Structure of the Upper Crust beneath the Klyuchevskoy Group of Volcanoes Revealed from Ambient Noise Tomography

Abstract ––The Klyuchevskoy group of volcanoes (KGV) located in the central part of Kamchatka is a unique complex that demonstrates exceptional variety and intensity of volcanic manifestations. These features of the eruptive activity of the KGV are determined by a complex system of magmatic sources in the crust and mantle. While the structure of deep anomalies is quite reliably determined by tomography techniques based on body waves, the structure of the upper crust can only be determined using ambient noise tomography. We present the results of processing data from the KISS temporary network. This network consisted of more than 100 seismic stations that were installed from 2015 to 2016 over a large area covering the Klyuchevskoy group of volcanoes and its surroundings. To retrieve Rayleigh surface waves, cross-correlation of continuous seismic noise records from pairs of stations was used. We obtained the dispersion curves of the group velocities of these Rayleigh surface waves using frequency–time analysis (FTAN) of the calculated correlograms. These curves served as input data for performing ambient noise tomography. Tomography was performed in two stages: (1) computation of two-dimensional group velocity maps for different frequencies and (2) calculation of a three-dimensional model of the shear wave velocity to a depth of about 8 km based on the inversion of local dispersion curves obtained from these maps. The resulting models revealed the structural features of individual volcanic systems of the KGV. High velocities were observed at shallow depths beneath the large basaltic edifices of the Ushkovsky and Tolbachik volcanoes. At greater depths, while the velocity structure beneath Ushkovsky remained unchanged, we detected low velocities beneath Tolbachik. This fact illustrates the difference between dormant and active magmatic systems. Velocity anomalies of a complex shape are observed beneath the Klyuchevskoy, Kamen, and Bezymianny volcanoes, varying both laterally and with depth. Absolute velocities in vertical sections show that the edifices of these volcanoes are relatively low-velocity bodies located on a horizontal high-velocity basement. A low-velocity anomaly was discovered under the Bezymianny Volcano at a depth of 6 km, which is presumably associated with a shallow magma reservoir. An intense low-velocity anomaly was found beneath the Udina Volcano. It was interpreted as an image of a magma reservoir experiencing strong seismic unrest that began in December 2017 and continues to this day.

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Azimuthal multiple signal classification of dispersive and aliased surface waves recorded in 3D seismic acquisition

Geophysics ◽

10.1190/geo2020-0417.1 ◽

2021 ◽

pp. 1-84

Author(s):

Chunying Yang ◽

Wenchuang Wang

Keyword(s):

Surface Wave ◽

Surface Waves ◽

Body Waves ◽

Signal Classification ◽

Dispersion Pattern ◽

Velocity Spectrum ◽

Low Velocity ◽

Surface Wave Dispersion ◽

Multiple Signal Classification ◽

Multiple Signal

Irregular acquisition geometry causes discontinuities in the appearance of surface wave events, and a large offset causes seismic records to appear as aliased surface waves. The conventional method of sampling data affects the accuracy of the dispersion spectrum and reduces the resolution of surface waves. At the same time, mode kissing of the low-velocity layer and inhomogeneous scatterers requires a high-resolution method for calculating surface wave dispersion. This study tested the use of the multiple signal classification (MUSIC) algorithm in 3D multichannel and aliased wavefield separation. Azimuthal MUSIC is a useful method to estimate the phase velocity spectrum of aliased surface wave data, and it represent the dispersion spectra of low-velocity and inhomogeneous models. The results of this study demonstrate that mode-kissing affects dispersion imaging, and inhomogeneous scatterers change the direction of surface-wave propagation. Surface waves generated from the new propagation directions are also dispersive. The scattered surface wave has a new dispersion pattern different to that of the entire record. Diagonal loading was introduced to improve the robustness of azimuthal MUSIC, and numerical experiments demonstrate the resultant effectiveness of imaging aliasing surface waves. A phase-matched filter was applied to the results of azimuthal MUSIC, and phase iterations were unwrapped in a fast and stable manner. Aliased surface waves and body waves were separated during this process. Overall, field data demonstrate that azimuthal MUSIC and phase-matched filters can successfully separate aliased surface waves.

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

Seismological Research Letters ◽

10.1785/0220190166 ◽

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.

