[303657] Artigo – CBM – Congresso Brasileiro de Metrologia

Resumo: Although subsea assets in the oil and gas (O&G) industry are very robust equipment, the consequences of their failures may be catastrophic for people, environment and companies. Nevertheless, the inspection procedures comprise measurement in loco with ROVs, which involve a high resource allocation in costs and planning. For this reason, O&G industries have been pushing a massive investment in digital technologies, like digital twins, with important simulation tools to estimate and predict the behavior of a process or the conditions of an asset. Digital twins for integrity management lay on several degradation models, the most relevant ones which subsea assets undergo, such as erosion and corrosion. In this context, the decision to inspect (or not) is driven by the outcomes from these degradation models, which are always a compromise between resource allocation and the risk associated with a catastrophic failure. It is called risk based inspection (RBI). This work aims to analyze how uncertainties related to the modeling process can influence the model outcomes and hence the reliability of the decisions based on them.