| 基于Bregman迭代的复杂地震波场稀疏域插值方法 |
| |
| 引用本文： | 勾福岩,;刘财,;刘洋,;冯晅,;崔芳姿.基于Bregman迭代的复杂地震波场稀疏域插值方法[J].应用地球物理,2014,11(3):277-288. |
| |
| 作者姓名： | 勾福岩 ;刘财 ;刘洋 ;冯晅 ;崔芳姿 |
| |
| 作者单位： | [1]吉林大学地球探测科学与技术学院,长春130026; [2]中国地质调查局水文地质环境地质调查中心,保定071051 |
| |
| 基金项目： | supported by the National Natural Science Foundation of China（Nos.41274119,41174080,and 41004041）; the 863 Program of China（No.2012AA09A20103） |
| |
| 摘 要： | 在地震勘探中,野外施工条件等因素使观测系统很难记录到完整的地震波场,因此,资料处理中的地震数据插值是一个重要的问题。尤其在复杂构造条件下,缺失的叠前地震数据给后续高精度处理带来严重的影响。压缩感知理论源于解决图像采集问题,主要包含信号的稀疏表征以及数学组合优化问题的求解,它为地震数据插值问题的求解提供了有效的解决方案。在应用压缩感知求解复杂地震波场的插值问题中,如何最佳化表征复杂地震波场以及快速准确的迭代算法是该理论应用的关键问题。Seislet变换是一个特殊针对地震波场表征的稀疏多尺度变换,该方法能有效地压缩地震波同相轴。同时,Bregman迭代算法在以稀疏表征为核心的压缩感知理论中,是一种有效的求解算法,通过选取适当的阈值参数,能够开发地震波动力学预测理论、图像处理变换方法和压缩感知反演算法相结合的地震数据插值方法。本文将地震数据插值问题纳入约束最优化问题,选取能够有效压缩复杂地震波场的OC-seislet稀疏变换,应用Bregman迭代方法求解压缩感知理论框架下的混合范数反问题,提出了Bregman迭代方法中固定阈值选取的H曲线方法,实现地震波场的快速、准确重建。理论模型和实际数据的处理结果验证了基于H曲线准则的Bregman迭代稀疏域插值方法可以有效地恢复复杂波场的缺失信息。
|
| 关 键 词： | Bregman迭代 OC-seislet变换 地震数据插值 压缩感知 H曲线准则 |
Complex seismic wavefield interpolation based on the Bregman iteration method in the sparse transform domain |
| |
| Fu-Yan Gou,Cai Liu,Yang Liu,Xuan Feng,Fang-Zi Cui.Complex seismic wavefield interpolation based on the Bregman iteration method in the sparse transform domain[J].Applied Geophysics,2014,11(3):277-288. |
| |
| Authors: | Fu-Yan Gou Cai Liu Yang Liu Xuan Feng Fang-Zi Cui |
| |
| Institution: | 1. College of Geo-exploration Science and Technology, Jilin University, Changchun, 130026, China
2. Center for Hydrogeology and Environmental Geology Survey, CGS, Baoding, 071051, China
|
| |
| Abstract: | In seismic prospecting, field conditions and other factors hamper the recording of the complete seismic wavefield; thus, data interpolation is critical in seismic data processing. Especially, in complex conditions, prestack missing data affect the subsequent highprecision data processing workflow. Compressive sensing is an effective strategy for seismic data interpolation by optimally representing the complex seismic wavefield and using fast and accurate iterative algorithms. The seislet transform is a sparse multiscale transform well suited for representing the seismic wavefield, as it can effectively compress seismic events. Furthermore, the Bregman iterative algorithm is an efficient algorithm for sparse representation in compressive sensing. Seismic data interpolation methods can be developed by combining seismic dynamic prediction, image transform, and compressive sensing. In this study, we link seismic data interpolation and constrained optimization. We selected the OC-seislet sparse transform to represent complex wavefields and used the Bregman iteration method to solve the hybrid norm inverse problem under the compressed sensing framework. In addition, we used an H-curve method to choose the threshold parameter in the Bregman iteration method. Thus, we achieved fast and accurate reconstruction of the seismic wavefield. Model and field data tests demonstrate that the Bregman iteration method based on the H-curve norm in the sparse transform domain can effectively reconstruct missing complex wavefield data. |
| |
| Keywords: | Bregman iteration OC-seislet transform seismic data interpolation compressive sensing H-curve norm |
| 本文献已被 维普 SpringerLink 等数据库收录！ |
|
