scholarly journals Structure of the Suasselkä postglacial fault in northern Finland obtained by analysis of local events and ambient seismic noise

Solid Earth ◽  
2017 ◽  
Vol 8 (2) ◽  
pp. 531-544 ◽  
Author(s):  
Nikita Afonin ◽  
Elena Kozlovskaya ◽  
Ilmo Kukkonen ◽  
Keyword(s):  
Seismic Noise ◽  
Ambient Seismic Noise ◽  
Seismic Events ◽  
S Wave ◽  
Noise Sources ◽  
Surface Wave Dispersion ◽  
Velocity Models ◽  
Wave Velocities ◽  
Short Period ◽  
Single Station

Abstract. Understanding the inner structure of seismogenic faults and their ability to reactivate is particularly important in investigating the continental intraplate seismicity regime. In our study we address this problem using analysis of local seismic events and ambient seismic noise recorded by the temporary DAFNE array in the northern Fennoscandian Shield. The main purpose of the DAFNE/FINLAND passive seismic array experiment was to characterize the present-day seismicity of the Suasselkä postglacial fault (SPGF), which was proposed as one potential target for the DAFNE (Drilling Active Faults in Northern Europe) project. The DAFNE/FINLAND array comprised an area of about 20 to 100 km and consisted of eight short-period and four broadband three-component autonomous seismic stations installed in the close vicinity of the fault area. The array recorded continuous seismic data during September 2011–May 2013. Recordings of the array have being analysed in order to identify and locate natural earthquakes from the fault area and to discriminate them from the blasts in the Kittilä gold mine. As a result, we found a number of natural seismic events originating from the fault area, which proves that the fault is still seismically active. In order to study the inner structure of the SPGF we use cross-correlation of ambient seismic noise recorded by the array. Analysis of azimuthal distribution of noise sources demonstrated that during the time interval under consideration the distribution of noise sources is close to the uniform one. The continuous data were processed in several steps including single-station data analysis, instrument response removal and time-domain stacking. The data were used to estimate empirical Green's functions between pairs of stations in the frequency band of 0.1–1 Hz and to calculate corresponding surface wave dispersion curves. The S-wave velocity models were obtained as a result of dispersion curve inversion. The results suggest that the area of the SPGF corresponds to a narrow region of low S-wave velocities surrounded by rocks with high S-wave velocities. We interpret this low-velocity region as a non-healed mechanically weak fault damage zone (FDZ) formed due to the last major earthquake that occurred after the last glaciation.

scholarly journals Structure of Suasselkä Postglacial Fault in northern Finland obtained by analysis of local events and ambient seismic noise

2016 ◽  
Author(s):  
Nikita Afonin ◽  
Elena Kozlovskaya ◽  
Ilmo Kukkonen ◽  
DAFNE/FINLAND Working Group
Keyword(s):  
Seismic Noise ◽  
Dispersion Curves ◽  
Ambient Seismic Noise ◽  
Seismic Events ◽  
S Wave ◽  
Noise Sources ◽  
Velocity Models ◽  
Wave Velocities ◽  
Short Period ◽  
Single Station

