Corrosion and crack anomalies are the major threats to the safety and structural integrity of oil and gas transmission pipelines. Pipeline operators commonly manage the corrosion and crack threats by regular in-line inspection.

After inspection, operators need to identify critical anomalies and plan mitigation works. Traditionally, a deterministic approach is used to assess anomalies using characteristic values of pipe properties, anomaly size, growth rate, and considering a minimum required safety factor (e.g., 1.25). TC Energy has used a full reliability-based method to determine the mitigation plan for corrosion and stress corrosion cracking (SCC) anomalies considering all the uncertainties associated with pipe geometry, material properties, anomaly size, growth rate and assessment model error explicitly. This method enables TC Energy to maintain the annual probability of failure of all known anomalies with the same location class not exceeding a consistent threshold (e.g., 1E−3 per anomaly per year).

Anomalies that do not meet the minimum safety margin (e.g., deterministic safety factor or reliability-based threshold) and cannot be mitigated timely, are usually managed by applying short-term self-imposed pressure restriction (derate). Derate pressure is typically calculated deterministically with conservative anomaly size, growth rate and a global safety factor. To account for potential parameter variation, conservative inputs often lead to conservative derate pressure. There is inconsistency between a full reliability-based mitigation plan and a deterministic short-term derate plan.

This study introduces a new efficient reliability-based approach using a Monte Carlo simulation technique to determine the derate schedule (e.g., the minimum required derate pressure for each month) to maintain the system to a consistent safety level. Two case studies, one MFL and one EMAT inspection with reported critical corrosion and crack anomalies, are conducted to demonstrate the advantage of fully reliability-based derate approach. The optimized derate plan minimizes the economical business impact to operators. The proposed framework in this study can be widely used to improve derate programs.

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