scholarly journals Ambient noise multimode Rayleigh and Love wave tomography to determine the shear velocity structure above the Groningen gas field

2019 ◽  
Vol 218 (3) ◽  
pp. 1781-1795 ◽  
Author(s):  
M Chmiel ◽  
A Mordret ◽  
P Boué ◽  
F Brenguier ◽  
T Lecocq ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Rayleigh Waves ◽  
Seismic Activity ◽  
Ambient Noise ◽  
Velocity Model ◽  
S Wave ◽  
Gas Field ◽  
Rayleigh And Love Waves ◽  
Wave Tomography ◽  
Groningen Gas Field

SUMMARY The Groningen gas field is one of the largest gas fields in Europe. The continuous gas extraction led to an induced seismic activity in the area. In order to monitor the seismic activity and study the gas field many permanent and temporary seismic arrays were deployed. In particular, the extraction of the shear wave velocity model is crucial in seismic hazard assessment. Local S-wave velocity-depth profiles allow us the estimation of a potential amplification due to soft sediments. Ambient seismic noise tomography is an interesting alternative to traditional methods that were used in modelling the S-wave velocity. The ambient noise field consists mostly of surface waves, which are sensitive to the Swave and if inverted, they reveal the corresponding S-wave structures. In this study, we present results of a depth inversion of surface waves obtained from the cross-correlation of 1 month of ambient noise data from four flexible networks located in the Groningen area. Each block consisted of about 400 3-C stations. We compute group velocity maps of Rayleigh and Love waves using a straight-ray surface wave tomography. We also extract clear higher modes of Love and Rayleigh waves. The S-wave velocity model is obtained with a joint inversion of Love and Rayleigh waves using the Neighbourhood Algorithm. In order to improve the depth inversion, we use the mean phase velocity curves and the higher modes of Rayleigh and Love waves. Moreover, we use the depth of the base of the North Sea formation as a hard constraint. This information provides an additional constraint for depth inversion, which reduces the S-wave velocity uncertainties. The final S-wave velocity models reflect the geological structures up to 1 km depth and in perspective can be used in seismic risk modelling.

scholarly journals An integrated shear-wave velocity model for the Groningen gas field, The Netherlands

2017 ◽  
Vol 15 (9) ◽  
pp. 3555-3580 ◽  
Author(s):  
Pauline P. Kruiver ◽  
Ewoud van Dedem ◽  
Remco Romijn ◽  
Ger de Lange ◽  
Mandy Korff ◽  
...  
Keyword(s):  
The Netherlands ◽  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Velocity Model ◽  
Gas Field ◽  
Groningen Gas Field

scholarly journals Application of a complete workflow for 2D elastic full-waveform inversion to recorded shallow-seismic Rayleigh waves

Geophysics ◽  
2017 ◽  
Vol 82 (2) ◽  
pp. R109-R117 ◽  
Author(s):  
Lisa Groos ◽  
Martin Schäfer ◽  
Thomas Forbriger ◽  
Thomas Bohlen
Keyword(s):  
Wave Velocity ◽  
Rayleigh Waves ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Full Waveform Inversion ◽  
S Wave ◽  
Full Waveform ◽  
Shallow Seismic ◽  
Lateral Variations ◽  
Seismic Rayleigh Waves

The S-wave velocity of the shallow subsurface can be inferred from shallow-seismic Rayleigh waves. Traditionally, the dispersion curves of the Rayleigh waves are inverted to obtain the (local) S-wave velocity as a function of depth. Two-dimensional elastic full-waveform inversion (FWI) has the potential to also infer lateral variations. We have developed a novel workflow for the application of 2D elastic FWI to recorded surface waves. During the preprocessing, we apply a line-source simulation (spreading correction) and perform an a priori estimation of the attenuation of waves. The iterative multiscale 2D elastic FWI workflow consists of the preconditioning of the gradients in the vicinity of the sources and a source-wavelet correction. The misfit is defined by the least-squares norm of normalized wavefields. We apply our workflow to a field data set that has been acquired on a predominantly depth-dependent velocity structure, and we compare the reconstructed S-wave velocity model with the result obtained by a 1D inversion based on wavefield spectra (Fourier-Bessel expansion coefficients). The 2D S-wave velocity model obtained by FWI shows an overall depth dependency that agrees well with the 1D inversion result. Both models can explain the main characteristics of the recorded seismograms. The small lateral variations in S-wave velocity introduced by FWI additionally explain the lateral changes of the recorded Rayleigh waves. The comparison thus verifies the applicability of our 2D FWI workflow and confirms the potential of FWI to reconstruct shallow small-scale lateral changes of S-wave velocity.

