Inrecent years, machine learning and specifically deep learning has captured the attention of all industries, and Oil & Gas is no exception. Obviously, the end goal of petroleum companies is to extract oil; yet, one must first find prominent locations inside the Earth to do so.
That is where seismic exploration comes in: it is the study of subterranean formations to help us locate structures underneath. There are a lot of stages of seismic exploration, from processing the raw acoustic signal traces into a regular fixed-grid volume to detecting subterranean facies inside of it. Neural networks could immensely reduce the time taken by these procedures while simultaneously improving the accuracy of results.