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.

Ocean bottom seismometer (OBS) can record both pressure and displacement data by modern marine seismic acquisitions with four-component (4C) sensors. Elastic full-waveform inversion (EFWI) has shown to recover high-accuracy parameter models from multicomponent seismic data. However, due to limitation of the standard elastic wave equation, EFWI can hardly simulate and utilize the pressure components. To remedy this problem, we propose an elastic full-waveform inversion method based on a modified acoustic-elastic coupled (AEC) equation. Our method adopts a new misfit function to account for both 1C pressure and 3C displacement data, which can easily adjust the weight of different data components and eliminate the differences in the order of magnitude. Owing to the modified AEC equation, our method can simultaneously generate pressure and displacement records and avoid explicit implementation of the boundary condition at the seabed. Besides, we also derive a new preconditioned truncated Gauss–Newton algorithm to consider the Hessian associated with ocean bottom seismic 4C data. We analyze the multiparameter sensitivity kernels of pressure and displacement components and use two numerical experiments to demonstrate that the proposed method can provide more accurate multiparameter inversions with higher resolution and convergence rate.