Generation of a pseudo-2D shear-wave velocity section by inversion of a series of 1D dispersion curves

2008 ◽  
Vol 64 (3-4) ◽  
pp. 115-124 ◽  
Author(s):  
Yinhe Luo ◽  
Jianghai Xia ◽  
Jiangping Liu ◽  
Yixian Xu ◽  
Qingsheng Liu
Keyword(s):  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Dispersion Curves ◽  
Velocity Section

Experimental Estimation of Shear Wave Velocity Profile Using MASW Method and Inversion Technique

2013 ◽  
Vol 300-301 ◽  
pp. 955-958
Author(s):  
Pei Hsun Tsai ◽  
Chih Chun Lou
Keyword(s):  
Genetic Algorithm ◽  
Velocity Profile ◽  
Dispersion Curve ◽  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Dispersion Curves ◽  
Real Parameter ◽  
Shear Wave Velocity Profile ◽  
Experimental Dispersion

In the paper the shear wave velocity profile is studied using the MASW test. The experimental dispersion curves were obtained from the signal process proposed by Ryden. Theoretical dispersion curve can be constructed by thin layer stiffness matrix method. A real-parameter genetic algorithm is required to minimize the error between the theoretical and experimental dispersion curves. To reduce the error of experimental and theoretical dispersion curve using real-parameter genetic algorithm is feasible. The results show that the soil layers of the study area can be modeled as a sandy fill overlaid on an underlying half space. Test results also show that the asymptotes at high frequencies of the fundamental mode approach the phase velocities for the fill of 190 m/s. The depths of weathered bedrock estimating from dispersion curves match well with that of borehole data.

Shear wave velocity model of the ABANICO formation underlying The santiago City Metropolitan Area, chile, using ambient seismic noise tomography

2020 ◽  
Author(s):  
J Salomón ◽  
C Pastén ◽  
S Ruiz ◽  
F Leyton ◽  
M Sáez ◽  
...  
Keyword(s):  
Shear Wave ◽  
Wave Velocity ◽  
Metropolitan Area ◽  
Shear Wave Velocity ◽  
Seismic Noise ◽  
Velocity Model ◽  
Dispersion Curves ◽  
Ambient Seismic Noise ◽  
Travel Times ◽  
Abanico Formation

Summary The seismic response of the Santiago City, the capital of Chile with more than 5.5 million inhabitants, is controlled by the properties of the shallower quaternary deposits and the impedance contrast with the underlying Abanico formation, among other factors. In this study, we process continuous records of ambient seismic noise to perform an ambient seismic noise tomography with the aim of defining the shallower structure of the Abanico formation underneath the densely populated metropolitan area of Santiago, Chile. The seismic signals were recorded by a network consisting of 29 broadband seismological stations and 12 accelerograph stations, located in a 35 × 35 km2 quadrant. We used the average coherency of the vertical components to calculate dispersion curves from 0.1 to 5 Hz and Bootstrap resampling to estimate the variance of the travel times. The reliable frequency band of the dispersion curves was defined by an empirical method based on sign normalization of the coherency real part. The ambient noise tomography was solved on a domain discretized into 256 2 × 2 km2 cells. Using a regularized weighted least squares inversion, we inverted the observed travel-times between stations, assuming straight ray paths, in order to obtain 2D phase velocity maps from 0.2 Hz to 1.1 Hz, linearly spaced every 0.05 Hz, in 157 of the 256 square cells of the domain. In each square cell with information, dispersion curves were assembled and used to invert shear wave velocity profiles, which were interpolated using the ordinary Kriging method to obtain a 3D shear wave velocity model valid from 0.6 to 5 km depth. The 3D velocity model shows that the Abanico formation is stiffer in the south of the study area with larger velocity anomalies towards the shallower part of the model. The value of the shear wave velocity narrows with depth, reaching an average value of 3.5 km/s from 3 to 5 km depth.

