One-Way Wave Equation Least-Squares Migration Based on Illumination Compensation

Least-squares migration is a linear seismic inversion method which is established based on the linear relationship between seismic reflection data and underground reflection. Compared with conventional imaging technique, it has better performance in preserving amplitude. This paper presents an one-way wave equation least-squares migration based on illumination compensation. Firstly, we use the stable Born approximation generalized screen one-way wave-field propagator to construct the linear operator between reflected seismic data and underground reflection. Then we use the linear optimization method to solve the linear inverse problem of the least-squares migration. In the process of solving the optimization problems iteratively, we employ the seismic wave illumination as a preconditioned operator of the iterative inversion, so as to accelerate the convergence of iteration. During the one-way wave propagation, we consider the transmission effect arising from velocity interface, and substitute monopole source for the dipole source in conventional migration. Applying the method proposed in this paper to the layered theory model and the Marmosi model achieved ideal results.