TY - CONF A1 - de Araujo Abilio, André T1 - Expert System for Screening Microbiologically Influenced Corrosion (MIC) as Internal Failure Cause in Oil and Gas Upstream Pipelines N2 - The analysis of pipeline failures due to Microbiologically Influenced Corrosion (MIC) is challenging due to the complex interaction of many influencing parameters including pipeline operation conditions, fluid chemistry and microbiology, as well as the analysis of corrosion features and products. To help address this challenge, an expert system was developed to assist non-specialists in screening internal pipeline corrosion failures due to MIC related threats. To accomplish this, 15 MIC subject matter experts (with a total of 355 man-years of accumulated MIC based experience) were recruited to evaluate a total of 65 MIC failure cases based on real-life scenarios. These case study parameters and the expert elicited results were input into an Artificial Neural Network (ANN) model to create a model system which can screen whether a given failure scenario is one of three outcomes: a) failure is likely due to MIC, b) failure is likely not due to MIC, or c) the conclusion is inconclusive (analysis needs more data/information). The model system had an overall accuracy of 74.8% and it showcases that knowledge from subject matter experts can be captured in a reasonably effective way to screen for possible MIC failures. Based on that, this presentation will provide details of the model development process and key results to date. Important considerations regarding the level of confidence of the diagnoses and variation between expert opinion will also be discussed alongside with ideas on how to improve the model for field applicability. T2 - ISMOS 9 CY - Edinburgh, United Kingdom DA - 27.06.2023 KW - Expert System KW - Microbiologically Influenced Corrosion (MIC) KW - Oil and Gas Upstream KW - Failure Investigation KW - Artificial neural networks (ANN) PY - 2023 AN - OPUS4-64603 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -