Crustal and upper mantle velocity structure of the Pannonian Region using Rayleigh wave ambient noise tomography

2021 ◽  
Author(s):  
Máté Timkó ◽  
Lars Wiesenberg ◽  
Amr El-Sharkawy ◽  
Zoltán Wéber ◽  
Thomas Meier ◽  
...  
Keyword(s):  
Rayleigh Wave ◽  
Ambient Noise ◽  
Velocity Structure ◽  
Pannonian Basin ◽  
Vertical Component ◽  
High Heat ◽  
Moho Depth ◽  
Ambient Noise Tomography ◽  
Period Range ◽  
Waveform Data

<p>The Pannonian Basin is located in Central-Europe surrounded by the Alpine, Carpathian, and Dinarides mountain ranges. This is a back-arc basin characterized by shallow Moho depth, updoming mantle and high heat flow. In this study, we present the results of the Rayleigh wave based ambient noise tomography to investigate the velocity structure of the Carpathian-Pannonian region. </p><p>For the ambient noise measurements, we collected the continuous waveform data from more than 1280 seismological stations from the broader Central-Eastern European region. This dataset embraces all the permanent and the temporary (AlpArray, PASSEQ, CBP, SCP) stations from the 9-degree radius of the Pannonian Basin which were operating between the time period between 2005 and 2018. All the possible vertical component noise cross-correlation functions were calculated and all phase velocity curves were determined in the 5-80 s period range using an automated measuring algorithm. </p><p>The collected dispersion measurements were then used to create tomographic images that are characterized by similar velocity anomalies in amplitude, pattern and location that are consistent with the well-known tectonic and geologic structure of the research area and are comparable to previous tomographic models published in the literature.</p>

Lithospheric structure of the Pannonian Basin using Rayleigh wave ambient noise tomography – preliminary results

2020 ◽  
Author(s):  
Máté Timkó ◽  
Lars Wiesenberg ◽  
Amr El-Sharkawy ◽  
Zoltán Wéber ◽  
Thomas Meier ◽  
...  
Keyword(s):  
Phase Velocity ◽  
Rayleigh Wave ◽  
Ambient Noise ◽  
Velocity Structure ◽  
Pannonian Basin ◽  
Vertical Component ◽  
Ambient Noise Tomography ◽  
Crust And Upper Mantle ◽  
Mountain Chain ◽  
One Year

<p>We used Rayleigh wave ambient noise tomography to investigate the crust and uppermost mantle structure of the Pannonian Basin. The Pannonian Basin and the surrounding orogens are located within the arcuate Alpine–Carpathian mountain chain in Central Europe. It is a back-arc basin characterized by a thinned lower crust and an updoming mantle. Benath the basin both the crust and the lithosphere have smaller thickness than the continental average. Imaging the velocity structure of the crust and upper mantle may help us to better understand the structure and formation of the Carpathian–Pannonian region.</p><p>We used data from the permanent seismological stations of the broader Central European region together with the AlpArray Seismic Network (AASN) and analysed one-year seismic data from 2017. More than 18 thousand vertical component noise cross-correlation functions were calculated and Rayleigh wave inter-station phase velocity curves were determined using an automated measuring algorithm. Anisotropic phase velocity tomographic imaging were carried out for the whole Pannonian Basin between 2 and 40s periods (~5-60 km).</p><p>The locations of the retrieved phase-velocity anomalies consistent with the well-known geologic and tectonic structure of the area (deep basins and orogenic belts) and are comparable to recent tomographic models published in the literature.</p>

scholarly journals Imaging Alpine crust using ambient noise wave-equation tomography

2020 ◽  
Vol 222 (1) ◽  
pp. 69-85 ◽  
Author(s):  
Y Lu ◽  
L Stehly ◽  
R Brossier ◽  
A Paul ◽  
Keyword(s):  
Wave Equation ◽  
Ambient Noise ◽  
Broad Band ◽  
Vertical Component ◽  
Moho Depth ◽  
Initial Model ◽  
Ambient Noise Tomography ◽  
Period Range ◽  
Final Model ◽  
Velocity Models

