Ambient Noise Radiation by “Soliton” Surface Waves

1988 ◽  
pp. 325-335
Author(s):  
R. H. Mellen ◽  
D. Middleton
Keyword(s):  
Surface Waves ◽  
Ambient Noise ◽  
Noise Radiation ◽  
Soliton Surface

scholarly journals On ambient noise generation by “soliton” surface waves

1989 ◽  
Vol 85 (S1) ◽  
pp. S152-S153
Author(s):  
Robert H. Mellen ◽  
David Middleton
Keyword(s):  
Surface Waves ◽  
Ambient Noise ◽  
Noise Generation ◽  
Soliton Surface

scholarly journals Lithospheric structure beneath the northern Central Andean Plateau from the joint inversion of ambient noise and earthquake‐generated surface waves

2016 ◽  
Vol 121 (11) ◽  
pp. 8217-8238 ◽  
Author(s):  
Kevin M. Ward ◽  
George Zandt ◽  
Susan L. Beck ◽  
Lara S. Wagner ◽  
Hernando Tavera
Keyword(s):  
Surface Waves ◽  
Ambient Noise ◽  
Joint Inversion ◽  
Lithospheric Structure

Seismic imaging at a mineral-deposit scale using high-frequency surface waves (0.5–24 Hz) in ambient noise wavefield

2020 ◽  
Author(s):  
Y. Xu ◽  
S. Lebedev ◽  
R. Bonadio ◽  
T. Meier ◽  
C. Bean ◽  
...  
Keyword(s):  
Surface Waves ◽  
High Frequency ◽  
Ambient Noise ◽  
Seismic Imaging ◽  
Mineral Deposit

Extracting Long-Period Surface Waves and Free Oscillations Using Ambient Noise Recorded by Global Distributed Superconducting Gravimeters

2020 ◽  
Vol 91 (4) ◽  
pp. 2234-2246
Author(s):  
Hang Li ◽  
Jianqiao Xu ◽  
Xiaodong Chen ◽  
Heping Sun ◽  
Miaomiao Zhang ◽  
...  
Keyword(s):  
Surface Waves ◽  
Group Velocity ◽  
Ambient Noise ◽  
Velocity Dispersion ◽  
Group Velocity Dispersion ◽  
Dispersion Curves ◽  
Free Oscillations ◽  
Long Period ◽  
Superconducting Gravimeters ◽  
Noise Data

Abstract Inversion of internal structure of the Earth using surface waves and free oscillations is a hot topic in seismological research nowadays. With the ambient noise data on seismically quiet days sourced from the gravity tidal observations of seven global distributed superconducting gravimeters (SGs) and the seismic observations for validation from three collocated STS-1 seismometers, long-period surface waves and background free oscillations are successfully extracted by the phase autocorrelation (PAC) method, respectively. Group-velocity dispersion curves at the frequency band of 2–7.5 mHz are extracted and compared with the theoretical values calculated with the preliminary reference Earth model. The comparison shows that the best observed values differ about ±2% from the corresponding theoretical results, and the extracted group velocities of the best SG are consistent with the result of the collocated STS-1 seismometer. The results indicate that reliable group-velocity dispersion curves can be measured with the ambient noise data from SGs. Furthermore, the fundamental frequency spherical free oscillations of 2–7 mHz are also clearly extracted using the same ambient noise data. The results in this study show that the SG, besides the seismometer, is proved to be another kind of instrument that can be used to observe long-period surface waves and free oscillations on seismically quiet days with a high degree of precision using the PAC method. It is worth mentioning that the PAC method is first and successfully introduced to analyze SG observations in our study.

