forward direction. The azimuthal spectral variations are specifically dominant in the vertical components indicating we map rays of direct P-waves prevailing (Hanks, 1980). The spatial variation in corner frequencies carries information on co-seismic fault segmentation, slip distribution, focal mechanisms and stress drop. Second, spectral fall-off rates are variably inferred during picking the associated corner frequencies to identify the crossover from near-field to far-field spectral behaviour in dependence on distance and azimuth. Third, we determine static displacements with the help of near-field seismic spectra.</p><p>Our findings highlight the future potential of spectral analysis of spatially dense (low frequency) ground motion observations for inferring earthquake kinematics and understanding earthquake physics directly from near-field data; while synthetic studies are crucial to identify "what to look for" in the vast amount of data generated.</p><p><em>References:</em></p><p>Hanks, T.C., 1980. The corner frequency shift, earthquake source models and Q.</p><p>Madariaga, R., Ruiz, S., Rivera, E., Leyton, F. and Baez, J.C., 2019. Near-field spectra of large earthquakes. Pure and Applied Geophysics, 176(3), pp.983-1001.</p><p>Wollherr, S., Gabriel, A.-A. and Mai, P.M., 2019.  Landers 1992 “reloaded”: Integrative dynamic earthquake rupture modeling. Journal of Geophysical Research: Solid Earth, 124(7), pp.6666-6702.</p><p>Zhan, Z., 2020. Distributed Acoustic Sensing Turns Fiber‐Optic Cables into Sensitive Seismic Antennas. Seismological Research Letters, 91(1), pp.1-15.</p>

Combining Distributed Acoustic Sensing and Beamforming in a Volcanic Environment on Mount Meager, British Columbia.

2021 ◽  
Author(s):  
Sara Klaasen ◽  
Patrick Paitz ◽  
Jan Dettmer ◽  
Andreas Fichtner
Keyword(s):  
British Columbia ◽  
Power Distribution ◽  
High Frequency ◽  
Low Frequency ◽  
Volcanic Tremor ◽  
Extreme Environment ◽  
Volcanic Complex ◽  
Acoustic Sensing ◽  
Distributed Acoustic Sensing ◽  
Volcanic Environment

<p>We present one of the first applications of Distributed Acoustic Sensing (DAS) in a volcanic environment. The goals are twofold: First, we want to examine the feasibility of DAS in such a remote and extreme environment, and second, we search for active volcanic signals of Mount Meager in British Columbia (Canada). </p><p>The Mount Meager massif is an active volcanic complex that is estimated to have the largest geothermal potential in Canada and caused its largest recorded landslide in 2010. We installed a 3-km long fibre-optic cable at 2000 m elevation that crosses the ridge of Mount Meager and traverses the uppermost part of a glacier, yielding continuous measurements from 19 September to 17 October 2019.</p><p>We identify ~30 low-frequency (0.01-1 Hz) and 3000 high-frequency (5-45 Hz) events. The low-frequency events are not correlated with microseismic ocean or atmospheric noise sources and volcanic tremor remains a plausible origin. The frequency-power distribution of the high-frequency events indicates a natural origin, and beamforming on these events reveals distinct event clusters, predominantly in the direction of the main peaks of the volcanic complex. Numerical examples show that we can apply conventional beamforming to the data, and that the results are improved by taking the signal-to-noise ratio of individual channels into account.</p><p>The increased data quantity of DAS can outweigh the limitations due to the lower quality of individual channels in these hazardous and remote environments. We conclude that DAS is a promising tool in this setting that warrants further development.</p>

Capturing Glacier-Wide Cryoseismicity With Distributed Acoustic Sensing

2021 ◽  
Author(s):  
Fabian Walter ◽  
Patrick Paitz ◽  
Andreas Fichtner ◽  
Pascal Edme ◽  
Wojciech Gajek ◽  
...  
Keyword(s):  
Fiber Optic ◽  
Flow Line ◽  
Ground Deformation ◽  
Sensor Coverage ◽  
Mountain Glacier ◽  
Acoustic Sensing ◽  
Alpine Glacier ◽  
Glacier Ice ◽  
Distributed Acoustic Sensing ◽  
Ice Sheet Dynamics

<p>Over the past 1-2 decades, seismological measurements have provided new and unique insights into glacier and ice sheet dynamics. At the same time, sensor coverage is typically limited in harsh glacial environments with littile or no access. Turning kilometer-long fiber optic cables placed on the Earth’s surface into thousands of seismic sensors, Distributed Acoustic Sensing (DAS) may overcome the limitation of sensor coverage in the cryosphere.</p><p>First DAS applications on the Greenland and Antarctic ice sheets and on Alpine glacier ice have highlighted the technique’s superiority. Signals of natural and man-made seismic sources can be resolved with an unrivaled level of detail. This offers glaciologists new perspectives to interpret their seismograms in terms of ice structure, basal boundary conditions and source locations. However, previous studies employed only relatively small network scales with a point-like borehole deployment or < 1 km cable aperture at the ice surface.</p><p>Here we present a DAS installation, which aims to cover the majority of an Alpine glacier catchment: For one month in summer 2020 we deployed a 9 km long fiber optic cable on Rhonegletscher, Switzerland, and gathered continuous DAS data. The cable followed the glacier’s central flow line starting in the lowest kilometer of the ablation zone and extending well into the accumulation area. Even for a relatively small mountain glacier such as Rhonegletscher, cable deployment was a considerable logistical challenge. However, initial data analysis illustrates the benefit compared to conventional cryoseismological instrumentation: DAS measurements capture ground deformation over many octaves, including typical high-frequency englacial sources (10s to 100s of Hz) related to crevasse formation and basal sliding as well as long period signals (10s to 100s of seconds) of ice deformation. Depending on the presence of a snow cover, DAS records contain strong environmental noise (wind, meltwater flow, precipitation) and thus exhibit lower signal-to-noise ratios compared to conventional on-ice seismic installations. This is nevertheless outweighed by the advantage of monitoring ground unrest and ice deformation of nearly an entire glacier. We present a first compilation of signal and noise records and discuss future directions to leverage DAS data sets in glaciological research.</p><p> </p><p> </p><p> </p>

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