The goal of this work is to demonstrate the detection and extraction of salt tops from seismic data via the application of deep learning. Motivations for automated salt top extraction is a growing necessity in the field of petroleum exploration. Synthetic data is used for automatic label generation and training of a convolutional neural network is capable of predict with higher accuracy the salt top in unseen data during the training. Several experiments were performed and evaluated for exploring the effects of changing various parameters during training. The best model produced in this study provides excellent results when is compared with the interpretation.
