(175f) Advances in Salt Point Management Practices: Mitigating Overhead Corrosion with Big Data

In the world of overhead corrosion, it has long been recognized colloquially that ninety percent of metal loss occurs during ten percent of the time in operation. In many types of fractionating tower overheads, the largest unresolved dynamical aspects of overhead corrosion are caused by a fluctuating tendency to form amine hydrochloride salts in areas of the overhead system that result in corrosion. Because of the constantly changing tendency to form corrosive salts in an operating unit, it has remained difficult using traditional approaches to systematically identify the proverbial ten percent of time where damage causing episodes occur so that effective intervention and mitigation is possible.

Because of the challenges above, the fundamental principles of overhead corrosion mitigation have remained largely unchanged in the last decades. While advances in metallurgy, inhibitors, injection practices, and monitoring techniques have advanced, overhead corrosion measurement and predictive practices have not. The result is that crude unit overhead systems continue to experience corrosion that leads to unexpected failures, fouling, unplanned outages, and significant lost profit opportunities.

Salt point management practices continue to rely largely on series of unconnected salt point calculations over time using sparse data sets. Here we will present a new computational framework to allow continuous and quantitative sensitivity computations for amine hydrochloride salt formation. This capability then leads to the rapid identification of seemingly random corrosion events and their precise causes. During an emerging corrosion event, the onset can be rapidly flagged and alerted while the driving forces of salt formation and their sensitivities are quantitatively revealed. The demonstrated method takes real-time data from operating crude units and uses it to compute how changing factors such as crude diet, processing objectives, operations, control schema, physical constraints, set points, and randomly varying amine and chloride levels cause corrosion events. The practical objective of the methodology is to drive timely, precise, and proactive mitigation options in a granular and systematic fashion across a wide variety of event types. Real world examples taken from operating refineries will be used to demonstrate the technique.