SS: The Future of Seismic Imaging; Reverse Time Migration and Full Wavefield Inversion - 3D Prestack Full Waveform Inversion

2009 ◽  
Author(s):  
Denes Vigh ◽  
Eugene William Starr ◽  
Kenneth Dingwall
Keyword(s):  
Seismic Imaging ◽  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Full Waveform ◽  
Time Migration ◽  
The Future ◽  
Wavefield Inversion

From classical reflectivity-to-velocity inversion to full-waveform inversion using phase-modified and deconvolved reverse time migration images

Geophysics ◽  
2017 ◽  
Vol 82 (1) ◽  
pp. S31-S49 ◽  
Author(s):  
Chen Tang ◽  
George A. McMechan
Keyword(s):  
Waveform Inversion ◽  
Time Integration ◽  
Multiscale Approach ◽  
Full Waveform Inversion ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Velocity Inversion ◽  
Full Waveform ◽  
Time Migration ◽  
Gradient Based

To obtain a physical understanding of gradient-based descent methods in full-waveform inversion (FWI), we find a connection between the FWI gradient and the image provided by reverse time migration (RTM). The gradient uses the residual data as a virtual source, and RTM uses the observed data directly as the boundary condition, so the FWI gradient is similar to a time integration of the RTM image using the residual data, which physically converts the phase of the reflectivity to the phase of the velocity. Therefore, gradient-based FWI can be connected to the classical reflectivity-to-velocity/impedance inversion (RVI). We have developed a new FWI scheme that provides a self-contained and physically intuitive derivation, which naturally establishes a connection among the amplitude-preserved RTM, the Zoeppritz equations (amplitude variation with angle inversion), and RVI, and combines them into a single framework to produce a preconditioned inversion formula. In this scheme, the relative velocity update is a phase-modified and deconvolved RTM image obtained with the residual data. Consistent with the deconvolution, the multiscale approach applies a gradually widening low-pass frequency filter to the deconvolved wavelet at early iterations, and then it uses the unfiltered deconvolved wavelet for the final iterations. Our numerical testing determined that the new method makes a significant improvement to the quality of the inversion result.

Efficient snapshot-free reverse time migration and computation of multiparameter gradients in full waveform inversion

Geophysics ◽  
2021 ◽  
pp. 1-79
Author(s):  
Johan O. A. Robertsson ◽  
Fredrik Andersson ◽  
René-Édouard Plessix
Keyword(s):  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Principle Of Superposition ◽  
Model Parameter ◽  
Inversion Model ◽  
Full Waveform ◽  
Time Migration ◽  
Anisotropic Elastic

Computing images in reverse time migration and model parameter gradients from adjoint wavefields in full waveform inversion requires the correlation of a forward propagated wavefield with another reverse propagated wavefield. Although in theory only two wavefield propagations are required, one forward propagation and one reverse propagation, it requires storing the forward propagated wavefield as a function of time to carry out the correlations which is associated with significant I/O cost. Alternatively, three wavefield propagations can be carried out to reverse propagate the forward propagated wavefield in tandem with the reverse propagated wavefield. We show how highly accurate reverse time migrated images and full waveform inversion model parameter gradients for anisotropic elastic full waveform inversion can be efficiently computed without significant disk I/O using two wavefield propagations by means of the principle of superposition.

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