Improving The Reliability Of Differential Pressure Level Instrumentation
1. Improving the reliability of differential pressure level type instrumentation. Case Study: Soku Gas Plant. Shell Petroleum Development Company Akhibi, Osemhen Jennifer Intern, Shell Assessed Internship Program 2008
9. Cost Balance Model for a typical month: Based on past failure trends, the production capacity of an AG compressor and vendor’s prices. Initial Cost Running Costs, $ Fill System Sealed Capillary Cost of unscheduled deferment, $ 16,750 - Cost of man-hours expended on CMs, $ 600 - Glycol, $ 160 - Total 17,510 -
Slide 1 Introduce yourself: Osemhen Akhibi, Final year elect./elect. Engineering, University of Lagos. Assigned to the Instrumentation, Control and Automation Maintenance Team of Soku Gas Plant.
Slide 2 Relationship to other projects: This project is one of many that Shell is commissioning group-wide to eliminate waste, reduce deferment, streamline operations and render them as effective as possible. It’s a Group thing and not just about Soku, or Shell Nigeria. Soku however, has a lot of lessons to teach other facilities. This project was also about highlighting exemplary practices that could be adopted in other locations.
Slide 4 I learned the principles of DP level transmitters, their various configurations, control philosophies amongst other things. This process was a continuous one. It was at this stage I determined the calculations for range, from instrument manuals. The next step was to retrieve reactive maintenance records on instruments from SAP. Because I did not have SAP access, I had to rely on my team members to that for me. The graphs identified trends in instrument failure and were the major source of significant highlights. Some of the failure causes were registered in SAP, others were suggested by operation and maintenance team members. However, the identified failure causes were only symptoms. By applying root-cause analysis, I was able to isolate the root-causes of the failures and propose solutions that would address them. This approach fit into my schedule, mostly because I was doing most steps concurrently.
Slide 4 The transmitter is not intelligent enough to compensate for changes in parameters (Density and height of fill fluid) that reflect in its calibration as constant.
Slide 5 Today's situation: Summarize current situations (include significant highlights & principal findings) : The false alarms represent forty percent of the faults corrected in the same period. On the average, three spurious trips occur per month. The occurrence of false alarms is almost random. Principal findings: most of the problems with the instruments directly concern the wet legs. A number of situations invariably lead to a reduction in the wet legs. So not only do you have false indications by the instruments, but you now have a lot of man-hours expended on refilling the wet legs, time and resources that could be better spent. Another problem identified with the wet legs was the fact that the fill fluid is rather expensive (glycol).
Records identify two CMs in four years. Corresponds to recommended change-out. Presents an opportunity to upgrade to Foundation Fieldbus.
65mmscf=$100,500 1100mmscf=$1.7 million 16,750 Man-hours: 1 Man-hour = $25 51 false alarms rectified = 616 man hours = $15’400. Glycol per litre: $21 Deferment Worst Case Scenario: 24 hours deferment of the plant is a loss of 1.7 million dollars.
Slide 11 Recommendations. Note to self: maintenance for sealed systems, if any. Recording of Trip Free Days and reward at target e.g. 100 days My foremost recommendations: replace transmitters with sealed capillary models.
Learning was an internship-long process. Fluid mechanics; Pascal’s principle & Bernoulli’s principle. I now understand their applications, and business implications. I was introduced to control & automation on a scale I had never before imagined, at least in Nigeria. I was introduced to asset management systems, Computerized maintenance management system (SAP). I learnt what it meant to work as one member in a team of a large global organization.
