基于信号处理的欠规则地震数据重构方法综述

A Review of Irregular Seismic Data Reconstruction Methods Based on Signal Processing

不规则采样地震资料的插值重建是地震资料处理过程中一个非常重要的环节。文章主要从信号处理的角度介绍了近年来提出的地震数据重建方法,主要有基于压缩感知和基于深度学习的地震数据重建。基于压缩感知的方法主要介绍了基于低秩约束和稀疏约束的地震数据重建方法。依据时间先后梳理了地震数据重建方法的特点和发展的脉络,对各种方法的优缺点展开了总结说明,探讨了地震数据重建方法下一步的研究方向。

Interpolation reconstruction of irregular sampling seismic data is a very important part of seismic data processing.This paper mainly introduces the seismic data reconstruction methods proposed in recent years from the perspective of signal processing,mainly including the seismic data reconstruction based on compressive sensing and deep learning.The method based on compressive sensing mainly introduces the seismic data reconstruction method based on low rank constraint and sparse constraint.According to time,the characteristics and development of seismic data reconstruction methods are sorted out,the advantages and disadvantages of various methods are summarized,and the next research direction of seismic data reconstruction methods is discussed.