An expert-based approach to production performance analysis of oil and gas facilities considering time-independent Arctic operating conditions

Springer Science and Business Media LLC - 2015
Masoud Naseri1, Javad Barabady1
1Department of Engineering and Safety, UiT The Arctic University of Norway, Tromsø, Norway

Tóm tắt

The availability and throughput of offshore oil and gas plants operating in the Arctic are adversely influenced by the harsh environmental conditions. One of the major challenges in quantifying such effects is lack of adequate life data. The data collected in normal-climate regions cannot effectively reflect the negative effects of harsh Arctic operating conditions on the reliability, availability, and maintainability performance of the facilities. Expert opinions, however, can modify such data. In an analogy with proportional hazard models, this paper develops an expert-based availability model to analyse the performance of the plants operating in the Arctic, while accounting for the uncertainties associated with expert judgements. The presented model takes into account waiting downtimes and those related to extended active repair times, as well as the impacts of operating conditions on components’ reliability. The model is illustrated by analysing the availability and throughput of the power generation unit of an offshore platform operating in the western Barents Sea.

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Tài liệu tham khảo

Ansell JI, Philipps MJ (1997) Practical aspects of modelling of repairable systems data using proportional hazards models. Reliab Eng Syst Saf 58:165–171. doi:10.1016/S0951-8320(97)00026-4

Artiba A, Riane F, Ghodrati B, Kumar U (2005) Reliability and operating environment-based spare parts estimation approach: a case study in Kiruna Mine. Swed J Qual Maint Eng 11:169–184

Barabadi A, Markeset T (2011) Reliability and maintainability performance under Arctic conditions. Int J Syst Assur Eng Manag 2:205–217. doi:10.1007/s13198-011-0071-8

Barabadi A, Barabady J, Markeset T (2011a) Maintainability analysis considering time-dependent and time-independent covariates. Reliab Eng Syst Saf 96:210–217. doi:10.1016/j.ress.2010.08.007

Barabadi A, Barabady J, Markeset T (2011b) A methodology for throughput capacity analysis of a production facility considering environment condition. Reliab Eng Syst Saf 96:1637–1646. doi:10.1016/j.ress.2011.09.001

Barabadi A, Gudmestad OT, Barabady J (2015) RAMS data collection under Arctic conditions. Reliab Eng Syst Saf 135:92–99. doi:10.1016/j.ress.2014.11.008

Bedford T, Cooke R (2001) Probabilistic risk analysis: foundations and methods. Cambridge University Press, Cambridge

Clemen RT, Winkler RL (1999) Combining probability distributions from experts in risk analysis. Risk Anal 19:187–203

Clemen RT, Winkler RL (2007) Aggregating probability distributions. In: Edwards W, Miles RF Jr, Von Winterfeldt D (eds) Advances in decision analysis: from foundations to applications. Cambridge University Press, Cambridge, pp 154–176

Cooke RM (1991) Experts in uncertainty: opinion and subjective probability in science. Oxford University Press, Oxford

Dale CJ (1985) Application of the proportional hazards model in the reliability field. Reliab Eng 10:1–14. doi:10.1016/0143-8174(85)90038-1

Dubi A (2000) Monte Carlo applications in systems engineering. Wiley, Chichester

French S (1985) Group consensus probability distributions: a critical survey. In: Bernardo JM, Groot MHD, Lindley DV, Smith AFM (eds) Bayesian statistics. Elsevier, North Holland, pp 183–201

Gao X, Barabady J, Markeset T (2010) An approach for prediction of petroleum production facility performance considering Arctic influence factors. Reliab Eng Syst Saf 95:837–846. doi:10.1016/j.ress.2010.03.011

Genest C, McConway KJ (1990) Allocating the weights in the linear opinion pool. J Forecast 9:53–73. doi:10.1002/for.3980090106

Genest C, Zidek JV (1986) Combining probability distributions: a critique and an annotated bibliography. Stat Sci 1:114–135

