• Corpus ID: 246240150

Application of an RBF-FD solver for the Helmholtz equation to full-waveform inversion

@article{Londoo2022ApplicationOA,
  title={Application of an RBF-FD solver for the Helmholtz equation to full-waveform inversion},
  author={M. A. Londo{\~n}o and Francisco J. Rodr'iguez-Cort'es},
  journal={ArXiv},
  year={2022},
  volume={abs/2201.09378}
}
Full waveform inversion (FWI) is one of a family of methods that allows the reconstruction of earth subsurface parameters from measurements of waves at or near the surface. This is a numerical optimization problem that uses the whole waveform information of all arrivals to update the subsurface parameters that govern seismic wave propagation. We apply FWI in the multi-scale approach on two well-known benchmarks: Marmousi and 2004 BP velocity model. For the forward modeling, we use an RBF-FD… 

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References

SHOWING 1-10 OF 18 REFERENCES
Optimal shape parameter for meshless solution of the 2D Helmholtz equation
The solution of the Helmholtz equation is a fundamental step in frequency domain seismic imaging. This paper deals with a numerical study of solutions for 2D Helmholtz equation using a Gaussian
Time-domain multiscale full-waveform inversion using the rapid expansion method and efficient step-length estimation
Full-waveform inversion (FWI) is rapidly becoming a standard tool for high-resolution velocity estimation. However, the application of this method is usually limited to low frequencies due to the
Full Waveform Inversion With Extrapolated Low Frequency Data
TLDR
This paper explores the possibility of synthesizing the low frequencies computationally from high-frequency data, and uses the resulting prediction of the missing data to seed the frequency sweep of FWI and demonstrates surprising robustness to the inaccuracies in the extrapolated low frequency data.
A review of the adjoint-state method for computing the gradient of a functional with geophysical applications
SUMMARY Estimating the model parameters from measured data generally consists of minimizing an error functional. A classic technique to solve a minimization problem is to successively determine the
The Marmousi experience; velocity model determination on a synthetic complex data set
TLDR
The motivation behind seismic data acquisition and processing is simple—to obtain a depth image of the earth—but performing this process correctly is extremely difficult, and large amounts of man/CPU hours are devoted to the velocity estimation.
Full-waveform inversion using a nonlinearly smoothed wavefield
We thank KAUST for its support and the SWAG for collaborative environment. We also thank Z. Wu for the useful discussions. We would like to thank V. Socco, D. Draganov, D. Komatitsch, and two
Numerical Optimization
no exception. MRP II and JIT=TQC in purchasing and supplier education are covered in Chapter 15. Without proper education MRP II and JIT=TQC will not be successful and will not generate their true
Optimization and Control with Applications, chapter On the Barzilai-Borwein Method
  • 2005
Encyclopedia of Exploration Geophysics, chapter 6. An introduction to full waveform inversion, pages R1–1–R1–40
  • 2017
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