Least-squares reverse-time migration in VTI media using a T-distribution-based misfit function.

Anisotropy of subsurface media can affect the seismic wave travel time estimates, and then affect the imaging of target regions. To calibrate the effect of anisotropy, a VTI (transverse isotropy media with vertical symmetry axis) least-squares reverse-time migration (LSRTM) algorithm is used. However, if seismic data contains noise especially the outliers, the high-quality images cannot be produced by LSRTM based on an L2 norm. Considering that Student's t -distribution has better robustness than the L2 norm, this study derives a VTI-LSRTM algorithm based on Student's t-distribution (T-VTI-LSRTM) misfit function. The plane-wave encoding is introduced into the T-VTI-LSRTM to improve the computational efficiency. We conduct numerical tests using the complex models to illustrate the effectiveness and adaptability of the method. The sensitivity analysis of velocity and anisotropy parameters demonstrate that anisotropy and velocity parameters have a distinct effect on imaging results, in which velocity sensitivity is the strongest, then the epsilon and parameter delta sensitivity is the weakest. [ABSTRACT FROM AUTHOR]