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Subsea Processing Systems:
Optimising the Maintenance, Maximizing the Production
Klas Eriksson and Konstantions Antonakopoulos, Aker Solutions
Copyright 2014, Offshore Technology Conference
This paper was prepared for presentation at the Offshore Technology Conference Asia held in Kuala Lumpur, Malaysia, 25–28 March 2014.
This paper was selected for presentation by an OTC program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been
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Abstract
Subsea pumping systems are increasingly used to increase production and extend lifetime of fields. More complex
subsea processing plants are being built, including subsea separation and gas compression.
When rotating equipment is placed on the seabed, the lifetime of such will typically be shorter than the operational
lifetime of the field, such that e.g. a pump will need to be replaced several times. This gives an increased interest in
Condition Monitoring techniques and Condition Based Maintenance, such that such interventions can be planned
in advance.
Gradual degradation of subsea equipment can be monitored, and intervention / replacement thus planned some
time in advance. The actual changeout of a subsea pump module typically takes 24 hours, but the preparatory
work before can take a month. Thus any advance warning will reduce the downtime (and production loss). This
paper describes a generic subsea separation/pumping/compression plant, and discusses some techniques for
Condition Monitoring and Condition Based Maintenance. Some experience from recent projects are presented

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Introduction
Subsea pumping systems and stations are now commonly used subsea, 50+ subsea pumps have been deployed on the seabed.
Subsea compression stations are emerging, and are more complex.
A subsea compressor pilot has been built and operated for a year in a test pit on land for the Ormen Lange filed (15 MW
Compressor), and a subsea installation of 2 x 8 MW compressors is now being built for the Asgard field in Norway.
Subsea systems with rotating equipment will typically NOT operate for 25 years without service (for other subsea equipment,
like e.g. for a subsea well head system, 25 years design life is a typical requirement.)
Typical lifetime for a subsea pump or compressor is in the range 5 – 10 years, depending on how hard it is operated.
Knowing that some maintenance will be required, how do we optimize this in order to maximize the uptime and revenue
stream?
For subsea equipment, service is typically done by swapping a process module with a new one when necessary. Such a module
can weigh 50 tons for a pump module, and 150 tons for a compressor module. An intervention vessel with good crane capacity
is thus needed, and may take some time to find.
The spare module needs to be prepared for use and tested, and one may have to wait for good weather.
3 typical maintenance strategies are:
- Run until it fails (“if it works, don’t touch it”)
- Replace after e.g. every 2 years (this is typically done for aircraft)
- Replace when it is degraded but before it has failed (“just in time service”)
In practice one often uses a mix of these strategies. For my own car, I may:
- Replace the oil filter every 12 months or every 20 000 miles / 30 000 km, whichever comes first (time / runtime
based maintenance)
- If the tire thread wears down to less than 1/16th “ or 1.5 mm, plan tire replacement in a month or so (condition based
maintenance)
- If a rattling sound appears in the front wheel bearing, drive slowly to the nearest garage
We can do a coarse comparison of the cost of the 3 strategies using some typical generic data (the numbers will of course be
different for different fields and configurations, so this just gives an order of magnitude overview).
We assume that:
- It takes 24 hours to change out a module (once the installation vessel is on top of the installation, the module has been
tested and is ready for deployment)
- It takes 1 month to mobilize the spare module, a crew, check that the spare module works, mobilize a vessel with a 50
/150 ton crane, wait for good weather (this is typical data from experience. In some fields it might not be possible to
do any interventions at all for the 6 winter months)
- When a compressor or pump is shut down, the hydrocarbon production is decreased. The lost revenue can be 3
MUSD/day for a subsea compressor, and 0.5 MUSD/day for a subsea pump.
- The cost for the module replacement operation is approximately 3 MUSD (in addition there will be a cost for
repairing the faulty module, but this is not considered in this discussion)
- The lifetime of the pump / compressor is 5 years, i.e. it will break after 5 years operation (this can be less, and it can
be more).
If we “run until it breaks”, then we will get a 30 day shutdown every time. The cost per breakdown then becomes 30 x 0.5 + 3
= 18 MUSD for the pump, and 30 x 3 + 3 = 93 MUSD for the compressor.
Assuming they break after 5 years, the average cost per year then becomes 18 / 5 = 3.6 MUSD/year for the pump and 93 / 5 =
18.6 MUSD/year for the compressor.
If we replace the pump compressor / pump every 2 years (while they are still operating well), the risk for unplanned

