Enhancing OBN Data Processing with Curvature Domain Extended Filtering for Shear Wave Leakage Noise Attenuation

Ocean Bottom Node (OBN) collection has found extensive use in geophysical exploration for acquiring more comprehensive multi-component seismic data. Conventional filtering algorithms struggle to effectively separate useful information from the leaked noise. In this paper, we propose a shear wave leakage matching attenuation method based on curvelet domain extended filtering. Firstly, we create Hilbert transform records, time derivative records, and Hilbert transform time derivative records of the Z component, based on the shear wave data from the X and Y components in the OBN data. This process enables the extended expression of the Z component in the curvelet domain. Subsequently, we perform shear wave leakage matching subtraction using a least-squares extended filtering method to distinguish the valuable information from the shear wave leakage noise. The results from both theoretical model experiments and field data processing experiments demonstrate that our proposed method leverages the advantages of curved wave transformation for effectively separating the desired signal from shear-wave leakage noise. It also demonstrates the adaptability of the extended filter for predicting shear-wave leakage errors. Consequently, our method significantly enhances the accuracy of eliminating shear wave leakage interference while preserving valuable signals, ultimately improving the imaging precision of OBN data.