{"title":"一种用于逆时偏移的波场分解方法以减少低波数伪影","authors":"Fei Lei, Xinrong Mao, Jin Liu, Yuanguo Zhou","doi":"10.1109/CSQRWC.2019.8799134","DOIUrl":null,"url":null,"abstract":"Reverse time migration (RTM) is a powerful tool for reconstructing images, and has great advantage in imaging complex velocity models. However, traditional cross-correlation imaging condition brings low-wavenumber artifact (LWA). In this paper, we present a wave-field decomposition method to reduce these high-amplitude noises and achieve better imaging results.The main procedures include decompose source and receiver wave fields into up-going and down-going wave components, then a cross-correlation imaging condition are adopted to image the wave fields respectively. Several numerical examples indicate that the proposed method can effectively suppress LWA and obtain high-quality reconstructed images.","PeriodicalId":254491,"journal":{"name":"2019 Cross Strait Quad-Regional Radio Science and Wireless Technology Conference (CSQRWC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Wave-field Decomposition for Reverse Time Migration to Reduce the Low-wavenumber Artifact\",\"authors\":\"Fei Lei, Xinrong Mao, Jin Liu, Yuanguo Zhou\",\"doi\":\"10.1109/CSQRWC.2019.8799134\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Reverse time migration (RTM) is a powerful tool for reconstructing images, and has great advantage in imaging complex velocity models. However, traditional cross-correlation imaging condition brings low-wavenumber artifact (LWA). In this paper, we present a wave-field decomposition method to reduce these high-amplitude noises and achieve better imaging results.The main procedures include decompose source and receiver wave fields into up-going and down-going wave components, then a cross-correlation imaging condition are adopted to image the wave fields respectively. Several numerical examples indicate that the proposed method can effectively suppress LWA and obtain high-quality reconstructed images.\",\"PeriodicalId\":254491,\"journal\":{\"name\":\"2019 Cross Strait Quad-Regional Radio Science and Wireless Technology Conference (CSQRWC)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Cross Strait Quad-Regional Radio Science and Wireless Technology Conference (CSQRWC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSQRWC.2019.8799134\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Cross Strait Quad-Regional Radio Science and Wireless Technology Conference (CSQRWC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSQRWC.2019.8799134","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Wave-field Decomposition for Reverse Time Migration to Reduce the Low-wavenumber Artifact
Reverse time migration (RTM) is a powerful tool for reconstructing images, and has great advantage in imaging complex velocity models. However, traditional cross-correlation imaging condition brings low-wavenumber artifact (LWA). In this paper, we present a wave-field decomposition method to reduce these high-amplitude noises and achieve better imaging results.The main procedures include decompose source and receiver wave fields into up-going and down-going wave components, then a cross-correlation imaging condition are adopted to image the wave fields respectively. Several numerical examples indicate that the proposed method can effectively suppress LWA and obtain high-quality reconstructed images.