This paper proposes modified angle-domain dot-product imaging conditions for vector-based elastic reverse time migration, which yields PP and PS angle gathers that capture improved amplitude-versus-angle (AVA) information. The vector P-wavefields and converted S-wavefields can be constructed by separating the coupled elastic wavefields. A simple and stable dot-product imaging condition can be employed to generate scalar PP and PS angle gathers. However, estimating amplitudes via migrated angle gathers using the conventional angle-domain dot-product imaging conditions leads to inaccurate AVA information. The inaccuracy arises because the dot-product imaging condition does not correctly represent seismic PP and PS reflectivity. Hence, the relationship between the dot-product imaging conditions and the reflection coefficients is explicitly derived in this paper. Then, the modified angle-domain dot-product imaging conditions for calculating PP and PS angle gathers are presented based on the kinematic characteristics of the vector P- and S-wavefields, along with an explanation of their amplitude correction mechanism. Finally, simple layer models with positive and negative reflection polarities are used to compute angle gathers to demonstrate the accuracy of the proposed imaging conditions in calculating AVA imaging. Numerical results from the Marmousi2 model validate the effectiveness and correctness of the proposed imaging conditions in complex media.

The application of full waveform inversion (FWI) on field data is currently a widely concerned challenge in seismic exploration. FWI has been proven on synthetic data to have the ability to obtain high-accuracy subsurface velocity and improve the imaging effect of the pre-stack depth migration (PSDM). However, its practical application remains constrained by challenges such as cycle-skipping. Meanwhile, the method’s capability to recover detailed subsurface properties retains considerable, yet underexploited, potential for advanced geological interpretation. In this study, we integrated FWI with amplitude variation with angle (AVA) analysis to identify potential gas reservoirs using 2D OBC data from the South China Sea. Our workflow began with 0–9 Hz FWI processing to obtain an updated velocity model. Comparative analysis demonstrated the FWI model’s superiority over the initial model through: (1) improved data fitting, (2) enhanced PSDM imaging with better structural alignment, and (3) higher-quality ADCIGs. The FWI results revealed a distinct high-velocity anomaly, which was validated through integration with PSDM images and well data. Subsequent AVA analysis suggested this anomaly may represent gas-bearing sandstone, though additional verification would be required to fully characterize the formation. Nonetheless, our workflow offers a reference for subsequent interpretations, which narrows down the scope for targeted objects. Our findings demonstrate that FWI and ADCIGs can obtain more geological information than traditional velocity modeling methods, thereby becoming a valuable tool for geological interpretation.