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Petrobras of Brazil, an integrated energy producer, has signed a contract with Rovsing Dynamics for an advanced monitoring solution for its P43 floating production storage and offloading (FPSO) unit.

The cooperative project is intended to optimise production output of the P43 unit at Petrobras’s mature Barracuda deepwater field in the Campos basin: Brazil’s biggest oil reserve, accounting for nearly 84 per cent of the country’s oil production.

To identify unexploited business potential, Rovsing Dynamics and Petrobras initially conducted an analysis to assess: the most important economical risks; the main downtime contributors; and any opportunities to further expand condition-based maintenance.

Jose Antonio Figueiredo, executive manager at Petrobras, said: ‘With support from Rovsing Dynamics, we identified several improvement areas for our P43 FPSO and a significant potential to increase revenue and reduce risk and cost.

‘To achieve higher machine availability and increased efficiency, we will, in 2009, implement advanced, predictive monitoring of our most critical production assets.

‘The project is an important element in our strategy to grow oil-and-gas production sustainably and to be recognised for world-class excellence in exploration and production operations,’ he added.

The analysis identified three mission-critical production systems to be monitored by Rovsing’s Openpredictor monitoring solution: four water-injection pumps, each with an equivalent oil production capacity of 50,000 barrels per day, which are crucial for oil production; three centrifugal compressors for the compression of natural gas; and four gas-turbine generators with a capacity of 20MW each, which provide power for the installations on the FPSO.

The project includes a failure-mode effect analysis (FMEA) on downtime and economic risk.

This is facilitated by Dutch company Maxgrip, which specialises in all facets of maintenance and reliability engineering work processes.

The outcome of the study will be: business objectives with risk thresholds; a set of failure modes for the considered system, including mean times in between failures and mean times to repair; classification of critical and non-critical failure modes with corresponding effects per business objective; and an integrated (user-oriented) solution.

Different monitoring types will be applied to assess the electrical, mechanical and performance condition of the machines to assess future business risk.

Advanced online condition monitoring will assess machinery condition and will automatically warn about changes in the dynamic behaviour of critical machines related to short-term operational risk and long-term maintenance.

Performance deterioration is continuously monitored to assess future capacity reduction.

Early warnings and forecasts are intended to facilitate better planning of overhauls and cyclic maintenance.

The FMEA analysis gives input to Openpredictor’s reliability monitoring module, which provides statistics on machine downtime, reliability, availability and utilisation.

Decision makers use such key performance indicators to identify non-performing assets and to prioritise maintenance based on historic and future downtime assessment.

Openpredictor integrates signals and data from several subsystems such as vibration protection devices, partial discharge monitors, local control systems and data historians.

Partial discharge monitors of the electric motors and generators are supplied by Swiss company PDTech to identify insulation deterioration between high-voltage windings.

Openpredictor also analyses offline vibration measurements from non-critical machinery, obtained with a new type of handheld data collector, developed by French company Impedance, and providing on-the-spot fault analysis.

Remote monitoring will enable turbine specialists at Petrobras’s headquarters in Rio de Janeiro to effectively support field operation.

Henk Smith, director of Rovsing Dynamics, said: ‘Openpredictor provides one common interface with information distribution and prioritisation to operation, maintenance and management.

‘As part of the delivery, we will also develop a training and knowledge exchange programme for the Petrobras University.

‘Openpredictor performs fully automated interpretation of machinery fault symptoms [Autodiagnosis] with early warnings and prediction of lead time to inspection.

‘This is a cost-efficient way to provide Petrobras’ operation and maintenance staff with insight into actual and future machinery health.

‘The vital information from the integrated, predictive monitoring solution will facilitate a significant improvement of the availability and efficiency and result in operational excellence at P43,’ he added.

Increased machine availability, such as process uptime, by one to two per cent is typically achieved through: a reduction of unscheduled downtime as a result of fewer trips and faster start-up after trips; a reduction of scheduled downtime owing to fewer inspections and optimised maintenance planning (clustering of activities); and a focus on avoiding re-occurring problems, which mostly contribute to the downtime.

An efficiency/capacity improvement of 0.5 per cent to 1.0 per cent will typically be achieved by: planning overhauls and cyclic maintenance (compressor wash, filter cleaning/exchange and so on) for the best economic moment; balancing production loss owing to deterioration/fouling with the loss a result of standstill and market demand; optimising machinery work point and losses as a result of bleeding, leakage and recycling; and choosing the most efficient production units in case of redundancy.

Overall benefits from higher availability and efficiency include: increased production output at the same cost level; reduced energy consumption and emissions per produced unit; and less flaring and image loss.

Rovsing Dynamics

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