Machine learning methods in seismic facies analysis problems
https://doi.org/10.18303/2619-1563-2024-4-50
Abstract
The principles of machine learning and its use in solving seismic facies analysis problems are considered. The issues of the efficiency of the obtained solutions at a qualitative level, as well as significant aspects influencing their efficiency are discussed. The latter include: data quality, groups of attributes used, features of clustering algorithms. As an example, the results obtained for horizons related to the Bobrikovian–Tournasian strata of the Lower Carboniferous age in the southwestern part of the Orenburg region are given.
Keywords
3D seismic exploration,
classification,
clustering,
seismic attribute,
K-means method,
Kohonen method,
Bayesian classifier,
supervised learning,
seismic facies extraction
Supporting agencies: The study was carried out as part of government assignment to the Russian Academy of Sciences in basic research, Project FWZZ-2022-0017.
About the Authors
E. I. Korytkin
Trofimuk Institute of Petroleum Geology and Geophysics, SB RAS; SakhalinNIPI Oil and Gas Ltd
Russian Federation
Russian Federation
Evgeny I. Korytkin
Koptyug Ave., 3, Novosibirsk, 630090
Amurskaya Str., 53, Yuzhno-Sakhalinsk, 693009
G. M. Mitrofanov
Trofimuk Institute of Petroleum Geology and Geophysics, SB RAS; Novosibirsk State University; Novosibirsk State Technical University
Russian Federation
Russian Federation
Georgy M. Mitrofanov
Koptyug Ave., 3, Novosibirsk, 630090
Pirogova Str., 1, Novosibirsk, 630090
K. Marks Ave., 20, Novosibirsk, 630073
A. M. Kamashev
Trofimuk Institute of Petroleum Geology and Geophysics, SB RAS; Novosibirsk State University
Russian Federation
Russian Federation
Aleksandr M. Kamashev
Koptyug Ave., 3, Novosibirsk, 630090
Pirogova Str., 1, Novosibirsk, 630090
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Review
For citations:
Korytkin E.I., Mitrofanov G.M., Kamashev A.M. Machine learning methods in seismic facies analysis problems. Russian Journal of Geophysical Technologies. 2024;(4):50-63. (In Russ.) https://doi.org/10.18303/2619-1563-2024-4-50
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