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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,

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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 

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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

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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.

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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

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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: bernard_hagger@fwuk.fwc.com

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