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breakdown is greatly reduced. This is the approach taken by the aircraft industry, which has a good record in this area.
As we have a much shorter production stop (1 day instead of 1 month), the cost for each replacement is 0.5 + 3 = 3.5 M$ for a
pump and 3 + 3 = 6 M$ for a compressor. The average cost per year becomes 3.5 / 2 = 1.75 MUSD/year for the pump, and 6 /
2 = 3 MUSD/year for the compressor.
One should point out that there is always a certain risk with subsea interventions; something could get damaged by the
intervention itself. The cost of this risk should be entered into the calculations. The old wisdom “if it works, don’t touch it”
points to this factor.
There is also a cost for refurbishing the replaced compressor module such that it is ready for use, this should also be added to
the calculation for completeness. This has not been included in this simplistic calculation.
IF we are able to detect faults developing a month in advance, then we can do service “just in time”. This is of course a big IF,
and this is the main topic for this paper.
Assuming that this can be done, such that we will be able to see a fault developing a month ahead or more, and plan the
intervention just in time (i.e. after 5 years operation), the average cost then becomes 0.5 + 3 / 5 = 0.7 MUSD/year for the
pump, and 3 + 3 / 5 = 1.1 MUSD/year for the compressor.
Cost per year for the 3 tactics then becomes for a pump
Run to break: 3.60 M$/year
Replace every 2 years: 1.75 M$/year
Replace “just in time”: 0.70 M$/year
So, for a pump system we see here that the potential for cost saving by doing service “just in time” is in the order of 3 M$/year
per pump. If we can see a fault 1 month ahead of time just once, we will gain 15 M$ in reduced deferred production.
The cost per year for the 3 tactics for a subsea compressor likewise becomes:
Run to break: 18.60 M$/year
Replace every 2 years: 3.00 M$/year
Replace “just in time”: 1.10 M$/year
For a subsea compressor system we see here that the potential for cost saving by doing service “just in time” is in the order of
17 M$/year per compressor. If we can just once see a fault 1 month ahead of time just once, we will gain 90 M$ in reduced
deferred production.
From the calculations above, even if they are generic and simplified, we can see that there is a potential for saving costs by
optimizing the maintenance, particularly if one can detect failures some time before the machine breaks down.
This concept is commonly used topside, and is called CBM or Condition Based Maintenance. A simplistic definition (from
www.wikipedia.com ) is
“Condition-based maintenance (CBM), shortly described, is maintenance when need arises. This maintenance is performed
after one or more indicators show that equipment is going to fail or that equipment performance is deteriorating.”
It does not work for everything. Your own car, however well maintained, may always suffer a sudden breakdown on the
highway. However, good maintenance can reduce the risk of this happening, giving a higher average uptime.
Some faults develop slowly over time, and some of these can also be measured such that one can track the degradation over
time. For these types of faults, CBM can be applied.
How fast a machine wears depends on how hard it is driven. E.g. for certain types of bearings the lifetime is related to the
power at which the machine runs. If the machine runs at twice the power, the bearing wears out in 1/8 of the time, and if the
machine runs at half the power the bearing will last 8 times longer. For such a bearing, if the machine runs at e.g. 80% power
instead of 100%, the bearing life is almost doubled.
Conversely, if the machine is run at 120 % power, the bearing life is halved.
So in this case, by monitoring the power at which the machine is run, one can estimate how much lifetime there is left in the
bearing, and when this is down to e.g. 1 month one should consider intervention and replacement.

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This is a typical example of Condition Based Maintenance, or CBM.
CBM is actually used in some cars. Traditionally car service has been interval based, e.g.: “Replace oil filter every 12 months
or 20 000 miles / 30 000 km, whichever comes first”. More advanced cars now have sensors which measure how card the car
is driven, and automatically suggests service intervals based on this.
Figure 1 Condition Indicator in a car
The sample shown above indicates 5 green bars when the car has been newly serviced and is in perfect shape.
The green bars go out one by one. The harder the car is driven, the faster they go out.
When the yellow warning light goes on, the engine oil should be changed within 1 month.
When the red light goes on, the engine oil should be changed immediately (drive to the nearest garage, there is an imminent
risk of engine damage).
So, the whole idea with CBM is to get some advance warning before something breaks down.
This in turn will give us less downtime.
The ultimate goal for CBM is thus “Service just in time”.
In practice, this is not possible for all faults. There will always be instantaneous breakdowns, just as with a car.
It is not always possible to see a fault developing a month ahead of time (but all advance warning is good, 3 days advance
warning means 3 days less downtime).
The terms Condition Monitoring and Condition Based Maintenance are to some extent overlapping. One simple definition is
as follows:
Condition Monitoring = Measuring and monitoring the state of the machine (historic and current data, “Now” and “Earlier”)
Condition Base Maintenance = Using this information to do service “just in time” (extrapolate into “Future” and plan when to
do it)
In practice, one normally uses a mix of strategies. Again using my own car as an example:
- Change the oil filter at least once per year (time based maintenance)
- Change the oil filter every 15 000 km or 10 000 miles (mileage based maintenance)
- Monitor the tire threads, and if the pattern becomes less than 2 mm or 1/16th “ schedule a tire replacement some
convenient day within the next month (CM / CBM)
- If I hear a rattling sound in the front bearing I’ll slow down and drive carefully to the nearest garage (or call a tow
truck) (CM/CBM)
CM/CBM systems have been used topside for many years (a Google search for “pump condition based maintenance” gives 6
M+ results), and are now being deployed subsea by most vendors to varying extents.

