Surface wave tomography using 3D active-source seismic data

Geophysics ◽  
2021 ◽  
Vol 86 (1) ◽  
pp. EN13-EN26
Author(s):  
Ilaria Barone ◽  
Emanuel Kästle ◽  
Claudio Strobbia ◽  
Giorgio Cassiani
Keyword(s):  
Surface Wave ◽  
Phase Velocity ◽  
Wave Velocity ◽  
Computational Time ◽  
Surface Wave Tomography ◽  
S Wave ◽  
Data Set ◽  
Velocity Models ◽  
Active Source ◽  
Wave Tomography

Surface wave tomography (SWT) is a powerful and well-established technique to retrieve 3D shear-wave (S-wave) velocity models at the regional scale from earthquakes and seismic noise measurements. We have applied SWT to 3D active-source data, in which higher modes and heterogeneous spatial sampling make phase extraction challenging. First, synthetic traveltimes calculated on a dense, regular-spaced station array are used to test the performance of three different tomography algorithms (linearized inversion, Markov chain Monte Carlo [MCMC], and eikonal tomography). The tests suggest that the lowest misfit to the input model is achieved with the MCMC algorithm, at the cost of a much longer computational time. Then, real phases were extracted from a 3D exploration data set at different frequencies. This operation included an automated procedure to isolate the fundamental mode from higher order modes, phase unwrapping in two dimensions, and the estimation of the zero-offset phase. These phases are used to compute traveltimes between each source-receiver couple, which are input into the previously tested tomography algorithms. The resulting phase-velocity maps show good correspondence, highlighting the same geologic structures for all three methods. Finally, individual dispersion curves obtained by the superposition of phase-velocity maps at different frequencies are depth inverted to retrieve a 3D S-wave velocity model.

Seismic Surface Wave Tomography on dense 3D active data

2020 ◽  
Author(s):  
Ilaria Barone ◽  
Emanuel Kästle ◽  
Claudio Strobbia ◽  
Giorgio Cassiani
Keyword(s):  
Surface Wave ◽  
Phase Velocity ◽  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Seismic Exploration ◽  
Surface Wave Tomography ◽  
Travel Times ◽  
Velocity Models ◽  
Wave Tomography

<p>Surface Wave Tomography (SWT) is a well-established technique in global seismology: signals from strong earthquakes or seismic ambient noise are used to retrieve 3D shear-wave velocity models, both at regional and global scale. This study aims at applying the same methodology to controlled source data, with specific focus on 3D acquisition geometries for seismic exploration. For a specific frequency, travel times between all source-receiver couples are derived from phase differences. However, higher modes and heterogeneous spatial sampling make phase extraction challenging. The processing workflow includes different steps as (1) filtering in f-k domain to isolate the fundamental mode from higher order modes, (2) phase unwrapping in two spatial dimensions, (3) zero-offset phase estimation and (4) travel times computation. Surface wave tomography is then applied to retrieve a 2D phase velocity map. This procedure is repeated for different frequencies. Finally, individual dispersion curves obtained by the superposition of phase velocity maps at different frequencies are depth inverted to retrieve a 3D shear wave velocity model.</p>

Ground roll: A potential tool for constraining shallow shear‐wave structure

Geophysics ◽  
1993 ◽  
Vol 58 (5) ◽  
pp. 713-719 ◽  
Author(s):  
Ghassan I. Al‐Eqabi ◽  
Robert B. Herrmann
Keyword(s):  
Surface Wave ◽  
Phase Velocity ◽  
Wave Velocity ◽  
Wave Structure ◽  
S Wave ◽  
Data Set ◽  
Velocity Inversion ◽  
Ground Roll ◽  
Lateral Variations ◽  
Wave Arrival

The objective of this study is to demonstrate that a laterally varying shallow S‐wave structure, derived from the dispersion of the ground roll, can explain observed lateral variations in the direct S‐wave arrival. The data set consists of multichannel seismic refraction data from a USGS-GSC survey in the state of Maine and the province of Quebec. These data exhibit significant lateral changes in the moveout of the ground‐roll as well as the S‐wave first arrivals. A sequence of surface‐wave processing steps are used to obtain a final laterally varying S‐wave velocity model. These steps include visual examination of the data, stacking, waveform inversion of selected traces, phase velocity adjustment by crosscorrelation, and phase velocity inversion. These models are used to predict the S‐wave first arrivals by using two‐dimensional (2D) ray tracing techniques. Observed and calculated S‐wave arrivals match well over 30 km long data paths, where lateral variations in the S‐wave velocity in the upper 1–2 km are as much as ±8 percent. The modeled correlation between the lateral variations in the ground‐roll and S‐wave arrival demonstrates that a laterally varying structure can be constrained by using surface‐wave data. The application of this technique to data from shorter spreads and shallower depths is discussed.

