# A comparative study of texture attributes for characterizing subsurface structures in seismic volumes

## TL;DR

This paper compares various texture attributes to effectively characterize and segment subsurface geological structures in seismic volumes, aiding seismic interpretation through automated volume labeling.

## Contribution

It provides a systematic comparison of texture attributes for seismic volume segmentation, demonstrating their feasibility and analyzing their advantages and disadvantages.

## Key findings

- Texture attributes can successfully segment seismic volumes.
- Different attributes have specific strengths and weaknesses.
- Feasibility of automated seismic volume labeling is confirmed.

## Abstract

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.