The increasing urgency to mitigate global warming has driven many efforts to control green house gas emissions. One solution among many is carbon capture and storage. However, CO2 emitters are not necessarily in the close vicinity of potential geologic storage sites. In consequence CO2 will be transported from generation site to storage sites under high pressures. This will necessitate a network of pipelines gathering supercritical CO2 from diverse sources and transporting it through transmission lines to the storage sites. These pipelines will be under corrosion risks, particularly because of possible carryover of trace impurities produced from the different sources, such as water, chloride, NOx, SOx, and O2. The effects of impurities on corrosion in supercritical CO2 have yet to be evaluated systematically. Corrosion of carbon steel associated with water and impurities in supercritical CO2 was studied by Electrochemical Impedance Spectroscopy in autoclaves. Five impurities were studied by introducing them in the liquid condensed phase: water, amine, HCl, HNO3 and NaOH. Results were analyzed in terms of the phase behavior and speciation.

No abstract

No abstract

Operations operates multiple carbon steel oil flow lines, which are emplaced on the desert surface of Abu Dhabi. The company's main oil pipelines are buried with coating and cathodic protection and internally protected by chemical inhibition, but the flow lines are without coating and cathodic protection. Over the years, this approach has been successful for flow lines, but the frequency of corrosion related leaks has increased recently due to changing operating and external conditions. This paper describes the use of a Bayesian network model that combines physics based models and expert knowledge of the flow lines to predict corrosion flaws depth and leak probability. It is shown that the Bayesian network approach can be useful in estimating location specific probability of failure and thus providing input to the prioritisation of inspections and corrosion mitigation. The approach was validated for five selected flow lines, where detailed field examination was available for comparison to model predictions.