scholarly journals Velocity structure of the Whataroa Valley using Ambient Noise Tomography

2021 ◽  
Author(s):  
◽  
Andy McNab
Keyword(s):  
Rayleigh Wave ◽  
Group Velocity ◽  
Shear Wave Velocity ◽  
Correlation Functions ◽  
Ambient Noise ◽  
Cross Correlation ◽  
Velocity Dispersion ◽  
Group Velocity Dispersion ◽  
Velocity Model ◽  
Ambient Noise Tomography

<p>This thesis applies ambient noise tomography to investigate the shallow structure of the Whataroa Valley. Ambient noise techniques are applied to continuous seismic recordings acquired on 158 geophones deployed during the Whataroa Active Source Seismic Experiment. Despite only having four days of data, a robust shear-wave velocity model is calculated using a phase-weighted stacking approach to improve the cross-correlation functions' signal-to-noise ratios, allowing for robust velocity measurements to be obtained between periods of 0.3 and 1.8\,s. This yields a database of 12,500 vertical component cross correlation functions and the corresponding Rayleigh wave phase and group velocity dispersion curves. Linearised straight-ray tomography is applied to phase and group velocity dispersion measurements at periods ranging from periods of 0.3 to 1.8\,s. The tomography reveals a velocity that decreases from the vicinity of the DFDP-2B borehole to the centre of the valley. This is interpreted to be the geologic basement deepening towards the centre of the valley. A Monte-Carlo inversion technique is used to jointly invert Rayleigh-wave phase and group velocity dispersion curves constructed from phase and group velocity tomography maps of successively higher periods. Linear interpolation of the resulting 1D shear-wave velocity profiles produces a pseudo-3D velocity model of the uppermost 1,000\,m of the Whataroa Valley. Using sharp increases in velocity to represent lithological change, we interpret two velocity contours at 1,150 and 1,250\,m/s as potential sediment-basement contacts. Depth isocontours of these velocities reveal that the basement deepens towards the centre of the valley, reaching a maximum depth of 400 or 600\,m for the 1,150 and 1,250\,m/s velocity contours respectively. These depths indicate strong glacial over-deepening and have implications for future drilling projects in the Whataroa Valley. A sharp velocity increase of 200\,m/s also occurs at 100\,m depth at the DFDP-2B borehole. We interpret this to be a change in sedimentary rock lithology from fluvial gravels to lacustrine silty sands, related to a change in sedimentary depositional environment.</p>

scholarly journals Velocity structure of the Whataroa Valley using Ambient Noise Tomography

2021 ◽  
Author(s):  
◽  
Andy McNab
Keyword(s):  
Rayleigh Wave ◽  
Group Velocity ◽  
Shear Wave Velocity ◽  
Correlation Functions ◽  
Ambient Noise ◽  
Cross Correlation ◽  
Velocity Dispersion ◽  
Group Velocity Dispersion ◽  
Velocity Model ◽  
Ambient Noise Tomography

<p>This thesis applies ambient noise tomography to investigate the shallow structure of the Whataroa Valley. Ambient noise techniques are applied to continuous seismic recordings acquired on 158 geophones deployed during the Whataroa Active Source Seismic Experiment. Despite only having four days of data, a robust shear-wave velocity model is calculated using a phase-weighted stacking approach to improve the cross-correlation functions' signal-to-noise ratios, allowing for robust velocity measurements to be obtained between periods of 0.3 and 1.8\,s. This yields a database of 12,500 vertical component cross correlation functions and the corresponding Rayleigh wave phase and group velocity dispersion curves. Linearised straight-ray tomography is applied to phase and group velocity dispersion measurements at periods ranging from periods of 0.3 to 1.8\,s. The tomography reveals a velocity that decreases from the vicinity of the DFDP-2B borehole to the centre of the valley. This is interpreted to be the geologic basement deepening towards the centre of the valley. A Monte-Carlo inversion technique is used to jointly invert Rayleigh-wave phase and group velocity dispersion curves constructed from phase and group velocity tomography maps of successively higher periods. Linear interpolation of the resulting 1D shear-wave velocity profiles produces a pseudo-3D velocity model of the uppermost 1,000\,m of the Whataroa Valley. Using sharp increases in velocity to represent lithological change, we interpret two velocity contours at 1,150 and 1,250\,m/s as potential sediment-basement contacts. Depth isocontours of these velocities reveal that the basement deepens towards the centre of the valley, reaching a maximum depth of 400 or 600\,m for the 1,150 and 1,250\,m/s velocity contours respectively. These depths indicate strong glacial over-deepening and have implications for future drilling projects in the Whataroa Valley. A sharp velocity increase of 200\,m/s also occurs at 100\,m depth at the DFDP-2B borehole. We interpret this to be a change in sedimentary rock lithology from fluvial gravels to lacustrine silty sands, related to a change in sedimentary depositional environment.</p>

