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- Volume 2, Issue 4, 2004
Near Surface Geophysics - Volume 2, Issue 4, 2004
Volume 2, Issue 4, 2004
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Surface‐wave method for near‐surface characterization: a tutorial
Authors L.V. Socco and C. StrobbiaABSTRACTSurface‐wave methods (SWMs) are very powerful tools for the near‐surface characterization of sites. They can be used to determine the shear‐wave velocity and the damping ratio overcoming, in some cases, the limitations of other shallow seismic techniques.
The different steps of SWM have to be optimized, taking into consideration the conditions imposed by the small scale of engineering problems. This only allows the acquisition of apparent dispersion characteristics: i.e. the high frequencies and short distances involved make robust modelling algorithms necessary in order to take modal superposition into account.
The acquisition has to be properly planned to obtain quality data over an adequate frequency range. Processing and inversion should enable the interpretation of the apparent dispersion characteristics, i.e. evaluating the local quality of the data, filtering coherent noise due to other seismic events and determining energy distribution, higher modes and attenuation.
The different approaches that are used to estimate and interpret the dispersion characteristics are considered. Their potential and limits with regard to sensitivity to noise, reliability and capability of extracting significant information present in surface waves are discussed. The theory and modelling algorithms, and the acquisition, processing and inversion procedures suitable for providing stiffness and damping ratio profiles are illustrated, with particular attention to reliability and resolution.
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Surface waves in inversely dispersive media
More LessABSTRACTThe dispersion of surface waves in inversely dispersive media where the shear‐wave velocity decreases with depth is studied. Theoretical dispersion curves are calculated in the complex wavenumber domain. Excitability and attenuation due to leakage are calculated for each point on the dispersion curves. These additional parameters are critical for a correct understanding of the dispersion properties of surface waves. Mode shapes are included in the study to visualize displacements inside the medium. The results of the study show that, for inversely dispersive media, the Rayleigh‐wave assumption is not valid, and other types of interface waves and leaky Lamb waves contribute to the surface wavefield. They also show that, in this case, true theoretical dispersion curves can be approximated by Lamb‐wave dispersion curves for a free plate in a vacuum, provided that the stiffness contrast between the top layer and the underlying half‐space is large, and also that the shear‐wave velocity of the stiff layer is greater than the compressional‐wave velocity in the underlying media. The error in the phase velocity resulting from this approximation is investigated and it is shown that the error does not exceed 5% for the fundamental antisymmetric Lamb‐wave dispersion curve. Because of the numerical simplicity of calculating its theoretical dispersion curves, the Lamb‐wave approximation can provide an effective evaluation method to resolve the thickness and elastic parameters of the stiff top layer. This is exemplified using a set of field data.
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Advanced signal processing tools for dispersive waves
Authors J. I. Mars, F. Glangeaud and J. L. MariABSTRACTTwo field examples are presented, showing the advantages of using multicomponent sensors for surface‐wave studies. Multicomponent sensors allow the use of specific signal‐processing tools such as the multicomponent singular value decomposition filter and the multicomponent polarization filter, which are both very efficient at separating surface waves from the other waves that comprise a seismic field record.
Firstly, some signal‐processing tools for studying surface waves are described. The various filters range from classical to advanced techniques. For processing single‐component data, the filters are the filter and filters based on singular value decomposition and on spectral matrix decomposition. For processing multicomponent data, the filters are the 4C‐singular value decomposition filter and the classical or high‐order polarization filter.
Secondly, processing sequences that can be applied to the field data are described and the single‐component processing sequence and the multicomponent processing sequence are compared. Two field examples are presented. The first data set is a land seismic data recording on 2C sensors. The second data set was obtained from a marine acquisition with OBS (4 components). The results obtained illustrate the advantages of using multicomponent filters. The efficiency of the 4C‐SVD filter and the high‐order statistic polarization filter is demonstrated.
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Surface‐wave inversion using a direct search algorithm and its application to ambient vibration measurements
Authors M. Wathelet, D. Jongmans and M. OhrnbergerABSTRACTPassive recordings of seismic noise are increasingly used in earthquake engineering to measure in situ the shear‐wave velocity profile at a given site. Ambient vibrations, which are assumed to be mainly composed of surface waves, can be used to determine the Rayleigh‐wave dispersion curve, with the advantage of not requiring artificial sources. Due to the data uncertainties and the non‐linearity of the problem itself, the solution of the dispersion‐curve inversion is generally non‐unique. Stochastic search methods such as the neighbourhood algorithm allow searches for minima of the misfit function by investigating the whole parameter space. Due to the limited number of parameters in surface‐wave inversion, they constitute an attractive alternative to linearized methods. An efficient tool using the neighbourhood algorithm was developed to invert the one‐dimensional profile from passive or active source experiments. As the number of generated models is usually high in stochastic techniques, special attention was paid to the optimization of the forward computations. Also, the possibility of inserting a priori information into the parametrization was introduced in the code.
This new numerical tool was successfully tested on synthetic data, with and without a priori information. We also present an application to real‐array data measured at a site in Brussels (Belgium), the geology of which consists of about 115 m of sand and clay layers overlying a Palaeozoic basement. On this site, active and passive source data proved to be complementary and the method allowed the retrieval of a profile consistent with borehole data available at the same location.