Reconciling phase velocities from ambient noise and earthquake-generated surface waves by accounting for arrival-angle effects

2020 ◽  
Author(s):  
Giovanni Diaferia ◽  
Fabrizio Cammarano ◽  
Lapo Boschi ◽  
Fabio Cammarano
Keyword(s):  
Surface Waves ◽  
Ambient Noise ◽  
Radial Component ◽  
Systematic Bias ◽  
Finite Frequency ◽  
Arrival Angle ◽  
Phase Velocities ◽  
Shear Wave Velocities ◽  
Lateral Inhomogeneity ◽  
Seismic Anomalies

<p>The shear-wave velocities structure at depth can be unraveled from ambient noise (AN) as well as from earthquake-generated (EQ) surface waves. While the first approach mostly provides information at crustal scale, earthquake-based surface waves sense deeper structures due to their lower frequency content. However, for periods between 20 and 40 s, where the two methods often overlap, a number of studies have shown that phase velocities from EQ surface waves are systematically higher (~1%) than those retrieved from AN. The reason for such systematic bias is still debated; finite-frequency effects, overtone contamination, and off-path propagation of surface waves due to structural inhomogeneities have all been invoked as possible explanations of the discrepancy in question.</p><p>We explore the validity of the latter hypothesis, by correcting Rayleigh-wave phase velocities for the effect of off-path arrivals at two stations. The deviation from the theoretical path is estimated by evaluating the resemblance of the vertical with the π/2-shifted radial component of the recorded seismograms. We developed a two-station algorithm implementing such a correction and tested it on a dataset of seismograms collected from more than 350 stations recording 443 earthquake events from 2005 to 2019. We demonstrate that by compensating for the arrival-angle effects, the discrepancy between the two methods is significantly reduced. This result suggests that the off-path propagation between epicenters and receivers due to lateral inhomogeneity in the Earth's structure explains most of the discrepancy between AN and EQ phase velocities previously reported in the literature. Such improvement in determining Rayleigh phase velocities will lead to more reliable seismic tomographies and enhanced interpretations of seismic anomalies in terms of thermo-chemical characteristics.</p>

scholarly journals Fault detection by reflected surface waves based on ambient noise interferometry

2021 ◽  
pp. 100035
Author(s):  
G.U. Ning ◽  
Z.H.A.N.G. Haijiang ◽  
Nori NAKATA ◽  
G.A.O. Ji
Keyword(s):  
Fault Detection ◽  
Surface Waves ◽  
Ambient Noise ◽  
Noise Interferometry

scholarly journals Causes of artifacts in ambient noise surface wave tomography in mantle investigations and ways for their elimination

2020 ◽  
Vol 2 (2) ◽  
pp. 58-65
Author(s):  
Tat’iana Koroleva ◽  
Evgeniia Lyskova
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Ambient Noise ◽  
Love Waves ◽  
Limited Area ◽  
Time Interval ◽  
Surface Wave Tomography ◽  
Noise Component ◽  
Long Time ◽  
Wave Tomography

Ambient noise surface wave tomography is a widely used method for determining the velocity structure of the upper layers of the Earth. It is based on the fact that the cross-correlation function (CCF) of noise at two stations, averaged over a long time interval, determines the Green's function of the surface wave. This allows us to estimate the group and phase velocities of surface waves on the paths between stations, which are used in surface-wave tomography. This makes it possible to ultimately estimate the spatial distribution of the S-wave velocities. The method is well-grounded on the assumption that the “noise” is a result of the superposition of surface waves propagating from sources uniformly distributed over the surface. Therefore, the initial data, which are long-period seismic records, are subjected to preliminary processing, an important stage of which is normalization, which allows reducing the effect of earthquakes and averaging the resulting CCFs over a long time interval. At the same time, we have shown that earthquakes mainly contribute to noise at periods above 30-40 s, whose sources are distributed unevenly. Therefore, in cases of clustering of foci in a certain limited area, for example, because of aftershocks after a strong earthquake, the CCF maxima, which determines the dispersion curve of the surface wave, are shifted to shorter times, and the group velocities are correspondingly overestimated. In determining the dispersion of Love waves from the CCF transversal (T-T) noise component, the presence of clusters leads to an additional underestimation of the group velocity due to the superposition on the T component (perpendicular to the inter-station path) of the radial component of the Rayleigh wave having a velocity less than the Love wave velocity. Therefore, the anisotropy coefficient, determined from the noise, is underestimated as compared to that obtained from the records of earthquakes along nearby paths. Obviously, to obtain more correct dispersion curves of both Rayleigh and Love waves, it is necessary, for summing the CCFs, to use time intervals in which earthquake clusters would be absent as far as possible.

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