An approach for prediction of petroleum production facility performance considering Arctic influence factors

Gao, Xiaohong; Barabady, Javad; Markeset, Tore

doi:10.1016/j.ress.2010.03.011

Cited by 66 publications

(50 citation statements)

References 16 publications

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“…This makes them disposed to the possibility of cracking due to thermal stress. This has to be considered in the design of the SAR helicopters and equipment (Gao et al, 2010); (Løset, 1995); (Freitag and McFadden, 1997).…”

Section: Low Temperaturesmentioning

confidence: 99%

Assessment of Helicopter Emergency Response Capacity in the Barents Sea

Jakobsen

Milaković

Ehlers³

2016

Volume 8: Polar and Arctic Sciences and Technology; Petroleum Technology

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As the global demand for energy is increasing, oil and gas exploration is moving further north to more remote areas. Offshore activity in these areas is challenging. Arctic-specific environmental conditions, long distances from onshore facilities and general lack of infrastructure are some of the challenges faced. Therefore, new and more robust solutions — both on technological and operational side — are required before commencing operations safely in these areas. In this paper, a helicopter emergency response capacity — with respect to prevailing wind conditions — for operations in the Barents Sea is studied and a method for mapping the rescue capacity in the given area is presented. The goal is to develop a method capable of assessing the probability of a successful rescue at different locations within given time requirements and under prevailing wind conditions. This is accomplished using a simulation model capable to determine how the wind speed and direction affect the search and rescue helicopter operations in the Barents Sea. The simulation model uses historical wind data along a potential route as input for evaluating the flying time to different locations in an area under the given wind conditions. In addition to the wind conditions, the variation in recovery time, and mobilisation time is implemented into the simulation model. By running the simulation model multiple times, probability distributions of the number of personnel which can be recovered within the given time requirements are established. This information is then used to plot isocurves of equal rescue probability on top of a map of the Barents Sea. Based on the results, it is concluded that wind conditions have significant effect on rescue capacity of a helicopter, and thus thorough weather observations should be made before establishing a search and rescue system for a given area.

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Section: Low Temperaturesmentioning

confidence: 99%

Assessment of Helicopter Emergency Response Capacity in the Barents Sea

Jakobsen

Milaković

Ehlers³

2016

Volume 8: Polar and Arctic Sciences and Technology; Petroleum Technology

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“…Typically, for each transport mode i, the spare parts deliverability can be quantified using a covariate model, such as the proportional hazard model (PHM) (Gao et al 2010;Cox 1972).…”

Section: Spare Parts Deliverability Considering Time-dependent and Timentioning

confidence: 99%

“…However, with the increased mechanisation and complexity in the production facilities, there is a rise in the number of component failure scenarios (Hassan et al 2012). Failure of components incurred downtime and unavailability of the system, which can cause substantial production losses and affect business performance (Gao et al 2010;Barabadi et al 2014).…”

Section: Introductionmentioning

confidence: 99%

“…Given the fastchanging nature of the arduous Arctic environment, this is considered as a big drawback. Further, not fully considering these effects can result in imprecise estimation of transportation time and probabilities (Gao et al 2010;Barabadi et al 2012;Kayrbekova et al 2011). Hence, the model that is used for prediction of the spare parts transportation time must be able to quantify the effect of the dynamic operating environment on transportation time.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic spare parts transportation model for Arctic production facility

Ayele

Barabadi

Barabady

2015

Int J Syst Assur Eng Manag

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Timely delivery of the required spare parts plays an important role in meeting the availability target and reducing the downtime of production facilities. Spare parts logistics is affected in complex ways while operating in the Arctic, since the area is sparsely populated and has insufficient infrastructure. It is also greatly affected by the distinctive operational environment of the region, such as cold temperature, varying forms of sea ice, blizzards, heavy fog, etc. Therefore, in order to have an effective logistic plan, the effect of all influencing factors, called covariates, on the transportation of the spare parts need to be identified, modelled and quantified by the use of an appropriate dynamic model. The traditional models, however, lack the comprehensive integration of the effect of covariates on the spare parts transportation. The purpose of this paper is to introduce the concept of a dynamic model for spare parts transportation in Arctic conditions by considering the time-independent and time-dependent covariates. The model continuously updates the prior probabilities according to the most recent time-dependent covariates to provide posterior probabilities. The application of the model is illustrated using a case study.

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“…However, such databases and handbooks do not reflect upon the impact of the harsh environmental and operating conditions on plant RAM performance, and thus their application to Arctic O&G industry may be associated with a great deal of uncertainty (Artiba et al, 2005;Gao et al, 2010;Homlong et al, 2012;Larsen and Markeset, 2007;Markeset et al, 2015;Naseri and Barabady, 2015b). Such conditions can give rise to the severity of issues involved in plant design and operations.…”

Section: Introductionmentioning

confidence: 99%

On RAM performance of production facilities operating under the Barents Sea harsh environmental conditions

Naseri

Barabady

2016

Int J Syst Assur Eng Manag

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Oil and gas (O&G) industry is expanding its activities into Arctic offshore, where is characterised with severe operating conditions and less-developed infrastructure. Such conditions affect the reliability, availability, and maintainability (RAM) of offshore O&G plants, operations, and activities through different scenarios. Plant RAM analysis provides key information for decision-making on, for instance, life-cycle cost management, inventory management, future investments, establishing maintenance policies, and safety-barrier management. Such decisions are of crucial value in Arctic offshore applications due to higher initial and operational costs. Therefore, a thorough evaluation and quantification of the effects of operating conditions on plant RAM performance play a significant role in such decisionmaking processes. In this regard, the aim of this paper is to broadly review and discuss different elements of offshore operating conditions specific to the Barents Sea, and further investigate various effects of such conditions on plant RAM. The present study can provide fundamental information to the academic and industrial sectors involved in the research and development of Arctic offshore O&G facilities and operations.

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An approach for prediction of petroleum production facility performance considering Arctic influence factors

Cited by 66 publications

References 16 publications

Assessment of Helicopter Emergency Response Capacity in the Barents Sea

Assessment of Helicopter Emergency Response Capacity in the Barents Sea

Dynamic spare parts transportation model for Arctic production facility

On RAM performance of production facilities operating under the Barents Sea harsh environmental conditions

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