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96011 PREDICTION OF CORROSIVITY OF CO2/H2S PRODUCTION ENVIRONMENTS

Product Number: 51300-96011-SG
ISBN: 96011 1996 CP
Author: Sridhar Srinivasan, Russell D. Kane
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One of the most fundamental issues in current day corrosion research is assessment of corrosion rates in steels and determination of corrosivity of typical operating environments in oil and gas production. Such an assessment requires an understanding of the role of primary environmental and metallurgical variables and underlying mechanisms of corrosion. This paper presens a novel hierarchical approach to assess system corrosivity and prediction of corrosion rates in carbon steels in production environments containing CO2 and/or H2S. Critical environmental parameters that influence system corrosivity are identifixl and the effects of these parameters on corrosion are examined. Modeling for synergistic assessment of system corrosivity as a function of relevant operating parameters is presented and is accompanied by a description of a computer program to capture the model so described. Keywords: CO2 H2S, Corrosivity, prediction, corrosion rates, computer model
One of the most fundamental issues in current day corrosion research is assessment of corrosion rates in steels and determination of corrosivity of typical operating environments in oil and gas production. Such an assessment requires an understanding of the role of primary environmental and metallurgical variables and underlying mechanisms of corrosion. This paper presens a novel hierarchical approach to assess system corrosivity and prediction of corrosion rates in carbon steels in production environments containing CO2 and/or H2S. Critical environmental parameters that influence system corrosivity are identifixl and the effects of these parameters on corrosion are examined. Modeling for synergistic assessment of system corrosivity as a function of relevant operating parameters is presented and is accompanied by a description of a computer program to capture the model so described. Keywords: CO2 H2S, Corrosivity, prediction, corrosion rates, computer model
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