A Texture-based Approach for Automated Detection of Listric Faults

Abstract

Classical interpretation of listric faults is usually performed manually by the geophysicist, 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 the obtained binary maps, which include morphological opening and curve fitting, to yield a delineated listric fault surface 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 the structural interpretation.