SUMMARY We present an improved crustal Vs model and Moho depth map using ambient noise wave-equation tomography. The so-called ‘ambient noise wave-equation tomography’ is a method to invert seismic ambient noise phase dispersion data based on elastic waveform simulation, which accounts for 3-D and finite-frequency effects. We use cross-correlations of up to 4 yr of continuous vertical-component ambient seismic noise recordings from 304 high-quality broad-band stations in the Alpine region. We use model LSP_Eucrust1.0 obtained from traditional ambient noise tomography as initial model, and we iteratively improve the initial model by minimizing frequency-dependent phase traveltime differences between the observed and synthetic waveforms of Rayleigh waves in the period range 10–50 s. We obtain the final model after 15 iterations with ∼65 per cent total misfit reduction compared to the initial model. At crustal depth, the final model significantly enhances the amplitudes and adjusts the shapes of velocity anomalies. At Moho and upper-mantle depth, the final model corrects an obvious systematic velocity shift of the initial model. The resulting isovelocity Moho map confirms a Moho step along the external side of the external crystalline massifs of the northwestern Alps and reveals underplated gabbroic plutons in the lower most crust of the central and eastern Alps. Ambient noise wave-equation tomography turns out to be a useful tool to refine shear wave velocity models obtained by traditional ambient noise tomography based on ray theory.

scholarly journals Group velocity maps using subspace and Trans-dimensional inversions: ambient noise tomography in the Western part of Java, Indonesia

2019 ◽  
Author(s):  
Shindy Rosalia ◽  
Phil Cummins ◽  
Sri Widiyantoro ◽  
Tedi Yudistira ◽  
Andri Dian Nugraha ◽  
...  
Keyword(s):  
Rayleigh Wave ◽  
Group Velocity ◽  
Ambient Noise ◽  
Regularization Parameter ◽  
Least Square ◽  
Disaster Mitigation ◽  
Wave Group ◽  
Ambient Noise Tomography ◽  
Waveform Data ◽  
Subspace Optimization

Summary In this paper, we compare two different methods for group velocity inversion: iterative, least-squares subspace optimization, and probabilistic sampling based on the Trans-dimensional Bayesian method with tree-based wavelet parameterization. The wavelet parameterization used a hierarchical prior for wavelet coefficients which could adapt to the data. We applied these inversion methods for ambient noise tomography of the western part of Java, Indonesia. This area is an area prone to multiple geological hazards due to its proximity to the subduction of the Australia Plate beneath Eurasia. It is therefore important to have a better understanding of upper crustal structure to support seismic hazard and disaster mitigation efforts in this area. We utilized a new waveform dataset collected from 85 temporary seismometers deployed during 2016–2018. Cross-correlation of the waveform data was applied to retrieve empirical Rayleigh wave Green's functions between station pairs, and the spatial distribution of group velocity was obtained by inverting dispersion curves. Our results show that, although computationally expensive, the Trans-dimensional Bayesian approach offered important advantages over optimization, including more effective explorative of the model space and more robust characterization of the spatial pattern of Rayleigh wave group velocity. Meanwhile, the iterative, least-square subspace optimization suffered from the subjectivity of choice for reference velocity model and regularization parameter values. Our Rayleigh wave group velocity results show that for short (1–10 s) periods group velocity correlates well with surface geology, and for longer periods (13–25 s) it correlates with centers of volcanic activity.

scholarly journals Delineation of Upper Crustal Structure Beneath the Island of Lombok, Indonesia, Using Ambient Seismic Noise Tomography

