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51318-11381-Naphthenic Acid Corrosion Prediction Using Jip Model - Evaluation and Validation

Evaluation of the proprietary prediction model and validation studies conducted in IOCL’s refinery crude units. Case studies comparing predictions with the refinery inspection / measured corrosion rate data are provided.

Product Number: 51318-11381-SG
Author: Amir Q M / Kannan Chandrasekaran / Sridhar Srinivasan / Kwei Meng Yap
Publication Date: 2018
$0.00
$20.00
$20.00

Accurate quantification of corrosivity of crude oil fractions has been a major challenge for refiners, stemming from inadequate understanding of complex influence of naphthenic acid and type/morphology, molecular weight of acid species, sulfur content and speciation, temperature, and fluid flow on corrosion. A proprietary model has been developed encapsulating data from Honeywell’s Crude Corrosivity Phase-I Joint Industry Program (JIP), conducted between 2006 and 2011. This research program, sponsored by Indian Oil Corporation Limited (IOCL) and nineteen other global refining and engineering companies, led to the development of the first ever quantitative engineering database and decision-support model to predict corrosion for common materials of construction employed in high temperature refinery crude fractionation. Data were generated in simulated refinery environments for relevant temperature ranges, varying naphthenic acid content, and active Sulphur levels for different process oils.

This paper provides details from the evaluation of the proprietary prediction model and validation studies conducted in IOCL’s refinery crude units. Case studies comparing the model predictions with the refinery inspection / measured corrosion rate data as a function of key operating parameters are provided. Guidelines on the utility of the prediction model and suggestions for improvements are also provided.

Key Words: Prediction model, Naphthenic acid corrosion, Crude corrosivity, Sulphidic corrosion, Joint Industry Project, CDU, VDU, Fractions

 

Accurate quantification of corrosivity of crude oil fractions has been a major challenge for refiners, stemming from inadequate understanding of complex influence of naphthenic acid and type/morphology, molecular weight of acid species, sulfur content and speciation, temperature, and fluid flow on corrosion. A proprietary model has been developed encapsulating data from Honeywell’s Crude Corrosivity Phase-I Joint Industry Program (JIP), conducted between 2006 and 2011. This research program, sponsored by Indian Oil Corporation Limited (IOCL) and nineteen other global refining and engineering companies, led to the development of the first ever quantitative engineering database and decision-support model to predict corrosion for common materials of construction employed in high temperature refinery crude fractionation. Data were generated in simulated refinery environments for relevant temperature ranges, varying naphthenic acid content, and active Sulphur levels for different process oils.

This paper provides details from the evaluation of the proprietary prediction model and validation studies conducted in IOCL’s refinery crude units. Case studies comparing the model predictions with the refinery inspection / measured corrosion rate data as a function of key operating parameters are provided. Guidelines on the utility of the prediction model and suggestions for improvements are also provided.

Key Words: Prediction model, Naphthenic acid corrosion, Crude corrosivity, Sulphidic corrosion, Joint Industry Project, CDU, VDU, Fractions

 

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