Abstract
This paper discusses the typical corrosion anomalies likely to occur in the wet oil system of a Floating Storage and Offloading Vessel (FPSO). The root causes and operational mitigations are identified. A neural network is proposed for capturing relationships within the large volume and diversity of data and hence permit effective modelling of corrosion and integrity of specific piping sections. Novel mitigations which can minimize severity of wall loss for flowing lines include; corrosion modelling of separator fluids and consequent pressure and temperature adjustments and calculated partition coefficients P derived from corrosion inhibitor (CI) injection and residual lab data for first-pass assessment of the effectiveness of CI injections, hence providing adequate inhibition.
Paper version not known (
Free)
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call