Abstract. Understanding inner structure of seismogenic faults and their ability to reactivate is particularly important in investigating continental intraplate seismicity regime. In our study we address this problem using analysis of local seismic events and ambient seismic noise recorded by the temporary DAFNE array in northern Fennoscandian Shield. The main purpose of the DAFNE/FINLAND passive seismic array experiment was to characterize the present-day seismicity of the Suasselkä post-glacial fault (SPGF) that was proposed as one potential target for the DAFNE (Drilling Active Faults in Northern Europe) project. The DAFNE/FINLAND array comprised the area of about 20 to 100 km and consisted of 8 short-period and 4 broad-band 3-component autonomous seismic stations installed in the close vicinity of the fault area. The array recorded continuous seismic data during September, 2011–May, 2013. Recordings of the array have being analyzed in order to identify and locate natural earthquakes from the fault area and to discriminate them from the blasts in the Kittilä Gold Mine. As a result, we found several dozens of natural seismic events originating from the fault area, which proves that the fault is still seismically active. In order to study the inner structure of the SPGF we use cross-correlation of ambient seismic noise recorded by the array. Analysis of azimuthal distribution of noise sources demonstrated that during the time interval under consideration the distribution of noise sources is close to the uniform one. The continuous data were processed in several steps including single station data analysis, instrument response removal and time-domain stacking. The data were used to estimate empirical Green’s functions between pairs of stations in the frequency band of 0.1–1 Hz and to calculate correspondent surface wave dispersion curves. The S-wave velocity models were obtained as a result of dispersion curves inversion. The results suggest that the area of the SPGF corresponds to a narrow region of low S-wave velocities surrounded by rocks with high S-wave velocities. We interpret this low velocity region as a non-healed mechanically weak fault damage zone (FDZ) that remained after the last major earthquake that occurred after the last glaciation.

Ambient-Noise Tomography of the Baiyun Gold Deposit in Liaoning, China

2020 ◽  
Vol 91 (5) ◽  
pp. 2791-2802 ◽  
Author(s):  
Xuantao Li ◽  
Jinli Huang ◽  
Zhikun Liu
Keyword(s):  
Gold Deposit ◽  
Wave Velocity ◽  
Ambient Noise ◽  
Velocity Structure ◽  
S Wave ◽  
Ambient Noise Tomography ◽  
Surface Wave Dispersion ◽  
Wave Velocities ◽  
Metal Mine ◽  
Single Station

Abstract Ambient-noise tomography (ANT) has become an effective method for determining the fine velocity structure of the shallow crust. However, studies on metal mines using this method are rarely reported. To investigate the tectonic background and prospecting of the deep mine in the Baiyun gold deposit (BYGD) of eastern Liaoning Province, China, we use ANT to determine a 3D S-wave velocity structure model of the BYGD. A total of 21 broadband seismic stations were installed in an area of 15×14  km, centered at the BYGD. Continuous observations for approximately three months were made. After single-station preprocessing, cross correlation of ambient noise, and phase-weighted stacking, the empirical Green’s function for the Rayleigh waves between stations was recovered. Next, group-velocity dispersion with 0.8–3 s periods was measured. A direct inversion method of surface-wave dispersion based on raytracing was then adopted to determine a 3D S-wave velocity structure of the BYGD from the ground surface to a depth of 1.8 km. The results show that the distribution of S-wave velocities in the study area well reflected the geological characteristics of the surface. The velocities were significantly low within the “ore field” and the regional ore-controlling Jianshanzi fault. Combining this with the fact that a large number of magmatic veins were visible inside both structures, it was deduced that both structures had experienced large-scale magmatic intrusion activities, thus confirming that BYGD was a magmatic hydrothermal deposit. The significantly low S-wave velocities beneath the gold deposit extended to a depth of 1.8 km. This might imply the occurrence of blind ore bodies at that depth. The fine velocity structure of the BYGD reconstructed by this study provided a direction for subsequent prospecting of deep regions and demonstrated that ANT has good potential in metal mine exploration.

scholarly journals Crustal Velocity Models Retrieved from Surface Wave Dispersion Data for Gujarat Region, Western Peninsular India

2019 ◽  
Vol 23 (2) ◽  
pp. 147-155
Author(s):  
Vishwa Joshi
Keyword(s):  
Wave Dispersion ◽  
Data File ◽  
Western India ◽  
Nonlinear Inversion ◽  
S Wave ◽  
Surface Wave Dispersion ◽  
Peninsular India ◽  
Velocity Models ◽  
Crustal Velocity ◽  
Dispersion Data

