PREDICTIVE MAINTENANCE
Insidious corrosion of fixed equipment detected Pipes and vessels monitored to detect and mitigate corrosion using wireless instrumentation By Jake Davies
Figure 1: Manual ultrasonic thickness measurements from a single point over 30-year period illustrate the type of variability often found when monitoring corrosion in piping and vessels. Image courtesy: Chevron
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iscussions of predictive maintenance in the oil & gas industry usually focus on rotating equipment such as pumps and turbines. Those are certainly valid areas of concern, but the result of a failure is usually limited to the equipment itself. On the other hand, static equipment such as piping, vessels and similar equipment is not as maintenance intensive, but a failure can be catastrophic. This equipment should also receive predictive maintenance attention. Major loss of hydrocarbon containment can result in fatalities while damaging equipment, the environment and a company’s reputation. The economic impact will often be felt long after the initial clean-up and repair is completed. Two well-documented events tell the tale: BP Cherry Point in February of 2012 and Chevron Richmond in August of 2012 both experienced containment losses caused by corrosion damage from inside piping, and major fires ensued. The threat of internal corrosion and erosion exists throughout the hydrocarbon production chain, from the wellhead, through midstream, to refinery and distribution. To avoid unplanned outages or disaster, equipment must be repaired or replaced before the metal thickness reaches a critical minimum limit. But how can operators determine when that point is approaching?
10 • FEBRUARY 2020 OIL&GAS ENGINEERING
Monitoring metal loss Traditional approaches to this challenge send technicians into the plant to take manual thickness measurements. Since sections can’t be cut open, the most common method is ultrasonic thickness measurement. This technique is nonintrusive, so it can be performed with the plant in operation, with no effect on the process or safety risk. Naturally, manual inspections incur costs for the technician to gain access to the desired measurement location, which may involve erecting scaffolding, removing insulation and so forth. Despite these costs, a refinery will typically have several thousand locations scheduled for inspection at periodic intervals ranging from every few weeks in high-risk locations to once every five years in other less-critical areas. These inspections produce volumes of data, manually entered into inspection management software for analysis. Even with thousands of measurements generated each year, this inspection data is inadequate to understand plant health in real time. Plant personnel can’t see how the plant is coping with the ever-changing corrosion and erosion sources or use data to predict when metal thickness will reach its retirement point. Why is manual measurement so ineffective? Most consecutive periodic measurements are performed in slightly different locations on the pipe, by different technicians, often armed with different inspection equipment. Such variances in measurements (See figure 1) add up to data noise, rendering the information largely useless. Variability of ±1 mm (.040 in.) is expected, but if a pipe wall is 5 mm (.200 in.) thick, the engineer evaluating the data will lack confidence when trying to determine when that pipe will reach its retirement thickness. Predicting damage rates is challenging, especially in areas where the corrosivity or erosivity of the process fluid varies frequently. Nowhere
