We invert three-dimensional seismic data by a multiscale phase inversion scheme, a modified version of full waveform inversion, which applies higher order integrations to the input signal to produce low-boost signals. These low-boost signals are used as the input data for the early iterations, and lower order integrations are computed at the later iterations. The advantages of multiscale phase inversion are that it (1) is less dependent on the initial model compared to full waveform inversion, (2) is less sensitive to incorrectly modelled magnitudes and (3) employs a simple and natural frequency shaping filtering. For a layered model with a three-dimensional velocity anomaly, results with synthetic data show that multiscale phase inversion can sometimes provide a noticeably more accurate velocity profile than full waveform inversion. Results with the Society of Exploration Geophysicists/European Association of Geoscientists and Engineers overthrust model shows that multiscale phase inversion more clearly resolves meandering channels in the depth slices. However, the data and model misfit functions achieve about the same values after 50 iterations. The results with three-dimensional ocean-bottom cable data show that, compared to the full waveform inversion tomogram, the three-dimensional multiscale phase inversion tomogram provides a better match to the well log, and better flattens angle-domain common image gathers. The problem is that the tomograms at the well log provide an incomplete low-wavenumber estimate of the log's velocity profile. Therefore, a good low-wavenumber estimate of the velocity model is still needed for an accurate multiscale phase inversion tomogram.
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The authors would like to thank Statoil ASA and the Volve license partners, ExxonMobil E&P Norway AS and Bayern-gas Norge AS, for the release of the Volve data. The research reported in this publication was supported by the King Abdul-lah University of Science and Technology (KAUST) in Thuwal,Saudi Arabia. We are grateful to the sponsors of the Center for Subsurface Imaging and Modelling (CSIM) Consortium for their financial support. For computer time, this research used the resources of the Supercomputing Laboratory at KAUST and the IT Research Computing Group. We thank them for providing the computational resources required for carrying out this work.