Effects of near-surface spatial variability of soil stiffness on surface wave dispersion

2019 ◽  
Author(s):  
Siavash Mahvelati ◽  
Joseph Thomas Coe ◽  
Alireza Kordjazi
Keyword(s):  
Surface Wave ◽  
Spatial Variability ◽  
Wave Dispersion ◽  
Surface Wave Dispersion ◽  
Near Surface ◽  
Soil Stiffness

scholarly journals Probabilistic seismic-hazard site assessment in Kitimat, British Columbia, from Bayesian inversion of surface-wave dispersion

2018 ◽  
Vol 55 (7) ◽  
pp. 928-940
Author(s):  
Jeremy M. Gosselin ◽  
John F. Cassidy ◽  
Stan E. Dosso ◽  
Camille Brillon
Keyword(s):  
British Columbia ◽  
Surface Wave ◽  
Seismic Hazard ◽  
Industrial Development ◽  
Wave Dispersion ◽  
Site Amplification ◽  
Site Classification ◽  
Surface Wave Dispersion ◽  
Near Surface ◽  
Amplification Factors

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.

Frost quakes – the sound of a dynamic cryosphere and a convenient source for passive surface wave imaging of permafrost

2021 ◽  
Author(s):  
Rowan Romeyn ◽  
Alfred Hanssen ◽  
Andreas Köhler ◽  
Bent Ole Ruud ◽  
Helene Meling Stemland ◽  
...  
Keyword(s):  
Thermal Stress ◽  
Surface Wave ◽  
Wave Dispersion ◽  
Surface Wave Dispersion ◽  
Near Surface ◽  
Wave Imaging ◽  
Passive Seismic ◽  
Temporal Occurrence ◽  
Similar Class ◽  
Cooling Air

<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>

scholarly journals 2D characterization of near‐surface : surface‐wave dispersion inversion versus refraction tomography

2015 ◽  
Vol 13 (4) ◽  
pp. 315-332 ◽  
Author(s):  
Sylvain Pasquet ◽  
Ludovic Bodet ◽  
Laurent Longuevergne ◽  
Amine Dhemaied ◽  
Christian Camerlynck ◽  
...  
Keyword(s):  
Surface Wave ◽  
Wave Dispersion ◽  
Surface Wave Dispersion ◽  
Near Surface ◽  
Refraction Tomography

scholarly journals Potential Use of Time-Lapse Surface Seismics for Monitoring Thawing of the Terrestrial Arctic

2020 ◽  
Vol 10 (5) ◽  
pp. 1875
Author(s):  
Helene Meling Stemland ◽  
Tor Arne Johansen ◽  
Bent Ole Ruud
Keyword(s):  
Surface Wave ◽  
Seismic Data ◽  
Rock Physics ◽  
Wave Dispersion ◽  
Time Lapse ◽  
Unconsolidated Sediments ◽  
Frozen Ground ◽  
Surface Wave Dispersion ◽  
Near Surface ◽  
Surface Temperatures

The terrestrial Arctic is warming rapidly, causing changes in the degree of freezing of the upper sediments, which the mechanical properties of unconsolidated sediments strongly depend upon. This study investigates the potential of using time-lapse surface seismics to monitor thawing of currently (partly) frozen ground utilizing synthetic and real seismic data. First, we construct a simple geological model having an initial temperature of −5 °C, and infer constant surface temperatures of −5 °C, +1 °C, +5 °C, and +10 °C for four years to this model. The geological models inferred by the various thermal regimes are converted to seismic models using rock physics modeling and subsequently seismic modeling based on wavenumber integration. Real seismic data reflecting altered surface temperatures were acquired by repeated experiments in the Norwegian Arctic during early autumn to mid-winter. Comparison of the surface wave characteristics of both synthetic and real seismic data reveals time-lapse effects that are related to thawing caused by varying surface temperatures. In particular, the surface wave dispersion is sensitive to the degree of freezing in unconsolidated sediments. This demonstrates the potential of using surface seismics for Arctic climate monitoring, but inversion of dispersion curves and knowledge of the local near-surface geology is important for such studies to be conclusive.