Sedimentary structure of the Sichuan Basin derived from seismic ambient noise tomography

2020 ◽  
Author(s):  
Xin Xia ◽  
Zhiwei Li ◽  
Feng Bao ◽  
Jun Xie ◽  
Yutao Shi ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Sichuan Basin ◽  
Ambient Noise ◽  
Large Scale ◽  
Velocity Model ◽  
S Wave ◽  
Ambient Noise Tomography ◽  
Ground Acceleration ◽  
The Sichuan Basin ◽  
Sedimentary Layer

Summary Determining a detailed 3-D velocity model with high resolution for the sedimentary layer in the Sichuan Basin is potentially beneficial both to the industrial oil/gas exploration and earthquake hazards mitigation. In this study, we apply the ambient noise tomography method to construct a 3-D S-wave velocity model. This model focuses on the sedimentary layer of the Sichuan Basin, with a 0.3° × 0.3° grid precision. Dispersion curves of both group and phase velocities of Rayleigh wave at 4 to 40 s periods are utilized, which are extracted from 87 broadband stations in the Sichuan Basin and the surrounding areas. The 3-D model reveals a thick sedimentary layer of the Sichuan Basin with S-wave velocity ranging from ∼2.0 km/s to 3.4 km/s. The sediment thickness in the margins of the Sichuan Basin is generally greater than the typical values of 6–10 km in the central areas due to surrounding orogenic activities, with a maximum depth of ∼13 km in the northwestern margin. Moreover, a prominent low S-wave velocity anomaly in the margins may be caused by the sediment accumulations from large-scale landslides and pronounced denudation of the surrounding orogenic belts. Major geologic units in the sedimentary layer are delineated in this study. The S-wave velocity values within each geologic unit and their bottom interfaces are obtained. Based on our model, we calculate synthetic ground motions for the 2013 Lushan earthquake and obtain the distribution of the peak ground acceleration from the earthquake epicenter to the western Sichuan Basin. The result clearly illustrates the basin amplification effect on the seismic waves.

scholarly journals 3D wave-equation dispersion inversion of Rayleigh waves

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. R673-R691 ◽  
Author(s):  
Zhaolun Liu ◽  
Jing Li ◽  
Sherif M. Hanafy ◽  
Gerard Schuster
Keyword(s):  
Wave Equation ◽  
Wave Velocity ◽  
Rayleigh Waves ◽  
Waveform Inversion ◽  
Shear Velocity ◽  
Velocity Model ◽  
Azimuth Angle ◽  
Inversion Method ◽  
S Wave ◽  
Starting Model

The 2D wave-equation dispersion (WD) inversion method is extended to 3D wave-equation dispersion inversion of surface waves for the shear-velocity distribution. The objective function of 3D WD is the frequency summation of the squared wavenumber [Formula: see text] differences along each azimuth angle of the fundamental or higher modes of Rayleigh waves in each shot gather. The S-wave velocity model is updated by the weighted zero-lag crosscorrelation between the weighted source-side wavefield and the back-projected receiver-side wavefield for each azimuth angle. A multiscale 3D WD strategy is provided, which starts from the pseudo-1D S-velocity model, which is then used to get the 2D WD tomogram, which in turn is used as the starting model for 3D WD. The synthetic and field data examples demonstrate that 3D WD can accurately reconstruct the 3D S-wave velocity model of a laterally heterogeneous medium and has much less of a tendency to getting stuck in a local minimum compared with full-waveform inversion.

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