Crustal structure of the Iceland region from dispersion of surface waves

1962 ◽  
Vol 52 (2) ◽  
pp. 359-388
Author(s):  
Eysteinn Tryggvason
Keyword(s):  
Surface Layer ◽  
Surface Wave ◽  
Surface Waves ◽  
Wave Velocity ◽  
Crustal Structure ◽  
Wave Dispersion ◽  
P Wave ◽  
S Wave ◽  
Surface Wave Dispersion ◽  
Mid Atlantic Ridge

ABSTRACT A number of Icelandic records of earthquakes originating in the Mid-Atlantic Seismic Belt between 52° and 70° N. lat. have been investigated. The surface waves on these records are chiefly in the period interval 3–10 sec, and are first mode Love-waves and Rayleigh-waves. The surface wave dispersion can be explained by a three-layered crustal structure as follows. A surface layer of S-wave velocity about 2.7 km/sec covering the whole region studied, a second layer of S-wave velocity about 3.6 km/sec covering Iceland and extending several hundred kilometers off the coasts and a third layer of S-wave velocity about 4.3 km/sec and P-wave velocity about 7.4 km/sec underlying the whole region. The thickness of the surface layer appears to be about 4 km on the Mid-Atlantic Ridge south of Iceland and in western Iceland, 3 km in central Iceland and 7 km northwest of Iceland. The second layer is apparently of similar thickness than the surface layer, while the third layer is thick; and the surface wave dispersion does not indicate any layer of higher wave velocity. This 7.4-layer is supposed to belong to the mantle, although its wave velocity is significantly lower than usually found in the upper mantle

scholarly journals 3D wave-equation dispersion inversion of surface waves recorded on irregular topography

Geophysics ◽  
2020 ◽  
Vol 85 (3) ◽  
pp. R147-R161 ◽  
Author(s):  
Zhaolun Liu ◽  
Jing Li ◽  
Sherif M. Hanafy ◽  
Kai Lu ◽  
Gerard Schuster
Keyword(s):  
Wave Equation ◽  
Surface Wave ◽  
Surface Waves ◽  
Wave Velocity ◽  
Field Data ◽  
P Wave ◽  
Topographic Effects ◽  
S Wave ◽  
Surface Wave Dispersion ◽  
Irregular Topography

Irregular topography can cause strong scattering and defocusing of propagating surface waves, so it is important to account for such effects when inverting surface waves for shallow S-wave velocity structures. We have developed a 3D surface-wave dispersion inversion method that takes into account the topographic effects modeled by a 3D spectral element solver. The objective function is the frequency summation of the squared wavenumber differences [Formula: see text] along each azimuthal angle of the fundamental mode or higher-order modes of Rayleigh waves in each shot gather. The wavenumbers [Formula: see text] associated with the dispersion curves are calculated using the data recorded along the irregular free surface. Numerical tests on synthetic and field data demonstrate that 3D topographic wave equation dispersion inversion (TWD) can accurately invert for the S-wave velocity model from surface-wave data recorded on irregular topography. Field data tests for data recorded across an Arizona fault demonstrate that, for this example, the 2D TWD model can be as accurate as the 3D tomographic model. This suggests that in some cases, the 2D TWD inversion is preferred over 3D TWD because of its significant reduction in computational costs. Compared to the 3D P-wave velocity tomogram, the 3D S-wave tomogram agrees much more closely with the geologic model taken from the trench log. The agreement with the trench log is even better when the [Formula: see text] tomogram is computed, which reveals a sharp change in velocity across the fault. The localized velocity anomaly in the [Formula: see text] tomogram is in very good agreement with the well log. Our results suggest that integrating the [Formula: see text] and [Formula: see text] tomograms can sometimes give the most accurate estimates of the subsurface geology across normal faults.

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

Multi-Window Weighted Stacking of Surface-Wave Dispersion

Geophysics ◽  
2020 ◽  
pp. 1-53
Author(s):  
Sylvain Pasquet ◽  
Wei Wang ◽  
Po Chen ◽  
Brady A. Flinchum
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Real Data ◽  
Wave Dispersion ◽  
Lateral Resolution ◽  
Data Sets ◽  
S Wave ◽  
Surface Wave Dispersion ◽  
Shallow Subsurface ◽  
Depth Of Investigation

