A measurement-driven corrosion progression model for maintenance planning in subsea pipelines
Year: 2025
Type: article
Abstract: Corrosion is one of the most common degradation mechanisms affecting subsea oil and gas pipelines. The operating installations are continuously exposed to various degrading factors and require regular inspections to identify and locate potential damage. Accurate navigation at depths of hundreds of meters is challenging due to cluttered conditions. The precise alignment of the corrosion pits is crucial for constructing an accurate progression model, as it ensures that the spatial distribution and growth patterns of the pits are accurately represented, allowing for reliable predictions of material degradation. Without accurate alignment, the model can misinterpret corrosion behaviour, leading to flawed assessments of structural integrity and lifespan. This paper proposes optimal alignment strategies and an effective progression model for accurately assessing the depth of corrosion pits, using the actual rate of progression to predict future degradation. Sensitivity analysis is applied to identify suitable distance thresholds and orientation tolerances for alignment. By integrating these models, the study calculates the burst pressure to ensure safe operational limits, providing critical information to maintain structural integrity and prevent failures in corroded pipelines or structures. Experimental verification carried out on real inspection datasets demonstrates the practical applicability of the proposed alignment strategies and progression models, validating their effectiveness in real-world scenarios. This confirmation ensures that the methods can be reliably used to assess the progression of corrosion and predict the burst pressure, enhancing decision-making for maintenance and safety in industrial applications. • A data-driven model predicts corrosion pit growth using real-time inspection data. • An alignment method ensures accurate pit tracking with orientation verification. • A Monte Carlo model improves corrosion forecasting by handling uncertainties. • Safe operation burst pressure is estimated using corrosion depth trends and probability models. • Integrated modules enhance pit growth analysis for reliable pipeline maintenance.
Source: Measurement
Institution: Western Norway University of Applied Sciences
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,760
OpenAlex ID: W4415679905