Joint inversion of H/V ratios and dispersion curves from seismic noise: Estimating the S-wave velocity of bedrock

We use teleseismic P-to-S converted waves from a permanent station to estimate the uncertainties in a 1D elastic model of the shallow crust (0–7 km depth) obtained from the inversion of receiver function (RF) data. Our earth model consists of layers with a constant S-wave velocity [Formula: see text] and P- to S-wave velocity ratio ([Formula: see text]). We apply a Bayesian formulation and transdimensional Monte Carlo sampling to compute the posterior uncertainties of the earth model. The model uncertainties rely on a realistic representation of the data uncertainties, and we estimate directly from the stacking of the teleseismic data, a full-error covariance matrix. To explore the effect of the number of teleseismic events and the RF frequency content, we compare the results of inverting a single RF computed for a cut-off filter frequency of 4 Hz with the joint inversion of four RFs computed from independent ensembles in a larger pool of events for cut-off frequencies of 0.5, 1, 2, and 4 Hz. The inversion results are compared with the lithostratigraphy and sonic-log measurements from a 7 km deep borehole drilled near the seismic station. The inversion of a single RF results in larger uncertainties in the recovered [Formula: see text] profile and in the depth to seismic discontinuities compared with the multifrequency inversion. Moreover, the multifrequency inversion predicts more accurately the depth to a velocity inversion at approximately 6 km below the surface and matches more closely the borehole sonic-log data. Our results indicate that RF data can be used to map shallow (3–5 km depth) crustal interfaces with uncertainties in the order of 300–500 m, whereas uncertainties are consistently smaller (<300 m) for interfaces in the top kilometer.

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Love-wave waveform inversion in time domain for shallow shear-wave velocity

Geophysics ◽

10.1190/geo2014-0225.1 ◽

2016 ◽

Vol 81 (1) ◽

pp. R1-R14 ◽

Cited By ~ 25

Author(s):

Yudi Pan ◽

Jianghai Xia ◽

Yixian Xu ◽

Lingli Gao ◽

Zongbo Xu

Keyword(s):

Surface Wave ◽

Wave Velocity ◽

Time Domain ◽

Love Wave ◽

Waveform Inversion ◽

Dispersion Curves ◽

Gradient Algorithm ◽

S Wave ◽

Near Surface ◽

Earth Models

High-frequency surface-wave techniques are widely used to estimate S-wave velocity of near-surface materials. Surface-wave methods based on inversions of dispersion curves are only suitable to laterally homogeneous or smoothly laterally varying heterogeneous earth models due to the layered-model assumption during calculation of dispersion curves. Waveform inversion directly fits the waveform of observed data, and it can be applied to any kinds of earth models. We have used the Love-wave waveform inversion in the time domain to estimate near-surface S-wave velocity. We used the finite-difference method as the forward modeling method. The source effect was removed by the deconvolution technique, which made our method independent of the source wavelet. We defined the difference between the deconvolved observed and calculated waveform as the misfit function. We divided the model into different sizes of blocks depending on the resolution of the Love waves, and we updated the S-wave velocity of each block via a conjugate gradient algorithm. We used two synthetic models to test the effectiveness of our method. A real-world case verified the validity of our method.

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Characteristics of the horizontal component of Rayleigh waves in multimode analysis of surface waves

Geophysics ◽

10.1190/geo2014-0018.1 ◽

2015 ◽

Vol 80 (1) ◽

pp. EN1-EN11 ◽

Cited By ~ 14

Author(s):

Tatsunori Ikeda ◽

Toshifumi Matsuoka ◽

Takeshi Tsuji ◽

Toru Nakayama

Keyword(s):

