Adaptive least-squares RTM and application to Freedom WAZ subsalt imaging

Abstract

We propose an adaptive approach to address the practical issues in least-squares reverse time migration (LSRTM) with a focus on subsalt imaging. The problems include imperfect migration velocity, slow convergence in subsalt area, and extra migration artifacts introduced in gradient computation. The adaptive solution involves strategies to enhance data consistency in time domain and control the migration aperture to precondition the LSRTM gradient for fast convergence. We use constrained dynamic warping to correct the misalignments between synthetic and input waveforms due to short-wavelength velocity errors. The waveform amplitude differences are mitigated by a locally windowed gain using input data as reference. During the LSRTM iterations we gradually open the migration aperture to control the weighting for updating structures with different dips. The extra artifacts introduced during gradient computation by the two-way migration operator are suppressed via a structure-oriented smoothing process. We demonstrate the effectiveness of the proposed adaptive strategies via a 3D synthetic model derived from the true geology of the Gulf of Mexico (GoM). Lastly, we examine the results of the adaptive LSRTM approach on our multiclient wide-azimuth data acquired in the Freedom area of the GoM. The images of shadow zone and subsalt area are significantly improved after a few iterations regardless of the practical limitations such as velocity error and weak illumination near and below the salt body.