Том: 14389 , Год издания: 2023

Издатель: Springer International Publishing , Место издания: Berlin

The presented paper is devoted to the numerical study of the applicability of 3D inversion for fracture model reconstruction based on machine learning. In practice, geophysicists use seismic inversion for predicting reservoir properties. One-dimensional convolutional model lies in the basis of standard versions of inversion, but geology is more complex. That is why we provide implementation and investigation of the approach for 3D fracture model reconstruction based machine learning, which uses U-net neural network and 3D convolutional model. We provide numerical results for a realistic 3D synthetic fractured model from the North of Russia.