Prediction of products quality parameters of a crude fractionation section of an oil refinery using neural networks

K. Bawazeer; A. Zilouchian

doi:10.1109/ICNN.1997.611656

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$Prediction of products quality parameters of a crude fractionation section of an oil refinery using neural networks$

Conference proceeding

Prediction of products quality parameters of a crude fractionation section of an oil refinery using neural networks

K. Bawazeer and A. Zilouchian

Proceedings of International Conference on Neural Networks (ICNN'97), Vol.1, pp.157-162 vol.1

1997

DOI: https://doi.org/10.1109/ICNN.1997.611656

Abstract

Artificial neural networks

Data analysis

Fractionation

Neural networks

Neurons

Oil refineries

Performance analysis

Petroleum

Predictive models

Production

Inferential analysis using neural network technology is proposed for an existing crude fractionation section of an oil refinery. Plant data for a three month operation period is analyzed in order to construct various neural network models using a backpropagation algorithm. The proposed neural networks can predict various properties associated with crude oil productions. The simulation results for modeling Naphtha 95% cut point and Naphtha Reid vapor pressure properties are analyzed. The results of the proposed work can ultimately enhance the online prediction of crude oil product quality parameters for crude fractionation processes.

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Details

Title: Prediction of products quality parameters of a crude fractionation section of an oil refinery using neural networks
Creators - without role: K. Bawazeer - Florida Atlantic University
A. Zilouchian - Florida Atlantic University
Publication Details: Proceedings of International Conference on Neural Networks (ICNN'97), Vol.1, pp.157-162 vol.1
Publisher: IEEE
Identifiers: 9937646108331
Academic Unit: King Abdulaziz University
Language: English
Resource Type: Conference proceeding