Using corrosion rate predictions, from either direct measurements or calculated corrosion rates, is not a new or novel approach. Both of these approaches have their own advantages and disadvantages. Corrosion, is a main pipeline degradation mechanism, and therefore understanding its effects, greatly improves integrity planning. Direct measurements can be more accurate compared to corrosion modelling, due to the dynamic variability of corrosion reaction kinetics, which corrosion models cannot account for. However, direct inspection is not always achievable, therefore engineers are forced to rely on the calculations of corrosion models.
In this work, the predictions of a selection of sweet corrosion models against actual corrosion rates in multiphase pipelines will be discussed. Subsequently, the benefits and limitations of flow modelling to improve corrosion predictions will be demonstrated.
In an ever more cost conscious economic environment, the importance of modelling and prediction of pipeline degradation has a much larger part to play in effective Asset Integrity Management (AIM). Cost-effective inspection intervals, avoiding un-necessary repairs and overall extending the asset life without compromising safe operation, is the ultimate goal of modern AIM systems (1). Historically, integrity management was based on direct inspection and operation, as part of "data gathering" for the specific asset and could be considered a learning cycle and the AIM system is then developed in a reactive way. The problem with reactive methodologies, which have trial and error or practical learning at their core, is the associated cost. As there must inherently be some form of failure or shortcoming before actions can be conducted, or implemented. Therefore, having the ability to account for likely future scenarios, and plan accordingly, negates the need for repetitive reactive practices and consequently reduces costs.
