Seismic structure-oriented filtering constrained by WOA-PWD dip information

This study introduces a high-precision dip estimation method, termed WOA-PWD, that integrates the Whale Optimization Algorithm (WOA) with Plane-Wave Decomposition (PWD) to enhance noise suppression and structure preservation in structure-oriented filtering. Leveraging the global search capability and robustness of WOA, the proposed method significantly improves the accuracy and stability of local dip estimation, which in turn enhances the adaptability of structure-oriented filtering for accurate seismic reflector tracking. Comparative experiments on both synthetic and field seismic datasets demonstrate that the WOA-PWD method outperforms traditional PWD, median filtering, and multichannel singular spectrum analysis in noise attenuation, effective signal preservation, and fault identification. Local similarity analysis further confirms the method's effectiveness in minimizing valid signal loss, showcasing its superior amplitude preservation characteristics and practical utility. The findings provide a reliable and robust technical framework for high-resolution seismic imaging and interpretation in structurally complex areas, indicating strong potential for broader application.