Abstract
In this paper, we present an intelligent agent (ADDGEO) that assists geologists identifying rocks constituents during thin section analysis. ADDGEO is a hybrid tool using both a knowledge base and a neural net to recognize existent visual patterns in thin sections alone or with the user participation. ADDGEO was recently deployed in a Brazilian oil company presenting benefits to improve the geologists task completion. In addition, it has shown a potential use as a training tool.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
6 References
Garcia, A. C. B. — Active Design Documents: A New Approach for Supporting Documentation in Preliminary Routine Design — Ph. D. Thesis — Civil Engineering Department — Stanford University — 1992.
Decatur, S. E. — Applications of Neural Networks to Terrain Classifications — Proceedings of the International Joint Conference on Neural Networks 89 — Washington — 1989.
Roli, F., Serpico, S. and Vernazza, G. — Neural Networks for Classification od Remotely Sensed Images in Fuzzy Logic and Neural Networks Handbook — McGraw Hill Inc. — New York — 1996.
Hwang, J. N., Lay, S. R. and Kiang, R. — Robust Construction Neural Networks for Classification on Remotely Sensed Data — Proceedings of World Congress on Neural Networks 93 — Portland — 1993.
Freeman, J. A. e Skapura, D. M. — Neural Networks Algorithms, Applications and Programming Techniques — Addison-Wesley Publishing Company — Reading — 1991
Klimasausker, Casimir C. e Guiner, John P. Neuralworks — Neuralware Inc.-Pitsburgh-1988.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Garcia, A.C.B., Maciel, P.M., Ferraz, I.N. (2000). ADDGEO: An Intelligent Agent to Assist Geologist Finding Petroleum in Offshore Lands. In: Logananthara, R., Palm, G., Ali, M. (eds) Intelligent Problem Solving. Methodologies and Approaches. IEA/AIE 2000. Lecture Notes in Computer Science(), vol 1821. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45049-1_38
Download citation
DOI: https://doi.org/10.1007/3-540-45049-1_38
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67689-8
Online ISBN: 978-3-540-45049-8
eBook Packages: Springer Book Archive