The complementarity of H/V and dispersion curves

Geophysics ◽  
2016 ◽  
Vol 81 (6) ◽  
pp. T323-T338 ◽  
Author(s):  
Silvia Castellaro
Keyword(s):  
Surface Waves ◽  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Love Wave ◽  
Velocity Profiles ◽  
Dispersion Curves ◽  
Source Surface ◽  
Diagnostic Features ◽  
Single Station

Noninvasive geophysical techniques based on the dispersion of surface waves in layered media are commonly used approaches for measuring shear-wave velocity profiles of the subsoil. Acquiring surface waves is a simple task, but the interpretation of their dispersion curves poses a number of challenges. In an increasing number of cases, shear-wave velocity profiles are derived from the inversion of dispersion curves of surface waves and single-station passive horizontal-to-vertical (H/V) spectral ratios, mostly using a blind joint fit of the two sets of curves. Here we emphasize the benefits of carrying out H/V surveys prior to any array acquisition. We propose to start by collecting at least two H/V recordings at a site to verify the 1D plane-parallel soil condition, as this is essential in dispersion curve inversion/modeling. Then, we look for the diagnostic features of velocity inversions in the H/V curves: when they occur, the interpretation of dispersion curves is made difficult by mode splitting/superposition and Love wave arrays will not be effective. Then we inspect the shape of the H/V curves: flat curves acquired on rock usually imply poor dispersion curves. Large receiver spacings are recommended in the arrays and Love wave arrays will not be efficient. Flat curves on soft material sites represent gently increasing [Formula: see text] gradients and Rayleigh wave arrays should be preferred. H/V curves with high frequency peaks indicate shallow impedance contrasts: this makes Love wave arrays efficient for the soft layer characterization, but provide little information at depth. H/V curves with low frequency peaks indicate deep bedrock and their inversion can provide approximate [Formula: see text] profiles down to greater depths than from an array. Equipped with the information coming from accurate H/V observations, practitioners could make better-informed decisions about array acquisition geometries, source/surface wave types, and inversion strategies.

scholarly journals Shear-wave Velocity Structure of Greenland from Rayleigh-wave Analysis

2016 ◽  
Vol 20 (1) ◽  
pp. 1-11 ◽  
Author(s):  
V. Corchete
Keyword(s):  
Rayleigh Wave ◽  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Velocity Structure ◽  
Wave Dispersion ◽  
Dispersion Curves ◽  
Depth Range ◽  
Velocity Models ◽  
Rayleigh Wave Dispersion