2021 ◽  
Vol 9 ◽  
Author(s):  
Achmad F. N. Sarjan ◽  
Zulfakriza Zulfakriza ◽  
Andri D. Nugraha ◽  
Shindy Rosalia ◽  
Shengji Wei ◽  
...  
Keyword(s):  
Group Velocity ◽  
Ambient Noise ◽  
Velocity Structure ◽  
Seismic Velocity ◽  
Inversion Method ◽  
Good Resolution ◽  
Ambient Noise Tomography ◽  
Fast Marching ◽  
Waveform Data ◽  
Short Period

We have successfully conducted the first ambient noise tomography on the island of Lombok, Indonesia using local waveform data observed at 20 temporary stations. Ambient noise tomography was used to delineate the seismic velocity structure in the upper crust. The waveform data were recorded from August 3rd to September 9th, 2018, using short-period and broadband sensors. There are 185 Rayleigh waves retrieved from cross-correlating the vertical components of the seismograms. We used frequency-time analysis (FTAN) to acquire the interstation group velocity from the dispersion curves. Group velocity was obtained for the period range of 1 s to 6 s. The group velocity maps were generated using the subspace inversion method and Fast Marching Method (FMM) to trace ray-paths of the surface waves through a heterogeneous medium. To extract the shear wave velocity (Vs) from the Rayleigh wave group velocity maps, we utilize the Neighborhood Algorithm (NA) method. The 2-D tomographic maps provide good resolution in the center and eastern parts of Lombok. The tomograms show prominent features with a low shear velocity that appears up to 4 km depth beneath Rinjani Volcano, Northern Lombok, and Eastern Lombok. We suggest these low velocity anomalies are associated with Quaternary volcanic products, including the Holocene pyroclastic deposits of Samalas Volcano (the ancient Rinjani Volcano) which erupted in 1257. The northeast of Rinjani Volcano is characterized by higher Vs, and we suggest this may be due to the presence of igneous intrusive rock at depth.

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

2019 ◽  
Vol 220 (3) ◽  
pp. 1965-1977 ◽  
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.

Near-surface Structure of Downtown Jinan, China: Application of Ambient Noise Tomography with a Dense Seismic Array

2019 ◽  
Vol 24 (4) ◽  
pp. 641-652
Author(s):  
Feng Liang ◽  
Zhihui Wang ◽  
Hailong Li ◽  
Kai Liu ◽  
Tao Wang
Keyword(s):  
Surface Wave ◽  
Human Activities ◽  
High Frequency ◽  
Urban Areas ◽  
Ambient Noise ◽  
Velocity Structure ◽  
Shear Velocity ◽  
Ambient Noise Tomography ◽  
Surface Wave Dispersion ◽  
Near Surface

Urban geophysics ups the ante in the world of applied geophysics, which requires innovative thinking and seemingly off-the-wall approaches, if for no other reason than the settings. Ambient-noise-tomography (ANT) can play a pivotal role in yielding subsurfa2ce information in urban areas, which is capable of dealing with challenges related to these scenarios ( e.g., human activities and low signal-to-noise ratio). In this study, the ANT was conducted to investigate the near-surface shear-velocity structure in the surrounding area of the Baotu Spring Park in downtown Jinan, Shandong Province, China. Quiet clear Rayleigh waves have been obtained by the cross-correlation, which indicates that strong human activities, such as moving vehicles and municipal engineering constructions, can produce approximately isotropic distribution of noise sources for high-frequency signals. The direct surface-wave tomographic method with period-dependent ray-tracing was used to invert all surface-wave dispersion data in the period band 0.2-1.5 s simultaneously for 3D variations of shear-velocity (Vs) structure. Our results show a good correspondence to the geological features with thinner Quaternary sediments, the geological structural characteristic of the limestone surrounded by the igneous which has the highest velocity than that of the limestone in the study area, and several concealed faults of which specific location has been detected at depth. The results demonstrate that it is possible to successfully use ANT with high-frequency signal in an urban environment provided a detailed planning and execution is implemented.

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