Rayleigh Wave Analysis in the Presence of High Impedance Boundaries

2020 ◽  
Author(s):  
Gabriel Gribler
Keyword(s):  
Surface Wave ◽  
Shear Wave ◽  
High Velocity ◽  
Inversion Method ◽  
Surface Wave Dispersion ◽  
Wave Data ◽  
Wave Velocities ◽  
Shear Wave Velocities ◽  
High Impedance ◽  
Surface Wave Data

Surface wave data is commonly used to estimate shear wave velocity of the subsurface. Most standard approaches for analyzing surface wave data fail under conditions when high-impedance boundaries, or sharp contrasts, exists within the range of sensitivities. I present two primary scenarios, one with a high velocity bedrock layer in the upper 20 meters overlain by low velocity unconsolidated sediment, and a thin high velocity road layer on top of unconsolidated sediments. For the shallow bedrock case, I present new multicomponent methods to more accurately and reliably extract surface wave dispersion information from active source waveforms. I also present a new data inversion method that utilizes additional information from multicomponent wavefields, allowing for more accurate estimates of shear wave velocities in these environments. For the thin, high velocity surface layer, I highlight the potential pitfalls of ignoring this layer when inverting for the underlying shear wave velocities, and I propose a solution that yields more accurate velocity estimates. All of these approaches are explained and presented using modeled data, then extended to highlight the improvements over standard approaches using real data.

Crustal imaging of northern Harrat Rahat, Saudi Arabia, from ambient noise tomography

2019 ◽  
Vol 219 (3) ◽  
pp. 1532-1549 ◽  
Author(s):  
F Civilini ◽  
W D Mooney ◽  
M K Savage ◽  
J Townend ◽  
H Zahran
Keyword(s):  
Saudi Arabia ◽  
Surface Wave ◽  
Shear Wave ◽  
Magma Chamber ◽  
Lower Crust ◽  
Volcanic Field ◽  
Surface Wave Dispersion ◽  
Wave Velocities ◽  
Shear Wave Velocities ◽  
Harrat Rahat

SUMMARY Harrat Rahat is a volcanic field located in west-central Saudi Arabia and is the site of the most recent eruption in the country (1256 CE). An earthquake swarm at a nearby volcanic field in 2009 prompted the need for new hazard models for this region, which includes the holy city of Medina. Tomography studies can be used to infer material properties of the subsurface such as partial melt, and are instrumental for volcanic hazard assessment. Regional earthquakes have been used to determine mantle structure, but such crustal models are often hindered by an insufficient number of earthquakes in the plate interior. We use ambient seismic noise to compute Rayleigh and Love surface-wave dispersion maps between 5 and 12 s for northern Harrat Rahat. The surface-wave maps are inverted to produce shear-wave velocities using a neighbourhood algorithm and interpolated into a pseudo-3-D model. The distributions of surface-wave and shear-wave velocities are heterogenous, varying between ±3 and 8 per cent. However, low velocities are not restricted to the Harrat. We observed a difference between Rayleigh- and Love-wave velocities that extends north from the site of the 1256 CE eruption and coincides with a low gravity anomaly. We obtain a shear-wave velocity increase of 10–15 per cent between 15 and 25 km depth consistent with the Conrad discontinuity, the interface between andesitic upper crust and the mafic lower crust of the Arabian Shield. The average velocities of the upper and lower crust are estimated to be 3.64 and 3.95 km s–1 using Rayleigh waves and 3.53 and 4.16 km s–1 using Love waves, which are in good agreement with the results of other geophysical studies of this area. The magnitude of the low-velocity anomalies, their location away from the Harrat, and the lack of reversals in the shear-velocity inversions suggest that the presence of a crustal magma chamber is not likely. If a magma chamber exists, it is smaller than can be imaged with a secondary microseism source (approximately 15 km wavelength), deeper than 30 km, or shallower than 5 km with a small velocity contrast.