Advances in surface-wave tomography for near-surface applications

2021 ◽  
Vol 40 (8) ◽  
pp. 567-575
Author(s):  
Myrto Papadopoulou ◽  
Farbod Khosro Anjom ◽  
Mohammad Karim Karimpour ◽  
Valentina Laura Socco
Keyword(s):  
Surface Wave ◽  
Wave Velocity ◽  
P Wave ◽  
Seismic Exploration ◽  
S Wave ◽  
Data Set ◽  
Near Surface ◽  
Processing Times ◽  
Spatial Coverage ◽  
Wave Tomography

Surface-wave (SW) tomography is a technique that has been widely used in the field of seismology. It can provide higher resolution relative to the classical multichannel SW processing and inversion schemes that are usually adopted for near-surface applications. Nevertheless, the method is rarely used in this context, mainly due to the long processing times needed to pick the dispersion curves as well as the inability of the two-station processing to discriminate between higher SW modes. To make it efficient and to retrieve pseudo-2D/3D S-wave velocity (VS) and P-wave velocity (VP) models in a fast and convenient way, we develop a fully data-driven two-station dispersion curve estimation, which achieves dense spatial coverage without the involvement of an operator. To handle higher SW modes, we apply a dedicated time-windowing algorithm to isolate and pick the different modes. A multimodal tomographic inversion is applied to estimate a VS model. The VS model is then converted to a VP model with the Poisson's ratio estimated through the wavelength-depth method. We apply the method to a 2D seismic exploration data set acquired at a mining site, where strong lateral heterogeneity is expected, and to a 3D pilot data set, recorded with state-of-the-art acquisition technology. We compare the results with the ones retrieved from classical multichannel analysis.

Phase-velocity inversion from data-based diffraction kernels: seismic Michelson interferometer

2020 ◽  
Vol 224 (2) ◽  
pp. 1287-1300
Author(s):  
Małgorzata Chmiel ◽  
Philippe Roux ◽  
Marc Wathelet ◽  
Thomas Bardainne
Keyword(s):  
Surface Wave ◽  
Phase Velocity ◽  
Waveform Inversion ◽  
Michelson Interferometer ◽  
Surface Wave Tomography ◽  
Velocity Inversion ◽  
Full Waveform ◽  
Active Source ◽  
Iterative Inversion ◽  
Wave Tomography

SUMMARY We propose a new surface wave tomography approach that benefits from densely sampled active-source arrays and brings together elements from active-source seismic-wave interferometry, full waveform inversion and dense-array processing. In analogy with optical interferometry, seismic Michelson interferometer (SMI) uses seismic interference patterns given by the data-based diffraction kernels in an iterative inversion scheme to image a medium. SMI requires no traveltime measurements and no spatial regularization, and it accounts for bent rays. Furthermore, the method does not need computation of complex synthetic models, as it works as a data-driven inversion technique that makes it computationally very fast. In an automatic way, it provides high-resolution phase-velocity maps and their error estimation. SMI can complete traditional surface wave tomography studies, as its use can be easily extended from land active seismic data to the virtual source gathers of ambient-noise-based studies with dense arrays.

scholarly journals Joint Body‐ and Surface‐Wave Tomography of Yucca Flat, Nevada, Using a Novel Seismic Source

2019 ◽  
Vol 109 (5) ◽  
pp. 1922-1934 ◽  
Author(s):  
Liam D. Toney ◽  
Robert E. Abbott ◽  
Leiph A. Preston ◽  
David G. Tang ◽  
Tori Finlay ◽  
...  
Keyword(s):  
Surface Wave ◽  
Phase Velocity ◽  
Wave Velocity ◽  
Velocity Structure ◽  
Joint Inversion ◽  
P Wave ◽  
S Wave ◽  
Surface Wave Dispersion ◽  
Velocity Models ◽  
Phase Velocity Dispersion