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Figure 2 CB/ CBM Pyramid
All CM/CBM systems have similar buildingblocks as sketched above, namely:
- Sensors (to measure a physical property, like pressure, temperature, speed, vibration,…)
- Data acquisition system (to capture the signals into an electronic system)
- Data storage system (to store the signals for some time for analysis)
- Viewing and Analysis capability (for viewing and analysing the stored data)
- Calculation of KPIs (e.g. the efficiency of a pump)
- Prediction of remaining lifetime (time to service)
The lower levels can be called Condition Monitoring, and the higher level Condition Based Maintenance.
Condition Monitoring views current and past state of the machine, and Condition based Maintenance tries to look into the
future and predict when maintenance should be done (preferably a month ahead).
The difficult part is the CBM part. We can (and do) easily log millions of data per second, and store them for months in multi-
Terabyte database (the one for Ormen Lange Pilot and Asgard has a 60 TByte harddisk, which fills up in a month or two).
The hard part is to make sense of the data, and ideally convert it to green, yellow and red lights as we saw for the car indicator
above.
Today we can do this for some degradation mechanisms, of which a few will be discussed further down. However, much
remains to be done in this area.
As we gather more operational experience of such subsea systems, we will learn how to make better use of the logged data for
CM and CBM purposes.
We do not know today how the data we are logging will be used in a few years’ time. But if we never logged it, we can never
analyse it! The cost difference between logging a few data (which you know what to do with) and logging all data (hoping you
may have use for it later) is not that high. Computer hardware is cheap, the main cost is for logging the first data (=setting up
the infrastructure), whether 1 or 1000 data points are logged usually don’t differ much in cost.
A simple approach is thus to log and preserve as much as possible, and actively spend time to analyse it to make more and
more sense of it.
Typical subsea plant pump / compressor
We will discuss a couple of typical subsea plants involving rotating equipment.

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Figure 3 Typical subsea pumping station
In the picture above we show a generic subsea pumping station. It consists of two physical parts, one lower manifold module
(with very few moving parts and sensors) and one upper part with the pump, sensors, accumulators and most valves.
The pump module can be quickly disconnected from the manifold by opening 2 clamp connectors, and can be replaced with
another one in 24 hours.
If the pump fails, the production flow can be diverted around the pump (but will flow at a lower rate).
Figure 4 Ormen Lange Pilot subsea Compressor sketch, process part
In the picture above is shown a typical subsea compression plant (Ormen Lange Pilot). At the inlet is a scrubber which
separates any liquid from the incoming wet gas.

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The liquid is boosted by a pump, and the dry gas is boosted by a compressor.
The high pressure gas and fluid are then recombined and pushed into the flowline.
The compressor has a recycle loop through a recycle cooler, which is used for start-up and for avoiding surge conditions.
Figure 5 Ormen Lange Pilot subsea Compressor sketch, electro system part
For the Ormen Lange pilot, subsea units for Variable Speed Drives (VSDs), High Voltage Circuit Breakers (HVCB) and Un-
interruptible Power Supplies (UPS) were also developed. These are necessary due to the very long stepout (150 km for Ormen
Lange). A VSD must be located within 50-100 km from the motor for stability reasons, so for very long step-outs it must be
located subsea.
The UPS can be located either topside or subsea. For Ormen Lange pilot, a subsea UPS module was qualified. One main
purpose for this is to keep the magnetic bearing powered long enough for a safe coast-down in case there is a sudden power cut
in the HV system on land.
Long distance HV transmission voltage is 132 kV, and is transformed down at the subsea end to 22 kV.
The HVCB module is used for distributing HV power at the 22 kV level to various consumers subsea, and for isolation of
faulty equipment in case of malfunction.
One HV cable can supply enough power to drive 2 complete compressor trains. If there is a malfunction in one, it can thus be
isolated and the other train kept running.

