Distributed acoustic sensing for shallow seismic investigations and void detection

Geophysics ◽  
2021 ◽  
pp. 1-69
Author(s):  
Yarin Abukrat ◽  
Moshe Reshef
Keyword(s):  
Vertical Component ◽  
Test Site ◽  
Wave Mode ◽  
Invasive Technique ◽  
S Wave ◽  
Near Surface ◽  
Acoustic Sensing ◽  
Shallow Subsurface ◽  
Diffraction Imaging ◽  
Distributed Acoustic Sensing

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.

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.

scholarly journals Urban Near-surface Seismic Monitoring using Distributed Acoustic Sensing

2019 ◽  
Author(s):  
Gang Fang ◽  
Yunyue Li ◽  
Yumin Zhao ◽  
Eileen Martin
Keyword(s):  
Seismic Monitoring ◽  
Near Surface ◽  
Acoustic Sensing ◽  
Distributed Acoustic Sensing

scholarly journals Distributed acoustic sensing as a tool for exploration and monitoring: a proof-of-concept

2021 ◽  
Author(s):  
Nicola Piana Agostinetti ◽  
Alberto Villa ◽  
Gilberto Saccorotti
Keyword(s):  
High Resolution ◽  
Plane Wave ◽  
Geothermal Field ◽  
P Wave ◽  
Apparent Velocity ◽  
Near Surface ◽  
Acoustic Sensing ◽  
Geothermal Activity ◽  
Distributed Acoustic Sensing ◽  
Microseismic Event

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.

Near-surface scattering phenomena and implications for tunnel detection

2015 ◽  
Vol 3 (1) ◽  
pp. SF43-SF54 ◽  
Author(s):  
Shelby L. Peterie ◽  
Richard D. Miller
Keyword(s):  
Synthetic Data ◽  
P Wave ◽  
S Wave ◽  
Seismic Line ◽  
Data Set ◽  
Near Surface ◽  
Tunnel Detection ◽  
Impedance Contrast ◽  
Diffraction Imaging ◽  
Imaging Algorithms

Tunnel locations are accurately interpreted from diffraction sections of focused mode converted P- to S-wave diffractions from a perpendicular tunnel and P-wave diffractions from a nonperpendicular (oblique) tunnel. Near-surface tunnels are ideal candidates for diffraction imaging due to their small size relative to the seismic wavelength and large acoustic impedance contrast at the tunnel interface. Diffraction imaging algorithms generally assume that the velocities of the primary wave and the diffracted wave are approximately equal, and that the diffraction apex is recorded directly above the scatterpoint. Scattering phenomena from shallow tunnels with kinematic properties that violate these assumptions were observed in one field data set and one synthetic data set. We developed the traveltime equations for mode-converted and oblique diffractions and demonstrated a diffraction imaging algorithm designed for the roll-along style of acquisition. Potential processing and interpretation pitfalls specific to these diffraction types were identified. Based on our observations, recommendations were made to recognize and image mode-converted and oblique diffractions and accurately interpret tunnel depth, horizontal location, and azimuth with respect to the seismic line.

Robust Empirical Time–Frequency Relations for Seismic Spectral Amplitudes, Part 1: Application to Regional S Waves in Southeastern Iran

2020 ◽  
Author(s):  
Maryam Safarshahi ◽  
Igor B. Morozov
Keyword(s):  
Seismic Waves ◽  
Joint Inversion ◽  
Vertical Component ◽  
Transverse Component ◽  
Model Parameters ◽  
S Wave ◽  
Near Surface ◽  
S Waves ◽  
Time Frequency ◽  
Frequency Independent

ABSTRACT Empirical models of geometrical-, Q-, t-star, and kappa-type attenuation of seismic waves and ground-motion prediction equations (GMPEs) are viewed as cases of a common empirical standard model describing variation of wave amplitudes with time and frequency. Compared with existing parametric and nonparametric approaches, several new features are included in this model: (1) flexible empirical parameterization with possible nonmonotonous time or distance dependencies; (2) joint inversion for time or distance and frequency dependencies, source spectra, site responses, kappas, and Q; (3) additional constraints removing spurious correlations of model parameters and data residuals with source–receiver distances and frequencies; (4) possible kappa terms for sources as well as for receivers; (5) orientation-independent horizontal- and three-component amplitudes; and (6) adaptive filtering to reduce noise effects. The approach is applied to local and regional S-wave amplitudes in southeastern Iran. Comparisons with previous studies show that conventional attenuation models often contain method-specific biases caused by limited parameterizations of frequency-independent amplitude decays and assumptions about the models, such as smoothness of amplitude variations. Without such assumptions, the frequency-independent spreading of S waves is much faster than inferred by conventional modeling. For example, transverse-component amplitudes decrease with travel time t as about t−1.8 at distances closer than 90 km and as t−2.5 beyond 115 km. The rapid amplitude decay at larger distances could be caused by scattering within the near surface. From about 90 to 115 km distances, the amplitude increases by a factor of about 3, which could be due to reflections from the Moho and within the crust. With more accurate geometrical-spreading and kappa models, the Q factor for the study area is frequency independent and exceeds 2000. The frequency-independent and Q-type attenuation for vertical-component and multicomponent amplitudes is somewhat weaker than for the horizontal components. These observations appear to be general and likely apply to other areas.

scholarly journals Distributed Acoustic Sensing Using Dark Fiber for Near-Surface Characterization and Broadband Seismic Event Detection

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jonathan B. Ajo-Franklin ◽  
Shan Dou ◽  
Nathaniel J. Lindsey ◽  
Inder Monga ◽  
Chris Tracy ◽  
...  
Keyword(s):  
Event Detection ◽  
Surface Characterization ◽  
Seismic Event ◽  
Near Surface ◽  
Acoustic Sensing ◽  
Seismic Event Detection ◽  
Distributed Acoustic Sensing
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