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Neural Computing and Applications
Published in: Neural Computing and Applications 12/2019

08-01-2019 | Machine Learning - Applications & Techniques in Cyber Intelligence

First break of the seismic signals in oil exploration based on information theory

Authors: Qiu-Jing Zhang, Ming-Yue Zhai

Published in: Neural Computing and Applications | Issue 12/2019

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Abstract

In oil seismic exploration, automatic picking of first arrivals is very important but difficult for seismic data with low signal-to-noise ratios. In the paper, we proposed a new method based on mutual information in information theory. Mutual information between signals and noises is zero theoretically; thus, random noises have fewer effects on first arrivals pickup with the criterion of mutual information. The paper presents a detailed description of the method based on mutual information. Tests and verification with simulation data and field measurements are carried out. When compared with other well-known methods, the first break picking accuracy and efficiency of the proposed algorithm are verified.
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Metadata
Title
First break of the seismic signals in oil exploration based on information theory
Authors
Qiu-Jing Zhang
Ming-Yue Zhai
Publication date
08-01-2019
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 12/2019
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3955-6

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