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07553 Case-based Reasoning Model of CO2 Corrosion Based on Field Data

Picture for 07553 Case-based Reasoning Model of CO2 Corrosion Based on Field Data
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Product Number: 51300-07553-SG
ISBN: 07553 2007 CP
Author: Burzin Khajotia, Dusan Sormaz, and Srdjan Nesic
Publication Date: 2007
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$20.00
$20.00
An important aspect in corrosion prediction for oil and gas wells and pipelines is to obtain a realistic estimate of the corrosion rate. Corrosion rate prediction involves developing a predictive model that utilizes commonly available operational parameters, existing lab/field data and theoretical models to obtain realistic assessments of corrosion rates. The Case-based Reasoning (CBR) model for CO2 corrosion prediction is designed to mimic the approach of experienced field corrosion personnel. The model takes knowledge of corrosion rates for existing cases and uses CBR techniques and Taylor series expansion to predict corrosion rates for new fields having somewhat similar parameters. The corrosion prediction using CBR model is developed in three phases: case retrieval, case ranking, and case revision. In case retrieval phase, the database of existing cases is queried in order to identify the group of cases with similar values of critical corrosion parameters. Those cases are ranked in the second phase, using a modified Taylor series expansion of the corrosion function around each case. The most similar case is passed to the third phase: case revision. The correction of the corrosion rate by using a mechanistic corrosion model is utilized in order to predict the corrosion rate of the problem under consideration. The (CBR) model has been implemented as a prototype and verified on a large hypothetical case database and a small field database with real data.
An important aspect in corrosion prediction for oil and gas wells and pipelines is to obtain a realistic estimate of the corrosion rate. Corrosion rate prediction involves developing a predictive model that utilizes commonly available operational parameters, existing lab/field data and theoretical models to obtain realistic assessments of corrosion rates. The Case-based Reasoning (CBR) model for CO2 corrosion prediction is designed to mimic the approach of experienced field corrosion personnel. The model takes knowledge of corrosion rates for existing cases and uses CBR techniques and Taylor series expansion to predict corrosion rates for new fields having somewhat similar parameters. The corrosion prediction using CBR model is developed in three phases: case retrieval, case ranking, and case revision. In case retrieval phase, the database of existing cases is queried in order to identify the group of cases with similar values of critical corrosion parameters. Those cases are ranked in the second phase, using a modified Taylor series expansion of the corrosion function around each case. The most similar case is passed to the third phase: case revision. The correction of the corrosion rate by using a mechanistic corrosion model is utilized in order to predict the corrosion rate of the problem under consideration. The (CBR) model has been implemented as a prototype and verified on a large hypothetical case database and a small field database with real data.
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The NORSOK M-506 is an empirical model based on experiments undertaken in a single phase water flow loop. The data is from experiments with low content of iron ions in the water phase, and the model is thus regarded to give a fair representation of the maximum corrosion rate in a CO2 corrosion controlled system.
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