王华忠1,,
1. 同济大学海洋与地球科学学院 波现象与智能反演成像研究组, 上海 200092
2. 中国石油化工股份有限公司石油物探技术研究院, 南京 211103
基金项目: 国家重点研发计划重点专项（2017YFB0202904），国家自然科学基金（41774126）和国家科技重大专项（2016ZX05024-001，2016ZX05006-002）资助
详细信息
作者简介: 张兵, 男, 1982年生, 在读博士研究生, 副研究员, 主要从事勘探地震速度建模技术研究.E-mail:zhangbin.swty@sinopec.com
通讯作者: 王华忠, 男, 1964年生, 教授, 博士生导师, 主要从事地震波传播、偏移成像与反演、近地表与中深层速度分析(反演)和速度模型建立、地震数据的规则化处理等方面的研究工作.E-mail:herbhuak@vip.163.com
中图分类号: P631收稿日期:2018-09-02
修回日期:2019-03-15
上线日期:2019-07-05
Velocity modeling for joint tomography of data domain first-arrival traveltime and imaging domain reflection traveltime
ZHANG Bing1,2,,WANG HuaZhong1,,
1. Wave Phenomena and Intelligent Inversion Imaging Group(WPI), School of Ocean & Earth Science, Tongji University, Shanghai 200092, China
2. Sinopec Geophysical Research Institute, Nanjing 211103, China
More Information
Corresponding author: WANG HuaZhong,E-mail:herbhuak@vip.163.com
MSC: P631--> Received Date: 02 September 2018
Revised Date: 15 March 2019
Available Online: 05 July 2019
摘要
摘要:复杂地表探区，尤其是盆山过渡区的油气勘探是我国也是世界上油气勘探的重点区域，但是此类区域油气地震勘探中满足精确地震成像的速度建模一直是个没有很好解决的问题.本文提出了一种综合性的数据域初至波走时与成像域反射波走时联合层析复杂地表浅中深层速度建模方法，并针对联合层析速度反演解的非唯一性问题，深入地分析了层析反演中正则化的本质意义，指出了建立构造特征正则化方法的具体技术路线，提出了联合层析的实现流程及策略.理论和实际数据试验表明，本文提出的数据域初至走时与成像域反射走时联合层析浅中深层速度建模技术避免了常规建模方法中浅层速度模型与中深层速度模型的融合问题，较好地解决了传统成像域反射层析对近地表模型的不可控更新问题，整体提升了深度域浅中深层速度模型的建模精度，进而提高了复杂地表、复杂构造区的地震成像质量.
关键词: 联合层析/
初至走时层析/
成像域反射走时层析/
浅中深层速度建模/
正则化方法
Abstract:Exploration of oil and gas in complex surface regions, especially basin-mountain transition areas, is significant in China and elsewhere in the world. Velocity modeling for accurate seismic imaging in such areas remains unsolved. This work proposes an integrated method for velocity modeling in the shallow and deep subsurface, which combines first break travel time in the data domain with reflection travel time in the imaging domain. Given that tomographic velocity inversion is nonlinear with strong non-uniqueness, the essence of regularization in tomographic inversion is discussed. Following the specific technical thought for regularization established with structural characteristics, the implementation and strategy of joint tomography are presented. Theoretical and real data experiments demonstrate that this joint tomography method in both the data and imaging domain avoids the fusion problem of velocity modeling from shallow to deep, while escaping from uncontrollability of conventional reflection tomography for the near surface model in imaging domain and improving the accuracy of velocity modeling both shallow and deep in the depth domain, thus enhances the quality of seismic imaging in areas with complex surface and structure.
Key words:Joint tomography/
First-arrival traveltime tomography/
Imaging domain reflection traveltime tomography/
Shallow-mid-deep velocity modeling/
Regularization
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