Deep learning applications in EM imaging

Abstract

Deep learning is now one of the most powerful techniques for solving various scientific and engineering problems. These deep learning techniques have recently begun to be applied in the field of subsurface imaging. As a part of the effort, we have applied the deep learning techniques to the imaging of subsurface from electromagnetic (EM) data. This presentation introduces three cases of the application: salt delineation and monitoring of injected CO2 using towed streamer EM data sets and kimberlite exploration using airborne EM data set. The results with significant qualities open up the possibility of the deep learning as an alternative of the conventional inversion techniques.