Abstract In preparation for the next phase of the Source Physics Experiments, we acquired an active‐source seismic dataset along two transects totaling more than 30 km in length at Yucca Flat, Nevada, on the Nevada National Security Site. Yucca Flat is a sedimentary basin which has hosted more than 650 underground nuclear tests (UGTs). The survey source was a novel 13,000 kg modified industrial pile driver. This weight drop source proved to be broadband and repeatable, richer in low frequencies (1–3 Hz) than traditional vibrator sources and capable of producing peak particle velocities similar to those produced by a 50 kg explosive charge. In this study, we performed a joint inversion of P‐wave refraction travel times and Rayleigh‐wave phase‐velocity dispersion curves for the P‐ and S‐wave velocity structure of Yucca Flat. Phase‐velocity surface‐wave dispersion measurements were obtained via the refraction microtremor method on 1 km arrays, with 80% overlap. Our P‐wave velocity models verify and expand the current understanding of Yucca Flat’s subsurface geometry and bulk properties such as depth to Paleozoic basement and shallow alluvium velocity. Areas of disagreement between this study and the current geologic model of Yucca Flat (derived from borehole studies) generally correlate with areas of widely spaced borehole control points. This provides an opportunity to update the existing model, which is used for modeling groundwater flow and radionuclide transport. Scattering caused by UGT‐related high‐contrast velocity anomalies substantially reduced the number and frequency bandwidth of usable dispersion picks. The S‐wave velocity models presented in this study agree with existing basin‐wide studies of Yucca Flat, but are compromised by diminished surface‐wave coherence as a product of this scattering. As nuclear nonproliferation monitoring moves from teleseismic to regional or even local distances, such high‐frequency (>5  Hz) scattering could prove challenging when attempting to discriminate events in areas of previous testing.

Two-station continuous wavelet transform cross-coherence analysis for surface-wave tomography using active-source seismic data

Geophysics ◽  
2020 ◽  
Vol 85 (1) ◽  
pp. EN17-EN28
Author(s):  
Tatsunori Ikeda ◽  
Takeshi Tsuji
Keyword(s):  
Wavelet Transform ◽  
Surface Wave ◽  
Phase Velocity ◽  
Seismic Data ◽  
Velocity Dispersion ◽  
Dispersion Curves ◽  
Surface Wave Tomography ◽  
S Wave ◽  
Phase Velocity Dispersion ◽  
Wave Tomography

ABSTRACT Surface-wave tomography has great potential to improve the lateral resolution of near-surface characterization compared to 2D surface-wave analysis with multichannel analysis of surface waves (MASW). Surface-wave tomography has been widely applied to obtain high-resolution maps of phase or group velocity from dispersion curves between pairs of stations in seismological studies. However, very few studies have done surface-wave tomography with active-source (exploration) seismic data, probably because extracting surface-wave dispersion curves between two stations is difficult due to the complex wave propagation in heterogeneous near-surface structures. Here, we describe a method to estimate reliable phase-velocity dispersion curves between two stations from exploration seismic data. In our approach, we compute cross coherences between pairs of stations to extract phase information, stacking the cross coherences from different shot gathers to improve the signal-to-noise ratio. To further distinguish surface-wave signals from noise in the time domain, we perform a time-frequency analysis using the continuous wavelet transform (CWT) on the stacked cross coherences. We used modeling of the wavelet transform between station pairs to extract phase-velocity dispersion curves from the stacked cross coherences. We apply this two-station CWT cross-coherence method to synthetic and field data sets. Both applications demonstrate that our method can extract stable phase-velocity dispersion curves between two stations better than two-station or multistation analysis without time-domain filtering. In phase-velocity distributions constructed by surface-wave tomography from the dispersion curves between two stations, the horizontal resolution is improved over MASW-based analyses. Improvement of the horizontal resolution is also achieved in S-wave velocity structures derived by inversion of the phase-velocity distributions. Our method is effective in estimating reliable phase-velocity dispersion curves and may contribute to constructing high-resolution S-wave velocity models located with a laterally heterogeneous structure, by subsequent surface-wave tomography and S-wave velocity inversion.

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