{"title":"An Adaptive Demultiple Method Based on Inversion of Two-Dimensional Nonstationary Filter","authors":"P. Zhao, H. Zhao, H. Li, S. He, G. Li","doi":"10.3997/2214-4609.202010633","DOIUrl":null,"url":null,"abstract":"Summary This study uses the separability of the primary and multiple waves in the Radon domain to invert the filter coefficients at each point in the space-time profile, thereby suppressing the multiples using a two-dimensional nonstationary filtering technique. Compared with the parabolic Radon transform, it does not need to perform the inverse Radon transform, and alleviates the truncation effect caused by clearing the data in the Radon domain. Compared with two-dimensional nonstationary filtering, the uncertainty and subjectivity of filter design are avoided. Therefore, it is not just a simple combination of parabolic Radon transform and two-dimensional non-stationary filtering. Synthetic and field data examples show that this method has better ability of demultiple and amplitude preserving.","PeriodicalId":354849,"journal":{"name":"EAGE 2020 Annual Conference & Exhibition Online","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"EAGE 2020 Annual Conference & Exhibition Online","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3997/2214-4609.202010633","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Summary This study uses the separability of the primary and multiple waves in the Radon domain to invert the filter coefficients at each point in the space-time profile, thereby suppressing the multiples using a two-dimensional nonstationary filtering technique. Compared with the parabolic Radon transform, it does not need to perform the inverse Radon transform, and alleviates the truncation effect caused by clearing the data in the Radon domain. Compared with two-dimensional nonstationary filtering, the uncertainty and subjectivity of filter design are avoided. Therefore, it is not just a simple combination of parabolic Radon transform and two-dimensional non-stationary filtering. Synthetic and field data examples show that this method has better ability of demultiple and amplitude preserving.