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Statistical Analysis for Partial Inspection of Heat Exchanger Tube BundlesNormal access

Authors: M. Alathba, R. Jones, N. Laycock, F. Hoeve, A. Ostrowska, S. Terpstra and S. Kuniewski
Event name: IPTC 2014: International Petroleum Technology Conference
Session: Session 47: PRODUCTION AND OPERATIONS - Integrity Management
Publication date: 19 January 2014
Organisations: EAGE
Language: English
Info: Extended abstract, PDF ( 284.75Kb )
Price: € 20

Summary:
The Pearl GTL plant in Qatar is the largest Gas-To-Liquids plant in the world, located north of Doha in Ras Laffan Industrial City. Like any other plant, it has to be maintained carefully, with the right tools and technology. During the forthcoming major turnaround, there is a need for the planned inspection of more than 60 shell and tube heat exchangers, with a total of more than 40,000 tubes. With the obvious desire to minimize the total shutdown cost and duration, it is desirable to only inspect the minimum fraction of the tubes that is necessary to determine their condition with a degree of confidence that is consistent with each individual item’s criticality in terms of both safety and production. Statistical data analysis, and in particular a range of techniques based on Extreme Value theory, are an important tool that can assist in this endeavour. In general terms, there is increasing interest within the Oil and Gas industry in the use of statistical methods in asset integrity management, and one major area of application is the planning and evaluation of inspections. The potential benefits from applying these techniques are seen to include more effective management of the risks associated with in-service degradation and, although the techniques have been around for some time, these methods are gaining traction in the industry now that the latest inspection technologies make available more quantitative information. Indeed, statistical analysis is already a fundamental part of some aspects of integrity management; for example, it is a key requirement of the HOIS approach to NII.


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