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Figure 6 Ormen Lange Subsea Compressor Pilot in test pit
In the picture above the Ormen Lange pilot station is shown while being installed in a test pit at Nyhamna/Norway, where the
landfall is for the Ormen Lange gas field. It has since then been operated for 1 year +.
For Condition Based Maintenance some kind of performance indicator is needed, which can be tracked and used to predict the
remaining useful lifetime of a component.
Such an indicator (or KPI) needs to be:
- Possible to measure
- We must have an idea at what level of degradation we must replace the component
- We must be able to predict the evolution of the KPI sometime into the future, such that we can get advance warning
(ideally 1 month, but every day of advance warning helps)
Typical monitoring and prediction techniques
We will now go through a few typical examples of wear and tear mechanisms which are suitable for use for CBM.

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Figure 7 Typical KPI concept used for CM/CBM
This picture above is from a simple system used for a subsea pumping system a few years ago. However it illustrates the basic
concept:
- The KPI is plotted over time
- The evolution into the future is estimated (based on knowledge of the underlying degradation mechanism, and fitting
a curve to the observed data)
- An acceptance limit is defined
- The time remaining until the KPI reaches the acceptance limit is calculated
If this is < 30 days, a “yellow alarm” is triggered
If this is < 10 days a “red alarm” is triggered
Figure 8 Typical KPI: Pump lube oil consumption

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One example of such a KPI is for the lube oil consumption in a subsea pumping system. For this particular application, the
lube oil is supplied through a very long umbilical, and due to the high viscosity of this particular lube-oil, only a fairly small
amount can be supplied per hour through the umbilical.
The lube oil leaks from the motor into the process, and this leak will increase over time as the pump seals wear.
By plotting the lube oil consumption over time, one can then estimate fairly accurately how much time is left until the limit is
reached.
(Once the limit IS reached), the overpressure in the motor versus the process will be lost. One can then for a while reduce the
motor speed to compensate, but this will give a production loss).
Figure 9 Typical KPI: Number of active accumulators
For the same pump station, short term variations in lube oil consumption are handled by a bank of subsea accumulators. 4 of
these are required in order to get the required pressure/time characteristics.
Peak demand occurs after a shutdown as the motor cools down, and a large amount of fluid is needed in a short time due to
cool-down and contraction effects. It is not possible to supply the required amount of lube oil fast enough through the
umbilical, so subsea accumulators are required to handle the peak demand.
For redundancy, 8 accumulators are used. One can thus afford to lose 4 of them, but if 5 are lost the module should be
replaced, as the overpressure can then not be held in the motor during a shutdown.
To monitor how many accumulators are operational, a calculation is done every time there is a pump stop (for whatever
reason).
The observed pressure/time curve is compared with several simulated cases (for 8,7,6,… live accumulators) to determine how
many are operational.
Over time, the accumulators may stop working one after one (e.g. through loss of nitrogen pre-charge), and when only 4 are
functional the pump module should be replaced.

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Figure 10 Typical KPI: Power supply quality to motor
The subsea VSDs used for the Ormen Lange Pilot generate a certain amount of harmonics. These are basically converted to
heat in the motor. The allowable amount of harmonics is specified in IEC norms, and the motor lifetime is calculated based on
this.
If the amount of harmonics is higher, the motor lifetime will be shorter.
The VSD has some ageing effects such that the amount of harmonics is expected to increase over time.
When it gets too bad, VSD replacement should be considered.
Figure 11 Typical KPI: Long term logging of THC
For the Ormen Lange pilot, the total amount of harmonic current (THC) is calculated every second and logged as a long term
trend. Above is such a log, One can see that there are large transients during start / stop / speed changes, this is quite normal. It
is the long term trend which should be monitored. As the harmonics exceed the specified limit, the temperature in the motor
windings will increase, and the lifetime of the motor will degrade.

