  In this paper, we explore how to computationally characterize subsurface
geological structures presented in seismic volumes using texture attributes.
For this purpose, we conduct a comparative study of typical texture attributes
presented in the image processing literature. We focus on spatial attributes in
this study and examine them in a new application for seismic interpretation,
i.e., seismic volume labeling. For this application, a data volume is
automatically segmented into various structures, each assigned with its
corresponding label. If the labels are assigned with reasonable accuracy, such
volume labeling will help initiate an interpretation process in a more
effective manner. Our investigation proves the feasibility of accomplishing
this task using texture attributes. Through the study, we also identify
advantages and disadvantages associated with each attribute.
