Shearlet域稀疏约束地震数据重建
发布时间：2018-08-07 16:11
【摘要】：在地震数据处理流程中,通常对不规则的、稀疏的或者缺失的地震数据进行插值处理,通过插值方法来避免多次波的预测错误和成像假频等现象,使地震数据处理更加精准。Shearlet变换是一种多尺度变换,具有最佳的稀疏性、方向性以及局部化特性。将Shearlet变换与基于Landweber加速下降迭代方法结合起来对地震数据进行插值,在保证求解精度的同时提高了计算效率。信号和噪声在Shearlet域具有不同的分布特点,通过阈值法压制随机噪声,可提高算法的抗噪性。此外,采用jitter采样的方式,更好地压制了假频信息。理论和实际地震数据验证了该方法的有效性。
[Abstract]:In the process of seismic data processing, irregular, sparse or missing seismic data are usually interpolated to avoid multiple prediction errors and false imaging frequency. Making the seismic data processing more accurate, the Shearlet transform is a multi-scale transform with the best sparsity, directionality and localization characteristics. The Shearlet transform is combined with the accelerated descent iteration method based on Landweber to interpolate the seismic data, which not only ensures the accuracy of the solution, but also improves the computational efficiency. The signal and noise have different distribution characteristics in Shearlet domain. The anti-noise of the algorithm can be improved by using threshold method to suppress random noise. In addition, jitter sampling is used to suppress the false frequency information better. The validity of the method is verified by theoretical and practical seismic data.
【作者单位】： 吉林大学地球探测科学与技术学院;
【基金】：国家科技重大专项项目(2011ZX05023-005-008) 国家自然科学基金项目(41374108)~~
【分类号】：P631.44
，
本文编号：2170585
[Abstract]:In the process of seismic data processing, irregular, sparse or missing seismic data are usually interpolated to avoid multiple prediction errors and false imaging frequency. Making the seismic data processing more accurate, the Shearlet transform is a multi-scale transform with the best sparsity, directionality and localization characteristics. The Shearlet transform is combined with the accelerated descent iteration method based on Landweber to interpolate the seismic data, which not only ensures the accuracy of the solution, but also improves the computational efficiency. The signal and noise have different distribution characteristics in Shearlet domain. The anti-noise of the algorithm can be improved by using threshold method to suppress random noise. In addition, jitter sampling is used to suppress the false frequency information better. The validity of the method is verified by theoretical and practical seismic data.
【作者单位】： 吉林大学地球探测科学与技术学院;
【基金】：国家科技重大专项项目(2011ZX05023-005-008) 国家自然科学基金项目(41374108)~~
【分类号】：P631.44
，
本文编号：2170585
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