论文详情
海底节点（OBN）地震数据采集技术已广泛用于海上地球物理勘探中。但其Z分量数据中横波泄露噪声的存在严重降低了地震数据的信噪比，因而影响了其应用效果。传统滤波算法和匹配衰减算法难以实现有效信号及泄露噪声的有效分离。提出了基于曲波域扩展滤波的横波泄露噪声匹配衰减方法。该方法基于OBN数据中X和Y分量数据构建相应的希尔伯特变换记录、时间导数记录以及希尔伯特变换的时间导数记录来预测Z分量中的横波泄露噪声。在此基础上，采用曲波域最小二乘扩展滤波的横波泄露噪声匹配相减方法，实现有效信号与横波泄露噪声的高精度分离。理论模型实验与实际数据处理结果均表明，该方法兼顾了曲波变换在分离有效信号与横波泄露噪声方面的优势以及扩展滤波对横波泄露噪声预测误差的适应性。在避免损伤有效信号的前提下，能够有效压制横波泄露噪声，从而提升OBN数据的成像精度。
Despite its extensive use in geophysical exploration, OBN data suffer from low signal-to-noise ratio caused by Z component contaminated by shear waves from horizontal components. Such leakage noises have a negative impact on dual-sensor merging based on Z component to obtain high-quality up-going and down-going waves for imaging, but it is hard to separate useful signals from leakage noises by using common filtering and matching attenuation algorithms. To suppress shear-wave leakage noises, we propose a matching attenuation method based on curvelet-domain extended filtering. The method constructs Hilbert transform records, time derivative records, and Hilbert transform followed by time derivative records from the X and Y component data of OBN to predict shear-wave leakage noises in the Z component, which enables the extended expression of Z component in the curvelet domain. Shear-wave leakage matching subtraction will then be performed using curvelet-domain least-squares extended filtering to separate effective signals from leakage noises. According to a model test and field data processing, our method has the advantage of leveraging curvelet transform for signal-noise separation and extended filtering for shear-wave leakage error prediction. Consequently, OBN data imaging will be improved because shear-wave leakage noises could be eliminated significantly without damaging effective signals.