OBN shear-wave leakage noise attenuation based on curvelet-domain extended filtering

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.