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- Title
DAS coupling noise suppression based on MCA–FK.
- Authors
Xu, Yankai; Zhu, Hongduo; Cao, Siyuan; Chen, Siyuan; Li, Jiawei; Liu, Hongwei
- Abstract
In recent years, distributed fiber acoustic sensor (DAS) technology has been applied for high-precision acquisition of vertical seismic profile (VSP) data, which has the advantages of high-density acquisition, low cost, safety and coordination. However, coupling noise with characteristics similar to that of the spring is produced and mixed in the VSP data collected by the distributed optical fiber in the well. The energy of the coupling noise tends to be very strong, resulting in the effective VSP data being covered. In this paper, coupling noise is constructed by analyzing its morphological characteristics. The dictionaries of coupling noise and clean VSP data are constructed respectively using their different characteristics, and the morphological component analysis (MCA) algorithm is proposed to separate them. The alternating direction multiplier method (ADMM) is used to solve the objective function, for which both L1 and L2 norm regularizations are adopted in the MCA algorithm. However, the performance of the algorithm heavily relies on the coefficient selection of the threshold, which can lead to noise residue in the denoised VSP data and effective signal attenuation due to the inappropriate selection of the threshold. Therefore, the frequency-wavenumber (FK) transform is further used to extract VSP data from the separated coupling noise. The proposed MCA and FK transform (MCA–FK) algorithm is applied to the field data and has achieved good results.
- Subjects
VERTICAL seismic profiling; NOISE; OPTICAL fibers
- Publication
Acta Geophysica, 2024, Vol 72, Issue 4, p2465
- ISSN
1895-6572
- Publication type
Article
- DOI
10.1007/s11600-023-01225-y