Surface Waves ◽

Wave Velocity ◽

Rayleigh Waves ◽

Field Data ◽

Vertical Component ◽

Dispersion Curves ◽

Horizontal Component ◽

S Wave ◽

Higher Modes ◽

Explosive Source

In surface-wave analysis, S-wave velocity estimations can be improved by the use of higher modes of the surface waves. The vertical component of P-SV waves is commonly used to estimate multimode Rayleigh waves, although Rayleigh waves are also included in horizontal components of P-SV waves. To demonstrate the advantages of using the horizontal components of multimode Rayleigh waves, we investigated the characteristics of the horizontal and vertical components of Rayleigh waves. We conducted numerical modeling and field data analyses rather than a theoretical study for both components of Rayleigh waves. As a result of a simulation study, we found that the estimated higher modes have larger relative amplitudes in the vertical and horizontal components as the source depth increases. In particular, higher-order modes were observed in the horizontal component data for an explosive source located at a greater depth. Similar phenomena were observed in the field data acquired by using a dynamite source at 15-m depth. Sensitivity analyses of dispersion curves to S-wave velocity changes revealed that dispersion curves additionally estimated from the horizontal components can potentially improve S-wave velocity estimations. These results revealed that when the explosive source was buried at a greater depth, the horizontal components can complement Rayleigh waves estimated from the vertical components. Therefore, the combined use of the horizontal component data with the vertical component data would contribute to improving S-wave velocity estimations, especially in the case of buried explosive source signal.

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Inversion of reflection traveltimes for transverse isotropy

Geophysics ◽

10.1190/1.1443838 ◽

1995 ◽

Vol 60 (4) ◽

pp. 1095-1107 ◽

Cited By ~ 70

Author(s):

Ilya Tsvankin ◽

Leon Thomsen

Keyword(s):

Wave Velocity ◽

Vertical Velocity ◽

Joint Inversion ◽

Transverse Isotropy ◽

Taylor Series Expansion ◽

High Sensitivity ◽

Transversely Isotropic ◽

P Wave ◽

S Wave ◽

Quartic Term

In anisotropic media, the short‐spread stacking velocity is generally different from the root‐mean‐square vertical velocity. The influence of anisotropy makes it impossible to recover the vertical velocity (or the reflector depth) using hyperbolic moveout analysis on short‐spread, common‐midpoint (CMP) gathers, even if both P‐ and S‐waves are recorded. Hence, we examine the feasibility of inverting long‐spread (nonhyperbolic) reflection moveouts for parameters of transversely isotropic media with a vertical symmetry axis. One possible solution is to recover the quartic term of the Taylor series expansion for [Formula: see text] curves for P‐ and SV‐waves, and to use it to determine the anisotropy. However, this procedure turns out to be unstable because of the ambiguity in the joint inversion of intermediate‐spread (i.e., spreads of about 1.5 times the reflector depth) P and SV moveouts. The nonuniqueness cannot be overcome by using long spreads (twice as large as the reflector depth) if only P‐wave data are included. A general analysis of the P‐wave inverse problem proves the existence of a broad set of models with different vertical velocities, all of which provide a satisfactory fit to the exact traveltimes. This strong ambiguity is explained by a trade‐off between vertical velocity and the parameters of anisotropy on gathers with a limited angle coverage. The accuracy of the inversion procedure may be significantly increased by combining both long‐spread P and SV moveouts. The high sensitivity of the long‐spread SV moveout to the reflector depth permits a less ambiguous inversion. In some cases, the SV moveout alone may be used to recover the vertical S‐wave velocity, and hence the depth. Success of this inversion depends on the spreadlength and degree of SV‐wave velocity anisotropy, as well as on the constraints on the P‐wave vertical velocity.

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Estimation of shallow subsurface S-wave velocity structure in urban area based on inversion of apparent dispersion curve

Journal of Geophysics and Engineering ◽

10.1093/jge/gxaa054 ◽

2020 ◽

Vol 17 (6) ◽

pp. 940-955

Author(s):

Zhiwei You ◽

Peifen Xu ◽

Suqun Ling ◽

Yanan Du ◽

Ruohan Zhang ◽

...

