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.

Effects of thin soft layers on body waves

1969 ◽  
Vol 59 (5) ◽  
pp. 2071-2078
Author(s):  
Tom Landers ◽  
Jon F. Claerbout
Keyword(s):  
Surface Wave ◽  
Upper Mantle ◽  
Body Wave ◽  
Wave Dispersion ◽  
Soft Material ◽  
Body Waves ◽  
Surface Wave Dispersion ◽  
Wave Data ◽  
Use Of Time ◽  
Surface Wave Data

abstract The inability of simple layered models to fit both Rayleigh wave and Love wave data has led to the proposal of an upper mantle interleaved with thin soft horizontal layers. Since surface-wave dispersion is not sensitive to the distribution of soft material but only to the fraction of soft material a variety of models is possible. The solution to this indeterminancy is found through body-wave analysis. It is shown that body waves are dispersed according to the thinness and softness of the layers. Three models, each of which satisfy all surface-wave data, are examined. Transmission seismograms calculated for these models show one to be impossible, one improbable and the other possible. Synthesis of the seismograms is accomplished through the use of time domain theory as the complicated frequency response of the models makes a frequency oriented Haskell-Thompson approach impractical.

A model study of elastic waves in a layered sphere

1967 ◽  
Vol 57 (5) ◽  
pp. 959-981
Author(s):  
Victor Gregson
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Elastic Waves ◽  
Wave Dispersion ◽  
Flat Space ◽  
Dispersion Curves ◽  
Body Waves ◽  
Surface Wave Dispersion ◽  
Steel Sphere ◽  
Long Wave

abstract Elastic waves produced by an impact were recorded at the surface of a solid 12.0 inch diameter steel sphere coated with a 0.3 inch copper layer. Conventional modeling techniques employing both compressional and shear piezoelectric transducers were used to record elastic waves for one millisecond at various points around the great circle of the sphere. Body, PL, and surface waves were observed. Density, layer thickness, compressional and shear-wave velocities were measured so that accurate surface-wave dispersion curves could be computed. Surface-wave dispersion was measured as well as computed. Measured PL mode dispersion compared favorably with theoretical computations. In addition, dispersion curves for Rayleigh, Stoneley, and Love modes were computed. Measured surface-wave dispersion showed Rayleigh and Love modes were observed but not Stoneley modes. Measured dispersion compared favorably with theoretical computations. The curvature correction applied to dispersion calculations in a flat space has been estimated to correct dispersion values at long-wave lengths to about one per cent of correct dispersion in a spherical model. Measured dispersion compared with such flat space dispersion corrected for curvature proved accurate within one per cent at long wave lengths. Two sets of surface waves were observed. One set was associated with body waves radiating outward from impact. The other set was associated with body waves reflecting at the pole opposite impact. For each set of surface waves, measured dispersion compared favorably with computed dispersion.

scholarly journals Imaging the subsurface using induced seismicity and ambient noise: 3-D tomographic Monte Carlo joint inversion of earthquake body wave traveltimes and surface wave dispersion

2020 ◽  
Vol 222 (3) ◽  
pp. 1639-1655
Author(s):  
Xin Zhang ◽  
Corinna Roy ◽  
Andrew Curtis ◽  
Andy Nowacki ◽  
Brian Baptie
Keyword(s):  
Surface Wave ◽  
Ambient Noise ◽  
Velocity Structure ◽  
Joint Inversion ◽  
Body Wave ◽  
Source Parameters ◽  
Wave Dispersion ◽  
Inversion Method ◽  
Surface Wave Dispersion ◽  
Wave Data

