Subsurface Depths Structure Maps Reconstruction with Generative Adversarial Networks. (arXiv:2206.07388v1 [physics.geo-ph])

This paper described a method for reconstruction of detailed-resolution depth
structure maps, usually obtained after the 3D seismic surveys, using the data
from 2D seismic depth maps. The method uses two algorithms based on the
generative-adversarial neural network architecture. The first algorithm
StyleGAN2-ADA accumulates in the hidden space of the neural network the
semantic images of mountainous terrain forms first, and then with help of
transfer learning, in the ideal case - the structure geometry of stratigraphic
horizons. The second …

arxiv generative adversarial networks maps networks physics