Application of machine learning to predict the acoustic properties of rock samples
https://doi.org/10.24887/2587-7399-2018-4-67-70
Abstract
In the cases of absence acoustic logging, alternative methods of calculating the necessary rock properties are required. This article describes the results of applying machine learning technologies to predict the velocities of elastic waves propagation.
About the Authors
I. S. Chebyshev
Gazpromneft NTC LLC
Russian Federation
Russian Federation
Saint-Petersburg
E. S. Baryshnikov
Skolkovo institute of science and technology
Russian Federation
Russian Federation
V. A. Legkokonets
Saint-Petersburg Mining University
Russian Federation
Russian Federation
References
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4. Chebyshev I., Legkokonets V., Lukin S., Specifics of mechanical and strength rock properties estimation for wells drilling and exploitation, Procedia Structural Integrity, 2017, no. 6, pp. 252-258.
5. Hastie T., Tibshirani R., Friedman J., The elements of statistical learning: data mining, inference, and prediction, Springer, 2017, 745 p.
Review
For citations:
Chebyshev I.S., Baryshnikov E.S., Legkokonets V.A. Application of machine learning to predict the acoustic properties of rock samples. PROneft. Professionally about Oil. 2018;(4):67-70. (In Russ.) https://doi.org/10.24887/2587-7399-2018-4-67-70
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