Multi-Scale Deep Network for Fault Detection

A system for detecting an unknown fault in a target seismic volume, comprising:

• a computer processor;
• and
• memory storing instructions executed by the computer processor, wherein the instructions comprise functionality to:
• generate a plurality of patches from a training seismic volume that is separate from the target seismic volume, wherein a patch of the plurality of patches comprises a set of training areas;
• generate a label for assigning to the patch, wherein the label represents a subset, of the set of training areas, intersected by a known fault specified by a user in the training seismic volume;
• train, during a training phase and based at least on the label and the training seismic volume, a machine learning model;
• and
• generate, by applying the machine learning model to the target seismic volume during a prediction phase subsequent to the training phase, a result to identify the unknown fault in the target seismic volume;
• a display device for rendering the result to identify the unknown fault;
• and
• a repository for storing the plurality of patches and the plurality of training areas during the training phase.