Geological Fractures Detection by Methods of Machine Learning.

Autor: Muratov, M. V., Biryukov, V. A., Petrov, I. B.
Zdroj: Lobachevskii Journal of Mathematics; Apr2020, Vol. 41 Issue 4, p533-537, 5p
Abstrakt: The aim of this article is representing of approach to solve the inverse exploration seismilogy problems with use of methods of machine learning. The two-dimensional problem of fracture placement and spacial orientation detection is cosidered in this article. To solve this problem the neural network is used. The training of network was produced by the direct exploration seismology problems with different placement and orientation of fracture solutions with use of mathematical modeling by grid-characteristic method on regular meshes. The use of such numerical method takes into consideration the characteristic physical properties of describing processes and give us possibility to construct correct algorithms on boundaries and contact boundaries in integrational domain. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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