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