Advanced prediction migration method research in tunnel engineering investigation
文献类型:期刊论文
作者 | Zha XinJie1,2; Gao Xing1; Wang Wei1; Hou XianHua3; Yang Fei1; Zhang XiaoYan1 |
刊名 | CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION |
出版日期 | 2018-03-01 |
卷号 | 61期号:3页码:1150-1156 |
ISSN号 | 0001-5733 |
关键词 | Advanced prediction Staggered-grid Reverse time migration |
DOI | 10.6038/cjg2018L0764 |
通讯作者 | Gao Xing(gxing@igsnrr.ac.cn) |
英文摘要 | In this study, a two-dimensional tunnel model with low-velocity bodies was constructed to investigate elastic wave field propagation in tunnels, and pre-stack reverse time migration was used to conduct imaging. The stability and boundary conditions for advanced tunnel prediction numerical stimulation were obtained via the high-order staggered-grid finite-difference method and the first-order velocity-stress elastic wave equation to numerically simulate the wave field of the tunnel model. The pre-stack reverse time migration method, which is widely utilized in petroleum exploration, was applied for imaging of the tunnel model with the cross-correlation imaging condition and noise suppression technique. The modeling and migration results show that, reflection wave from abnormal body boundary and scatter wave from breakpoint are clear using the high-order staggered-grid finite-difference numerical modeling, the more accurate imaging results are obtained using reverse time migration method, which improves the resolution and accuracy for tunnel advanced prediction, and the observation system of single source closed to tunneling face with multi-channel receiver brings out the optimal abnormal body imaging, which provides theoretical basis for efficient data acquisition of advanced prediction in tunnel. |
WOS研究方向 | Geochemistry & Geophysics |
语种 | 英语 |
出版者 | SCIENCE PRESS |
WOS记录号 | WOS:000428609900028 |
源URL | [http://ir.igsnrr.ac.cn/handle/311030/57440] |
专题 | 中国科学院地理科学与资源研究所 |
通讯作者 | Gao Xing |
作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Chinese Acad Geol Sci, Inst Mineral Resources, Key Lab Saline Lake Resources & Environm, Minist Land & Resources, Beijing 100037, Peoples R China |
推荐引用方式 GB/T 7714 | Zha XinJie,Gao Xing,Wang Wei,et al. Advanced prediction migration method research in tunnel engineering investigation[J]. CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION,2018,61(3):1150-1156. |
APA | Zha XinJie,Gao Xing,Wang Wei,Hou XianHua,Yang Fei,&Zhang XiaoYan.(2018).Advanced prediction migration method research in tunnel engineering investigation.CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION,61(3),1150-1156. |
MLA | Zha XinJie,et al."Advanced prediction migration method research in tunnel engineering investigation".CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION 61.3(2018):1150-1156. |
入库方式: OAI收割
来源:地理科学与资源研究所
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