Horizon picking in 3D seismic data volumes

Authors:
Maria Faraklioti;Maria Petrou
Affiliations:
School of Electronics and Physical Sciences, University of Surrey, Guildford, GU2 7XH, UK;School of Electronics and Physical Sciences, University of Surrey, Guildford, GU2 7XH, UK and The Institute of Telematics and Informatics, CERTH, PO Box 361, Thermi, Thessaloniki, 57001, Greece
Venue:
Machine Vision and Applications
Year:
2004

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Abstract

In this paper, we present an automatic horizonpicking 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 that 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.