Surface wave (SW) methods are classically used to characterize shear (S-) wave velocities ( VS) of the shallow subsurface through the inversion of dispersion curves. When targeting 2D shallow structures with sharp lateral heterogeneity, windowing and stacking techniques can be implemented to provide a better description of VS lateral variations. These techniques, however, suffer from the trade-off between lateral resolution and depth of investigation, well-known when using multichannel analysis of surface waves (MASW). We propose a novel methodology aimed at enhancing both lateral resolution and depth of investigation of MASW results through the use of multi-window weighted stacking of surface waves (MW-WSSW). MW-WSSW consists in stacking dispersion images obtained from data segments of different sizes, with a wavelength-based weight that depends on the aperture of the data selection window. In that sense, MW-WSSW provides additional weight to short wavelengths in smaller windows so as to better inform shallow parts of the subsurface, and vice versa for deeper velocities. Using multiple windows improves the depth of investigation, while applying wavelength-based weights enhances shallow lateral resolution. MW-WSSW was implemented within the open-source package SWIP, and applied to the processing of synthetic and real data sets. In both cases we compared it with standard windowing and stacking procedures that are already implemented in SWIP. MW-WSSW provided convincing results with optimized lateral extent, improved shallow resolution, and increased depth of 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.

A comprehensive comparison between the refraction microtremor and seismic interferometry methods for phase-velocity estimation

Geophysics ◽  
2017 ◽  
Vol 82 (6) ◽  
pp. EN99-EN108 ◽  
Author(s):  
Zongbo Xu ◽  
T. Dylan Mikesell ◽  
Jianghai Xia ◽  
Feng Cheng
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Wave Velocity ◽  
Velocity Estimation ◽  
Seismic Interferometry ◽  
S Wave ◽  
Noise Sources ◽  
Surface Wave Dispersion ◽  
Near Surface ◽  
Refraction Microtremor

Passive-source seismic-noise-based surface-wave methods are now routinely used to investigate the near-surface geology in urban environments. These methods estimate the S-wave velocity of the near surface, and two methods that use linear recording arrays are seismic interferometry (SI) and refraction microtremor (ReMi). These two methods process noise data differently and thus can yield different estimates of the surface-wave dispersion, the data used to estimate the S-wave velocity. We have systematically compared these two methods using synthetic data with different noise source distributions. We arrange sensors in a linear survey grid, which is conveniently used in urban investigations (e.g., along roads). We find that both methods fail to correctly determine the low-frequency dispersion characteristics when outline noise sources become stronger than inline noise sources. We also identify an artifact in the ReMi method and theoretically explain the origin of this artifact. We determine that SI combined with array-based analysis of surface waves is the more accurate method to estimate surface-wave phase velocities because SI separates surface waves propagating in different directions. Finally, we find a solution to eliminate the ReMi artifact that involves the combination of SI and the [Formula: see text]-[Formula: see text] transform, the array processing method that underlies the ReMi method.

scholarly journals Two-Dimensional Full-Waveform Joint Inversion of Surface Waves Using Phases and Z/H Ratios

2021 ◽  
Vol 11 (15) ◽  
pp. 6712
Author(s):  
Chao Zhang ◽  
Ting Lei ◽  
Yi Wang
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Wave Velocity ◽  
Joint Inversion ◽  
Waveform Inversion ◽  
Small Scale ◽  
Imaging Method ◽  
S Wave ◽  
Surface Wave Dispersion ◽  
Full Waveform

Surface-wave dispersion and the Z/H ratio are important parameters used to resolve the Earth’s structure, especially for S-wave velocity. Several previous studies have explored using joint inversion of these two datasets. However, all of these studies used a 1-D depth-sensitivity kernel, which lacks precision when the structure is laterally heterogeneous. Adjoint tomography (i.e., full-waveform inversion) is a state-of-the-art imaging method with a high resolution. It can obtain better-resolved lithospheric structures beyond the resolving ability of traditional ray-based travel-time tomography. In this study, we present a systematic investigation of the 2D sensitivities of the surface wave phase and Z/H ratio using the adjoint-state method. The forward-modeling experiments indicated that the 2D phase and Z/H ratio had different sensitivities to the S-wave velocity. Thus, a full-waveform joint-inversion scheme of surface waves with phases and a Z/H ratio was proposed to take advantage of their complementary sensitivities to the Earth’s structure. Both applications to synthetic data sets in large- and small-scale inversions demonstrated the advantage of the joint inversion over the individual inversions, allowing for the creation of a more unified S-wave velocity model. The proposed joint-inversion scheme offers a computationally efficient and inexpensive alternative to imaging fine-scale shallow structures beneath a 2D seismic array.

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