New processing flow for surface wave dispersion curve inversion of near surface 2-D Vs model

Author(s):  
X. Song ◽  
G. Liu
2013 ◽  
Vol 353-356 ◽  
pp. 1196-1202 ◽  
Author(s):  
Jian Qi Lu ◽  
Shan You Li ◽  
Wei Li

Surface wave dispersion imaging approach is crucial for multi-channel analysis of surface wave (MASW). Because the resolution of inversed S-wave velocity and thickness of a layer are directly subjected to the resolution of imaged dispersion curve. The τ-p transform approach is an efficient and commonly used approach for Rayleigh wave dispersion curve imaging. However, the conventional τ-p transform approach was severely affected by waves amplitude. So, the energy peaks of f-v spectrum were mainly gathered in a narrow frequency range. In order to remedy this shortage, an improved τ-p transform approach was proposed by this paper. Comparison has been made between phase shift and improved τ-p transform approaches using both synthetic and in situ tested data. Result shows that the dispersion image transformed from proposed approach is superior to that either from conventionally τ-p transform or from phase shift approaches.


2018 ◽  
Vol 55 (7) ◽  
pp. 928-940
Author(s):  
Jeremy M. Gosselin ◽  
John F. Cassidy ◽  
Stan E. Dosso ◽  
Camille Brillon

This paper applies rigorous quantitative inversion methods to estimate seismic-hazard site classification and amplification factors in Kitimat, British Columbia, due to near-surface geophysical conditions. Frequency-wavenumber seismic-array processing is applied to passive data collected at three sites in Kitimat to estimate surface-wave dispersion. The dispersion data are inverted using a fully nonlinear Bayesian (probabilistic) inference methodology to estimate shear-wave velocity (VS) profiles and uncertainties. The VS results are used to calculate the travel-time average of VS to 30 m depth (VS30) as a representation of the average sediment conditions, and to determine seismic-hazard site classification with respect to the National Building Code of Canada. In addition, VS30-dependent site amplification factors are computed to estimate site amplification at the three Kitimat sites. Lastly, the VS profiles are used to compute amplification and resonance spectra for horizontally polarized shear waves. Quantitative uncertainties are estimated for all seismic-hazard estimates from the probabilistic VS structure. The Kitimat region is the site for several proposed large-scale industrial development projects. One of the sites considered in this study is co-located with a recently deployed soil seismographic monitoring station that is currently recording ground motions as part of a 5 year campaign. The findings from this work will be useful for mitigating seismic amplification and resonance hazards on critical infrastructure, as well as for future seismological research, in this environmentally and economically significant region of Canada.


2015 ◽  
Author(s):  
Yahui Yang ◽  
Hui Zhou ◽  
Yuhua Chen ◽  
Yanqi Li ◽  
Xiaofeng Zou ◽  
...  

2021 ◽  
Author(s):  
Rowan Romeyn ◽  
Alfred Hanssen ◽  
Andreas Köhler ◽  
Bent Ole Ruud ◽  
Helene Meling Stemland ◽  
...  

<p>A class of short-duration seismic events were recorded on dense, temporary geophone arrays deployed in Adventdalen, Svalbard in spring and autumn 2019. A similar class of events have also been detected in seismic records from the SPITS seismic array located on Janssonhaugen in Adventdalen, that has been in continuous operation since the 1990’s. In both cases, estimated source positions are dominantly local and cluster around frost polygon, ice-wedge geomorphologies. Correlation with periods of rapidly cooling air temperature and consequent thermal stress build-up in the near surface are also observed. These events are consequently interpreted as frost quakes, a class of cryoseism. The dense, temporary arrays allowed high quality surface-wave dispersion images to be generated, that show potential to monitor structure and change in permafrost through passive seismic deployments. While the lower wavenumber resolution of the sparser SPITS array is less suited to imaging the near-surface in detail, the long continuous recording period gives us a unique insight into the temporal occurrence of frost quakes. This allows us, for example, to better understand the dynamic processes leasing to frost quakes by correlating temporal occurrence with models of thermal stress in the ground, constrained by thermistor temperature measurements from a nearby borehole.</p>


Author(s):  
Sheng Dong ◽  
Zhengbo Li ◽  
Xiaofei Chen ◽  
Lei Fu

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.


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