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51318-10848-The Concept of Research Modelling and Lab Studies to Improve the Effectiveness of CMS

Picture for The Concept of Research Modelling and Lab Studies to Improve the Effectiveness of CMS
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In this work, we suggest and present an improved scheme of CMS with the additional element of external R&D studies, to achieve the highest level of reliability.

Product Number: 51318-10848-SG
Author: A. Almathami / M. Hoegerl / A. Al suwaij / T. Hafiz / M. Al Aljishi
Publication Date: 2018
Industry: Corrosion Monitoring and Control
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Corrosion management systems (CMS) have been developed for a variety of oil and gas assets. Improper implementation of CMS, by not adequately identifying and assessing possible corrosion root causes and risks during the Integrity Review Process, is one of the main reasons for corrosion failures. Life cycle management and continuous improvement often depends only on learning from asset failures, which cannot fully comprehend and evaluate complex root causes of typically complex corrosion processes.

In this work, we suggest and present an improved scheme of CMS with the additional element of external R&D studies, to achieve the highest level of reliability. Targeted research on selected key issues and investigative studies go beyond typical failure analysis. Findings and results of these studies should be implemented in the CMS and the documentation updated accordingly.

Two case studies demonstrate how results and knowledge gained from R&D studies directly improve corrosion management and prevent future failures. The first case is a research study on the origin of iron sulfide scale and corrosion. Clarification of the source and formation mechanism of iron sulfide directly affects the mitigation strategy and reduces workover with huge cost savings. The second case presents the advantages of an integrated approach of modelling and lab studies to clarify unforeseen causes of corrosion and uncover hidden design risks of high strength steel.

These two case studies highlight the importance of targeted research and studies as additional elements in the CMC to assess root causes of failures and identify hidden design risks to achieve the highest level of improvement and a life cycle of reliability.

Key words: Corrosion Management System, Research and Modelling, R&D Studies

Corrosion management systems (CMS) have been developed for a variety of oil and gas assets. Improper implementation of CMS, by not adequately identifying and assessing possible corrosion root causes and risks during the Integrity Review Process, is one of the main reasons for corrosion failures. Life cycle management and continuous improvement often depends only on learning from asset failures, which cannot fully comprehend and evaluate complex root causes of typically complex corrosion processes.

In this work, we suggest and present an improved scheme of CMS with the additional element of external R&D studies, to achieve the highest level of reliability. Targeted research on selected key issues and investigative studies go beyond typical failure analysis. Findings and results of these studies should be implemented in the CMS and the documentation updated accordingly.

Two case studies demonstrate how results and knowledge gained from R&D studies directly improve corrosion management and prevent future failures. The first case is a research study on the origin of iron sulfide scale and corrosion. Clarification of the source and formation mechanism of iron sulfide directly affects the mitigation strategy and reduces workover with huge cost savings. The second case presents the advantages of an integrated approach of modelling and lab studies to clarify unforeseen causes of corrosion and uncover hidden design risks of high strength steel.

These two case studies highlight the importance of targeted research and studies as additional elements in the CMC to assess root causes of failures and identify hidden design risks to achieve the highest level of improvement and a life cycle of reliability.

Key words: Corrosion Management System, Research and Modelling, R&D Studies

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