Solution of the Fracture Detection Problem
by Machine Learning Methods
M. V. Muratova,*, V. A. Biryukova, and Corresponding Member of the RAS I. B. Petrova
a Moscow Institute of Physics and Technology
(National Research University), Dolgoprudnyi,
Moscow oblast, 141701 Russia
Correspondence to: *e-mail: max.muratov@gmail.com
Received 28 June, 2019
Abstract—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.
Keywords: mathematical modeling, grid-characteristic method, machine learning, neural networks, inverse exploration seismology problem, fracture
DOI: 10.1134/S1064562420020167