While reflections associated with conformal sedimentary layers are usually coherent and continuous, other reflections, such as mass-transport complexes, karst collapse, and salt, may appear to be quite chaotic, without any specific orientation. We also may see chaotic events that have little to do with the target geology but rather are artifacts due to variations in the overburden and surface or budget limitations resulting in a suboptimum acquisition program. While some of these artifact issues can be handled at the time of processing, a certain level of randomness remains in most seismic data volumes. Geologic features of interpretational interest, such as fault damage zones, unconformities, and gas chimneys, often have randomness associated with them. The published work on randomness describes techniques such as cross correlation, which measures randomness associated with noise, the chaos attribute based on eigen-analysis of gradient covariance, and the seismic disorder attribute based on application of second derivative operators in the three axial directions in a 3D seismic volume. We apply the seismic disorder attribute to two different data sets and find that it is a useful attribute for assessing the signal-to-noise ratio and data quality, in addition to helping delineate damage zones associated with large faults and the interior of salt dome structures.