<p>The elastic structure beneath Greenland is shown by means of S-velocity maps for depths ranging from zero to 350 km, determined by the regionalization and inversion of Rayleigh-wave dispersion. The traces of 50 earthquakes, occurring from 1990 to 2011, have been used to obtain Rayleigh-wave dispersion data. These earthquakes were registered by 21 seismic station located in Greenland and the surrounding area. The dispersion curves were obtained for periods between 5 and 200 s, by digital filtering with a combination of MFT (Multiple Filter Technique) and TVF (Time Variable Filtering). Later, all seismic events (and some stations) were grouped to obtain a dispersion curve for each source-station path. These dispersion curves were regionalized and inverted according to the generalized inversion theory, to obtain shear-wave velocity models for a rectangular grid of 16x20 points. The shear-velocity structure obtained through this procedure is shown in the S-velocity maps plotted for several depths. These results agree well with the geology and other geophysical results previously obtained. The obtained S-velocity models suggest the existence of lateral and vertical heterogeneity. The zones with consolidated and old structures present greater S-velocity values than the other zones, although this difference can be very little or negligible in some case. Nevertheless, in the depth range of 15 to 45 km, the different Moho depths present in the study area generate the principal variation of S-velocity. A similar behaviour is found for the depth range from 80 to 230 km, in which the lithosphere-asthenosphere boundary (LAB) generates the principal variations of S-velocity. Finally, the new and interesting feature obtained in this study: the definition of the base of the asthenosphere (for the whole study area and for depths ranging from 130 to 280 km, respectively) should be highlighted.</p><p> </p><p><strong>Estructura de velocidad de cizalla de Groenlandia obtenida de análisis de onda Rayleigh</strong></p><p><strong><br /></strong></p><p><strong>Resumen</strong></p><p>La estructura elástica bajo Groenlandia es mostrada por medio de mapas de velocidad de onda para profundidades variando desde cero a 350 km, determinada por la regionalización e inversión de la dispersión de onda Rayleigh. Las trazas de 50 terremotos, ocurridos desde 1990 hasta 2011, han sido usados para obtener datos de dispersión de onda Rayleigh. Estos terremotos fueron registrados por 21 estaciones sísmicas localizadas en Groenlandia y el área circundante. Las curvas de dispersión fueron obtenidas para periodos entre 5 y 200 s, por filtrado digital con una combinación de MFT (Técnica de Filtrado Múltiple) y TVF (Filtrado en Tiempo Variable). Después, todos los eventos sísmicos (y algunas estaciones) fueron agrupados para obtener una curva de dispersión para cada trayecto fuente-estación. Estas curvas de dispersión fueron regionalizadas e invertidas de acuerdo con la teoría de la inversión generalizada, para obtener modelos de velocidad de cizalla para una rejilla rectangular de 16x20 puntos. La estructura de velocidad de cizalla obtenida a través de este procedimiento es mostrada in los mapas de velocidad de onda S representados para varias profundidades. Estos resultados muestran buen acuerdo con la geología y con otros resultados geofísicos obtenidos previamente. Los modelos de velocidad de onda S obtenidos sugieren la existencia de heterogeneidad lateral y vertical. Las zonas con estructuras antiguas y consolidadas presentan mayores valores de velocidad de onda S que las otras zonas, aunque esta diferencia puede ser muy pequeña o despreciable en algún caso. No obstante, en el rango de profundidad de 15 a 45 km, las diferentes profundidades del Moho presentes en el área de estudio generan la principal variación de velocidad de onda S. Un comportamiento similar es encontrado para el rango de profundidad desde 80 a 230 km, en el cual la frontera litosfera-astenosfera (LAB) genera las principales variaciones de velocidad de onda S. Finalmente, debería ser destacada la nueva e interesante característica obtenida en este estudio: la definición de la base de la astenosfera (para el área de estudio completa y para profundidades variando desde 130 a 280 km, respectivamente).</p>

scholarly journals Shear-wave velocity measurements and their uncertainties at six industrial sites

2021 ◽  
pp. 875529302098802
Author(s):  
Yaniv Darvasi
Keyword(s):  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Dispersion Curves ◽  
Shallow Subsurface ◽  
Industrial Sites ◽  
Wave Measurements ◽  
Average Shear ◽  
The Individual ◽  
Industrial Zones

This study assesses the variability of shear-wave ( VS) profile determinations for a suite of methods at six industrial sites. The methods include active, consisting of multi-channel analysis of surface waves (MASW), as well as passive, consisting of refraction microtremor (ReMi), and extended spatial autocorrelation (ESAC). The purpose is to ascertain the effect of the higher level of ambient noise on the results from the different methods, as only a few of these many methods are commonly used for site characterization. The measured dispersion curves are in fair agreement with one another. The average coefficient of variation (CoV; the percentage ratio of the standard deviation to the mean) for the dispersion curves varied from 2.5% to 12.6%. In contrast, over the VS-depth domain, the average shear-wave velocity profiles to a depth z ( VS,Z) vary from 11.6% to 16.5% between the various methods at the different sites. This indicates that the variance among the individual methods can lead to significant misinterpretation of the shallow subsurface, while the average VS,Z is much more robust. This reaffirms its use (mainly as VS,30) in building codes and within ground motion prediction equations (GMPEs). At all six sites, because of inversion processes, the variability within each method ranges from 4% up to 14%. There is no correlation between the test type and the CoV. Our study focused on surface-wave measurements in noisy industrial environments, where the signals processed are typically complex. Despite this complexity, our results suggest that such tests are also applicable to industrial zones, where the noisy environment constitutes an energy source.

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