Robust prediction of CO₂ corrosion rate in extraction and production hydrocarbon industry

Abstract

Purpose

CO₂ corrosion rate prediction is regarded as the backbone of materials selection in upstream hydrocarbon industry. This study aims to identify common types of errors in CO₂ rate calculation and to give guidelines on how to avoid them.

Design/methodology/approach

For the purpose of this study, 15 different “corrosion study and materials selection reports” carried out previously in upstream hydrocarbon industry were selected, and their predicted CO₂ corrosion rates were evaluated using various corrosion models. Errors captured in the original materials selection reports were categorized based on their type and nature.

Findings

The errors identified in the present study are classified into the following four main types: using inadequate or false data as the input to the model, failing to address factors which may have significant influence on corrosion rate, utilizing corrosion models beyond their validity range and utilizing a corrosion model for a specific set of input, where the model is considered to be inaccurate even though the input lies within the software’s range of validity.

Research limitations/implications

This study is mainly based on the use of various corrosion models, and except few cases for which some actual field corrosion monitoring data were available, no laboratory tests were performed to verify the predicted data.

Practical implications

The paper provides a checklist of common types of errors in CO₂ corrosion rate prediction and the guidelines on how to avoid them.

Originality/value

CO₂ corrosion rate calculation is regarded as the backbone of materials selection in hydrocarbon industry. In this work, the source of errors in terms of corrosion modeling tool and human factors were identified.

Citation

Hosseini, S.M.K. (2017), "Robust prediction of CO₂ corrosion rate in extraction and production hydrocarbon industry", Anti-Corrosion Methods and Materials, Vol. 64 No. 1, pp. 36-42. https://doi.org/10.1108/ACMM-08-2015-1564