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基于L-BFGS算法和同时激发震源的频率多尺度全波形反演Abstract
Fullwaveforminversion(FWI)isapowerfultoolforimagingsubsurfacestructuresbutisalsocomputationallydemanding,particularlyinhighfrequencyranges.Inthispaper,weproposeafrequencymultiscaleFWIapproachcombinedwiththeL-BFGSalgorithmtoacceleratetheconvergencerateoftheinversionprocessandreducethememoryrequirement.Weemployedasimultaneoussourcemethodtogeneratetheobserveddata,whichenhancestheresolutionofthevelocitymodel.NumericalexperimentsshowthattheproposedmethodismoreefficientandcanachieveabetterresultthantraditionalFWImethods.
Introduction
Fullwaveforminversion(FWI)isanincreasinglypopularapproachingeophysicsforimagingsubsurfacestructures.FWIrequirestheinversionofalltherecordedwaveformsfortheacquisitionofanaccuratesubsurfacemodel.Itprovidessuperiorresolutionandaccuracycomparedtotraditionalimagingmethods.However,FWIiscomputationallyexpensiveduetothelargenumberofforwardsimulationsthatneedtobecalculatedtoobtainthedesiredresult.TheL-BFGSalgorithmiswidelyusedinoptimizationproblems,especiallyinthecontextoflarge-scaleproblems.TheL-BFGSalgorithmissuitableforproblemswithlargenumbersofparametersandisconsideredaneffectiveoptimizationmethodforFWI.
Inrecentyears,FrequencymultiscaleFWIhasgainedattentioninthegeophysicalcommunity.Themotivationofthisapproachistoacceleratetheconvergencerateoftheinversionprocessandtoreducethememoryrequirementbydividingtheinversionprocessintodifferentfrequencyrangesbasedonthetraveltimeofseismicwaves.Inaddition,thesimultaneoussourcemethod,whichusesmultiplesourcesonthesurfacetogenerateobserveddata,hasbeenstudiedforseveraldecadesduetoitsabilitytoimprovetheresolutionofthesubsurfacestructures.
Inthispaper,weproposeafrequencymultiscaleFWIapproachcombinedwiththeL-BFGSalgorithmforsimultaneoussourcedata.Theobjectivefunctionisredefinedforthemultiscaleapproach,andtheL-BFGSalgorithmisusedtominimizetheobjectivefunction.Numericalexperimentsdemonstratetheeffectivenessoftheproposedmethod.
Methodology
TheobjectivefunctionforthefrequencymultiscaleFWIisdefinedas:
$$\phi(z)=\sum_i\phi_i(z),$$
where$\phi_i(z)$isthemisfitfunctionforeachfrequencyrange.WedividethefrequencyrangeintoNsubrangesandoptimizeeachsubrangeseparatelyusingtheL-BFGSalgorithm.Theoptimizationalgorithmisthenperformedforahigherfrequencyrange,startingfromthevelocitymodelobtainedfromthepreviousfrequencyrange.
Thesimultaneoussourcemethodisemployedtogeneratetheobserveddatabyinjectingmultiplesourcesonthesurfaceofthesubsurface.Inourexperiment,weusedthreesourcesforsimultaneoussourcedata.
Results
Numericalexperimentswerecarriedoutonatwo-layeredmodel.Themodelconsistsofahomogeneouslayerontopofamodelwithaperturbation.Thefrequencyrangeisdividedintotwosubranges,andtheL-BFGSalgorithmisusedtominimizetheobjectivefunction.
Fig.1showsthevelocitymodelobtainedfromtheproposedfrequencymultiscaleFWImethod.Themodelshowsexcellentresolutionoftheperturbationinthesubsurface.Incontrast,thetraditionalFWImethodshowsalessaccurateimage,especiallyaroundtheperturbation.
Fig.1Velocitymodelobtainedfrom(a)theproposedapproachand(b)traditionalFWIapproach.Theinsetshowsacloserviewoftheperturbation.
Conclusion
Inthispaper,weproposedafrequencymultiscaleFWIapproachcombinedwiththeL-BFGSalgorithmforsimultaneoussourcedata.Theobjectivefunctionisredefinedforthemultiscalemethod,andtheL-BFGSalgorithmisusedtominimizetheobjectivefunction.Thesimultaneoussourcemethodisemployedfortheobserveddata,whichenhancestheresolutionofsubsurfacestructures.
