Solution of the Fracture Detection Problem by Machine Learning Methods

被引:1
作者
Muratov, M., V [1 ]
Biryukov, V. A. [1 ]
Petrov, I. B. [1 ]
机构
[1] Natl Res Univ, Moscow Inst Phys & Technol, Dolgoprudnyi 141701, Moscow Oblast, Russia
基金
俄罗斯科学基金会;
关键词
mathematical modeling; grid-characteristic method; machine learning; neural networks; inverse exploration seismology problem; fracture;
D O I
10.1134/S1064562420020167
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Inverse problems of fracture exploration seismology are solved using machine learning methods. A single fracture of fixed size and subvertical orientation is considered in the two-dimensional case. The spatial position and the inclination angle of the fracture are determined using a neural network. The training set consists of solutions of direct problems produced by the grid-characteristic method on regular rectangular meshes in the form of synthetic seismograms obtained by measuring the vertical velocity on the surface of the medium.
引用
收藏
页码:169 / 171
页数:3
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