The physiographic features of Gujarat state of western India are unique, as they behaved dynamically with several alterations and modifications throughout the geological timescale. It displays a remarkable example of a terrain bestowed with geological, physiographical and climatic diversities. The massive 2001 Bhuj earthquake (M 7.7) over the Kachchh region caused severe damage and devastation to the state of Gujarat and attracted the scientific community of the world to comprehend on its structure and tectonics for future hazard reduction. In the present study, three clusters of wave paths A, B1, and B2 have considered. In each cluster, dispersion data were measured station by station which collectively formed a dispersion data file for a nonlinear inversion through Genetic algorithm. In this way, three crustal velocity models were generated for entire Gujarat. These models are 1) Across Cambay Basin (Path A), 2) Along Saurashtra - Kathiawar Horst (Path B1) and 3) Along Narmada Basin (Path B2), which were formed at different times during the Mesozoic. The average thickness of the crust estimated in the present study for paths A, B1 and B2 are 38.2 km, 36.2 km, and 41.6 km respectively and the estimated S-wave velocity in the lower crust is ~ 3.9 km/s for all the paths. The present study will improve our knowledge about the structure of the seismogenic layer of this active intraplate region 

scholarly journals Imaging New Zealand's Crustal Structure Using Ambient Seismic Noise Recordings from Permanent and Temporary Instruments

2021 ◽  
Author(s):  
◽  
Yannik Behr
Keyword(s):  
Seismic Noise ◽  
Cross Correlation ◽  
Velocity Structure ◽  
Shear Velocity ◽  
Ambient Seismic Noise ◽  
Uppermost Mantle ◽  
Noise Sources ◽  
Noise Field ◽  
Rayleigh And Love Waves ◽  
Noise Cross Correlation

<p>We use ambient seismic noise to image the crust and uppermost mantle, and to determine the spatiotemporal characteristics of the noise field itself, and examine the way in which those characteristics may influence imaging results. Surface wave information extracted from ambient seismic noise using cross-correlation methods significantly enhances our knowledge of the crustal and uppermost mantle shear-velocity structure of New Zealand. We assemble a large dataset of three-component broadband continuous seismic data from temporary and permanent seismic stations, increasing the achievable resolution of surface wave velocity maps in comparison to a previous study. Three-component data enables us to examine both Rayleigh and Love waves using noise cross-correlation functions. Employing a Monte Carlo inversion method, we invert Rayleigh and Love wave phase and group velocity dispersion curves separately for spatially averaged isotropic shear velocity models beneath the Northland Peninsula. The results yield first-order radial anisotropy estimates of 2% in the upper crust and up to 15% in the lower crust, and estimates of Moho depth and uppermost mantle velocity compatible with previous studies. We also construct a high-resolution, pseudo-3D image of the shear-velocity distribution in the crust and uppermost mantle beneath the central North Island using Rayleigh and Love waves. We document, for the first time, the lateral extent of low shear-velocity zones in the upper and mid-crust beneath the highly active Taupo Volcanic Zone, which have been reported previously based on spatially confined 1D shear-velocity profiles. Attributing these low shear-velocities to the presence of partial melt, we use an empirical relation to estimate an average percentage of partial melt of < 4:2% in the upper and middle crust. Analysis of the ambient seismic noise field in the North Island using plane wave beamforming and slant stacking indicates that higher mode Rayleigh waves can be detected, in addition to the fundamental mode. The azimuthal distributions of seismic noise sources inferred from beamforming are compatible with high near-coastal ocean wave heights in the period band of the secondary microseism (~7 s). Averaged over 130 days, the distribution of seismic noise sources is azimuthally homogeneous, indicating that the seismic noise field is well-suited to noise cross-correlation studies. This is underpinned by the good agreement of our results with those from previous studies. The effective homogeneity of the seismic noise field and the large dataset of noise cross-correlation functions we here compiled, provide the cornerstone for future studies of ambient seismic noise and crustal shear velocity structure in New Zealand.</p>

