A model was previously developed to predict internal pitting corrosion of oil and gas pipelines. The model considers the influence of temperature, total pressure, H2S partial pressure, CO2 partial pressure, the concentrations of sulfide, bicarbonate and chloride ions and the production rates of oil, gas, water, and solids on pitting corrosion rate. The model was based on experiments carried out in the laboratory at high pressure and high temperature under the operating conditions of the oil and gas pipelines and was validated by field trials and using field data. The model accounts for the statistical nature of pitting corrosion. Recently, a microbiologically influenced corrosion (MIC) risk model was also developed and merged with the internal pitting corrosion model so that the integrated model predicts the optimized pitting corrosion rate due to both non-MIC and MIC activities. Twenty years of field data was collected from 19 pipe sections from two sites (Site A and B) in an oil and gas production field. Within the limitations of field data and model inputs, the model prediction correlated well with the data.

Subject
Pits, Water, Polymerase chain reaction, Corrosion rate, Predicted corrosion rate, Pipelines, Gas pressure, Pitting corrosion rates, Partial pressures, Corrosion modeling, Risk management, Pitting, Microbiologically influenced corrosion
Keywords:
MIC, SEM, pitting, modeling
Government work published by the Association for Materials Protection and Performance (AMPP) with permission of the author(s). Positions and opinions advanced in this work are those of the author(s) and not necessarily those of AMPP. Responsibility for the content of the work lies solely with the author(s).
2013
GOV
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