A novel approach for automated detection of listric faults within migrated seismic volumes

One of the important geological structures that have significant geologic implications on petroleum and gas exploration in the subsurface are listric faults. The classical interpretation of listric faults is usually performed by manual picking, which is not only time consuming and labor intensive but also susceptible to interpreter bias. In this paper, we propose a texture-based interpretation workflow for the automated delineation of major listric faults in a 3D migrated seismic volume. In the first step, we compute three-dimensional gradient of texture (3D-GoT), which describes the texture dissimilarity between neighboring cubes around each voxel in a seismic volume across time or depth, crossline, and inline directions. In the second step, we calculate an adaptive global threshold and apply it to the 3D-GoT map to obtain a binary map, which highlights the probable boundary regions of the listric faults. Finally, we apply post-processing to obtained binary maps that includes morphological opening and curve fitting to yield a delineated listric fault within the migrated seismic volume. The experimental results on a real seismic dataset from the Stratton field in the Texas Gulf coast show the effectiveness of the proposed workflow indicating its great potential for assisting structural interpretation and reservoir characterization in the exploration areas dominated by listric faults as well as the associated rollover anticlines and normal faults.