scholarly journals Seismic Characterization of the Nevada National Security Site Using Joint Body Wave, Surface Wave, and Gravity Inversion

2019 ◽  
Vol 110 (1) ◽  
pp. 110-126
Author(s):  
Leiph Preston ◽  
Christian Poppeliers ◽  
David J. Schodt
Keyword(s):  
Surface Wave ◽  
National Security ◽  
Surface Waves ◽  
Body Wave ◽  
Wave Dispersion ◽  
The Body ◽  
Body Waves ◽  
Gravity Inversion ◽  
Surface Wave Dispersion ◽  
Near Surface

ABSTRACT As a part of the series of Source Physics Experiments (SPE) conducted on the Nevada National Security Site in southern Nevada, we have developed a local-to-regional scale seismic velocity model of the site and surrounding area. Accurate earth models are critical for modeling sources like the SPE to investigate the role of earth structure on the propagation and scattering of seismic waves. We combine seismic body waves, surface waves, and gravity data in a joint inversion procedure to solve for the optimal 3D seismic compressional and shear-wave velocity structures and earthquake locations subject to model smoothness constraints. Earthquakes, which are relocated as part of the inversion, provide P- and S-body-wave absolute and differential travel times. Active source experiments in the region augment this dataset with P-body-wave absolute times and surface-wave dispersion data. Dense ground-based gravity observations and surface-wave dispersion derived from ambient noise in the region fill in many areas where body-wave data are sparse. In general, the top 1–2 km of the surface is relatively poorly sampled by the body waves alone. However, the addition of gravity and surface waves to the body-wave dataset greatly enhances structural resolvability in the near surface. We discuss the methodology we developed for simultaneous inversion of these disparate data types and briefly describe results of the inversion in the context of previous work in the region.

Constrained Surface-wave Dispersion Inversion Using GPR Reflection Data

2020 ◽  
Author(s):  
Shufan Hu ◽  
Yonghui Zhao ◽  
Wenda Bi ◽  
Ruiqing Shen ◽  
Bo Li ◽  
...  
Keyword(s):  
Surface Wave ◽  
Wave Dispersion ◽  
Dispersion Curves ◽  
Data Sets ◽  
S Wave ◽  
Surface Wave Dispersion ◽  
Near Surface ◽  
Reflection Data ◽  
Uniqueness Of The Solution ◽  
S Model

<p>Ground penetrating radar (GPR) and Seismic Surface Wave methods (SWMs) are two nondestructive testing (NDT) methods commonly used in near-surface site investigations. These two methods investigate the media properties of subsurface based on different physical phenomena. GPR has a good resolvability to characterize the layered structure since the propagation of electromagnetic wave is sensitive to the change of electrical properties, while, the geometric dispersion of surface waves can be used to retrieve the variation of S-wave velocity (<em>V</em>s) with depth. In most situations, these two data sets are processed separately, and the results are later used for comprehensive interpretation. Constrained inversion, as a way to implement data fusion, can alleviate the non-uniqueness of the solution and produce more consistent information for the comprehensive site and material investigations.</p><p>We present an algorithm for the inversion of surface-wave dispersion curves with GPR interface constraints in 2D media. The reflection interfaces interpreted from the GPR profile are integrated into a cell- and boundary-based <em>V</em>s model. This implementation allows both vertical and lateral changes within each region while also allows sharp changes across the boundaries. In addition, our algorithm simultaneously inverts several dispersion curves extracted along the survey line using multi-size spatial windows, which mitigates the adverse effects of 1D assumption in traditional surface-wave dispersion inversion and improves the matching of GPR and SWMs in lateral variations. We use synthetic and field data sets to test the effectivity of the proposed method. Both results show the improved resolution of the <em>V</em>s model retrieved by the constrained inversion compared to the standard inversion.</p>

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