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Distributed acoustic sensing coupling noise removal based on sparse optimization

Chen Jianyou, Ning Junrui, Chen Wenchao, Wang Xiaokai, Wang Wei and Zhang Gulan
Distributed acoustic sensing coupling noise removal based on sparse optimization
Interpretation (Tulsa) (May 2019) 7 (2): T373-T382

Abstract

The industry treats the distributed acoustic sensing (DAS) system, which uses an optical fiber cable in vertical seismic profiling (VSP) data acquisition, as a new and fast-growing technology. The high-quality data set acquired from the DAS acquisition system can produce high-precision VSP images and obtain more detailed checkshots. However, in field data, the acquired VSP data set suffers from strong coherent DAS coupling noise. Many factors may cause coherent DAS coupling noise, such as the cable slapping and ringing due to the physical placement, the regular swing of the wireline in the well, and the uncoupling between the fiber cable and the casing. This DAS coupling noise reduces the signal-to-noise ratio and affects the subsequent processing and interpretation. Removing the DAS coupling noise can help to improve the quality of the VSP data set acquired with the DAS system. We have developed a sparse-optimization-based DAS coupling noise removing method. In the DAS-based VSP data set, the effective signal and the coupling noise have distinct morphological characteristics. The effective VSP signal has a wide bandwidth, whereas the DAS coupling noise appears in some narrow frequency bands in the frequency domain. The continuous wavelet transform and the discrete cosine transform can sparsely represent the effective VSP signal and DAS coupling noise, respectively. Therefore, we choose these two transforms as two sparse dictionaries and combine them to form an overcomplete dictionary. The morphological component analysis (MCA) can use the morphological difference between different components and the overcomplete dictionary to sparsely represent all components in the complicated signal. Based on the MCA theory, we use the block coordinate relaxation algorithm to separate the effective VSP signal and DAS coupling noise. Applications on a synthetic data set and two field data sets have validated the effectiveness of our method.


ISSN: 2324-8858
EISSN: 2324-8866
Serial Title: Interpretation (Tulsa)
Serial Volume: 7
Serial Issue: 2
Title: Distributed acoustic sensing coupling noise removal based on sparse optimization
Affiliation: Xi'an Jiaotong University, Department of Information and Communication Engineering, Xi'an, China
Pages: T373-T382
Published: 201905
Text Language: English
Publisher: Society of Exploration Geophysicists, Tulsa, OK, United States
References: 19
Accession Number: 2019-036092
Categories: Applied geophysics
Document Type: Serial
Bibliographic Level: Analytic
Annotation: Technical papers
Illustration Description: illus. incl. 1 table, sects.
Secondary Affiliation: SINOPEC, CHN, ChinaSouthwestern Petroleum University, CHN, China
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2019, American Geosciences Institute. Reference includes data supplied by Society of Exploration Geophysicists, Tulsa, OK, United States
Update Code: 201909
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