A comparative study of texture attributes for characterizing subsurface structures in seismic volumes
| Autor: | Mohamed Deriche, Motaz Alfarraj, Yazeed Alaudah, Muhammad Ali Qureshi, Asjad Amin, Ghassan AlRegib, Zhen Wang, Zhiling Long, Yuting Hu, Suhail Al-Dharrab, Haibin Di |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
FOS: Computer and information sciences
business.industry Computer Vision and Pattern Recognition (cs.CV) Computer Science - Computer Vision and Pattern Recognition Geology Pattern recognition 02 engineering and technology 010502 geochemistry & geophysics 01 natural sciences Texture (geology) Interpretation (model theory) Geophysics 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business 0105 earth and related environmental sciences |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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