For citation:
Nikolaenko S. V., Kovalenko A. A., Nateganov A. E., Kruk P. N., Deryushev A. B. Application of machine learning in the analysis of seismic data to identify tectonic faults in various seismogeological conditions. Izvestiya of Saratov University. Earth Sciences, 2024, vol. 24, iss. 1, pp. 49-55. DOI: 10.18500/1819-7663-2024-24-1-49-55, EDN: QKLHPI
This is an open access article distributed under the terms of Creative Commons Attribution 4.0 International License (CC-BY 4.0).
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Language:
Russian
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Article type:
Article
UDC:
502.08
EDN:
QKLHPI
Application of machine learning in the analysis of seismic data to identify tectonic faults in various seismogeological conditions
Autors:
Nikolaenko Sergey Viktorovich, Branch of LLC LUKOIL-Engineering PermNIPIneft
Kovalenko Andrey A., LLC LUKOIL-Engineering
Nateganov Andrey E., LLC LUKOIL-Engineering
Kruk Pavel N. K, LLC LUKOIL-Engineering
Deryushev Aleksandr B., LLC LUKOIL-Engineering
Abstract:
The article presents the results of a comparative analysis of algorithms for automatic interpretation of tectonic faults based on seismic data recorded in various seismogeological conditions. For each type of geological section (platform, salt tectonics, marine data), a cube of the probability of violations by an analytical algorithm and using trained neural networks was calculated.
Reference:
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Received:
27.11.2023
Accepted:
09.02.2024
Published:
29.03.2024