Adaptive structure-guided impedance inversion using implicit sparse constraint

Structure-guided inversion has been increasingly adopted to enhance structural features and improve the interpretability of seismic impedance imaging. However, the limited bandwidth of seismic wavelets leads to low-resolution poststack records, which inevitably compromises the accuracy of structural estimates in discontinuous regions. Consequently, the success of this approach critically depends on the appropriate use of structural information as geometric constraints. To address this limitation, we propose an adaptive structure-guided approach that maintains large-scale structural continuity while preserving fine-scale variability. The average structural similarity (ASSIM) index and structural constraint sensitivity (SCS) index are introduced to adjust the structural penalty intensity across adjacent traces. The former metric determines the upper bound of penalty intensity for uniform structural constraints, while the latter one characterizes regions prone to distortion where a local reduction in lateral smoothing is required. In addition, the sparse constraint is separated from the objective function and implicitly applied via an iteratively refined reference model, which is generated by an adaptive edge-preserving filter (AEPF) followed by L 2 -TV denoising. This combined strategy promotes blocky impedance reconstruction and effectively preserves thin-layer details. Numerical and field examples demonstrate the superiority of the proposed approach. These improvements establish a more rational and geologically consistent framework for incorporating prior structural information, thereby enhancing the practicality and imaging performance of the structure-guided inversion in complex scenarios.