Full-waveform inversion with alternating source and model update for shallow seismic

Author(s):  
Dmitry Borisov ◽  
Julian Ivanov ◽  
Shelby L. Peterie ◽  
Richard D. Miller
Geophysics ◽  
2017 ◽  
Vol 82 (2) ◽  
pp. R109-R117 ◽  
Author(s):  
Lisa Groos ◽  
Martin Schäfer ◽  
Thomas Forbriger ◽  
Thomas Bohlen

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.


Geophysics ◽  
2014 ◽  
Vol 79 (3) ◽  
pp. R91-R101 ◽  
Author(s):  
Tariq Alkhalifah ◽  
René-Édouard Plessix

In multiparameter full-waveform inversion (FWI) and specifically one describing the anisotropic behavior of the medium, it is essential that we have an understanding of the parameter resolution possibilities and limits. Because the imaging kernel is at the heart of the inversion engine (the model update), we drew our development and choice of parameters from what we have experienced in imaging seismic data in anisotropic media. In representing the most common (first-order influence and gravity induced) acoustic anisotropy, specifically, a transversely isotropic medium with a vertical symmetry direction (VTI), with the [Formula: see text]-wave normal moveout velocity, anisotropy parameters [Formula: see text], and [Formula: see text], we obtained a perturbation radiation pattern that has limited trade-off between the parameters. Because [Formula: see text] is weakly resolvable from the kinematics of [Formula: see text]-wave propagation, we can use it to play the role that density plays in improving the data fit for an imperfect physical model that ignores the elastic nature of the earth. An FWI scheme that starts from diving waves would benefit from representing the acoustic VTI model with the [Formula: see text]-wave horizontal velocity, [Formula: see text], and [Formula: see text]. In this representation, the diving waves will help us first resolve the horizontal velocity and then reflections, if the nonlinearity is properly handled, could help us resolve [Formula: see text], and [Formula: see text] could help improve the amplitude fit (instead of the density). The model update wavenumber for acoustic anisotropic FWI is very similar to that for the isotropic case, which is mainly dependent on the scattering angle and frequency.


Geophysics ◽  
2014 ◽  
Vol 79 (6) ◽  
pp. R247-R261 ◽  
Author(s):  
Lisa Groos ◽  
Martin Schäfer ◽  
Thomas Forbriger ◽  
Thomas Bohlen

Full-waveform inversion (FWI) of Rayleigh waves is attractive for shallow geotechnical investigations due to the high sensitivity of Rayleigh waves to the S-wave velocity structure of the subsurface. In shallow-seismic field data, the effects of anelastic damping are significant. Dissipation results in a low-pass effect as well as frequency-dependent decay with offset. We found this by comparing recorded waveforms with elastic and viscoelastic wave simulation. The effects of anelastic damping must be considered in FWI of shallow-seismic Rayleigh waves. FWI using elastic simulation of wave propagation failed in synthetic inversion tests in which we tried to reconstruct the S-wave velocity in a viscoelastic model. To overcome this, [Formula: see text]-values can be estimated from the recordings to quantify viscoelasticity. Waveform simulation in the FWI then uses these a priori values when inferring seismic velocities and density. A source-wavelet correction, which is inevitable in FWI of field data, can compensate a significant fraction of the residuals between elastically and viscoelastically simulated data by narrowing the signals’ bandwidth. This way, elastic simulation becomes applicable in FWI of data from anelastic media. This approach, however, was not able to produce a frequency-dependent amplitude decay with offset. Reconstruction, therefore, was more accurate when using appropriate viscoelastic modeling in FWI of shallow-seismic Rayleigh waves. We found this by synthetic inversion tests using elastic forward simulation as well as viscoelastic simulation with different a priori values for [Formula: see text].


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