scholarly journals A Reduced Order Approach for Probabilistic Inversions of 3D Magnetotelluric Data II: Joint inversion of 3D MT and Surface-Wave Data

2021 ◽  
Author(s):  
Maria Constanza Manassero ◽  
Juan Afonso ◽  
Fabio Zyserman ◽  
Sergio Zlotnik ◽  
Ilya Fomin
Keyword(s):  
Surface Wave ◽  
Large Scale ◽  
Joint Inversion ◽  
Mantle Metasomatism ◽  
Joint Analysis ◽  
Inversion Method ◽  
Surface Wave Dispersion ◽  
Magnetotelluric Data ◽  
Wave Data ◽  
Surface Wave Data

Joint probabilistic inversions of magnetotelluric (MT) and seismic data has great potential for imaging the thermochemical structure of the lithosphere as well as mapping fluid/melt pathways and regions of mantle metasomatism. In this contribution we present a novel probabilistic (Bayesian) joint inversion scheme for 3D MT and surface-wave dispersion data particularly designed for large-scale lithospheric studies. The approach makes use of a recently developed strategy for fast solutions of the 3D MT forward problem (Manassero et al.,2020) and combines it with adaptive Markov chain Monte Carlo (MCMC) algorithms and parallel-in-parallel strategies to achieve extremely efficient simulations. To demonstrate the feasibility, benefits and performance of our joint inversion method to image the temperature and conductivity structures of the lithosphere, we apply it to two numerical examples of increasing complexity. The inversion approach presented here is timely and will be useful in the joint analysis of MT and surface wave data that are being collected in many parts of the world. This approach also opens up new avenues for the study of translithospheric and transcrustal magmatic systems, the detection of metasomatised mantle and the incorporation of MT into multi-observable inversions for the physical state of the Earth's interior.

scholarly journals Reconstruction, with tunable sparsity levels, of shear-wave velocity profiles from surface wave data

2021 ◽  
Author(s):  
Giulio Vignoli ◽  
Julien Guillemoteau ◽  
Jeniffer Barreto ◽  
Matteo Rossi
Keyword(s):  
Surface Wave ◽  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Dispersion Curves ◽  
Surface Wave Dispersion ◽  
Near Surface ◽  
Wave Data ◽  
Surface Wave Data ◽  
Depth Of Investigation

Summary The analysis of surface wave dispersion curves is a way to infer the vertical distribution of shear-wave velocity. The range of applicability is extremely wide: going, for example, from seismological studies to geotechnical characterizations and exploration geophysics. However, the inversion of the dispersion curves is severely ill-posed and only limited efforts have been put in the development of effective regularization strategies. In particular, relatively simple smoothing regularization terms are commonly used, even when this is in contrast with the expected features of the investigated targets. To tackle this problem, stochastic approaches can be utilized, but they are too computationally expensive to be practical, at least, in case of large surveys. Instead, within a deterministic framework, we evaluate the applicability of a regularizer capable of providing reconstructions characterized by tunable levels of sparsity. This adjustable stabilizer is based on the minimum support regularization, applied before on other kinds of geophysical measurements, but never on surface wave data. We demonstrate the effectiveness of this stabilizer on: i) two benchmark—publicly available— datasets at crustal and near-surface scales; ii) an experimental dataset collected on a well-characterized site. In addition, we discuss a possible strategy for the estimation of the depth of investigation. This strategy relies on the integrated sensitivity kernel used for the inversion and calculated for each individual propagation mode. Moreover, we discuss the reliability, and possible caveats, of the direct interpretation of this particular estimation of the depth of investigation, especially in the presence of sharp boundary reconstructions.

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.

