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Reservoir Characterization Using Support Vector Machines

Wong, Kok Wai; Ong, Yew Soon; Gedeon, Tamas (Tom); Fung, Chun Che


Reservoir characterization especially well log data analysis plays an important role in petroleum exploration. This is the process used to identify the potential for oil production at a given source. In recent years, support vector machines (SVMs) have gained much attention as a result of its strong theoretical background. SVM is based on statistical learning theory known as the Vapnik-Chervonenkis theory. The theory has a strong mathematical foundation for dependencies estimation and...[Show more]

CollectionsANU Research Publications
Date published: 2005
Type: Conference paper
Source: Proceedings of International Conference on Computational Intelligence for Modelling, Control and Automation, and International Conference on Intelligent Agents, Web Technologies and Internet Commerce


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