The Least Squares Reverse Time Migration (LSRTM) can obtain high resolution and true amplitude imaging results. However, LSRTM for full model domain data requires simulation throughout the entire model space, resulting in significant computational costs. In addition, the Born approximation, which is based on single scattering theory, can cause imaging artifacts by treating multiple reflections from the overburden as primary reflections. To address these issues, the Marchenko redatuming method can be used to separate the influence of the overburden. However, due to factors such as acquisition aperture, phase and amplitude errors can occur in far offset Marchenko redatumed data. Therefore, a prestack correlative LSRTM method based on Marchenko redatumed data is proposed for target-oriented imaging, which includes two key points. Firstly, the method aims to reconstruct the data recorded from surface onto the target datum using Marchenko redatuming theory to obtain the response without the influence of overburden. Secondly, by constructing the prestack normalized zero-lag cross-correlation error function, the optimal reflection coefficient model is found for each shot’s record, and the final imaging result is generated by stacking the optimal reflection coefficient model of all redatumed data, thereby alleviating the problem of the incoherent stacking at far offset in redatumed data, which reduces the imaging quality. Numerical examples demonstrate that the proposed method has higher computational efficiency and can provide imaging results with fewer artifacts.

The inadequate resolution of cavity karst reservoir characterization is a key factor affecting the hydrocarbon production efficiency of ultra-deep marine carbonates. Full waveform inversion (FWI) using high-frequency seismic data can provide a higher resolution than conventional methods. However, computational efficiency limits its application. This paper proposed a target-oriented local FWI method for cavity karst reservoir characterization. Based on the wavefield injection and Marchenko redatuming methods, a local wavefield forward modeling operator is derived. It can obtain the local wavefield corresponding to the physical source at the surface. Based on this local wavefield reconstruction, an objective function of the local FWI is established. To enhance the reservoir boundaries in the inversion results, a stabilizing strategy that combines total variation and minimum support regularization is proposed. A synthetic data test demonstrates that the obtained model can well describe the cavity karst reservoir structures.

Local full-waveform inversion (FWI) methods use redatumed seismic responses of virtual receivers within the subsurface to build the local objective function based on the convolution-type representation theorem. The Marchenko method is widely used to obtain the redatumed data. The method only requires a smoothed velocity model with correct kinematic characteristics of seismic responses for redatuming of the single-sided reflection data. However, the standard Marchenko method is insensitive to lateral propagation of the wavefield. By injecting the standard Marchenko redatumed wavefield along the boundary of the target, the local wavefield propagation modeling produces errors, which affects the accuracy of the local FWI. In this paper, a method to obtain more accurate Green’s functions is proposed by incorporating vertical seismic profile data (VSP) into the calculation process of the Marchenko source-receiver redatuming. This method allows one to obtain the accurate laterally propagating waveform, resulting in a significant improvement of lateral resolution. The proposed method is applied to a benchmark model dataset and compared with the local FWI based on standard Marchenko redatuming.

Ultra-deep marine carbonate cavity reservoirs in Northwest China are characterized by strong heterogeneity and complex geometries. Conventional seismic inversion methods generate over-smoothed results, blur geological boundaries, and suffer from severe non-uniqueness, making it difficult to accurately identify low-impedance cavity anomalies. To tackle these problems, this study develops a shape-constrained multi-trace seismic inversion method based on the Mumford–Shah functional. To meet the computational requirements, a multi-trace inversion framework is adopted, and the Ambrosio–Tortorelli approximation is introduced to convert the non-smooth Mumford–Shah functional into a solvable smooth form. The proposed method realizes the joint inversion of acoustic impedance and geological interfaces, implicitly encourages piecewise constant regions and preserves sharp geological boundaries, and effectively mitigates inversion non-uniqueness. Numerical experiments and field applications validate that the method delivers high lateral resolution and boundary accuracy even with limited prior information and reliably delineates discrete “string-bead” cavity geometries with high consistency to drilling and logging data, providing a robust solution for fine characterization of complex carbonate cavity reservoirs.