Jardine's subsea performance forecasting methodology has been successfully applied to a range of subsea developments for major operators in the North Sea, Gulf of Mexico and West of Africa, assisting them in decision-making processes regarding: subsea facilities configuration selection; vessel intervention strategy selection; rig contracting strategy; reservoir development plans (e.g. number of wells); definition of availability targets for specific subsea equipment items/components and life-cycle economics.

Our approach
Utilising proven dynamic simulation software, MAROS (developed by Jardine Technology), we prepare detailed simulation models for subsea facilities which incorporate key system parameters, including:

• Failure distributions for each subsea component
• Intervention duration distributions
• Various intervention strategies
• Impact of weather on intervention durations
• Vessel availability constraints (seasonal issues, number of vessels)
• Individual well production profiles, including the effect of production deferment
• Wells phasing in and out over the duration of life
• Varying spare subsea well capacities
• Economic parameters (mobilisation costs, day rates, oil price etc, economic cut-off dates for interventions)

We have developed significant in-house experience regarding definition and selection of the above parameters to ensure that the output from the developed simulation model accurately reflects the failure patterns and proposed operating philosophy for a subsea asset. Analysis of the model output quantifies the following performance parameters on an annual basis throughout the field life:

• Achieved production efficiency and production losses
• Key contributors to incurred production losses
• Expected number of intervention vessel mobilizations and vessel days, broken down by activity
• Operating costs, revenue losses and through-life NPV impact of subsea failures/activities

The use of this approach also ensures that competing options are evaluated using a consistent methodology, focusing on the difference in predicted performance between options. Comparison of predicted through-life NPV (including incremental capital costs for any additional equipment for each option) allows selection of the optimum configuration or operating philosophy.

Benefits

• Use of dynamic simulation techniques ensures that the predicted performance includes the impact of the operating environment, its maintenance and logistics constraints and any potential changes over field life. Incorporation of all these factors in the analysis results in more realistic performance figures and improves confidence in the predicted values and, hence, in any derived recommendations
• The developed simulation models also incorporate the client's personnel understanding of the asset and the way it operates within their organisation
• Each asset and operator typically have their own specific issues, so the use of an across-the-board standard solution is often not advisable