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This paper explores optimized approaches used to assess the internal corrosion condition of several crude oil pipeline segments with the support of a robust internal corrosion predictive model (ICPM). Proven ICPMs can predict internal corrosion wall loss within ±10% of the actual wall loss confir me d b y inline inspection (ILI) or non-destructive techniques. In addition, the ICPM can accurately predict water and solid accumulations for the entire pipeline, enabling operators to proactively pinpoint susceptible locations and develop prevention and mitigation plans. Operators can also realize significant savings on inspecting and managing transmission pipelines, especially for non-piggable pipelines where ILI and/or hydrostatic testing is not practical. The results of this holistic assessment with ICPM were validated with ILI, and the comparison showed promising results. Lessons learnt and real-life case studies are presented to substantiate the presented arguments.
Key Words: ICPM, ILI, Direct Assessment, Crude Oil, Data Analysis and Integration, Pipeline Integrity, Internal Corrosion, Internal Corrosion Mechanisms, Validations.
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This paper will discuss the effectivity of ranking the crude pipelines due to their product corrosivity based on certain parameters such as corrosion coupons, cleaning pig deposit sampling analyses, microbial activity and previous ILI records.