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.

scholarly journals Distributed Acoustic Sensing from mHz to kHz: Empirical Investigations of DAS Instrument Response

2020 ◽  
Author(s):  
Patrick Paitz ◽  
Pascal Edme ◽  
Cédric Schmelzbach ◽  
Joesph Doetsch ◽  
Dominik Gräff ◽  
...  
Keyword(s):  
Urban Areas ◽  
Waveform Inversion ◽  
Geophysical Methods ◽  
Low Frequency ◽  
Acoustic Sensing ◽  
Temporal Sampling ◽  
Cable Properties ◽  
Instrument Response ◽  
Distributed Acoustic Sensing ◽  
Initial Results

<p>With the upside of high spatial and temporal sampling even in remote or urban areas using existing fiber-optic infrastructure, Distributed Acoustic Sensing (DAS) is in the process of revolutionising the way we look at seismological data acquisition. However, recent publications show variations of the quality of DAS measurements along a single cable. In addition to site- and orientation effects, data quality is strongly affected by the transfer function between the deforming medium and the fiber, which in turn depends on the fiber-ground coupling and the cable properties. Analyses of the DAS instrument response functions in a limited part of the seismological frequency band are typically based on comparisons with well-coupled conventional seismometers for which the instrument response is sufficiently well known to be removed from the signal.</p><p>In this study, we extend the common narrow-band analyses to DAS response analyses covering a frequency range of five orders of magnitude ranging from ~4000 s period to frequencies up to ~100 Hz. This is based on a series of experiments in Switzerland, including (1) active controlled-source experiments with co-located seismometers and geophones, (2) low-frequency strain induced by hydraulic injection in a borehole with co-located Fiber-Bragg-Grating (FBG) strain-meters, and (3) local to teleseismic ice- and earthquake recordings with  co-located broadband stations.</p><p>Initial results show a site-unspecific, approximately flat instrument response for all experiments.</p><p>The initial results suggest that the amplitude and phase information of DAS recordings are sufficient for conventional geophysical methods such as event localisation, full-waveform inversion, ambient noise tomography and even event magnitude estimation. Despite the promising initial results, further engagement by the DAS community is required to evaluate the DAS performance and repeatability among different interrogation units and study sites.</p>

Distributed Acoustic Sensing Using Dark Fiber for Array Detection of Regional Earthquakes

2021 ◽  
Author(s):  
Avinash Nayak ◽  
Jonathan Ajo-Franklin ◽  
Keyword(s):  
Urban Areas ◽  
Geothermal Field ◽  
Seismic Events ◽  
Broadband Seismometer ◽  
Acoustic Sensing ◽  
Array Detection ◽  
Distributed Acoustic Sensing ◽  
Back Azimuth ◽  
Ubiquitous Presence

Abstract The intrinsic array nature of distributed acoustic sensing (DAS) makes it suitable for applying beamforming techniques commonly used in traditional seismometer arrays for enhancing weak and coherent seismic phases from distant seismic events. We test the capacity of a dark-fiber DAS array in the Sacramento basin, northern California, to detect small earthquakes at The Geysers geothermal field, at a distance of ∼100  km from the DAS array, using beamforming. We use a slowness range appropriate for ∼0.5–1.0  Hz surface waves that are well recorded by the DAS array. To take advantage of the large aperture, we divide the ∼20  km DAS cable into eight subarrays of aperture ∼1.5–2.0  km each, and apply beamforming independently to each subarray using phase-weighted stacking. The presence of subarrays of different orientations provides some sensitivity to back azimuth. We apply a short-term average/long-term average detector to the beam at each subarray. Simultaneous detections over multiple subarrays, evaluated using a voting scheme, are inferred to be caused by the same earthquake, whereas false detections caused by anthropogenic noise are expected to be localized to one or two subarrays. Analyzing 45 days of continuous DAS data, we were able to detect all earthquakes with M≥2.4, while missing most of the smaller magnitude earthquakes, with no false detections due to seismic noise. In comparison, a single broadband seismometer co-located with the DAS array was unable to detect any earthquake of M<2.4, many of which were detected successfully by the DAS array. The seismometer also experienced a large number of false detections caused by spatially localized noise. We demonstrate that DAS has significant potential for local and regional detection of small seismic events using beamforming. The ubiquitous presence of dark fiber provides opportunities to extend remote earthquake monitoring to sparsely instrumented and urban areas.