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A model study of elastic waves in a layered sphere

Bulletin of the Seismological Society of America ◽

10.1785/bssa0570050959 ◽

1967 ◽

Vol 57 (5) ◽

pp. 959-981

Author(s):

Victor Gregson

Keyword(s):

Surface Wave ◽

Surface Waves ◽

Elastic Waves ◽

Wave Dispersion ◽

Flat Space ◽

Dispersion Curves ◽

Body Waves ◽

Surface Wave Dispersion ◽

Steel Sphere ◽

Long Wave

abstract Elastic waves produced by an impact were recorded at the surface of a solid 12.0 inch diameter steel sphere coated with a 0.3 inch copper layer. Conventional modeling techniques employing both compressional and shear piezoelectric transducers were used to record elastic waves for one millisecond at various points around the great circle of the sphere. Body, PL, and surface waves were observed. Density, layer thickness, compressional and shear-wave velocities were measured so that accurate surface-wave dispersion curves could be computed. Surface-wave dispersion was measured as well as computed. Measured PL mode dispersion compared favorably with theoretical computations. In addition, dispersion curves for Rayleigh, Stoneley, and Love modes were computed. Measured surface-wave dispersion showed Rayleigh and Love modes were observed but not Stoneley modes. Measured dispersion compared favorably with theoretical computations. The curvature correction applied to dispersion calculations in a flat space has been estimated to correct dispersion values at long-wave lengths to about one per cent of correct dispersion in a spherical model. Measured dispersion compared with such flat space dispersion corrected for curvature proved accurate within one per cent at long wave lengths. Two sets of surface waves were observed. One set was associated with body waves radiating outward from impact. The other set was associated with body waves reflecting at the pole opposite impact. For each set of surface waves, measured dispersion compared favorably with computed dispersion.

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First step towards an integrated geophysical-geological model of the W-Alps: A new Vs model from transdimensional ambient-noise tomography

10.5194/egusphere-egu21-3197 ◽

2021 ◽

Author(s):

Ahmed Nouibat ◽

Laurent Stehly ◽

Anne Paul ◽

Romain Brossier ◽

Thomas Bodin ◽

...

Keyword(s):

Group Velocity ◽

Shear Wave ◽

Wave Velocity ◽

Shear Wave Velocity ◽

Ambient Noise ◽

Receiver Functions ◽

Time Inversion ◽

Geological Model ◽

Ambient Noise Tomography ◽

Low Velocity

We have successfully derived a new 3-D high resolution shear wave velocity model of the crust and uppermost mantle of a large part of W-Europe from transdimensional ambient-noise tomography. This model is intended to contribute to the development of the first 3-D crustal-scale integrated geophysical-geological model of the W-Alps to deepen understanding of orogenesis and its relationship to mantle dynamics. We used an exceptional dataset of 4 years of vertical-component, daily seismic noise records (2015 - 2019) of more than 950 permanent broadband seismic stations located in and around the Greater Alpine region, complemented by 490 temporary stations from the AlpArray sea-land seismic network and 110 stations from Cifalps dense deployments.We firstly performed a 2-D data-driven transdimensional travel time inversion for group velocity maps from 4 to 150 s (Bodin & Sambridge, 2009). The data noise level was treated as a parameter of the inversion problem, and determined within a Hierarchical Bayes method. We used Fast Marching Eikonal solver (Rawlinson & Sambridge, 2005) jointly with the reversible jump algorithm to update raypath geometry during inversion. In the inversion of group velocity maps for shear-wave velocity, we set up a new formulation of the approach proposed by Lu et al (2018) by including group velocity uncertainties. Posterior probability distributions on Vs and interfaces were estimated by exploring a set of 130 millions synthetic 4-layer 1-D Vs models that allow for low-velocity zones. The obtained probabilistic model was refined using a linearized inversion. For the ocean-bottom seismometers of the Ligurian-Provencal basin, we applied a specific processing to clean daily noise signals from instrumental and oceanic noises (Crawford & Webb, 2000) and adapted the inversion for Vs to include the water column.Our Vs model evidences strong variations of the crustal structure along strike, particulary in the subduction complex. The European crust includes lower crustal low-velocity zones and a Moho jump of ~8-12 km beneath the W-boundary of the external crystalline massifs. We observe a deep LVZ structure (50 - 80 km) in the prolongation of the European continental subduction beneath the Ivrea body. The striking fit between the receiver functions ccp migrated section across the Cifalps profile and this new Vs model validate its reliability.

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

South African Journal of Geology ◽

10.25131/gssajg.120.3.341 ◽

2017 ◽

Vol 120 (3) ◽

pp. 341-350 ◽

Cited By ~ 1

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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Upper-plate structure in Ecuador coincident with the subduction of the Carnegie Ridge and the southern extent of large mega-thrust earthquakes

Geophysical Journal International ◽

10.1093/gji/ggz558 ◽

2019 ◽

Vol 220 (3) ◽

pp. 1965-1977 ◽

Cited By ~ 4

Author(s):

Colton Lynner ◽

Clinton Koch ◽

Susan L Beck ◽

Anne Meltzer ◽

Lillian Soto-Cordero ◽

...

