Prestack elastic RTM for VTI media using vector wavefield decomposition and vector imaging conditions

ABSTRACT

To date, studies of elastic reverse time migration (RTM) have undergone much improvement, but mainly focus on isotropic media. Because anisotropic media is widespread, it is necessary to explore the application of elastic RTM in anisotropic media. We extend the wavefield decomposition method, which is based on decoupled propagation, and three vector imaging conditions to transversely isotropic media with vertical symmetry isotropy (VTI). Two of the imaging conditions are based on the excitation amplitude (EA) and the third is based on source-normalized cross-correlation. First, the wavefield decomposition method is extended to VTI media. This is then tested in a two-layer model. The results show that this extension cannot decompose P- and S-waves perfectly in VTI media; some weak residuals remain. However, the results of a simple model test show that no obvious crosstalk is generated by these weak residuals. Finally, a Hess VTI model is adopted to test the adaptive use of this method in complex media. Many subsurface structures can be clearly recognized in the migrated result, for example, the high-velocity rock body, a fault and two low-velocity interlayers. Compared with PP images, converted PS images have many merits, such as clearer imaging of the anisotropic body, higher resolution and a wider migration aperture. We conclude that the vector decomposition method and three vector imaging conditions can be applied to prestack elastic RTM for VTI media and satisfactory results obtained.

KEYWORDS:

• Elastic
• reverse time migration
• VTI
• multicomponent
• decomposition

Acknowledgements

Thanks to the editors and two anonymous reviewers for their valuable suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The research work in this paper was supported by the National Natural Science Foundation of China (NSFC) [grant numbers 41374108 and 41504085] and National Science and Technology Major Project [grant number 2016ZX05026-002-003]; the project belongs to Ministry of Science and Technology of the People's Republic of China.