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

  • Machine Learning - Applications & Techniques in Cyber Intelligence
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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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Authors and Affiliations

  1. School of Computer and Information Engineering, Guangdong University of Petrochemical Technology, Maoming, China

    Qiu-Jing Zhang & Ming-Yue Zhai

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  1. Qiu-Jing Zhang
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  2. Ming-Yue Zhai
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Contributions

Q-JZ and M-YZ were involved in conceptualization. Q-JZ involved in methodology, software and resource selection, writing and preparing original draft, and supervision. M-YZ involved in formal analysis, investigation, data curation and supervision, and in writing, reviewing and editing original draft.

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Correspondence to Ming-Yue Zhai.

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Zhang, QJ., Zhai, MY. First break of the seismic signals in oil exploration based on information theory. Neural Comput & Applic 31, 8229–8237 (2019). https://doi.org/10.1007/s00521-018-3955-6

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  • DOI: https://doi.org/10.1007/s00521-018-3955-6

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