10183 Prediction and Assessment of Rich Amine Corrosion Under Simulated Refinery Conditions

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Experimental results and findings from a joint industry program entitled “Prediction and Assessment of Corrosion in Amine Solvents” conducted over the period from March 2003 to May 2007. An overview of experimental methods, observed results and trends, as well as comparison of predicted corrosion rates to refinery field data.

Product Number: 51300-10183-SG

ISBN: 10183 2010 CP

Author: Vishal V. Lagad, Michael S. Cayard and Sridhar Srinivasan

Publication Date: 2010

Industries: Petroleum Refining , Science of Corrosion

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The challenges of enhancing amine unit reliability along with demands for increased unit throughput, circulation and treatment capacity, have led to the need for corrosion quantification and improved corrosion prediction capabilities. This paper summarizes some of the experimental results and findings from a joint industry program entitled “Prediction and Assessment of Corrosion in Amine Solvents” conducted over the period from March 2003 to May 2007. The program was jointly sponsored by a group of refining and engineering companies and focused on rich amine corrosion. The impacts of relevant process variables such as acid gas loadings (H₂S and CO₂), heat stable amine salt (HSAS) concentration, flow velocity/shear stress and temperature on the corrosion of carbon steel, austenitic stainless steel, duplex stainless steel and a nickel-based alloy were quantified using laboratory tests performed under simulated refinery conditions. Data collected were used to develop a software tool to predict corrosion rates for the three amine solvents (mono-ethanolamine (MEA), di-ethanolamine (DEA) and aminoethoxyethanol (DGA)(¹)) evaluated in the program.

This paper presents an overview of the experimental methods, some of the results and trends observed and comparison of predicted corrosion rates to refinery field data.

Key Words: rich amine corrosion, MEA, DEA, aminoethoxyethanol, heat stable amine salts, refining, gas processing, corrosion prediction software, material selection