Abstract
Strong subsurface attenuation leads to distortion of amplitudes and phases of seismic waves propagating inside the earth. The amplitude and the dispersion losses from attenuation are often compensated for during prestack depth migration. However, most attenuation compensation or Qcompensation migration algorithms require an estimate of the background Q model. We have developed a wave-equation gradient optimization method that inverts for the subsurface Q distribution by minimizing a skeletonized misfit function ∈, where ∈ is the sum of the squared differences between the observed and the predicted peak/centroid-frequency shifts of the early arrivals. The gradient is computed by migrating the observed traces weighted by the frequency shift residuals. The background Q model is perturbed until the predicted and the observed traces have the same peak frequencies or the same centroid frequencies. Numerical tests determined that an improved accuracy of the Q model by wave-equation Q tomography leads to a noticeable improvement in migration image quality. © 2016 Society of Exploration Geophysicists.
| Original language | English (US) |
|---|---|
| Pages (from-to) | R471-R484 |
| Number of pages | 1 |
| Journal | GEOPHYSICS |
| Volume | 81 |
| Issue number | 6 |
| DOIs | |
| State | Published - Oct 12 2016 |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledgements: The research reported in this publication was supported by the King Abdullah University of Science and Technology (KAUST) in Thuwal, Saudi Arabia. We are grateful to the sponsors of the Center for Subsurface Imaging and Modeling Consortium for their financial support. For computer time, this research used the resources of the IT Research Computing Group and the Supercomputing Laboratory at KAUST. We thank them for providing the computational resources required for carrying out this work. The constructive comments of the assistant editor J. Shragge, the associate editor A. Baumstein, and three anonymous reviewers have greatly improved the quality of this paper. Finally, we thank Exxon for providing the crosswell data to us.