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This work presents a combined modeling and experimental methodology to determine the onset of droplet entrainment from the bottom and deposition at the top of the line.
The entrainment of liquid droplets, occurring in a limited range of gas and liquid flow conditions within the stratified flow region, could represent an effective way to transport a non-volatile liquid corrosion inhibitor through the gas phase and combat Top of the Line Corrosion (TLC). However, such an approach is only viable if the inhibitor can reach the top of the pipe and deposit at a rate higher than the local rate of condensing water can dilute it. This work presents a combined modeling and experimental methodology to determine the onset of droplet entrainment from the bottom and deposition at the top of the line. A modeling approach predicting the droplet entrainment onset is proposed and validated against new multiphase flow data recorded in a large scale flow loop, at operating conditions similar to those encountered in gas-condensate production facilities. Additionally, TLC experiments were performed in the same flow loop under simulated water condensation conditions to measure the actual corrosion at different rates of inhibiting droplet deposition. The results confirm that the droplet entrainment/deposition can effectively mitigate TLC when operating parameters are accurately controlled.
Key words: Droplet entrainment, droplet deposition, top of the line corrosion, inhibition.
A novel optical fiber sensor is being developed to monitor the internal corrosion processes in natural gas transmission pipelines.
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A top-of-line corrosion (TLC) model integrated into a CO2/H2S corrosion prediction model. The TLC model determines the top of the line corrosion rate of carbon steel based on water chemistry and film-wise condensation rate. The effect of various glycols, such as Monoethylene Glycol, Diethylene glycol and Triethylene Glycol, are included.
The model was evaluated and effects of various parameters on corrosion rates are described. Corrosion rates obtained from the model are compared with actual field and lab testing data as a basis to quantify accuracy and efficacy.