Keyword(s):

Ambient Noise ◽

Velocity Structure ◽

Sedimentary Basins ◽

Past Century ◽

Ambient Noise Tomography ◽

Plate Interface ◽

Crust And Upper Mantle ◽

Southern Boundary ◽

Plate Structure ◽

Velocity Anomaly

SUMMARY The Ecuadorian convergent margin has experienced many large mega-thrust earthquakes in the past century, beginning with a 1906 event that propagated along as much as 500 km of the plate interface. Many subsections of the 1906 rupture area have subsequently produced Mw ≥ 7.7 events, culminating in the 16 April 2016, Mw 7.8 Pedernales earthquake. Interestingly, no large historic events Mw ≥ 7.7 appear to have propagated southward of ∼1°S, which coincides with the subduction of the Carnegie Ridge. We combine data from temporary seismic stations deployed following the Pedernales earthquake with data recorded by the permanent stations of the Ecuadorian national seismic network to discern the velocity structure of the Ecuadorian forearc and Cordillera using ambient noise tomography. Ambient noise tomography extracts Vsv information from the ambient noise wavefield and provides detailed constraints on velocity structures in the crust and upper mantle. In the upper 10 km of the Ecuadorian forearc, we see evidence of the deepest portions of the sedimentary basins in the region, the Progreso and Manabí basins. At depths below 30 km, we observe a sharp delineation between accreted fast forearc terranes and the thick crust of the Ecuadorian Andes. At depths ∼20 km, we see a strong fast velocity anomaly that coincides with the subducting Carnegie Ridge as well as the southern boundary of large mega-thrust earthquakes. Our observations raise the possibility that upper-plate structure, in addition to the subducting Carnegie Ridge, plays a role in the large event segmentation seen along the Ecuadorian margin.

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Sensitivities of phase-velocity dispersion curves of surface waves due to high-velocity-layer and low-velocity-layer models

Journal of Applied Geophysics ◽

10.1016/j.jappgeo.2016.10.017 ◽

2016 ◽

Vol 135 ◽

pp. 367-374 ◽

Cited By ~ 7

Author(s):

Chao Shen ◽

Yixian Xu ◽

Yudi Pan ◽

Ao Wang ◽

Lingli Gao

Keyword(s):

Phase Velocity ◽

Surface Waves ◽

High Velocity ◽

Velocity Dispersion ◽

Dispersion Curves ◽

Low Velocity ◽

Phase Velocity Dispersion ◽

Low Velocity Layer ◽

High Velocity Layer ◽

Velocity Layer

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Ambient noise tomography of Gran Canaria island (Canary Islands)

10.5194/egusphere-egu21-10957 ◽

2021 ◽

Author(s):

Iván Cabrera Pérez ◽

Jean Soubestre ◽

Luca D'Auria ◽

Germán Cervigón-Tomico ◽

David Martínez van Dorth ◽

...

Keyword(s):

Group Velocity ◽

Canary Islands ◽

Ambient Noise ◽

Velocity Model ◽

Dispersion Curves ◽

Ambient Noise Tomography ◽

Gran Canaria ◽

Geothermal Reservoirs ◽

Velocity Models ◽

Non Linear

The island of Gran Canaria is located in the Canarian Archipelago, with an area of 1560 km2 and a maximum altitude of 1956 m.a.s.l., being the third island of the archipelago in terms of extension and altitude. The island has two very well differentiated geological domains: the southwest domain or Paleo-Canarias, which is the geologically oldest part, and the northeast domain or Neo-Canarias, where are located the vents of the most recent Holocene eruptions. This volcanic island hosted Holocene eruptions. Therefore, apart from being affected by volcanic risk, it potentially hosts geothermal resources that could be exploited to increase the percentage of renewable energy in the Canary Islands.The main objective of this work is to use Ambient Noise Tomography (ANT) for retrieving a high-resolution seismic velocity model of the first few kilometres of the crust, to improve local earthquake location and detect anomalies potentially related to active geothermal reservoirs. Currently, the 1-D velocity model of the island does not allow a correct determination of the hypocenters, being unable to take into account the substantial horizontal velocity contrasts correctly.To realize the ANT, we deployed 28 temporary broadband seismic stations in two phases. Each campaign lasted at least one month. We also exploited data recorded by the permanent seismic network Red S&#237;smica Canaria (C7) operated by INVOLCAN. After applying standard data processing to retrieve Green&#8217;s functions from ambient noise cross-correlations, we retrieved the dispersion curves using the FTAN (Frequency Time ANalysis) technique. The inversion of dispersion curves to obtain group velocity maps was realized using a novel non-linear multiscale tomographic approach (MAnGOSTA, Multiscale Ambient NOiSe TomogrAphy). The forward modelling of surface waves traveltimes was implemented using a shortest-path algorithm that allows the topography to be taken into account. The MANgOSTA method consists of successive non-linear inversion steps on progressively finer grids. This technique allows retrieving 2-D group velocity models in the presence of substantial velocity contrasts with up to 100% of the relative variation. Then, we performed a depth inversion of the Rayleigh wave dispersion curves using a transdimensional Bayesian formulation. The final result is a 3-D model of P- and S-wave velocities of the island. The preliminary results show the presence of a low-velocity zone in the eastern part of the island that coincides spatially with anomalies observed in previous geophysical and geochemical studies and which could be related to actual or fossil geothermal reservoirs. Furthermore, the model shows the presence of high-velocity anomalies that are associated with the mafic core of the island.

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