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>

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 Reciprocity-gap misfit functional for Distributed Acoustic Sensing, combining data from passive and active sources

Geophysics ◽  
2020 ◽  
pp. 1-59 ◽  
Author(s):  
Florian Faucher ◽  
Maarten V. de Hoop ◽  
Otmar Scherzer
Keyword(s):  
Quantitative Imaging ◽  
A Priori ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Inversion Method ◽  
Acoustic Sensing ◽  
Use Of Data ◽  
Combining Data ◽  
Distributed Acoustic Sensing ◽  
Priori Information

Quantitative imaging of sub-surface Earth’s properties in elastic media is performed from Distributed Acoustic Sensing data. A new misfit functional based upon the reciprocity-gap is designed, taking cross-correlations of displacement and strain, and these products further associate an observation with a simulation. In comparison with other misfit functionals, this one has the advantage to only require little a-priori information on the exciting sources. In particular, the misfit criterion enables the use of data from regional earthquakes (teleseismic events can be included as well), followed by exploration data to perform a multi-resolution reconstruction. The data from regional earthquakes contain the low-frequency content which is missing in the exploration ones, allowing for the recovery of the long spatial wavelength, even with very few sources. These data are used to build prior models for the subsequent reconstruction from the higher-frequency exploration data. This gives the elastic Full Reciprocity-gap Waveform Inversion method, and we demonstrate its performance with a pilot experiment for elastic isotropic reconstruction.

Distributed Acoustic Sensing Turns Fiber‐Optic Cables into Sensitive Seismic Antennas

2019 ◽  
Vol 91 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Zhongwen Zhan
Keyword(s):  
Seismic Waves ◽  
Fiber Optic ◽  
Glass Fibers ◽  
Ocean Bottom ◽  
Thin Glass ◽  
Acoustic Sensing ◽  
Wide Range ◽  
Solar System Bodies ◽  
Distributed Acoustic Sensing ◽  
Seismic Networks

Abstract Distributed acoustic sensing (DAS) is a new, relatively inexpensive technology that is rapidly demonstrating its promise for recording earthquake waves and other seismic signals in a wide range of research and public safety arenas. It should significantly augment present seismic networks. For several important applications, it should be superior. It employs ordinary fiber‐optic cables, but not as channels for data among separate sophisticated instruments. With DAS, the hair‐thin glass fibers themselves are the sensors. Internal natural flaws serve as seismic strainmeters, kinds of seismic detector. Unused or dark fibers are common in fiber cables widespread around the globe, or in dedicated cables designed for special application, are appropriate for DAS. They can sample passing seismic waves at locations every few meters or closer along paths stretching for tens of kilometers. DAS arrays should enrich the three major areas of local and regional seismology: earthquake monitoring, imaging of faults and many other geologic formations, and hazard assessment. Recent laboratory and field results from DAS tests underscore its broad bandwidth and high‐waveform fidelity. Thus, while still in its infancy, DAS already has shown itself as the working heart—or perhaps ear drums—of a valuable new seismic listening tool. My colleagues and I expect rapid growth of applications. We further expect it to spread into such frontiers as ocean‐bottom seismology, glacial and related cryoseismology, and seismology on other solar system bodies.

Distributed Acoustic Sensing Using a Large-Volume Airgun Source and Internet Fiber in an Urban Area

2021 ◽  
Author(s):  
Zhenghong Song ◽  
Xiangfang Zeng ◽  
Baoshan Wang ◽  
Jun Yang ◽  
Xiaobin Li ◽  
...  
Keyword(s):  
Urban Area ◽  
Urban Areas ◽  
Signal To Noise Ratio ◽  
Gauge Length ◽  
P Wave ◽  
S Wave ◽  
Near Surface ◽  
Acoustic Sensing ◽  
Wave Signal ◽  
Distributed Acoustic Sensing

Abstract Seismological methods have been widely used to construct subsurface images in urban areas, for both seismological and engineering purposes. However, it remains a challenge to continuously operate a dense array in cities for high-resolution 4D imaging. In this study, we utilized distributed acoustic sensing (DAS) and a 5.2 km long, L-shaped, telecom, fiber-optic cable to record the wavefield from a highly repeatable airgun source located 7–10 km away. No P-wave signal was observed, but the S-wave signal emerged clearly on the shot-stacked traces, and the arrivals were consistent with collocated geophone traces. Because the signal quality is significantly affected by cable coupling and local noise, three methods can be employed to improve signal-to-noise ratio: (1) stacking contiguous, colinear channels to increase effective gauge length, (2) connecting multiple fibers within a single conduit and stacking collocated channels, and (3) using engineered fiber. In conclusion, the combination of DAS, using internet fiber and an airgun source with proven efficient signal enhancement methods, can provide frequent snapshots of the near surface across an urban area.

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