石油物探2025，Vol.64Issue(2)：271-279,9.DOI:10.12431/issn.1000-1441.2023.0397
基于曲波域扩展滤波的OBN横波泄露噪声衰减
OBN shear-wave leakage noise attenuation based on curvelet-domain extended filtering
摘要
Abstract
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.关键词
OBN/Z分量/横波泄露噪声/曲波变换/扩展滤波/噪声衰减Key words
OBN/Z component/shear-wave leakage noise/curvelet transform/extended filtering/noise attenuation分类
天文与地球科学引用本文复制引用
张建峰,赵波,王志亮,张春燕,麻旭刚,李博闻,祖国昌,宋鹏,贺慧丽,韩晨..基于曲波域扩展滤波的OBN横波泄露噪声衰减[J].石油物探,2025,64(2):271-279,9.基金项目
国家自然科学基金项目(42074138,42206195)、崂山实验室科技创新项目(LSKJ202204803)、中国石油天然气集团有限公司科学研究与技术开发项目(2021ZG02)和国家大学生创新训练项目(202310423061)共同资助. This research is financially supported by the National Natural Science Foundation of China(Grant Nos.42074138,42206195),Laoshan Laboratory Science and Technology Innovation Project(Grant No.LSKJ202204803),the Research Project of the China National Petroleum Corporation(Grant No.2021ZG02)and the National University Student Innovation and Entrepreneurship Training Program(Grant No.202310423061). （42074138,42206195）
