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8/20/2019 Improving Refinery Distillation Operations
http://slidepdf.com/reader/full/improving-refinery-distillation-operations 1/5
8/20/2019 Improving Refinery Distillation Operations
http://slidepdf.com/reader/full/improving-refinery-distillation-operations 2/5
instrumentation, a fundamental process problem
or “custom and practice”
• Second, a reliable mass balance is required for
the unit.
There are a variety of reasons why mass
balance for a unit cannot be achieved and a
systematic exercise needs to be carried out to
identify these.
On a new unit, test runs are generally under-
taken and the mass balancing is done to sufcient
depth to meet the owner’s objectives and todemonstrate that the unit meets its guarantees. At
a later date, or on a unit that has been operating
for some time, when the rener tries to mass
balance the unit and simulate it in a process
simulator, it is often found that there are prob-
lems that need to be addressed.
The rst thing to look at is the instrument cali-
bration to ensure this is correct, as this is the
most common source of errors. This calibration
exercise should look at all the key streams,
2 PTQ Q2 2008 www.digitalrefining.com/article/1000082
including recycles, reux streams, lean oil streams
and offgases, not just the main input and output
streams. These secondary streams are often
neglected, but are important in any simulation
modelling.
The next issue is ow correction for tempera-
ture, pressure and molecular weight or density;
as-measured ow rates need correcting for actual
conditions. This instrumentation would have
originally been set up based on a given set of ow
conditions and standard conditions. This needs
checking and correcting against the current actual
plant operation. This can be very important if,
say, a different feed is being run or different prod-
uct specications are being targeted, as
temperatures and densities can be very different
to the original design. If the DCS is not
programmed to correct for these differences, a
manual calculation needs to be done. Generally,
the gas molecular weight or liquid density usedcan be taken from a daily analysis, selected at a
time when the unit is under stable operation.
The next stage is to cross-check liquid ows
with tank gauging, or preferably tank dips. These
should match the measured ow closely. If it does
not, it may indicate further unresolved problems
with the measurements. Gas ows are more dif-
cult to verify. It is sometimes possible to do
cross-checks by comparing ows between units.
Unfortunately at this stage, the unit may still not
mass balance. This may be due to incorrect basicinstrument installation or the data in the DCS may
have been incorrectly programmed. Even on the
best-constructed units, some of the instruments
may have developed problems over time,
including:
• Calibration errors, thermocouples that have
drifted over time
• Orice plates replaced and incorrectly installed
(wrong way round?)
• Meter ranges which are incorrect for the
current ows• DCS data input errors (wrong data for the
installed instrument)
• Issues that arise during operation with the
levels of instrumentation on key streams, or
instruments which do not remain in calibration
for long.
Many of the problems identied in this process
are easy to correct, and condence is built by
knowing how the unit is operating and under-
standing the mass balance.
Product stripper/vacuum dryer for a hydrodesulphuriser,a typical refinery column to investigate
Courtesy: Foster Wheeler/NZRC
8/20/2019 Improving Refinery Distillation Operations
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Finally, there are issues relating to analysis. In
a renery, the products are usually liquid prod-
ucts and a renery’s laboratories are set up to
analyse these streams very accurately.
Unfortunately, we usually nd that saturated
gas and unstabilised streams are not handled so
well. This is because they are much more dif-
cult to sample and analyse, unless a number of
special precautions are taken to maintain sample
integrity throughout the process. Obtaining a
good analysis of these streams is often the key to
getting a sensible material balance, especially
when looking at specic distillation columns.
With experience, it is often possible to overcome
some of these analysis issues. For instance, with
analysis of the overheads (ie, liquid and gas
streams from a distillation column overhead), it
is possible to cross-match the two using a simu-
lator, and ll in for the condensation losses of
the gas and evaporation losses of the liquid fromsampling and analysis.
Step 2: Steady-state modelling Assuming that the mass-balance issues have
been addressed, the next step is to model the
unit operation on a process simulator. To do
this, it is usually necessary to do a test run.
