Paper Info
Title
Seismic data reconstruction method based on morphological component analysis
Abstract
The real seismic data is usually under-sampled in space domain because of the physical or economic limitations. So the incomplete seismic data need to be reconstructed before the subsequent processing. A method based on morphological component analysis (MCA) is discussed in the paper, which uses the curvelet dictionary and local discrete cosine transform (LDCT) dictionary to reconstruct the smooth components and the singular components respectively. Block coordinate relaxation (BCR) algorithm is adopted to complete the sparse optimisation. The validity of the proposed method was tested by numerical experiments on synthetic and real data demonstrate. As the method based on curvelet combining with POCS is widely used in practice, we compare its reconstructed results with the MCA-based method. The numerical results validate that the proposed method has higher reconstruction performance.
Year
DOI
Venue
2021
10.1504/IJMIC.2021.121835
INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL
Keywords
DocType
Volume
seismic data reconstruction, morphological component analysis, MCA, curvelet, local discrete cosine transform, LDCT
Journal
37
Issue
ISSN
Citations 
3-4
1746-6172
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Jianhong Yao100.34
Jicheng Liu262.08
Ya Gu300.34
Yongxin Chou474.48