scholarly journals Rayleigh-wave group-velocity of the Icelandic crust from correlation of ambient seismic noise

2007 ◽  
Vol 34 (14) ◽  
Author(s):  
Ó. Gudmundsson ◽  
A. Khan ◽  
P. Voss
Keyword(s):  
Rayleigh Wave ◽  
Group Velocity ◽  
Seismic Noise ◽  
Ambient Seismic Noise ◽  
Wave Group

scholarly journals Rayleigh wave group velocity distributions for East Asia using ambient seismic noise

2014 ◽  
Vol 41 (22) ◽  
pp. 8045-8052 ◽  
Author(s):  
Michael Witek ◽  
Suzan van der Lee ◽  
Tae-Seob Kang
Keyword(s):  
Rayleigh Wave ◽  
East Asia ◽  
Group Velocity ◽  
Seismic Noise ◽  
Ambient Seismic Noise ◽  
Wave Group

scholarly journals Imaging of a Magma System Beneath the Merapi Volcano Complex, Indonesia, using Ambient Seismic Noise Tomography

2021 ◽  
Author(s):  
T Yudistira ◽  
J-P Metaxian ◽  
M Putriastuti ◽  
S Widiyantoro ◽  
N Rawlinson ◽  
...  
Keyword(s):  
Rayleigh Wave ◽  
Group Velocity ◽  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Seismic Noise ◽  
Ambient Seismic Noise ◽  
Wave Group ◽  
Velocity Anomaly ◽  
Cross Correlations

Summary Mt. Merapi, which lies just north of the city of Yogyakarta in Java, Indonesia, is one of the most active and dangerous volcanoes in the world. Thanks to its subduction zone setting, Mt Merapi is a stratovolcano, and rises to an elevation of 2968 m above sea level. It stands at the intersection of two volcanic lineaments, Ungaran–Telomoyo–Merbabu–Merapi (UTMM) and Lawu–Merapi–Sumbing–Sindoro–Slamet, which are oriented north-south and west-east, respectively. Although it has been the subject of many geophysical studies, Mt Merapi's underlying magmatic plumbing system is still not well understood. Here, we present the results of an ambient seismic noise tomography study, which comprise of a series of Rayleigh wave group velocity maps and a 3-D shear wave velocity model of the Merapi-Merbabu complex. A total of 10 months of continuous data (October 2013–July 2014) recorded by a network of 46 broadband seismometers were used. We computed and stacked daily cross-correlations from every pair of simultaneously recording stations to obtain the corresponding inter-station empirical Green's functions. Surface wave dispersion information was extracted from the cross-correlations using the multiple filtering technique, which provided us with an estimate of Rayleigh wave group velocity as a function of period. The group velocity maps for periods 3–12 s were then inverted to obtain shear wave velocity structure using the neighbourhood algorithm. From these results, we observe a dominant high velocity anomaly underlying Mt. Merapi and Mt. Merbabu with a strike of 152° N, which we suggest is evidence of old lava dating from the UTMM double-chain volcanic arc which formed Merbabu and Old Merapi. We also identify a low velocity anomaly on the southwest flank of Merapi which we interpret to be an active magmatic intrusion.

scholarly journals Using multicomponent ambient seismic noise cross-correlations to identify higher mode Rayleigh waves and improve dispersion measurements

2020 ◽  
Vol 222 (3) ◽  
pp. 1590-1605 ◽  
Author(s):  
Avinash Nayak ◽  
Clifford H Thurber
Keyword(s):  
Rayleigh Wave ◽  
Group Velocity ◽  
Particle Motion ◽  
Fundamental Mode ◽  
Rayleigh Waves ◽  
Seismic Noise ◽  
Vertical Plane ◽  
Ambient Seismic Noise ◽  
Cross Correlations ◽  
The Individual

SUMMARY Ambient seismic noise cross-correlation with three-component sensors yields a nine-component empirical Green's tensor, in which four components of the radial–vertical plane contain Rayleigh waves. We exploit the retrograde elliptical nature of particle motion of the fundamental mode Rayleigh wave to correct the phase of the four radial–vertical components and stack them to obtain an average fundamental mode Rayleigh-wave time-series. This technique can suppress incoherent noise and wave packets that do not follow the targeted elliptical particle motion. The same technique can be used to isolate the first higher mode Rayleigh wave that follows prograde elliptical particle motion. We first demonstrate the effectiveness of the method on synthetic waveforms and then apply it on noise cross-correlations computed in Central California. Using this method, we isolate 1st higher mode Rayleigh waves on noise cross-correlations in the Great Valley, California, which provides new phase velocity constraints for estimating velocity structure in the sedimentary basin. We also obtain improved estimates of fundamental mode Rayleigh-wave dispersion for surface-wave tomography. The waveforms stacked assuming retrograde particle motion return at least ∼20 per cent more group velocity dispersion measurements satisfying a minimum signal-to-noise ratio (SNR) criterion than the individual components for periods ∼4–18 s. For equivalent group velocity measurements, SNR for the stacked estimate of the fundamental mode Rayleigh wave is on average 40 per cent greater than that measured on the individual components at periods less than 10 s. The technique also provides an easy way to detect large errors in sensor orientation.

Rayleigh group velocity extraction from ambient seismic noise to map the south Eastern Cape Karoo region, South Africa

2017 ◽  
Vol 120 (3) ◽  
pp. 341-350 ◽  
Author(s):  
L.J. Bezuidenhout ◽  
M. Doucouré ◽  
V. Wagener ◽  
M. de Wit ◽  
A. Mordret ◽  
...  
Keyword(s):  
South Africa ◽  
Surface Waves ◽  
Group Velocity ◽  
Seismic Noise ◽  
Vertical Component ◽  
Ambient Seismic Noise ◽  
Seismic Signals ◽  
The South ◽  
Velocity Anomaly ◽  
Rayleigh Surface Waves

Abstract The Karoo region of South Africa is an ideal laboratory to use ambient seismic signals to map the shallow subsurface, as it is a quiet and pristine environment with a geology that is relatively well known. Ambient seismic signals were continuously recorded for a ten week period between August and October 2015. The ambient seismic noise network consisted of two groups of 17 temporary, stand-alone seismic stations each. These were installed in the southeastern Cape Karoo region, near the town of Jansenville. Here we present data on the retrieval and coherency of Rayleigh surface waves extracted from the vertical component recordings. We reconstruct and show, for the first time in the southeastern Cape Karoo, estimates of Green's function from cross-correlating ambient noise data between stations pairs, which can be successfully used to image the subsurface. The stacked cross-correlations between all station pairs show clear arrivals of the Rayleigh surface waves. The group velocities of the Rayleigh waves in the 3 to 7 seconds period range were picked and inverted to compute the 2-D group velocity maps. The resulting 2-D group velocity maps at different periods resulted in a group velocity model from approximately 2 to 7 km depth, which shows a high velocity anomaly in the north of the study area, most likely imaging the denser, thick sedimentary basin of the Karoo (Carboniferous-Permian). To the south, the low velocity anomaly could correspond to the overlying Jurassic-Cretaceous sedimentary sequences of the younger Algoa Basin (Uitenhage Group).

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