Ideally, product ows should be measured
against tank dips and extra analysis undertaken
to allow good denition of the product and feed
streams. For instance, with a debutaniser, it isnecessary to know the C
4 and C
5compositions to
simulate sensibly. Normal routine analysis may
just look at C4s and/or the Reid vapour pressure
(Rvp). We have found that in many circum-
stances it is better to dene the feed from
back-mixing the products, rather than trying to
dene and characterise the feed. Also, by using
the products as a basis for the feed, it is easier to
troubleshoot the model results; if you cannot get
out what you put in, the model is incorrect.
Successful simulation of process units is in partdown to good preparatory work and having a
comprehensive and consistent set of data.
Experience then plays a big part in trying to decide
which data may be erroneous. The rst results are
often not very good, so it is usually necessary to
stand back and ask, “Does it all make sense?” as
you try to work out which data may be in error.
This is where experience can really count.
Simple cross-checks of analysis data for dew-
point or bubble-points can often indicate if the
www.digitalrefining.com/article/1000082 PTQ Q2 2008 3
analysis is faulty. This can save a lot of trouble
later. Taking account of the relative sizes of
streams is also important. It is signicant if the
biggest stream is slightly wrong, but if the small-
est stream is slightly out it may be of less
consequence. So, if there is a large difference in
relative size, it is often best to initially assume the
smaller stream is correct.
Another common area where problems are
found is in using ASTM D86 analysis or other
kinds of analysis data, and compensating for inac-
curacies in the initial and nal boiling points. This
results from errors in both sampling, as well from
as the result of the sampling or test method.
In doing a steady-state simulation, problems
with the current instrument-ation are generally
found. Errors in mass-balance-related instru-
ments are usually identied rst in the plant,
because these are checked regularly by the oper-
ators. However, many measurement problemsare only picked up when trying to match detailed
test run data and may have been in existence for
some considerable time. Also, in trying to do a
process simulation of the plant, it is often found
that shortcomings in the plant instrumentation
are identied and additional instrumentation
may be found necessary, which may need to be
added later.
Once an initial plant model has been built, it
can be expanded to include items such as preheat
trains, which can add to the understanding of howexchanger fouling is progressing during a run. It
is important to model and understand all the
bypasses in these systems, and by checking
against control valve openings, it is possible to
ne-tune the model.
Similarly, for the model to be of use in predict-
ing future performance, it must be changed into a
“rating” model. This might include changing
exchangers to include an overall “UA”, or includ-
ing the detailed exchanger conguration to allow
a rigorous model of an exchanger. The columnspecications might also be altered more accu-
rately to reect the column’s actual control
strategy.
Step 3: Analysing plant operationOnce the unit has been mass balanced and simu-
lated, it is possible to analyse and understand
the unit. Plans can be made to evaluate the unit,
and it becomes relatively simple to look at moni-
toring and optimising the unit operation.
8/20/2019 Improving Refinery Distillation Operations
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Daily reviews By using the power of today’s DCS
and management information systems, it is easy
to check the daily material balance, especially if
the laboratory data and tank gauging informa-
tion is also used. Inferential data can be used to
highlight areas where the data may be errone-
ous. Routine daily monitoring can be set up,
looking at the mass-balance closure (identifying
potential instrument problems). Any reductionsin plant efciency are easily picked up by a daily
look at items such as yields, distillation gaps,
recoveries, purities, fouling, pressure drops,
heater and compressor efciencies. Once initially
established, these reports can be easily reviewed
and maintained.
Monthly/annual check-ups It is important to look
at any distillation equipment periodically to see
how it is operating. The operator should look at
what the key operational objectives are and ways
in which the operation could be improved. If theoperation has drifted away from the optimum,
the causes can be investigated and a plan devel-
oped to address the problem. It is at these times
that performing a test run and check simulation
can be of great benet. If the daily monitoring
has been successfully implemented, little extra
work will be needed to collect meaningful data
on an ongoing basis.
Operational issues Depending on needs, it is
useful to revisit plant objectives inside and
outside the unit. The issues
that might be explored
include:
• Energy consumed vs speci-
cations being achieved
— Review of specications
being achieved and whether
this is optimum
• Review of how close opera-
tion is to known constraints
and the potential for
increased capacity or
improved product quality or
recovery.
