摘要
Utilizingdatafromcontrolledseismicsourcestoimagethesubsurfacestructuresandinvertthephysicalpropertiesofthesubsurfacemediaisamajoreffortinexplorationgeophysics.Denseseismicrecordswithhighsignal-to-noiseratio(SNR)andhighfidelityhelpsinproducinghighqualityimagingresults.Therefore,seismicdatadenoisingandmissingtracesreconstructionaresignificantforseismicdataprocessing.Traditionaldenoisingandinterpolationmethodsrarelyoccasionedrelyonnoiselevelestimations,thusrequiringheavymanualworktodealwithrecordsandtheselectionofoptimalparameters.Weproposeasimultaneousdenoisingandinterpolationmethodbasedondeeplearning.Fornoisyrecordswithmissingtraces,weadoptaniterativealternatingoptimizationstrategyandseparatetheobjectivefunctionofthedatarestoringproblemintotwosub-problems.Theseismicrecordscanbereconstructedbysolvingaleast-squareproblemandapplyingasetofpre-traineddenoisingmodelsalternativelyanditeratively.Wedemonstratethismethodwithsyntheticandfielddata.
出版日期
2019年01月11日(中国Betway体育网页登陆平台首次上网日期,不代表论文的发表时间)