Evaluation of an empirical model to predict maximum pitting corrosion rate in wet sour crude transmission pipelines

A PREVIOUSLY PUBLISHED EMPIRICAL MODEL for the prediction of internal pitting corrosion rate (PCR) was assessed to predict maximum PCR in wet sour crude Saudi Arabian transmission pipelines. The assessment of the model was based on 10 lines representative of the company network and with a wide range of pit depths and growth rates as derived from in-line inspection (ILI) runs. Although, the original model did not capture actual PCRs, it succeeded to properly rank the selected pipelines by order of increasing PCRs. Two reasons were identified as the main source of discrepancy, namely, the corrosion mitigation availability and the flow-induced localized corrosion (FILC). The original empirical model was modified by introducing two correction factors. These correction factors were elucidated through numerical optimization and were based on delineating the contributions of each correction factor. Introduction of the correction factors significantly increased the agreement between predictions and field measurements. It should be noted that the correction factors are specific to the pipeline network considered in this study and application of these correction factors to other operating conditions should be further evaluated.