FORECASTING PETROLEUM PRODUCTION USING CHAOS TIME SERIES ANALYSIS AND FUZZY CLUSTERING

Abstract
Forecasting of petroleum production time series is a key task underlying scheduling of oil refinery production. In turn, forecasting requires analysing whether time series exhibits chaotic behavior. In this paper we consider chaos analysis based forecasting of time series of gasoline and diesel production. Chaos analysis is based on Lyapunov exponents and includes determination of optimal values of embedding dimension and time lag by using differential entropy approach. For forecasting of petroleum production, fuzzy “IF-THEN” rules constructed on the base of fuzzy clustering of the time series are used. The obtained prediction results show adequacy of the used methodology.

Authors
K. I. Jabbarova, O. H. Huseynov
Azerbaijan State Oil Academy, Azerbaijan

Keywords
Chaos, Lyapunov Exponents, Embedding Dimension, Petroleum Production, Fuzzy “IF-THEN” Rules
Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 4 , Issue: 4 )
Date of Publication :
July 2014

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