Application of machine learning in the analysis of seismic data to identify tectonic faults in various seismogeological conditions

Autor:	Nikolaenko, Sergey Viktorovich, Kovalenko, Andrey A., Nateganov, Andrey E., Kruk, Pavel N. K, Deryushev, Aleksandr B.
Jazyk:	English<br />Russian
Rok vydání:	2024
Předmět:	seismic exploration of mogt-3d tectonic faults neural networks machine learning Geology QE1-996.5 Geography (General) G1-922
Zdroj:	Известия Саратовского университета. Новая серия: Серия Науки о Земле, Vol 24, Iss 1, Pp 49-55 (2024)
Druh dokumentu:	article
ISSN:	1819-7663 2542-1921
DOI:	10.18500/1819-7663-2024-24-1-49-55
Popis:	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.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/2b6644c33c3f4ddb88843bc5b45f1932 Zobrazit plný text záznamu View record in DOAJ