  This paper reviews the most notable works applying machine learning
techniques (ML) in the context of geophysics and corresponding subbranches. We
showcase both the progress achieved to date as well as the important future
directions for further research while providing an adequate background in the
fields of weather forecast, wind energy, wave energy, oil and gas exploration.
The objective is to reflect on the previous successes and provide a
comprehensive review of the synergy between these two fields in order to speed
up the novel approaches of machine learning techniques in geophysics. Last but
not least, we would like to point out possible improvements, some of which are
related to the implementation of ML algorithms using DataFlow paradigm as a
means of performance acceleration.
