Source-independent least-squares Reverse time migration in vertical transversely isotropic Media based on the student's t-distribution

Abstract Seismic anisotropy exists in various type of strata and should be considered seismic imaging schemes. algorithms based on isotropic assumption neglect the impacts data, which causes migration artifact waveform distortion. To correct effects wave propagation, we propose an algorithm that performs least-squares reverse time vertical transversely acoustic media. We derive following operators to implement this algorithm, de-migration operator, its adjoint operator corresponding gradient. However, inaccurate estimated source wavelet will introduce error simulation, thus increase mismatch between observed synthetic data for migration. In addition, noises, especially noises with abnormal amplitudes damage inversion convergence reduce resolution. improve image quality, use convolved wavefields so such can independent wavelets. Also, employ student's t-distribution instead L2 norm our scheme better handle noise. Its implementation only modifies gradient conventional least square scheme. Our numerical tests show a clear improvement using proposed when compared anisotropic data. examples demonstrate feasibility effectiveness source-independent t-distribution.