Elastic Least-Squares Reverse-Time Migration Based on a Modified Acoustic-Elastic Coupled Equation for OBS Four-Component Data
Minao Sun, Shuanggen Jin, Pengfei Yu
Abstract
Elastic least-squares reverse-time migration (ELSRTM) yields subsurface high-resolution elastic images from multicomponent seismic data. For ocean bottom seismic (OBS) acquisitions, both pressure and displacement components are measured using four-component (4C) modern receivers. However, these 4C data cannot be effectively simulated and migrated using conventional ELSRTM approaches due to the limitation of the standard elastic wave equation. For this reason, we propose a new ELSRTM method based on a modified acoustic-elastic coupled (AEC) equation. Owing to this equation, either the prediction or the migration of OBS 4C data can be implemented using a one-time wavefield simulation. Incorporation with a perturbation imaging condition, the proposed method can invert for P- and S-wave velocity and density and generate amplitude-preserving images. Besides, it can provide subsurface impedance reflectivity models by stacking the obtained multi-parameter images. In the least-squares migration, a preconditioned conjugate gradient algorithm is implemented based on a multi-parameter diagonal Hessian. Numerical experiments on an uncorrelated layer model and a portion of the Southern Yellow China sea model can demonstrate the effectiveness of this method on improving imaging resolution and accelerating convergence rate.