Using Model Trees for Classification
Machine Learning
Machine Learning
Machine Learning
Generating Accurate Rule Sets Without Global Optimization
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Rotation Forest: A New Classifier Ensemble Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition, Third Edition
Pattern Recognition, Third Edition
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Automatic Cluster Selection Using Index Driven Search Strategy
AI*IA '09: Proceedings of the XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia on Emergent Perspectives in Artificial Intelligence
An AI tool for the petroleum industry based on image analysis and hierarchical clustering
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Unsupervised and supervised learning in cascade for petroleum geology
Expert Systems with Applications: An International Journal
Hi-index | 0.00 |
The integration of different data in reservoir understanding and characterization is of prime importance in petroleum geology. The large amount of data for each well and the presence of new unknown wells to be analyzed make this task complex and time consuming. Therefore it is important to develop reliable prediction methods in order to help the geologist reducing the subjectivity and time used in data interpretation. In this paper, we propose a novel prediction method based on the integration of unsupervised and supervised learning techniques. This method uses an unsupervised learning algorithm to evaluate in an objective and fast way a large dataset made of subsurface data from different wells in the same field. Then it uses a supervised learning algorithm to predict and propagate the characterization over new unknown wells. Finally predictions are evaluated using homogeneity indexes with a sort of reference classification, created by an unsupervised algorithm.