Wavefield-reconstructed least-squares reverse time migration with dynamic constraint factor

Least-squares reverse time migration is a high-precision migration method, the objective function of this method appears as a strong nonlinear function which is likely to plunge into local minimization, and the whole migration process requires massive calculation. Wavefield reconstruction is an optimized inversion theory proposed in recent years, and has achieved good results in full waveform inversion. In this method, the objective function introduces the wave equation as its penalty term to expand the search space of the solution and weaken the influence of the local minimization. In this paper, the idea of wavefield-reconstructed inversion is introduced into the least-squares reverse time migration. The scattering wavefield reconstruction algorithm under Born approximation is used to constrain the migration process, and the dynamic constraint factor in time–space domain is introduced to suppress the high-order scattering artifacts and improve the signal-to-noise ratio of the migration results. Generally, the method can ensure the accuracy of the update gradient. The experimental results show that this method can effectively suppress the artifacts caused by high-order scattering wave when there are large-scale high-velocity anomalies in the velocity field. In addition, the method has also achieved good results in the test of field datasets.