Horizon picking in 3D seismic images

Authors:
Maria Faraklioti;Maria Petrou
Affiliations:
University of Surrey, Guildford, UK;University of Surrey, Guildford, UK and The Institute of Telematics and Informatics, CERTH, Thermi, Thessaloniki, Greece
Venue:
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Year:
2003

Citing 0
Cited 1

Towards robust structure-based enhancement and horizon picking in 3-D seismic data

CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we present an automatic horizon picking algorithm, based on a surface detection technique, to detect horizons in 3D seismic data. The surface detection technique, and the use of 6- connectivity, allows us to detect fragments of horizons which are afterwards combined to form full horizons. The criteria of combining the fragments are similarity of orientation of the fragments, as expressed by their normal vectors, and proximity using 18-connectivity. The identified horizons are interrupted at faults, as required by the experts.