石油地球物理勘探2025，Vol.60Issue(2)：353-361,9.DOI:10.13810/j.cnki.issn.1000-7210.20240075
三种多次波自适应匹配相减方法的对比
Comparative analysis on three multiple adaptive subtraction methods
摘要
Abstract
Multiples reduce the signal-to-noise ratio of seismic data,affecting the identification of primaries,thereby increasing the difficulty of seismic processing,reducing the authenticity and reliability of seismic ima-ging,and even forming geological illusions,which affect subsequent seismic exploration and development.The multiple suppression method based on wave theory can better adapt to complex media,which mainly consists of two steps,multiple prediction and adaptive matching subtraction.Both steps impact the final accuracy of mul-tiple suppression.The paper compares three adaptive matching subtraction method,respectively based on mini-mum energy principle,pattern recognition,and deep learning.The advantages,disadvantages,and adaptability conditions of each method are also analyzed.The test results of model data containing surface-related multiples and field data with internal multiples show that the adaptive subtraction algorithm based on the principle of mini-mum energy principle assumes wavelet consistency,while the pattern recognition based adaptive subtraction technique requires high lateral consistency of seismic data.Compared with the two traditional methods,adap-tive matching subtraction based on deep learning can avoid assumed conditions and effectively protect primaries,achieving higher computational accuracy.关键词
多次波压制/自适应匹配相减/能量最小原则/模式识别/深度学习Key words
multiple suppression/adaptive matching subtraction/minimum energy principle/pattern recognition/deep learning分类
地质学引用本文复制引用
包培楠,石颖,韩宏伟,尚新民..三种多次波自适应匹配相减方法的对比[J].石油地球物理勘探,2025,60(2):353-361,9.基金项目
本项研究受国家青年科学基金项目"基于迭代反演求解的Marchenko层间多次波压制方法研究"(42304114)、黑龙江省自然科学基金项目"基于半监督学习的层间多次波压制方法研究"(LH2023D014)联合资助. （42304114）
