Morphological Component Analysis in Seismic Data Reconstruction
详细信息
- 责任者：Li Haishan (School of Geosciences ; China University of Petroleum (East China) ; Qingdao 266555 ; China) ; Wu Guochen
- 刊名：Oil Geophysical Prospecting
- 出版年：2012
- 卷期：47(2)
- 关键词：地震勘探 ; seismic exploration ; 形态分析 ; shape analysis
- 页码：p.236-243
- 图表：10 illus., 27 refs.
- 分类号：1600
- issnNo：ISSN1000-7210
- isbnNo：CN13-1095/TE
摘要
According to the theory of sparse signal recovery,morphological component analysis(MCA) method is used to reconstruct the seismic data in this paper.The key of MCA method is to select the appropriate dictionaries.In view of the characteristics of seismic data and computational complexity,two kinds of dictionaries are selected,that is the undecimated wavelet transform(UWT) dictionary and curvelet transform dictionary.One sparsely represents for local singular part of seismic data,the other sparsely represents for smooth and linear part of seismic data.BCR(Block Coordinate Relaxation) algorithm is used to solve the objective function,and seismic data is decomposed into two morphologically different components.Then the reconstruction results are obtained by summing the components after interpolated and inpainted.Model testing and real data processing show that MCA method can be used not only for reconstruction large spacing uneven data,but also for space aliasing elimination.At the same time,the method itself has the denoising effect without bandwidth restriction.