Keyword(s):

Spatial Autocorrelation ◽

Urban Area ◽

Wave Velocity ◽

Simulated Annealing Algorithm ◽

Velocity Structure ◽

Dispersion Curves ◽

Survey Method ◽

S Wave ◽

Geological Surveys ◽

Autocorrelation Method

Abstract Due to its efficiency, convenience, non-destructive nature and strong anti-interference capability, the microtremor survey method (MSM) has found wide applications in urban geological surveys. The spatial autocorrelation method is diffusely applied to extract the dispersion curves from microtremor signals, which needs to satisfy the assumption that the energy of the fundamental Rayleigh wave is dominant. However, for layered media containing a layer with a significant low- or high-velocity contrast, this assumption is distinctly incorrect for certain frequency ranges. We present a processing methodology comprising the extraction and inversion of the apparent dispersion curves based on extended spatial autocorrelation method and fast simulated-annealing algorithm. We analyse synthetic microtremor signals for three selected geological models, and then compare the S-wave velocity structures estimated from their inversions with the actual models. Subsequently, a filed data example is given to detect the shallow stratigraphic structures in Guangzhou city, China, in which the new MSM was used. The estimated two-dimensional S-wave velocity model provided an accurate description of the thickness and depth of the strata in the study area, based on a priori information. Moreover, the S-wave velocity structures estimated from the MSM and the results from the drilling match very well, indicating that MSM is a reliable geophysical technique in urban geological surveys. Combined with available borehole information, MSM can be a very robust and effective method for detecting the shallow three-dimensional velocity structures in an urban area.

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Shear wave velocity model of the ABANICO formation underlying The santiago City Metropolitan Area, chile, using ambient seismic noise tomography

Geophysical Journal International ◽

10.1093/gji/ggaa600 ◽

2020 ◽

Author(s):

J Salomón ◽

C Pastén ◽

S Ruiz ◽

F Leyton ◽

M Sáez ◽

...

Keyword(s):

Shear Wave ◽

Wave Velocity ◽

Metropolitan Area ◽

Shear Wave Velocity ◽

Seismic Noise ◽

Velocity Model ◽

Dispersion Curves ◽

Ambient Seismic Noise ◽

Travel Times ◽

Abanico Formation

Summary The seismic response of the Santiago City, the capital of Chile with more than 5.5 million inhabitants, is controlled by the properties of the shallower quaternary deposits and the impedance contrast with the underlying Abanico formation, among other factors. In this study, we process continuous records of ambient seismic noise to perform an ambient seismic noise tomography with the aim of defining the shallower structure of the Abanico formation underneath the densely populated metropolitan area of Santiago, Chile. The seismic signals were recorded by a network consisting of 29 broadband seismological stations and 12 accelerograph stations, located in a 35 × 35 km2 quadrant. We used the average coherency of the vertical components to calculate dispersion curves from 0.1 to 5 Hz and Bootstrap resampling to estimate the variance of the travel times. The reliable frequency band of the dispersion curves was defined by an empirical method based on sign normalization of the coherency real part. The ambient noise tomography was solved on a domain discretized into 256 2 × 2 km2 cells. Using a regularized weighted least squares inversion, we inverted the observed travel-times between stations, assuming straight ray paths, in order to obtain 2D phase velocity maps from 0.2 Hz to 1.1 Hz, linearly spaced every 0.05 Hz, in 157 of the 256 square cells of the domain. In each square cell with information, dispersion curves were assembled and used to invert shear wave velocity profiles, which were interpolated using the ordinary Kriging method to obtain a 3D shear wave velocity model valid from 0.6 to 5 km depth. The 3D velocity model shows that the Abanico formation is stiffer in the south of the study area with larger velocity anomalies towards the shallower part of the model. The value of the shear wave velocity narrows with depth, reaching an average value of 3.5 km/s from 3 to 5 km depth.

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