石油物探2024，Vol.63Issue(1)：161-169,181,10.DOI:10.12431/issn.1000-1441.2024.63.01.014
低信噪比地震数据图像结构引导去噪方法与应用
Image-guided denoising method and its application to low SNR seismic data
摘要
Abstract
In view of the negative effect of seismic noises on complicated structure and reservoir interpretation,effective noise re-duction without impairing seismic structural information is crucial to interpretation-oriented seismic data processing.Based on the principle of edge-preserved smoothing,a self-adapting image texture guided filtering method is developed to suppress scattered and random noises in poststack seismic data and improve the signal-to-noise ratio,and meanwhile seismic reflections related to faults,cracks,and reservoirs could be preserved effectively.Model tests show that this method performs better than conventional filtering methods in edge-preserved smoothing;compared with structure-guided filtering,this method has high computational efficiency be-cause it is unnecessary to extract strike and dip information explicitly.The field application to a 3D seismic survey shows the ad-vantages of this method in preserving structural details of faults and cracks,attenuating various noises to improve signal-to-noise ratio,and improving lateral continuity and seismic resolution.Coherence attributes calculated using seismic data after image-guided denoising show enhanced resolution of fractures and reservoirs,which is beneficial to subsequent seismic interpretation.关键词
图像结构引导滤波/保边光滑/信噪比/断层分辨能力/不同类型噪声Key words
image texture guided filtering/edge-preserved smoothing/signal-to-noise ratio/fault resolution/different types of noises分类
天文与地球科学引用本文复制引用
郑启明,李琦,都小芳,吴高奎..低信噪比地震数据图像结构引导去噪方法与应用[J].石油物探,2024,63(1):161-169,181,10.基金项目
国家科技重大专项(2016ZX05033)、中国石化科技部项目(P21043-3)和中国石化基础前瞻项目(P22214-2)共同资助.This research is financially supported by the National Science and Technology Major Project of China(Grant No.2016ZX05033),the Project of the SINOPEC Science&Technology Department(Grant No.P21043-3),and the SINOPEC Basic Prospective Project(Grant No.P22214-2). （2016ZX05033）