P- and S-wave velocity models from surface wave dispersion curves data transform

2017 ◽  
Author(s):  
Valentina Socco ◽  
Farbod Khosro Anjom ◽  
Cesare Comina ◽  
Daniela Teodor
Keyword(s):  
Surface Wave ◽  
Wave Velocity ◽  
Wave Dispersion ◽  
Dispersion Curves ◽  
S Wave ◽  
Surface Wave Dispersion ◽  
Velocity Models

Shallow velocity structure and poisson's ratio at the Tarzana, California, strong-motion accelerometer site

1996 ◽  
Vol 86 (6) ◽  
pp. 1704-1713 ◽  
Author(s):  
R. D. Catchings ◽  
W. H. K. Lee
Keyword(s):  
Urban Areas ◽  
Velocity Structure ◽  
Strong Motion ◽  
P Wave ◽  
S Wave ◽  
Near Surface ◽  
Velocity Models ◽  
Wave Velocities ◽  
Poisson's Ratios ◽  
Poisson’S Ratios

Abstract The 17 January 1994, Northridge, California, earthquake produced strong ground shaking at the Cedar Hills Nursery (referred to here as the Tarzana site) within the city of Tarzana, California, approximately 6 km from the epicenter of the mainshock. Although the Tarzana site is on a hill and is a rock site, accelerations of approximately 1.78 g horizontally and 1.2 g vertically at the Tarzana site are among the highest ever instrumentally recorded for an earthquake. To investigate possible site effects at the Tarzana site, we used explosive-source seismic refraction data to determine the shallow (&lt;70 m) P-and S-wave velocity structure. Our seismic velocity models for the Tarzana site indicate that the local velocity structure may have contributed significantly to the observed shaking. P-wave velocities range from 0.9 to 1.65 km/sec, and S-wave velocities range from 0.20 and 0.6 km/sec for the upper 70 m. We also found evidence for a local S-wave low-velocity zone (LVZ) beneath the top of the hill. The LVZ underlies a CDMG strong-motion recording site at depths between 25 and 60 m below ground surface (BGS). Our velocity model is consistent with the near-surface (&lt;30 m) P- and S-wave velocities and Poisson's ratios measured in a nearby (&lt;30 m) borehole. High Poisson's ratios (0.477 to 0.494) and S-wave attenuation within the LVZ suggest that the LVZ may be composed of highly saturated shales of the Modelo Formation. Because the lateral dimensions of the LVZ approximately correspond to the areas of strongest shaking, we suggest that the highly saturated zone may have contributed to localized strong shaking. Rock sites are generally considered to be ideal locations for site response in urban areas; however, localized, highly saturated rock sites may be a hazard in urban areas that requires further investigation.

Full-waveform matching of VP and VS models from surface waves

2019 ◽  
Vol 218 (3) ◽  
pp. 1873-1891 ◽  
Author(s):  
Farbod Khosro Anjom ◽  
Daniela Teodor ◽  
Cesare Comina ◽  
Romain Brossier ◽  
Jean Virieux ◽  
...  
Keyword(s):  
Surface Waves ◽  
Wave Velocity ◽  
Real Data ◽  
Test Site ◽  
P Wave ◽  
S Wave ◽  
Surface Wave Dispersion ◽  
Data Set ◽  
Near Surface ◽  
Velocity Models

SUMMARY The analysis of surface wave dispersion curves (DCs) is widely used for near-surface S-wave velocity (VS) reconstruction. However, a comprehensive characterization of the near-surface requires also the estimation of P-wave velocity (VP). We focus on the estimation of both VS and VP models from surface waves using a direct data transform approach. We estimate a relationship between the wavelength of the fundamental mode of surface waves and the investigation depth and we use it to directly transform the DCs into VS and VP models in laterally varying sites. We apply the workflow to a real data set acquired on a known test site. The accuracy of such reconstruction is validated by a waveform comparison between field data and synthetic data obtained by performing elastic numerical simulations on the estimated VP and VS models. The uncertainties on the estimated velocity models are also computed.

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