This is the second post in our series on OpendTect Machine Learning workflows. This time we show how to extract a salt body from 3D seismic. The ML workflow is called “Seismic Image Segmentation.” We train a 2D Unet (128x128 samples) to transform a seismic image into an image with values between 0 (no salt) and 1 (salt). The labels for training the Unet are created from interpretations of salt boundaries on a few sections. The trained Unet generates a new volume with values between 0 and 1 from which a 3D salt body is extracted.