{"title":"基于迭代集合卡尔曼平滑的地震波形弹性特性反演","authors":"M. Gineste, J. Eidsvik","doi":"10.3997/2214-4609.201902267","DOIUrl":null,"url":null,"abstract":"Summary Probabilistic inversion of subsurface elastic properties using seismic reflection data is considered. The methodology makes use of data partitioning as a divide-and-conquer strategy, while the conditioning to data makes use of an iterative ensemble Kalman smoother. Augmenting the ensemble Kalman framework with an variational approach is found suitable when conditioning on larger sets of seismic waveform data. The methodology is exemplified using a synthetic case for the inversion of acoustic- and shear velocity and density.","PeriodicalId":186806,"journal":{"name":"Petroleum Geostatistics 2019","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Seismic Waveform Inversion of Elastic Properties Using an Iterative Ensemble Kalman Smoother\",\"authors\":\"M. Gineste, J. Eidsvik\",\"doi\":\"10.3997/2214-4609.201902267\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Summary Probabilistic inversion of subsurface elastic properties using seismic reflection data is considered. The methodology makes use of data partitioning as a divide-and-conquer strategy, while the conditioning to data makes use of an iterative ensemble Kalman smoother. Augmenting the ensemble Kalman framework with an variational approach is found suitable when conditioning on larger sets of seismic waveform data. The methodology is exemplified using a synthetic case for the inversion of acoustic- and shear velocity and density.\",\"PeriodicalId\":186806,\"journal\":{\"name\":\"Petroleum Geostatistics 2019\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Petroleum Geostatistics 2019\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3997/2214-4609.201902267\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Petroleum Geostatistics 2019","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3997/2214-4609.201902267","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Seismic Waveform Inversion of Elastic Properties Using an Iterative Ensemble Kalman Smoother
Summary Probabilistic inversion of subsurface elastic properties using seismic reflection data is considered. The methodology makes use of data partitioning as a divide-and-conquer strategy, while the conditioning to data makes use of an iterative ensemble Kalman smoother. Augmenting the ensemble Kalman framework with an variational approach is found suitable when conditioning on larger sets of seismic waveform data. The methodology is exemplified using a synthetic case for the inversion of acoustic- and shear velocity and density.