georefid:2009-041631SEDIS Publication Catalogue

ana.macario@awi.de

http://sedis.iodp.org/pub-catalogue/informationpointOfContact2011-06-23T00:00:00Zhttp://sedis.iodp.org/pub-catalogue/index.php?id=2009-0416312006-01-01publicationgeorefid:2009-041631Xiong YanTongji University, State Key Laboratory of Marine Geology, Shanghai, ChinaauthorZhong GuangfaGuangzhou Marine Geological Survey, ChinaauthorLi QianyuauthorWu NengyouauthorLi XuejieauthorMa ZaitianauthorChina University of Geoscience, Wuhan, ChinapublisherdocumentHardcopyEarth Science. Journal of China University of Geoscience31 (6)851-856Based upon the relationship between carbonate content and stratal velocity and density, we attempted to apply an artificial neural network to the inversion of carbonate content summarized from high-resolution seismic data limited by controlled well measurements. The method was applied to the slope area of the northern South China Sea near ODP Sites 1146 and 1148, with satisfactory results. The key to this method is the collection of several properties from seismic profiles across or near the wells. Then the progressive regression method was used to determine the six seismic properties most closely related to carbonate content variations, which are defined as average frequency, integrated absolute amplitude, dominating frequency, reflection time, derivative instantaneous amplitude, and instantaneous frequency. Finally, the stratal carbonate content is reversed. The reversal results thus obtained, with the errors of carbonate content mostly ranging within + or -5% relative to that measured from sediment samples, show a relatively accurate picture of carbonate distribution along the slope profile.completedSedimentary petrologyApplied geophysicscarbonate rocksdata processinggeophysical methodsgeophysical profilesgeophysical surveysinverse problemLeg 184neural networksNorth PacificNorthwest PacificOcean Drilling ProgramODP Site 1146ODP Site 1148Pacific Oceansedimentary rocksseismic methodsseismic profilesSouth China SeasurveysWest Pacificurn:org.iodp:exp:184urnlargerWorkCitationcampaignurn:org.iodp:exp:184:site:1146urnlargerWorkCitationstudyurn:org.iodp:exp:184urnlargerWorkCitationcampaignurn:org.iodp:exp:184:site:1148urnlargerWorkCitationstudyurn:org.iodp:exp:184urnlargerWorkCitationcampaignChinesegeoscientificInformation116.1622116.335618.501019.2724