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.

scholarly journals Ambient noise cross-correlation observations of fundamental and higher-mode Rayleigh wave propagation governed by basement resonance

2021 ◽  
Author(s):  
Martha Savage ◽  
FC Lin ◽  
John Townend
Keyword(s):  
Rayleigh Wave ◽  
Correlation Functions ◽  
Rayleigh Waves ◽  
Ambient Noise ◽  
Cross Correlation ◽  
Amplitude Ratio ◽  
Sedimentary Basins ◽  
Longitudinal Motion ◽  
Resonance Frequencies ◽  
Noise Cross Correlation

Measurement of basement seismic resonance frequencies can elucidate shallow velocity structure, an important factor in earthquake hazard estimation. Ambient noise cross correlation, which is well-suited to studying shallow earth structure, is commonly used to analyze fundamental-mode Rayleigh waves and, increasingly, Love waves. Here we show via multicomponent ambient noise cross correlation that the basement resonance frequency in the Canterbury region of New Zealand can be straightforwardly determined based on the horizontal to vertical amplitude ratio (H/V ratio) of the first higher-mode Rayleigh waves. At periods of 1-3 s, the first higher-mode is evident on the radial-radial cross-correlation functions but almost absent in the vertical-vertical cross-correlation functions, implying longitudinal motion and a high H/V ratio. A one-dimensional regional velocity model incorporating a ~ 1.5 km-thick sedimentary layer fits both the observed H/V ratio and Rayleigh wave group velocity. Similar analysis may enable resonance characteristics of other sedimentary basins to be determined. © 2013. American Geophysical Union. All Rights Reserved.

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

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

&lt;p&gt;&lt;span&gt;We have successfully derived a new &lt;/span&gt;&lt;span&gt;3-D&lt;/span&gt;&lt;span&gt; high resolution shear wave velocity model of the crust and uppermost mantle of a large part of W-Europe from transdimensional&lt;/span&gt;&lt;span&gt;&lt;strong&gt; &lt;/strong&gt;&lt;/span&gt;&lt;span&gt;ambient-noise tomography. This model is intended to contribute to the development of the first &lt;/span&gt;&lt;span&gt;3-D&lt;/span&gt;&lt;span&gt; crustal-scale integrated geophysical-geological model of the W-Alps to deepen understanding of orogenesis and its relationship to mantle dynamics. &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;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.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;We firstly performed a &lt;/span&gt;&lt;span&gt;2-D&lt;/span&gt;&lt;span&gt; data-driven transdimensional travel time inversion for group velocity maps from 4 to 150 s (Bodin &amp; 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 &amp; 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&lt;/span&gt;&lt;span&gt; approach proposed by Lu et al (2018) by including group velocity uncertainties. Posterior probability distributions on &lt;/span&gt;&lt;span&gt;Vs&lt;/span&gt;&lt;span&gt; and interfaces were estimated by exploring a set of 130 millions synthetic &lt;/span&gt;&lt;span&gt;4-&lt;/span&gt;&lt;span&gt;layer &lt;/span&gt;&lt;span&gt;1-D Vs&lt;/span&gt;&lt;span&gt; models that allow for &lt;/span&gt;&lt;span&gt;low-velocity zones&lt;/span&gt;&lt;span&gt;&lt;em&gt;.&lt;/em&gt;&lt;/span&gt;&lt;span&gt; The obtained probabilistic model was refined using a linearized inversion&lt;/span&gt;&lt;span&gt;&lt;em&gt;. &lt;/em&gt;&lt;/span&gt;&lt;span&gt;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 &lt;/span&gt;&lt;span&gt;&amp;&lt;/span&gt;&lt;span&gt; Webb, 2000) and adapted the inversion for Vs to include the water column.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;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&lt;em&gt; &lt;/em&gt;structure (50 - 80 km) in the prolongation&lt;em&gt; &lt;/em&gt;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.&lt;/p&gt;

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.

Ambient Noise Tomography for Determining the Velocity Model of Rayleigh Wave in Java Island, Indonesia

2018 ◽  
Vol 5 (1) ◽  
pp. 9-13
Author(s):  
Muhajir Anshori ◽  
◽  
Sukir Maryanto ◽  
Tri Deni Rahman ◽  
Azwar Panshori
Keyword(s):  
Rayleigh Wave ◽  
Ambient Noise ◽  
Velocity Model ◽  
Ambient Noise Tomography
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