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低信噪比地震资料的子波处理方法.docx

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低信噪比地震资料的子波处理方法 Title:Sub-waveprocessingmethodsforlowsignal-to-noiseratioseismicdata Abstract: Seismicexplorationplaysacrucialroleintheunderstandingandexplorationofsubsurfacegeologicalstructures.However,oneofthemainchallengesinseismicdataanalysisisthepresenceoflowsignal-to-noiseratio(SNR)data.LowSNRseismicdatamaybecausedbyvariousfactorssuchasinsufficientenergysources,complexsubsurfacestructures,ornoiseinterference.Toovercomethischallenge,varioussub-waveprocessingmethodshavebeenproposed.Thispaperaimstoreviewanddiscusssomeofthesemethods,includingwavelettransform,traceinterpolation,andnoisesuppressiontechniques. 1.Introduction 1.1Background 1.2SignificanceoftheStudy 1.3Objective 2.Lowsignal-to-noiseratio(SNR)seismicdata 2.1CausesofLowSNR 2.2EffectsonDataAnalysis 3.Sub-waveprocessingmethods 3.1WaveletTransform 3.1.1PrinciplesofWaveletTransform 3.1.2ApplicationofWaveletTransforminLowSNRDataAnalysis 3.2TraceInterpolation 3.2.1PrinciplesofTraceInterpolation 3.2.2ApplicationofTraceInterpolationinLowSNRDataAnalysis 3.3NoiseSuppressionTechniques 3.3.1FrequencyFiltering 3.3.2AdaptiveFiltering 3.3.3Time-FrequencyAnalysis 3.3.4StatisticalAnalysis 4.CaseStudies 4.1ApplicationofWaveletTransforminLowSNRDataProcessing 4.2ApplicationofTraceInterpolationinLowSNRDataProcessing 4.3ApplicationofNoiseSuppressionTechniquesinLowSNRDataProcessing 5.ComparisonofSub-waveProcessingMethods 5.1StrengthsandLimitationsofeachmethod 5.2Factorstoconsiderinchoosingtheappropriatemethod 6.Conclusion 6.1Summaryofthereviewedmethods 6.2Recommendationsforfurtherresearch 7.References ThepaperwillbeginwithanintroductiontothechallengesposedbylowSNRseismicdataandtherelevanceofstudyingsub-waveprocessingmethods.ItwillthendelveintothecausesandeffectsoflowSNRseismicdata.Themainbodyofthepaperwillfocusondiscussingvarioussub-waveprocessingmethods,includingtheprinciples,applications,andcasestudiesofeachmethod.Acomparisonofthestrengthsandlimitationswillbepresented,alongwithfactorstoconsiderwhenchoosingtheappropriatemetho