Abstract
Matching horizons across faults in seismic data is an application problem arising from the field of structural geology. Automating this task is difficult because of the small amount of local information typical for seismic images. In this paper, we examine the hypothesis that the problem can only be solved satisfactorily by introducing global knowledge in addition to local features. Furthermore, an extension of the current approach is proposed, which aims at computing a throw value for every pixel at a fault.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Kemp, L.F., Threet, J.R., Veezhinathan, J.: A neural net branch and bound seismic horizon tracker. In: 62nd Annual International Meeting, Expanded Abstracts, Houston, USA, Society of Exploration Geophysicists (1992)
Alberts, P., Warner, M., Lister, D.: Artificial neural networks for simultaneous multi horizon tracking across discontinuities. In: 70th Annual International Meeting, Expanded Abstracts, Calgary, Canada, Society of Exploration Geophysicists (2000)
Aurnhammer, M., Tönnies, K.: The application of genetic algorithms in structural seismic image interpretation. In: Van Gool, L. (ed.) DAGM 2002. LNCS, vol. 2449, pp. 150–157. Springer, Heidelberg (2002)
Aurnhammer, M., Tönnies, K.: Horizon correlation across faults guided by geological constraints. In: Proceedings of SPIE, San Jose, California, USA, vol. #4667, pp. 312–322 (2002)
Badley, M.E.: Practical seismic interpretation. D. Reichel, Boston (1985)
Anstey, N.A.: Correlation techniques – a review. Geophysical Prospecting 12, 355–382 (1964)
Telford, W.M., Geldart, L.P., Sheriff, R.E.: Applied Geophysics. Cambridge University Press, Cambridge (1990)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Aurnhammer, M., Tönnies, K. (2003). On the Relevance of Global Knowledge for Correlation-Based Seismic Image Interpretation. In: Michaelis, B., Krell, G. (eds) Pattern Recognition. DAGM 2003. Lecture Notes in Computer Science, vol 2781. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45243-0_48
Download citation
DOI: https://doi.org/10.1007/978-3-540-45243-0_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40861-1
Online ISBN: 978-3-540-45243-0
eBook Packages: Springer Book Archive