Structural Interpretation with Deep Learning

Research papers
Today I am covering an exciting paper about Relative Geological Time (RGT) based horizon interpretation.

"Geng et al., 2020, Deep learning for relative geologic time and seismic horizons" is the title of the paper that provides a framework for calculating 2D RGTs and extracting horizons from them. Since extracting true RGT from field data is not straightforward, the network is trained using a synthetically-generated dataset. The proposed solution is tested on a range of field data that demonstrate promising results.

 I am particularly interested in such development. I believe that the future of structural interpretation would be tight around with Deep Learning-based RGT, meaning we would extract faults, horizont, and other features directly from RGT;

The link for the paper:
The link for the LinkedIn post