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Imaging scattered seismic surface waves
Authors X. Campman, K. van Wijk, C.D. Riyanti, J. Scales and G. HermanABSTRACTSurface‐wave analysis is a key tool for seismologists, ranging from near‐surface characterization in geotechnical applications to global seismology. Even in exploration seismology, where surface waves are regarded as a kind of noise, the fact that they typically represent the bulk of the recorded energy makes an understanding of surface‐wave propagation important. On the other hand, the heterogeneity of the near surface can make such analyses difficult since the heterogeneity is responsible for scattering and mode conversion.
Here, we show how multichannel seismic records of scattered surface waves can be used to obtain spatial images of the heterogeneity. We discuss both data processing and imaging and illustrate our method on laboratory‐scale data. Further, synthetic examples show that we can locate individual scatterers accurately, even when many scatterers produce interfering surface waves. Our laboratory results show that the method has the potential to locate near‐surface heterogeneities in the field.
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Using transfer function for estimating dissipative properties of soils from surface‐wave data
By S. FotiABSTRACTThe quality factor (or damping ratio) can be estimated by analysing the spatial attenuation of surface‐wave data. However, because of the link between geometrical and material dispersion, a coupled analysis of dispersion and attenuation curves is preferable. Using a transfer‐function approach, it is possible to estimate the dispersion and attenuation curves simultaneously, provided the seismic source is known. A formulation based on the deconvolution of seismic traces is used to extend the transfer‐function approach to ordinary seismic gathers in which the source wavelet is not known. The measured transfer function is used in a regression analysis to obtain estimates of the complex wavenumbers, which, in the framework of viscoelasticity, contain all the information relating to phase velocity and attenuation of surface waves for a layered medium. Application of this procedure to experimental data leads to results consistent with those obtained using conventional techniques (e.g. analysis and amplitude regression).
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Estimating seismic velocities below the sea‐bed using surface waves
More LessABSTRACTSeismic data acquired in shallow offshore surveys often display well‐defined dispersion patterns related to two types of surface wave, propagating in shallow subwater layers. The waves of the first type propagate as normal modes and are represented by a low‐velocity, low‐frequency wavetrain identified with Scholte waves. The phase velocities of Scholte waves are related to the shear‐wave velocities below the water‐bottom and can be inverted to estimate in the subwater layers. The waves of the second type propagate as leaking modes and are characterized by a number of distinctive features: their dispersion patterns have a resonant frequency‐tuned appearance, they have relatively high cut‐off frequencies and their phase velocities exceed the velocity in the water. When the subwater layers are composed of relatively soft saturated rocks with high Poisson’s ratio, the leaking modes can be closely approximated by acoustic waves. By inverting the approximating dispersion curves, the vertical distribution of the compressional‐wave velocity in the shallow subwater layers can be estimated.
Estimation of and below the sea‐bottom using the two types of surface wave is illustrated by examples from shallow offshore surveys conducted at several sites in the eastern Mediterranean area.
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Mechanical characterization of heterogeneous soils with surface waves: experimental validation on reduced‐scale physical models
Authors O. Abraham, R. Chammas, Ph. Cote, H.A. Pedersen and J.‐F. SemblatABSTRACTThe characterization of heterogeneous soils using common geotechnical techniques often proves impossible when the size of the heterogeneity is larger than a few tens of centimetres. Geophysical investigation techniques based on seismic wave propagation can help engineers to characterize the mechanical properties of such materials. In this paper, both refracted and surface waves are used to estimate the mechanical properties of an equivalent homogeneous medium.
A summary of the main results obtained numerically using finite‐element computations and homogenization theory is presented. It is shown that, for first‐mode surface‐wave wavelengths larger than 7.5 times the nominal size of the heterogeneity and within certain heterogeneity concentration ranges (up to 50% for matrix dominant soils), surface waves homogenize the soil in accordance with classical homogenization theory.
To validate these numerical results, a reduced‐scale model was built and seismograms, generated with a falling weight, were recorded. The phase‐velocity dispersion curve of the generated surface waves is inverted in order to obtain the shear‐wave velocity of the heterogeneous layer. The compressional‐wave velocity is calculated by means of seismic refraction analysis. Velocities obtained on the reduced‐scale model correspond to those predicted by homogenization theory from individual measurements of matrix and inclusion velocities.
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Volumes & issues
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Volume 22 (2024)
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Volume 21 (2023)
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Volume 20 (2022)
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Volume 19 (2021)
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Volume 18 (2020)
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Volume 17 (2019)
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Volume 16 (2018)
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Volume 15 (2017)
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Volume 14 (2015 - 2016)
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Volume 13 (2015)
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Volume 12 (2013 - 2014)
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Volume 11 (2013)
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Volume 10 (2012)
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Volume 9 (2011)
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Volume 8 (2010)
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Volume 7 (2009)
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Volume 6 (2008)
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Volume 5 (2007)
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Volume 4 (2006)
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Volume 3 (2005)
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Volume 2 (2004)
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Volume 1 (2003)