In the recent decade Deep Learning have revolutionised fields such as computer vision and image understanding. However, its use for the solution of inverse problems have been limited. In this work we examine the use of deep learning for the processing and inversion of airborne EM data. Preliminary results show that by incorporating deep learning it is possible to eliminate many of the artefacts that are commonly observed in airborne inversion allowing us to obtain much more reliable inversions that fit not only the data, but also our a-priori information.

Open-Access Online Publication: October 30, 2023