SUMMARY Seismic body wave traveltime tomography and surface wave dispersion tomography have been used widely to characterize earthquakes and to study the subsurface structure of the Earth. Since these types of problem are often significantly non-linear and have non-unique solutions, Markov chain Monte Carlo methods have been used to find probabilistic solutions. Body and surface wave data are usually inverted separately to produce independent velocity models. However, body wave tomography is generally sensitive to structure around the subvolume in which earthquakes occur and produces limited resolution in the shallower Earth, whereas surface wave tomography is often sensitive to shallower structure. To better estimate subsurface properties, we therefore jointly invert for the seismic velocity structure and earthquake locations using body and surface wave data simultaneously. We apply the new joint inversion method to a mining site in the United Kingdom at which induced seismicity occurred and was recorded on a small local network of stations, and where ambient noise recordings are available from the same stations. The ambient noise is processed to obtain inter-receiver surface wave dispersion measurements which are inverted jointly with body wave arrival times from local earthquakes. The results show that by using both types of data, the earthquake source parameters and the velocity structure can be better constrained than in independent inversions. To further understand and interpret the results, we conduct synthetic tests to compare the results from body wave inversion and joint inversion. The results show that trade-offs between source parameters and velocities appear to bias results if only body wave data are used, but this issue is largely resolved by using the joint inversion method. Thus the use of ambient seismic noise and our fully non-linear inversion provides a valuable, improved method to image the subsurface velocity and seismicity.

DISPERSION IN SEISMIC SURFACE WAVES

Geophysics ◽  
1951 ◽  
Vol 16 (1) ◽  
pp. 63-80 ◽  
Author(s):  
Milton B. Dobrin
Keyword(s):  
Surface Waves ◽  
Water Waves ◽  
Seismic Refraction ◽  
Wave Theory ◽  
Wave Dispersion ◽  
Surface Zone ◽  
Surface Wave Dispersion ◽  
Near Surface ◽  
Arrival Times ◽  
Ground Roll

A non‐mathematical summary is presented of the published theories and observations on dispersion, i.e., variation of velocity with frequency, in surface waves from earthquakes and in waterborne waves from shallow‐water explosions. Two further instances are cited in which dispersion theory has been used in analyzing seismic data. In the seismic refraction survey of Bikini Atoll, information on the first 400 feet of sediments below the lagoon bottom could not be obtained from ground wave first arrival times because shot‐detector distances were too great. Dispersion in the water waves, however, gave data on speed variations in the bottom sediments which made possible inferences on the recent geological history of the atoll. Recent systematic observations on ground roll from explosions in shot holes have shown dispersion in the surface waves which is similar in many ways to that observed in Rayleigh waves from distant earthquakes. Classical wave theory attributes Rayleigh wave dispersion to the modification of the waves by a surface layer. In the case of earthquakes, this layer is the earth’s crust. In the case of waves from shot‐holes, it is the low‐speed weathered zone. A comparison of observed ground roll dispersion with theory shows qualitative agreement, but it brings out discrepancies attributable to the fact that neither the theory for liquids nor for conventional solids applies exactly to unconsolidated near‐surface rocks. Additional experimental and theoretical study of this type of surface wave dispersion may provide useful information on the properties of the surface zone and add to our knowledge of the mechanism by which ground roll is generated in seismic shooting.

Azimuthal multiple signal classification of dispersive and aliased surface waves recorded in 3D seismic acquisition

Geophysics ◽  
2021 ◽  
pp. 1-84
Author(s):  
Chunying Yang ◽  
Wenchuang Wang
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Body Waves ◽  
Signal Classification ◽  
Dispersion Pattern ◽  
Velocity Spectrum ◽  
Low Velocity ◽  
Surface Wave Dispersion ◽  
Multiple Signal Classification ◽  
Multiple Signal

Irregular acquisition geometry causes discontinuities in the appearance of surface wave events, and a large offset causes seismic records to appear as aliased surface waves. The conventional method of sampling data affects the accuracy of the dispersion spectrum and reduces the resolution of surface waves. At the same time, ”mode kissing” of the low-velocity layer and inhomogeneous scatterers requires a high-resolution method for calculating surface wave dispersion. This study tested the use of the multiple signal classification (MUSIC) algorithm in 3D multichannel and aliased wavefield separation. Azimuthal MUSIC is a useful method to estimate the phase velocity spectrum of aliased surface wave data, and it represent the dispersion spectra of low-velocity and inhomogeneous models. The results of this study demonstrate that mode-kissing affects dispersion imaging, and inhomogeneous scatterers change the direction of surface-wave propagation. Surface waves generated from the new propagation directions are also dispersive. The scattered surface wave has a new dispersion pattern different to that of the entire record. Diagonal loading was introduced to improve the robustness of azimuthal MUSIC, and numerical experiments demonstrate the resultant effectiveness of imaging aliasing surface waves. A phase-matched filter was applied to the results of azimuthal MUSIC, and phase iterations were unwrapped in a fast and stable manner. Aliased surface waves and body waves were separated during this process. Overall, field data demonstrate that azimuthal MUSIC and phase-matched filters can successfully separate aliased surface waves.

