scholarly journals Frequency‐Bessel Transform Method for Effective Imaging of Higher‐Mode Rayleigh Dispersion Curves From Ambient Seismic Noise Data

2019 ◽  
Vol 124 (4) ◽  
pp. 3708-3723 ◽  
Author(s):  
Jiannan Wang ◽  
Gaoxiong Wu ◽  
Xiaofei Chen
Keyword(s):  
Seismic Noise ◽  
Dispersion Curves ◽  
Ambient Seismic Noise ◽  
Transform Method ◽  
Noise Data ◽  
Bessel Transform

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.

DisperNet: An Effective Method of Extracting and Classifying the Dispersion Curves in the Frequency–Bessel Dispersion Spectrum

2021 ◽  
Author(s):  
Sheng Dong ◽  
Zhengbo Li ◽  
Xiaofei Chen ◽  
Lei Fu
Keyword(s):  
Surface Wave ◽  
Dispersion Curve ◽  
Shear Wave ◽  
Wave Structure ◽  
Wave Dispersion ◽  
Dispersion Curves ◽  
Surface Wave Dispersion ◽  
Transform Method ◽  
Practical Applications ◽  
Noise Data

ABSTRACT The subsurface shear-wave structure primarily determines the characteristics of the surface-wave dispersion curve theoretically and observationally. Therefore, surface-wave dispersion curve inversion is extensively applied in imaging subsurface shear-wave velocity structures. The frequency–Bessel transform method can effectively extract dispersion spectra of high quality from both ambient seismic noise data and earthquake events data. However, manual picking and semiautomatic methods for dispersion curves lack a unified criterion, which impacts the results of inversion and imaging. In addition, conventional methods are insufficiently efficient; more precisely, a large amount of time is required for curve extraction from vast dispersion spectra, especially in practical applications. Thus, we propose DisperNet, a neural network system, to extract and discriminate the different modes of the dispersion curve. DisperNet consists of two parts: a supervised network for dispersion curve extraction and an unsupervised method for dispersion curve classification. Dispersion spectra from ambient noise and earthquake events are applied in training and validation. A field data test and transfer learning test show that DisperNet can stably and efficiently extract dispersion curves. The results indicate that DisperNet can significantly improve multimode surface-wave imaging.

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 seismic noise tomography in west-central and Southern Brazil, characterizing the crustal structure of the Chaco-Paraná, Pantanal and Paraná basins

2019 ◽  
Vol 220 (3) ◽  
pp. 2074-2085
Author(s):  
Taghi Shirzad ◽  
Marcelo Assumpcao ◽  
Marcelo Bianchi
Keyword(s):  
Surface Wave ◽  
Crustal Structure ◽  
Seismic Noise ◽  
Velocity Model ◽  
Dispersion Curves ◽  
Ambient Seismic Noise ◽  
Inversion Method ◽  
Crustal Layer ◽  
West Central ◽  
Lower Crustal

SUMMARY Surface wave analysis provides important information on crustal structure, but it is challenging to obtain accurate/robust models in aseismic regions because of the lack of local earthquake records. In this paper, interstation empirical Green's functions retrieved by ambient seismic noise in 75 broad-band stations from 2016 January to 2018 September were used to study crustal structure in west-central Brazil. Fast marching method was applied to calculate the 2-D surface wave tomographic maps, and local dispersion curves were estimated in the period range of 4–80 s for each geographic cell. 1-D damped least squares inversion method was then conducted to obtained shear wave velocity model. Finally, the average ($\tilde{\rm V}$S) of the calculated VSV and VSH quasi 3-D models were used to characterize the crustal structure. Besides the checkerboard test resolution, a stochastic test with the effect of errors in the dispersion curves and choice of inversion parameters were carried out to better evaluate model uncertainties. Our results show a clear relation between the sedimentary thickness and geological units with the shorter period tomographic maps. Agreement has also been observed in longer periods such as the clear N–S anomaly along the Asuncion and Rio Grande Arches representing the boundary between the Chaco-Paraná and the Paraná basins. A 3-D composite velocity model shows a crustal structure consisting of three main layers. Some differences in lower crustal properties were found between the Paraná and Chaco-Paraná basins, consistent with a recently postulated, gravity-derived Western Paraná suture zone. However, no high velocities along the SW–NE axis of the Paraná basin were found to confirm proposed underplating. At the eastern edge of the Pantanal basin, the thin crust seems to be associated with a very thin (or lack of) lower crustal layer, consistent with a recently proposed crustal delamination hypothesis for the formation of the Pantanal basin.

scholarly journals Joint Inversion of Rayleigh and Love Dispersion Curves Extracted from Ambient Seismic Noise Based on Secular Function

2022 ◽  
Vol 2148 (1) ◽  
pp. 012047
Author(s):  
Feng Gong ◽  
Xiaofei Chen ◽  
Youhua Fan ◽  
Xuefeng Liu ◽  
Haibing Tang
Keyword(s):  
Objective Function ◽  
Dispersion Curve ◽  
Seismic Noise ◽  
Joint Inversion ◽  
Dispersion Curves ◽  
Ambient Seismic Noise ◽  
Inversion Method ◽  
Mode Dispersion ◽  
Mode Discrimination ◽  
Multi Mode

Abstract Traditional multi-mode dispersion curve inversion requires correct mode discrimination. However, when the stratum contains complex structures such as low-speed soft interlayer or high-speed hard interlayer, the dispersion curve may show phenomena such as “mode kissing” and “mode jumping”, which can easily cause mode misjudgment and lead to erroneous inversion results. Based on the “secular function”, this paper constructs a new type of objective function applied to the inversion of dispersion curve. This objective function does not require prior mode discrimination, which effectively solves the “mode misjudgment” problem of multi-mode dispersion curve inversion. The joint inversion of Rayleigh and Love dispersion curves extracted from ambient seismic noise is used to improve the constraint of the inversion and avoid the inversion falling into a local minimum in the case of a large-scale search of parameters. Finally, a numerical simulation was performed to verify the feasibility of the new inversion method.

Removal of Crossed Artifacts from Multimodal Dispersion Curves with Modified Frequency–Bessel Method

2021 ◽  
Author(s):  
Jie Zhou ◽  
Xiaofei Chen
Keyword(s):  
Surface Wave ◽  
Correlation Functions ◽  
Fundamental Mode ◽  
Ambient Noise ◽  
Cross Correlation ◽  
Dispersion Curves ◽  
Hankel Function ◽  
Transform Method ◽  
Wave Inversion ◽  
Noise Data

ABSTRACT Frequency–Bessel (F-J) transform method can obtain higher-mode Rayleigh dispersion curves by multistation ambient noise data superposition (Wang et al., 2019). Because the dispersion curves of the overtones can provide more information compared with the single fundamental mode, the nonuniqueness of surface-wave inversion can be reduced. Because of the limited number of receivers, the integral in the process of transformation cannot be calculated precisely and there exists a kind of crossed artifacts which cuts off the real dispersion curves and contaminates the spectrum. Forbriger (2003) proposed to use the Hankel function instead of the Bessel function to conduct the transformation to remove the crossed artifacts. However, this method can reduce the resolution of the spectrum from ambient noise data. In this article, we give a complete workflow to deal with ambient noises which can eliminate the crossed artifacts without reducing the resolution. The Kramers–Kronig relations are used to obtain complete cross-correlation functions and a modified F-J transform is conducted to finally acquire the spectrum without crossed artifacts.

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