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Figure 12 Typical KPI: Magnetic bearing current
The Ormen Lange and Asgard subsea compressors have magnetic bearings in order to get a longer lifetime before service is
required. 3 radial and one axial bearing are used.
Each radial bearing has 4 magnetic coils and 2 position sensors.
For one coil pair, a plot is shown above of current used in top and bottom coil and the position sensor associated with this coil
pair.
Over time, as the compressor becomes more and more unbalanced, the magnetic coils need to work harder and harder to hold
it centred (i.e. more current is required).
There is a limit to how much current the magnetic bearing control system can generate, so eventually it may get overwhelmed.
Then it can no longer hold the shaft centred, the shaft will hit the backup bearing and the compressor will trip.
Operation may continue at a lower speed, but there will then be a production loss.
By monitoring the current over time, one can track how the available margin decreases over time, and replace the compressor
before the magnetic bearing system is overwhelmed.
To be more precise, the amount of current the amplifier can provide also depends on the frequency. An amplifier can provide
more power at a low frequency than at a high frequency, such that a high order harmonic may overwhelm the amplifier
although there is plenty of power left.
Figure 13 Typical KPI: Compressor head deviation from expected
One more possible KPI to track is the head generated by the compressor.

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For a given flow and speed, a certain head is expected (from the compressor curve measured when the compressor was new).
Over time, as the compressor wears, it will generate less head
Less head means that less gas is pushed through the flowline
This can be compensated for by running the compressor faster. However, if the compressor is already running at max speed,
then a loss of e.g. 10% head means 3 % less flow.
Assuming the compressor gives a production increase of 3 M$ day, a loss of 5 % flow is a loss of 30 x 0.03 * 3 M$/month or
2.7 M$ / month, or 32.4 M$/year.
Considering that the cost of a compressor module replacement is in the order of 6 M$, a head loss of just a few % over a year
can thus justify a compressor module replacement.
There are of course risks associated with subsea interventions, so we are not suggesting to replace the compressor every time
the head drops 1 %. However, this parameter is easy to calculate and track, and can then be used for a cost / benefit discussion
on when to replace the compressor.
Whenever a pump or compressor is started, one can log the vibration while the speed is changing. This
can give valuable information about critical frequencies and other issues. Below are shown some typical
such analysis, one for a pump and one for a compressor.
Figure 14 Vibration signature during pump speed change

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Figure 15 Vibration signature during compressor acceleration
So, looking at the CBM pyramid shown above, what can we do today?
There are qualified sensors available for most parameters of interest. A few are missing, and development programs are
ongoing. This is true e.g. for:
■ Displacement sensors for use inside pump mechanical bearings
■ Sensors for oil droplets in water, liquid droplets in gas, and solids in liquid
Data acquisition systems are available, with high sampling rates (e.g. 10 kHz for Ormen Lange pilot, even higher for Asgard)
Data storage systems (for Ormen Lange pilot approximately 1 M data samples are stored every second, and much more for
Asgard system)
For viewing of data, several software packages are available more or less off the shelf.
For analysis of data, it gets more complex. Some types of analysis are off-the-shelf (e.g. harmonic analysis), but the
interpretation of the data is more complex, and involves equipment expert who understand how to interpret the data. The
algorithms then need to be prepared with a deep knowledge of the equipment involved.
In the area of KPIs, which can be used to look ahead and predict when to do intervention, there are some that are well
understood and useful already today.
There are several more which are in various stages of development, but it in this area that much more work is needed,
component by component, in order to better understand the deterioration mechanism and how this may be observed by sensors
(direct or indirect).
The ultimate goal is to have an indicator for each and every component with green / yellow / red bars as shown earlier, giving
the “time to service” for each one.

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Conclusion
For subsea plants, due to the high cost and long time needed for intervention, it is of great interest to monitor wear and tear
mechanisms wherever possible.
Any advance warning before a breakdown will give a shorter shutdown, and less production loss.
Logging and analysis of data can thus be profitable. “Run until it breaks” is probably not a good idea for subsea rotating
equipment, where the anticipated lifetime is in the order of 5 – 10 years, and depending on how the equipment is operated.
Data logging systems and analysis tools are available right now more or less off the shelf. As much data as possible should be
logged, “If it was never logged, you can never analyse it”.
We don’t know today how we will use the logged data in 5 years’ time, so the simplest option is to log and save everything
(the cost difference between logging 10% of the data or 100 % of the data is not that big).
The missing link is where we turn the data into useful information, i.e. green/yellow/red indicators.
We can do this today for some parameters, and we have ideas under development for 50 more, but much more work is needed
in this area.
Systems like this are already being deployed, especially for subsea pumping and compression stations.
Using such systems will aid in increasing the uptime and production while reducing the maintenance costs.
Acknowledgements
Norske Shell AS