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.

scholarly journals Time-lapse monitoring of climate effects on earthworks using surface waves

Geophysics ◽  
2016 ◽  
Vol 81 (2) ◽  
pp. EN1-EN15 ◽  
Author(s):  
Paolo Bergamo ◽  
Ben Dashwood ◽  
Sebastian Uhlemann ◽  
Russell Swift ◽  
Jonathan E. Chambers ◽  
...  
Keyword(s):  
Surface Wave ◽  
Transportation Network ◽  
Wave Dispersion ◽  
Time Lapse ◽  
Spatial And Temporal Variability ◽  
Data Sets ◽  
Initial Model ◽  
Surface Wave Dispersion ◽  
Wave Data ◽  
Surface Wave Data

The UK’s transportation network is supported by critical geotechnical assets (cuttings/embankments/dams) that require sustainable, cost-effective management, while maintaining an appropriate service level to meet social, economic, and environmental needs. Recent effects of extreme weather on these geotechnical assets have highlighted their vulnerability to climate variations. We have assessed the potential of surface wave data to portray the climate-related variations in mechanical properties of a clay-filled railway embankment. Seismic data were acquired bimonthly from July 2013 to November 2014 along the crest of a heritage railway embankment in southwest England. For each acquisition, the collected data were first processed to obtain a set of Rayleigh-wave dispersion and attenuation curves, referenced to the same spatial locations. These data were then analyzed to identify a coherent trend in their spatial and temporal variability. The relevance of the observed temporal variations was also verified with respect to the experimental data uncertainties. Finally, the surface wave dispersion data sets were inverted to reconstruct a time-lapse model of S-wave velocity for the embankment structure, using a least-squares laterally constrained inversion scheme. A key point of the inversion process was constituted by the estimation of a suitable initial model and the selection of adequate levels of spatial regularization. The initial model and the strength of spatial smoothing were then kept constant throughout the processing of all available data sets to ensure homogeneity of the procedure and comparability among the obtained [Formula: see text] sections. A continuous and coherent temporal pattern of surface wave data, and consequently of the reconstructed [Formula: see text] models, was identified. This pattern is related to the seasonal distribution of precipitation and soil water content measured on site.

scholarly journals Characterization of the geological and geotechnical properties of soil using the surface wave approach

2015 ◽  
Vol 3 (2) ◽  
pp. 8
Author(s):  
Oluwatobi Oloye ◽  
Adekunle Adepelumi
Keyword(s):  
Surface Wave ◽  
Power Plant ◽  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Wave Data ◽  
Subsurface Layers ◽  
Low Strength ◽  
Surface Wave Data ◽  
Seismic Lines

<p>As part of the efforts to examine the elastic and engineering properties of the subsurface sequence at a proposed new power plant site in Edo State, a geophysical survey involving Multichannel Analysis of Surface Waves (MASW) was carried out. The MASW was adopted to determine the vertical and lateral variations in velocity beneath each seismic line. The MASW was carried out on two seismic lines each trending NE-SW. A geophone interval of 3 m was used, and the length of the seismic lines ranged from 60 – 90 m. The ES-3000 seismograph was used for the surface wave data acquisition and the Shear-Wave velocity structures of the area were obtained through the inversion of the acquired surface wave data. The one dimensional (1D) S-Wave velocity profiles along the lines were diagnostic of generally low velocity lithologies that suggest sand, clayey sand and sandy clay formations with relatively varying thicknesses. The subsurface layers delineated had shear-wave velocity values in the range of 63-400 m/s. They were classified using the NEHRP Seismic Site Classification, and all of them were in the range of stiff soil to soft clay soil. The bulk moduli (k) for these soils were in the range of 3.22-3.98 GPa. This depicts relatively low strength of the subsurface materials. The shear moduli (μ) values range from 7.15-7.43 MPa, which is indicative of low to moderate strength. The information provided in this study will aid the structural engineer or architect in foundation design of the proposed power plant. From the results of this study, it is concluded that although the subsurface layers are of relatively low strength, with the right intervention of the civil engineer, a suitable foundation can be designed for the gas plant.</p>

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