Sub‐kilometer correlation between near‐surface structure and ground motion measured with distributed acoustic sensing

Author(s):  
Yan Yang ◽  
James W. Atterholt ◽  
Zhichao Shen ◽  
Jack B. Muir ◽  
Ethan F. Williams ◽  
...  
Author(s):  
Patrick Paitz ◽  
Pascal Edme ◽  
Dominik Gräff ◽  
Fabian Walter ◽  
Joseph Doetsch ◽  
...  

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.


2021 ◽  
Author(s):  
Nicola Piana Agostinetti ◽  
Alberto Villa ◽  
Gilberto Saccorotti

Abstract. We use PoroTOMO experimental data to compare the performance of Distributed Acoustic Sensing (DAS) and geophone data in executing standard exploration and monitoring activities. The PoroTOMO experiment consists of two "seismic systems": (a) a 8.6 km long optical fibre cable deployed across the Brady geothermal field and covering an area of 1.5 x 0.5 km with 100 m long segments, and (b) an array of 238 co-located geophones with an average spacing of 60 m. The PoroTOMO experiment recorded continuous seismic data between March 10th and March 25th 2016. During such period, a ML 4.3 regional event occurred in the southwest, about 150 km away from the geothermal field, together with several microseismic local events related to the geothermal activity. The seismic waves generated from such seismic events have been used as input data in this study. For the exploration tasks, we compare the propagation of the ML 4.3 event across the geothermal field in both seismic systems in term of relative time-delay, for a number of configurations and segments. Defined the propagation, we analyse and compare the amplitude and the signal-to-noise ratio (SNR) of the P-wave in the two systems at high resolution. For testing the potential in monitoring local seismicity, we first perform an analysis of the geophone data for locating a microseismic event, based on expert opinion. Then, we a adopt different workflow for the automatic location of the same microseismic event using DAS data. For testing the potential in monitoring distant event, data from the regional earthquake are used for retrieving both the propagation direction and apparent velocity of the wavefield, using a standard plane-wave-fitting approach. Our results indicate that: (1) at a local scale, the seismic P-waves propagation and their characteristics (i.e. SNR and amplitude) along a single cable segment are robustly consistent with recordings from co-located geophones (delay-times δt ∼ 0.3 over 400 m for both seismic systems) ; (2) the interpretation of seismic wave propagation across multiple separated segments is less clear, due to the heavy contamination of scattering sources and local velocity heterogeneities; nonetheless, results from the plane-wave fitting still indicate the possibility for a consistent detection and location of the event; (3) at high-resolution (10 m), large amplitude variations along the fibre cable seem to robustly correlate with near surface geology; (4) automatic monitoring of microseismicity can be performed with DAS recordings with results comparable to manual analysis of geophone recordings (i.e. maximum horizontal error on event location around 70 m for both geophones and DAS data) ; and (5) DAS data pre-conditioning (e.g., temporal sub-sampling and channel-stacking) and dedicated processing techniques are strictly necessary for making any real-time monitoring procedure feasible and trustable.


2020 ◽  
Author(s):  
Nico Schliwa ◽  
Alice-Agnes Gabriel

<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>


Geophysics ◽  
2021 ◽  
pp. 1-69
Author(s):  
Yarin Abukrat ◽  
Moshe Reshef

During the last decade, fiber-optic-based distributed acoustic sensing (DAS) has emerged as an affordable, easy-to-deploy, reliable, and non-invasive technique for high-resolution seismic sensing. We show that fiber deployments dedicated to near-surface seismic applications, commonly employed for the detection and localization of voids, can be used effectively with conventional processing techniques. We tested a variety of small-size sources in different geological environments. These sources, operated on and below the surface, were recorded by horizontal and vertical DAS arrays. Results and comparisons to data acquired by vertical-component geophones demonstrate that DAS may be sufficient for acquiring near-surface seismic data. Furthermore, we tried to address the issue of directional sensing by DAS arrays and use it to solve the problem of wave-mode separation. Records acquired by a unique acquisition setup suggest that one can use the nature of DAS systems as uniaxial strainmeters to record separated wave modes. Lastly, we applied two seismic methods on DAS data acquired at a test site: multi-channel analysis of surface waves (MASW) and shallow diffraction imaging. These methods allowed us to determine the feasibility of using DAS systems for imaging shallow subsurface voids. MASW was used to uncover anomalies in S-wave velocity, whereas shallow diffraction imaging was applied to identify the location of the void. Results obtained illustrate that by using these methods we are able to accurately detect the true location of the void.


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

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