Reservoir Characterization Using Support Vector Machines
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]
|Collections||ANU Research Publications|
|Source:||Proceedings of International Conference on Computational Intelligence for Modelling, Control and Automation, and International Conference on Intelligent Agents, Web Technologies and Internet Commerce|
|01_Wong_Reservoir_Characterization_2005.pdf||141.15 kB||Adobe PDF||Request a copy|
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