High-frequency surface and body waves from ambient noise cross-correlations at Long Beach, CA

Chang, Jason P.; Nakata, Nori; Clapp, Robert G.; Biondi, Biondo; Ridder, Sjoerd de

doi:10.1190/segam2014-1363.1

Cited by 5 publications

(2 citation statements)

References 11 publications

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“…Applying this processing procedure to a line of receivers running perpendicular to Interstate 405, Chang et al (2014) verified that the extracted Green's functions above 3 Hz were dominated by fundamental-and first-order-mode Rayleigh waves generated by the highway and local roads. An example of an extracted Green's function with two Rayleigh-wave modes is shown in Figure 2.…”

Section: Estimating Green's Functionsmentioning

confidence: 94%

Rayleigh-wave tomography using traffic noise at Long Beach, CA

Chang

Biondi

2015

SEG Technical Program Expanded Abstracts 2015

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Passive seismic arrays on land provide the opportunity to push the use of ambient noise cross-correlation techniques to frequencies well beyond the microseism band. Using data recorded by a dense array in Long Beach, California, we demonstrate that high-frequency (> 3 Hz) fundamental-and first-order-mode Rayleigh waves generated by traffic noise can be extracted from the ambient noise field and used for tomographic studies. Here, we show group velocity maps derived from travel times of the fundamental-mode Rayleigh waves at 3.00 Hz and 3.50 Hz. The velocity trends in our results correlate well with lithologies outlined in a geologic map of the survey region. As expected, less-consolidated materials display relatively low velocities, while more-consolidated materials display relatively high velocities.

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Section: Estimating Green's Functionsmentioning

confidence: 94%

Rayleigh-wave tomography using traffic noise at Long Beach, CA

Chang

Biondi

2015

SEG Technical Program Expanded Abstracts 2015

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“…First, I average the coherence functions over the entire observations (approximately 12 h) to create C. I compute crosscoherence between all receiver pairs (300 × 300), although some combinations are not used for further processing (Figure 4a-4c). Strong noise originates from the highway (i.e., strong directionality of traffic noise), so the coherence functions in Figure 4 at traces 75-100 (on the other side of the highway relative to the virtual source) contain waves, which are not physically explained by waves propagating from the virtual source (Chang et al, 2014). Therefore, I do not use the receiver pairs that are across the highway for the dispersion analysis below.…”

Section: Seismic Interferometry and Dbfmentioning

confidence: 99%

Near-surface S-wave velocities estimated from traffic-induced Love waves using seismic interferometry with double beamforming

Nakata

2016

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I use ambient noise, especially traffic noise, to estimate the 2D near-surface S-velocity distribution. Nearsurface velocities are useful for understanding structure, stiffness, porosity, and pore pressure for engineering/environmental purposes and static correction of active-source imaging. I extract Love waves propagating between each receiver pair from 12 h of traffic noise using seismic interferometry with power-normalized crosscorrelation. The receiver array contained three parallel lines, each of which had 100 transverse-component geophones. I apply double beamforming to the correlations at the parallel lines for improving the signal-to-noise ratio of the extracted Love waves to satisfy the stationary phase assumption for seismic interferometry. I use these Love waves for a dispersion analysis to estimate a 2D near-surface S-wave velocity model based on the multichannel analysis of surface waves. To improve the lateral resolution of the velocity model, I sort the extracted waves according to common midpoints (CMPs) and limited the maximum offset of receiver pairs. The dispersion analysis at each CMP is based on the assumption of layered media, and using all CMPs, I can estimate high-resolution 2D velocities down to 80 m depth. The velocity variations are similar to the location of strong reflectors obtained by a previous study. The main features of the velocity model are recovered even from 1 h of continuous traffic-noise data, which means that the proposed technique can be used for efficient 4D surveys.

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

Ajo‐Franklin

Dou

Lindsey

et al. 2019

Sci Rep

395

199

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We present one of the first case studies demonstrating the use of distributed acoustic sensing deployed on regional unlit fiber-optic telecommunication infrastructure (dark fiber) for broadband seismic monitoring of both near-surface soil properties and earthquake seismology. We recorded 7 months of passive seismic data on a 27 km section of dark fiber stretching from West Sacramento, CA to Woodland, CA, densely sampled at 2 m spacing. This dataset was processed to extract surface wave velocity information using ambient noise interferometry techniques; the resulting VS profiles were used to map both shallow structural profiles and groundwater depth, thus demonstrating that basin-scale variations in hydrological state could be resolved using this technique. The same array was utilized for detection of regional and teleseismic earthquakes and evaluated for long period response using records from the M8.1 Chiapas, Mexico 2017, Sep 8th event. The combination of these two sets of observations conclusively demonstrates that regionally extensive fiber-optic networks can effectively be utilized for a host of geoscience observation tasks at a combination of scale and resolution previously inaccessible.

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High-frequency surface and body waves from ambient noise cross-correlations at Long Beach, CA

Cited by 5 publications

References 11 publications

Rayleigh-wave tomography using traffic noise at Long Beach, CA

Rayleigh-wave tomography using traffic noise at Long Beach, CA

Near-surface S-wave velocities estimated from traffic-induced Love waves using seismic interferometry with double beamforming

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

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