{"title":"A greed algorithm for seismic data interpolation using the approximate irregular discrete Fourier transform","authors":"A. Oliveira, H. Haas","doi":"10.22564/16cisbgf2019.011","DOIUrl":null,"url":null,"abstract":"In this paper, an alternative greed algorithm for interpolation/regularization of irregularly-sampled seismic data in the Fourier domain is described in connection with the approximate irregular discrete Fourier transform (AIDFT). The greed algorithm is used to fill in empty bins, generated by defective sampling, under statistical and/or physical constraints, so as to achieve an acceptable Fourier spetrum. Much like in other implementations, a least square norm Fourier spectrum is the input for the process. Here, this least square initial solution is provided by the AIDFT. The greed algorithm proposed is an iterative procedure that consists in, step by step, correcting for survey’s footprints of main Fourier components.","PeriodicalId":332941,"journal":{"name":"Proceedings of the 16th International Congress of the Brazilian Geophysical Society&Expogef","volume":"105 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 16th International Congress of the Brazilian Geophysical Society&Expogef","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22564/16cisbgf2019.011","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
In this paper, an alternative greed algorithm for interpolation/regularization of irregularly-sampled seismic data in the Fourier domain is described in connection with the approximate irregular discrete Fourier transform (AIDFT). The greed algorithm is used to fill in empty bins, generated by defective sampling, under statistical and/or physical constraints, so as to achieve an acceptable Fourier spetrum. Much like in other implementations, a least square norm Fourier spectrum is the input for the process. Here, this least square initial solution is provided by the AIDFT. The greed algorithm proposed is an iterative procedure that consists in, step by step, correcting for survey’s footprints of main Fourier components.
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