Efficient Full-Waveform Inversion with Normalized Plane-Wave Data

thomas e. casson;

Full-waveform inversion (FWI) provides a high-resolution velocity model, but carries a high computational cost. Additionally, modern seismic acquisition, with dense sources and receivers, generates massive data, resulting in an even greater computational cost. To reduce the computational burden of FWI, we have developed an FWI algorithm using plane-wave data. Using this approach, plane-wave gathers transformed from shot gathers are used as input data
in inversion. Because the number of plane-wave gathers is generally far smaller than that of common shot gathers for the same data set, we can significantly reduce the computational cost and efficiently handle a massive data set. 2-D numerical testing showed that the developed FWI algorithm was more efficient than conventional FWI using common shot gathers. However, estimation of the source wavelet is essential for successful FWI in most cases. The developed FWI algorithm here excludes the source effect by using the normalized wave field instead
of estimating the source wavelet through inversion processing. When the FWI algorithm was applied to data generated by slightly different source wavelets, a good velocity model was reconstructed without any artefacts from the effects of the different source wavelets. Furthermore, it presented a stable inversion result with only small artefacts, even though we used random noise-added data. Finally, in a numerical experiment with data from the SEG/EAGE 3-D overthrust model, which includes complex structures and thin layers, the developed FWI algorithm yielded a reasonable reconstructed velocity model.