Robust committee machine for water saturation prediction.

Citation

Mashohor, Syamsiah and Kenari, Seyed Ali Jafari (2013) Robust committee machine for water saturation prediction. Journal of Petroleum Science and Engineering, 104 (April). 10-Jan. ISSN 0920-4105

Abstract

Water saturation is one of the important physical properties of the petroleum reservoir which are usually determined by core analysis. An accurate determination of this parameter is significant to execute a realistic evaluation of hydrocarbon reserves in the formation and also decreasing the economic risk. In this study, a robust technique is proposed to determine an accurate value of this parameter from well log data in un-cored well or at un-cored interval of the same well by combining different types of machine learning techniques. The final results (sub-CM outputs) demonstrated that integrating these techniques using proposed method provides an accurate, fast and cost-effective method for estimating the target value.

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Additional Metadata

Item Type:	Article
Divisions:	Faculty of Engineering
DOI Number:	https://doi.org/10.1016/j.petrol.2013.03.009
Keywords:	committee machine genetic algorithm fuzzy logic neural network neural fuzzy watersaturation
Depositing User:	Muizzudin Kaspol
Date Deposited:	30 May 2014 08:30
Last Modified:	08 Oct 2015 07:22
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1016/j.petrol.2013.03.009
URI:	http://psasir.upm.edu.my/id/eprint/28591
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