Gudmestad OT, Karunakaran D (2012) Challenges faced by the marine contractors working in western and southern Barents Sea. Paper presented at the OTC Arctic technology conference, Houston, Texas, USA, 3–5 December

ISO (2001) ISO 12494: atmospheric icing of structures. ISO, Geneva

ISO (2010) ISO 19906: petroleum and natural gas industries—Arctic offshore structures. ISO, Geneva

Jardine A, Anderson P, Mann D (1987) Application of the Weibull proportional hazards model to aircraft and marine engine failure data. Qual Reliab Eng Int 3:77–82

Kumar D, Klefsjö B (1994) Proportional hazards model: a review. Reliab Eng Syst Saf 44:177–188. doi:10.1016/0951-8320(94)90010-8

Labeau PE, Zio E (2002) Procedures of Monte Carlo transport simulation for applications in system engineering. Reliab Eng Syst Saf 77:217–228. doi:10.1016/S0951-8320(02)00055-8

Løset S, Shkhinek K, Gudmestad OT, Strass P, Michalenko E, Frederking R, Kärnä T (1999) Comparison of the physical environment of some Arctic seas. Cold Reg Sci Technol 29:201–214. doi:10.1016/S0165-232X(99)00031-2

Mannan S (2014) Lees’ process safety essentials: hazard identification, assessment and control. Butterworth-Heinemann, Oxford. doi:10.1016/B978-1-85617-776-4.00004-X

Meyer MA, Booker JM (1991) Eliciting and analyzing expert judgement—a practical guide. Academic Press, London. doi:10.1137/1.9780898718485

Morris PA (1977) Combining expert judgments: a Bayesian approach. Manag Sci 23:679–693

Mosleh A, Apostolakis G (1986) The assessment of probability distributions from expert opinions with an application to seismic fragility curves. Risk Anal 6:447–461

Mosleh A, Bier VM, Apostolakis G (1987) Methods for the elicitation and use of expert opinion in risk assessment: phase 1, a critical evaluation and directions for future research (NUREG/CR-4962). U.S. Nuclear Regulatory Commission, Washington DC

Murthy DNP, Xie M, Jiang R (2004) Weibull models. Wiley, New Jersey

Naseri M, Barabady J (2013) Offshore drilling activities in Barents Sea: challenges and considerations. Paper presented at the proceedings of the 22nd international conference on port and ocean engineering under Arctic conditions (POAC), Espoo, Finland, 9–13 June

Naseri M, Barabady J (2015) Reliability analysis of Arctic oil and gas production plants: accounting for the effects of harsh weather conditions using expert data. J Offshorr Mech Arct Eng (under review)

OREDA Participants (2009) Offshore reliability data handbook, 5th edn. OREDA Participants, Trondhim

Pilcher JJ, Nadler E, Busch C (2002) Effects of hot and cold temperature exposure on performance: a meta-analytic review. Ergonomics 45:682–698

Podofillini L, Dang VN (2013) A Bayesian approach to treat expert-elicited probabilities in human reliability analysis model construction. Reliab Eng Syst Saf 117:52–64. doi:10.1016/j.ress.2013.03.015

Pulkkinen U (1993) Methods for combination of expert judgements. Reliab Eng Syst Saf 40:111–118. doi:10.1016/0951-8320(93)90101-4

Rausand M, Høyland A (2004) System reliability theory: models, statistical methods, and applications, vol 396. Wiley, Hoboken

Rufo MJ, Pérez CJ, Martín J (2012) A Bayesian approach to aggregate experts’ initial information. Electron J Stat 6:2362–2382

Stapelberg RF (2009) Handbook of reliability, availability, maintainability and safety in engineering design. Springer, New York

Winkler RL (1981) Combining probability distributions from dependent information sources. Manag Sci 27:479–488

Zio E (2013) The Monte Carlo simulation method for system reliability and risk analysis. Springer, London

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