Corrosion management continues to be a worldwide challenge, stretching the capabilities of institutions across various fields around the globe. One such industry is the Oil & Gas which accounts for approximately 60% of the worldwide cost of corrosion that is estimated to be $2.5 trillion per year. The main challenge facing the industry is the reactive nature of corrosion management and the consequences of the lack of a holistic management approach. Although some tools claim to assist in managing corrosion, their effectiveness and usefulness are always questioned by the failures that occur in their presence. With this in mind, Saudi Aramco has developed an in-house web-based technology known as the Corrosion Management Solution (CMS), which is an integrated solution for monitoring corrosion parameters through real-time data. The intent of CMS is to shift corrosion management from a reactive to a proactive process. This in return has served the company in its corporate strategy of being on the global forefront of the Fourth Industrial Revolution (4.0IR) applications, while also enhancing the asset integrity and reliability across its operating facilities. This paper details the approach the team took to develop the CMS driving forward a new paradigm in corrosion management, and establish the platform for an intelligent machine learning based system.
Maximizing asset uptime and reducing maintenance costs are essential in any process facility. Effective corrosion management is a key driver to achieving these goals. Corrosion management involves monitoring and controlling corrosion to maintain the integrity of equipment and improve availability and safety. To be effective, it requires a thorough understanding of a facility's processes and the potential threats to its assets. A well-structured corrosion management program is necessary to proactively address corrosion and prevent unplanned outages1.
Corrosion mitigation in oil and gas industry requires intensive synergetic efforts to control simultaneously various number of process factors within wide spectrum of production and operating assets. For example, in Saudi Aramco, more than 35,000 parameters (counting only for critical assets) from different data-sources need to be closely monitored to ensure effective corrosion management and assets integrity. As industrial organizations expand and optimize operations to meet customer demands, it is crucial to maintain their commitment to eliminate accidents, injuries and harm to the environment, especially with the increasing pressure to achieve greater productivity in the most efficient way.