In today’s business envi-
ronment, nding the
resources to do this can be a
problem. It is in this area
that an engineering, procure-
ment and constructioncontractor can be of assist-
ance. In undertaking a wide
range of revamps, it is experienced in assisting
in doing test runs, simulating plant operation,
identifying problem areas and analysing bottle-
necks. The initial setting up of the system is
another area that offers training and develop-
ment opportunities for younger renery-based
engineers under senior supervision.
Step 4: Advanced controlsOnce the basic regulatory controls are operating
and a mass balance can be achieved, the next
stage could be to investigate and potentially
implement more advanced controls. This can
vary from simple multivariable controls at one
end of the scale to complex supervisory controls
run in a separate computer system, with a proc-
ess simulation being used to reset the regulatory
controls and optimise the operation. These
systems then do the mass balancing and use
either analysers or inferential calculation tomonitor the product specications.
The steady-state process simulation can be
used as the basis for developing the advanced
control system or for developing a dynamic
simulation model for more detailed analysis of
the unit and for use in an operating training
simulator. More sophisticated monitoring can be
performed to look at equipment efciency and
fouling progression.
The extent of advanced controls that are
4 PTQ Q2 2008 www.digitalrefining.com/article/1000082
Agree objectives
Mass balance/test run
Simulate plant
Viability analysis
Estimate (curve type)( 30%)
Develop controloptions
Developupgrade key
option(s)
DevelopMonitoringmethods
Operationalissues
Adjustoperation
Analyzeoptions
Analyzeoperationsregularly
Execution approach
Recommendmodifications
Figure 1 Route map for improving operations
8/20/2019 Improving Refinery Distillation Operations
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implemented will depend on the potential
payback. For example, if a crude oil distillation
unit has frequent changes in crude oil feed, it
will be easier economically to justify supervisory
controls, which can greatly speed up lining out
the operation after a feed change. This could be
the result of:
1 Regular planned blocked ow on a campaign
basis
2 Semi-random changes owing to spot feeds or
the need for special products.
Sometimes, more sophisticated advanced
controls are not justied, and operating stability
and product quality might be better achieved
using multivariable controls and inferential
calculations.
Typical objectives for advanced process control
would be to optimise the plant operation by
simultaneously approaching multiple constraints,
but to avoid tipping points such as column ood,off-spec products and equipment constraints.
These objectives, which align closely with the
overall objectives for undertaking a distillation
efciency initiative, include:
• Maximising feed to a constrained unit
• Optimising product quality (minimising prod-
uct giveaway)
• Maximising production of highest valuable
products
• Operating stability
• Severity or yield improvements.
Step 5: Identifying future value-addedimprovements and revampsHaving pre-invested in all the work that is
needed in getting to a good process model, the
rener is then ideally placed to evaluate possible
process improve-ments and identify potential
process revamps. So, it will be possible to save
time and money in doing the required screening
studies.
It is possible to easily simulate the unit at
higher feed rates and then investigate which
items, such as pumps, are at their limits or distil-
lation column sections that are close to ooding.
Input from equipment specialists is then required
to rate the equipment, look at the plant layout
and prepare a capital cost estimate. This role is
often fullled by a contractor. Alternatively, it is
possible to look at the effects of improving prod-
uct qualities or energy usage on the overall unit
performance, within the current equipment
constraints. By doing this, the rener may be
able to identify potential operational improve-
ments and better controls, which could
potentially be implemented easily and
cost-effectively.
Tailoring of staged route approach With today’s high crude and energy prices, it is
essential to maintain high operational efcien-cies and regularly monitor unit performance.
The staged route map outlined here delivers an
approach that can be tailored to suit individual
needs (Figure 1). It can also be implemented
progressively, with benets being accrued as the
plant model is built and instrumentation issues
are resolved.
Bernard Hagger is chief engineer, refining, at Foster Wheeler
Energy Limited in Reading, UK. He currently specialises in processsimulation. Email: [email protected]
www.digitalrefining.com/article/1000082 PTQ Q2 2008 5
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