3D elastic full-waveform inversion of surface waves in the presence of irregular topography using an envelope-based misfit function

Geophysics ◽  
2018 ◽  
Vol 83 (1) ◽  
pp. R1-R11 ◽  
Author(s):  
Dmitry Borisov ◽  
Ryan Modrak ◽  
Fuchun Gao ◽  
Jeroen Tromp
Keyword(s):  
Surface Wave ◽  
Objective Function ◽  
Surface Waves ◽  
Large Scale ◽  
Body Wave ◽  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
S Wave ◽  
Near Surface ◽  
Full Waveform

Full-waveform inversion (FWI) is a powerful method for estimating the earth’s material properties. We demonstrate that surface-wave-driven FWI is well-suited to recovering near-surface structures and effective at providing S-wave speed starting models for use in conventional body-wave FWI. Using a synthetic example based on the SEG Advanced Modeling phase II foothills model, we started with an envelope-based objective function to invert for shallow large-scale heterogeneities. Then we used a waveform-difference objective function to obtain a higher-resolution model. To accurately model surface waves in the presence of complex tomography, we used a spectral-element wave-propagation solver. Envelope misfit functions are found to be effective at minimizing cycle-skipping issues in surface-wave inversions, and surface waves themselves are found to be useful for constraining complex near-surface features.

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.

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.

scholarly journals Geodynamic tomography: constraining upper-mantle deformation patterns from Bayesian inversion of surface waves

2020 ◽  
Vol 224 (3) ◽  
pp. 2077-2099
Author(s):  
J K Magali ◽  
T Bodin ◽  
N Hedjazian ◽  
H Samuel ◽  
S Atkins
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Upper Mantle ◽  
Wave Dispersion ◽  
Dispersion Curves ◽  
Bayesian Inversion ◽  
Model Parameters ◽  
Mantle Flow ◽  
Surface Wave Dispersion ◽  
Elastic Tensor

SUMMARY In the Earth’s upper mantle, seismic anisotropy mainly originates from the crystallographic preferred orientation (CPO) of olivine due to mantle deformation. Large-scale observation of anisotropy in surface wave tomography models provides unique constraints on present-day mantle flow. However, surface waves are not sensitive to the 21 coefficients of the elastic tensor, and therefore the complete anisotropic tensor cannot be resolved independently at every location. This large number of parameters may be reduced by imposing spatial smoothness and symmetry constraints to the elastic tensor. In this work, we propose to regularize the tomographic problem by using constraints from geodynamic modelling to reduce the number of model parameters. Instead of inverting for seismic velocities, we parametrize our inverse problem directly in terms of physical quantities governing mantle flow: a temperature field, and a temperature-dependent viscosity. The forward problem consists of three steps: (1) calculation of mantle flow induced by thermal anomalies, (2) calculation of the induced CPO and elastic properties using a micromechanical model, and (3) computation of azimuthally varying surface wave dispersion curves. We demonstrate how a fully nonlinear Bayesian inversion of surface wave dispersion curves can retrieve the temperature and viscosity fields, without having to explicitly parametrize the elastic tensor. Here, we consider simple flow models generated by spherical temperature anomalies. The results show that incorporating geodynamic constraints in surface wave inversion help to retrieve patterns of mantle deformation. The solution to our inversion problem is an ensemble of models (i.e. thermal structures) representing a posterior probability, therefore providing uncertainties for each model parameter.

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