{"title":"地震走时层析成像中的RMO自动拾取","authors":"Jianxing Zhang, Qin Yang, Xianhai Meng, Jigang Li","doi":"10.1109/ICNC.2014.6975997","DOIUrl":null,"url":null,"abstract":"The Residual Move Out (RMO) provides crucial information for updating velocity model in Pre-stack tomography. The accuracy and precision of picking result significantly determine the efficiency of the scheme. Two methods are produced respectively to warrant the requirements. The first method, namely energy spectrum based method, is conducted in a fully automatic way to ensure tomographic efficiency, and is very adapted to implement at the early iterative process of the tomography. The other method, which acts as a semi-automatic pickup based on the estimation of fourth-order cumulants, is executed to guarantee the accuracy for the late tomographic iterations. Practical applications witness the good effect of the two introduced approaches.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Automatic RMO picking in seismic travel time tomography\",\"authors\":\"Jianxing Zhang, Qin Yang, Xianhai Meng, Jigang Li\",\"doi\":\"10.1109/ICNC.2014.6975997\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Residual Move Out (RMO) provides crucial information for updating velocity model in Pre-stack tomography. The accuracy and precision of picking result significantly determine the efficiency of the scheme. Two methods are produced respectively to warrant the requirements. The first method, namely energy spectrum based method, is conducted in a fully automatic way to ensure tomographic efficiency, and is very adapted to implement at the early iterative process of the tomography. The other method, which acts as a semi-automatic pickup based on the estimation of fourth-order cumulants, is executed to guarantee the accuracy for the late tomographic iterations. Practical applications witness the good effect of the two introduced approaches.\",\"PeriodicalId\":208779,\"journal\":{\"name\":\"2014 10th International Conference on Natural Computation (ICNC)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 10th International Conference on Natural Computation (ICNC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNC.2014.6975997\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 10th International Conference on Natural Computation (ICNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2014.6975997","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic RMO picking in seismic travel time tomography
The Residual Move Out (RMO) provides crucial information for updating velocity model in Pre-stack tomography. The accuracy and precision of picking result significantly determine the efficiency of the scheme. Two methods are produced respectively to warrant the requirements. The first method, namely energy spectrum based method, is conducted in a fully automatic way to ensure tomographic efficiency, and is very adapted to implement at the early iterative process of the tomography. The other method, which acts as a semi-automatic pickup based on the estimation of fourth-order cumulants, is executed to guarantee the accuracy for the late tomographic iterations. Practical applications witness the good effect of the two introduced approaches.