#4: ML seismic data conditioning

Data quality is a cornerstone of any successful and effective work which uses data. All the results really depend on the quality of the data we are using in the work. Seismic data is a good example and interpretation results can be incorrect or incomplete if the data is of poor quality. Conventional approaches are either not efficient enough or very time consuming. Deep Learning algorithms in turn can be a good alternative to clean the data efficient and in a very short time.