Title :
The Extraction of Fractional-order Curvature Attributes and Applications in the Structure Interpretation
Author :
Junhua, Zhang ; Wang Wei ; Mingyou, Tan ; ShiLing, Cui ; Haiyun, Chen
Author_Institution :
Coll. of Geo-Resources & Inf., China Univ. of Pet., Dongying, China
Abstract :
Curvature attribute interpretation is a new interpretation technology rising in the recent two years. Curvature attributes provide images of structure and stratigraphy that complement those seen by the well accepted coherence algorithms. The article expounds the definition of the curvature, the physical meaning and its shortages in structural interpretation from the most basic mathematical definition. On this basis, we describe 2D curvature of the surface, list and compare the definition, physical meaning and its main usages of surface-derived attributes. After interpolation and 2D median filtering of t0 contour data, we extract 8 attributes with fractional-order method including mean curvature, Gaussian curvature, maximum curvature, minimum curvature, most positive curvature, most negative curvature, dip curvature, and strike curvature. Finally, we apply most positive curvature to detect fault and fracture and achieve better results.
Keywords :
computational geometry; curve fitting; geophysical image processing; interpolation; median filters; stratigraphy; topography (Earth); 2D curvature; 2D median filtering; Gaussian curvature; coherence algorithms; contour data; dip curvature; fractional order curvature attribute extraction; mean curvature; most negative curvature; most positive curvature; strike curvature; structure interpretation; surface derived attribute; Data mining; Feature extraction; Fourier transforms; Shape; Surface cracks; Surface morphology; Three dimensional displays; 2D median filter; fault; fractional-order interpretation; most positive curvature; t0 contour map;
Conference_Titel :
Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-8432-4
DOI :
10.1109/AICI.2010.149