Application of pattern recognition techniques to hydrogeological modeling of mature oilfields

Authors:
Leonid Sheremetov;Ana Cosultchi;Ildar Batyrshin;Jorge Velasco-Hernandez
Affiliations:
Mexican Petroleum Institute, Eje Central Lazaro Cardenas, San Bartolo Atepehuacan, Distrito Federal, Mexico;Mexican Petroleum Institute, Eje Central Lazaro Cardenas, San Bartolo Atepehuacan, Distrito Federal, Mexico;Mexican Petroleum Institute, Eje Central Lazaro Cardenas, San Bartolo Atepehuacan, Distrito Federal, Mexico;Mexican Petroleum Institute, Eje Central Lazaro Cardenas, San Bartolo Atepehuacan, Distrito Federal, Mexico
Venue:
MCPR'11 Proceedings of the Third Mexican conference on Pattern recognition
Year:
2011

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Time series pattern recognition based on MAP transform and local trend associations

CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications

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Abstract

Several pattern recognition techniques are applied for hydrogeological modeling of mature oilfields. Principle component analysis and clustering have become an integral part of microarray data analysis and interpretation. The algorithmic basis of clustering - the application of unsupervised machine-learning techniques to identify the patterns inherent in a data set - is well established. This paper discusses the motivations for and applications of these techniques to integrate water production data with other physicochemical information in order to classify the aquifers of an oilfield. Further, two time series pattern recognition techniques for basic water cut signatures are discussed and integrated within the methodology for water breakthrough mechanism identification.