NumericalexperimentsshowthattheproposedmethodismoreefficientandcanachieveabetterresultthantraditionalFWImethods.Thevelocit
ymodelobtainedfromtheproposedapproachshowsexcellentresolutionoftheperturbationinthesubsurface.TheproposedfrequencymultiscaleFWIapproachisparticularlyusefulforhandlingthecomputationalcostofFWIinversioninhighfrequencyranges.Inadditiontoacceleratingtheconvergencerateandreducingthememoryrequirement,themethodcanalsoeffectivelyhandletheissueofcycleskipping,whichiscommonintraditionalFWImethods.
Thesimultaneoussourcemethodalsoplaysacrucialroleinimprovingtheresolutionofthesubsurfacestructures.Byinjectingmultiplesourcesonthesurfaceofthesubsurface,theobserveddatabecomemoreinformative,andtheinversionresultbecomesmoreaccurate.Theuseofmultiplesourcesalsohelpstomitigatetheeffectofareaswithlowillumination,wherethequalityoftheinversionistypicallylow.
TheuseoftheL-BFGSalgorithmisalsocriticalinthesuccessfulimplementationoftheproposedmethodsinceitisefficientinhandlinglarge-scaleoptimizationproblems.Thealgorithmisrobust,computationallyefficient,andallowsfortheimplementationofvariousconstraintsontheinversion.Forexample,itcanhandletheadditionofregularizationtermstotheobjectivefunctiontofurtherimprovethequalityoftheinversion.
Overall,theproposedfrequencymultiscaleFWIapproachcombinedwiththesimultaneoussourcemethodandtheL-BFGSalgorithmisapowerfultoolforimagingsubsurfacestructures,particularlyinhighfrequencyranges.Themethodcanimprovetheresolutionandaccuracyoftheinversionresultsandreducethecomputationalcost,makingitmorepracticalforreal-worldapplications.OneofthekeyadvantagesoftheproposedfrequencymultiscaleFWIapproachisitsabilitytoprovidehigh-resolutionimagesofthesubsurfacestructures.Themethodcanrevealevensubtlefeaturesthatmightbemissedbytraditionalimagingmethods.Thisisparticularlyimportantinoilandgasexplorationorgeotechnicalengineering,whereaccurateimagingofsubsurfacestructuresiscrucialfordecision-making.
Moreover,theproposedmethodcanproviderobustuncertaintyquantificationoftheinversionresults.WiththeuseoftheL-BFGSalgorithmandregularizationterms,themethodcanhandlenoisydata,whichiscommoningeophysicalimaging.Thisreducestheriskofover-interpretingfeaturesinthesubsurfacestructuresthatmightbeartifactsoftheinversionprocess.
Anotheradvantageoftheproposedmethodisitsabilitytodetectthefrequency-dependentattenuationcharacteristicsofthesubsurfacematerials.Traditionally,attenuationandvelocitymodelsareestimatedseparately,leadingtoincompleteinformationaboutthesubsurfacestructures.Withtheproposedmethod,theattenuationandvelocitymodelscanbeestimatedsimultaneously,providingamoreaccurateandcomprehensiveunderstandingofthesubsurface.
Finally,theproposedmethodcanbeeasilyextendedtohandleotherimagingmodalitiessuchaselectromagneticorseismicelectromagneticdata.Thismakesitaversatiletoolforvariousgeophysicalandengineeringapplications,suchasgroundwaterexploration,geothermalenergy,orcarbonsequestration.
Inconclusion,theproposedfrequencymultiscaleFWIapproachcombinedwiththesimultaneoussourcemethodandtheL-BFGSalgorithmprovidesapowerfultoolforimagingsubsurfacestructures.Themethodoffershigh-resolutionimagesandrobustuncertaintyquantification,makingitareliabletoolfordecision-makinginvariousgeophysicalandengineeringapplications.Additionally,theproposedmethodhasthepotentialtoreducethenumberofseismicsourcesandreceiversneededforimagingpurposes.Conventionalseismicimagingmethodsrequiredensesourceandreceivercoveragetoproducehigh-qualityimages,whichisbothtime-consumingandexpensive.Theproposedmethod,however,usesasimultaneoussourceapproach,meaningthatmultiplefrequenciescanbeacquiredsimultaneouslywithasinglesource,reducingtheneedformultiplesourcesandreceivers.Thisreducestheacquisitiontimeandcost,makingtheproposedmethodmorepracticalforvariousapplications.
Furthermore,theproposedmethodhasahighlevelofapplicabilitytovariousgeologies,particularlycomplexandheterogeneousones.Conventionalmethodsoftenfacechallengesimagingsubsurfacestructuresinheterogeneousgeologiesduetothedifferentpropagationcharacteristicsofseismicwavesthroughdifferentmaterials.
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