| 基于弹性波全波形反演的主被动源多分量混采地震数据速度建模 |
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| 引用本文： | 张盼,邢贞贞,胡勇.基于弹性波全波形反演的主被动源多分量混采地震数据速度建模[J].地球物理学报,2019,62(10):3974-3987. |
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| 作者姓名： | 张盼 邢贞贞 胡勇 |
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| 作者单位： | 吉林大学地球探测科学与技术学院, 长春 130026 |
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| 基金项目： | 国家高技术研究发展计划（863计划）重大项目课题（2014AA06A605）和国家自然科学基金项目（41674124）联合资助. |
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| 摘 要： | 在常规地震采集中，被动源地震波场往往被视为噪声而去除，这就造成了部分有用信息的丢失.在目标区进行主动源和被动源弹性波地震数据的多分量混合采集，并对两种数据进行联合应用，使其在照明和频带上优势互补，能显著提高成像和反演的质量.本文针对两种不同类型的主被动源混采地震数据，分别提出了相应的联合全波形反演方法.首先，针对主动源与瞬态被动源弹性波混采地震数据，为充分利用被动源对深部照明的优势，同时有效压制被动震源点附近的成像异常值，提出了基于动态随机组合的弹性波被动源照明补偿反演策略.然后，针对低频缺失主动源与背景噪声型被动源弹性波混采地震数据，为充分利用被动源波场携带的低频信息，并避免对被动源的定位和子波估计，提出了基于地震干涉与不依赖子波算法的弹性波主被动源串联反演策略.最后，分别将两种方法在Marmousi模型上进行反演测试.结果说明，综合利用主动源和被动源弹性波混采地震数据，不仅能增强深部弹性参数反演效果，还能更好地构建弹性参数模型的宏观结构，并有助于缓解常规弹性波全波形反演的跳周问题.
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| 关 键 词： | 弹性波全波形反演 被动源 主动源 多分量 不依赖子波 |
| 收稿时间： | 2018-07-05 |
Velocity construction using active and passive multi-component seismic data based on elastic full waveform inversion |
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| ZHANG Pan,XING ZhenZhen,HU Yong.Velocity construction using active and passive multi-component seismic data based on elastic full waveform inversion[J].Chinese Journal of Geophysics,2019,62(10):3974-3987. |
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| Authors: | ZHANG Pan XING ZhenZhen HU Yong |
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| Institution: | College of Geo-exploration Science and Technology, Jilin University, Changchun 130026, China |
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| Abstract: | In conventional seismic acquisition, passive seismic wave fields are always seen as noises. The remove of passive seismic signals will lose some effective information. We propose to conduct joint multi-components acquisition of active and passive elastic seismic data on target areas and combine the two kinds of data together. The compensation in illumination and frequency band can obviously improve the quality of imaging and inversion. In this paper, aiming at combining two different kinds of active and passive seismic data, we proposed the corresponding joint full waveform inversion method. Firstly, aiming at active source and transient passive source elastic seismic data, to take full advantages of the deep illumination of passive sources and to suppress the imaging artifacts around the passive source locations, we proposed the elastic passive source illumination compensation inversion strategy based on dynamic random combination. Then, aiming at low-frequency absence active source and ambient noise passive source elastic seismic data, to adequately use the low-frequency information carried by passive source wavefields and to avoid passive source location and wavelet estimation, we proposed the elastic active and passive source successive inversion strategy based on seismic interferometry and source-independent algorithm. Finally, we tested the two inversion methods on Marmousi model. The results demonstrate that joint use of elastic active and passive seismic data can not only improve the inversion quality of elastic parameters in the deep part, but also better construct the macroscopic structures of the elastic media, and also helpful to mitigate the cycle-skipping problem of conventional elastic full waveform inversion. |
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| Keywords: | Elastic full waveform inversion Passive source Active source Multi-component Source-independent |
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