Modeling is the approach considered in this paper to predict localized corrosion inside oil and gas pipelines. It is proposed to develop a software which can also take microbiologically influenced corrosion (MIC)-related factors into consideration. Previously a software which can predict non-MIC related internal pitting corrosion was developed and validated. The following pipeline operational parameters were considered in its development: water in pipeline, temperature, pH, water quality (SO4(2-), Cl(-), bicarbonate), flow rate and partial pressure of H2S and CO2. A model to predict the susceptibility of MIC inside a pipeline has now developed as well. In addition to the operational parameters cited for the non-MIC pitting corrosion model, the redox potential and nutrient content of the water, as well as pipeline cleaning frequency and biocide application are considered in the MIC model. In both cases, model parameters were sought that could practically be measured or easily available to the pipeline operators. The validation of this MIC model based on case studies of pipeline failures, indicate that MIC susceptibility can be predicted. However there are other parameters such as operational history of pipeline, and type of chemicals used, among others, which can have an impact on the threat of MIC. The model needs additional data for its enhancement.
Validation of a predictive model for microbiologically influenced corrosion
Bestätigung eines Vorhersagemodells für die mikrobiologisch beeinflusste Korrosion
2008
17 Seiten, 1 Bild, 3 Tabellen, 49 Quellen
Aufsatz (Konferenz)
Englisch
Vorhersagetheorie , Simulationsmodell , bakterielle Korrosion , Pipeline , örtliche Korrosion , Rechnerprogramm , Betriebsdaten (technische Parameter) , Wassergehalt , Salzgehalt , pH-Wert , Temperatureinfluss , Strömungsgeschwindigkeit , Kohlendioxid , Schwefelwasserstoff , Biozid , Nährmedium , Korrosionsschaden
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