Leak Detection(Chapter 17)

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Chapter 17 - Leak Detection

Pipe Line Leak Detection Techniques

•

Causes and economical aspects of leaks• Simple leak detection systems

• Pig-based monitoring systems

• Computer-based monitoring systems

• Pipe line leak phenomena

• Background philosophy of pipe line modeling

• Basic pipe line modeling equations

• Impact of instrument accuracy

• System design aspects and guidelines

• Development of pipe line monitoring systems

Pipe Line Leak Detection Techniques

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R. A. Furness, Cranfield Institute of echnology, Cranfield, Bedford, !", and J. D. van Rett,

Scientific Soft#are Intercomp, $ouston, e%as, !S&

Summar

Pipe lines are no# an integral part of the #orld's economic structure and literally billions of

dollars #orth of products are no# moved annually in pipe lines( Both economic andenvironmental factors are influential in pipe line operation, and therefore integrity monitoring is

vitally important in the control and operation of comple% systems(

)eak detection systems range from simple, visual and #alking and checking to comple%

arrangements of hard#are and soft#are( *o one method is universally applicable and operating

requirements dictate #hich method is the most cost effective( he aim of the paper is to revie# the

basic techniques of leak detection that are currently in use( he advantages and disadvantages ofeach method are discussed and some indications of applicability are outlined(

+odern pipe line computer modeling and control is then revie#ed in detail( hese systems are the

most fle%ible and versatile and are steadily being adopted( he influence of instrument accuracyon system design and performance is discussed and the basic modeling equations are revie#ed(

!ntro"uction

ur need to transport fluids from the point of production to the area of end use has led to a rapid

increase in the number of pipe lines being designed and constructed( +any of these carry to%ic or

haardous products, often close to centers of high population or through areas of highenvironmental sensitivity( .ith the need to safeguard these lines, on-line monitoring is becoming

routine and in some cases /0 hour surveillance is mandatory( .ith the increase in #orld terrorism,

the need for rapid and reliable pipe line measurement and control systems #ill increase(

he revie# begins #ith a summary of causes of leaks and the implications of the failure to detectthem( Basic techniques are covered and the features of each are briefly discussed( he bulk of the

paper deals #ith modern computer-based techniques( Basic flo# equations are covered and the on-

line dynamic calculations required are listed together #ith the input data required to enable themonitoring to be accomplished #ith the minimum of do#ntime( he latest systems are capable of

resolving do#n to 12 of the ma%imum rated flo# #ith a response time of a fe# minutes( Practical

e%perience verifies this figure but the total costs of such a system could be high( he systemtherefore becomes a compromise bet#een response, performance, and alarm availability, and

choice of instrumentation is crucial( he integration of good quality instruments #ith advanced

real time models seems to be the current trend and the paper closes #ith some personal thoughts

on future trends(

Causes and Economic Aspects of Leaks

here are four main categories of pipe line failures( hese are3



• Pipe line corrosion and #ear

• peration outside design limits

• !nintentional third party damage

• Intentional damage

+any pipe lines are operated for a number of years #ith no regard to any possible mechanical

changes occurring in the line( Some of the products may be corrosive, the pipe line may be left partially full for periods of time, or atmospheric effects may cause e%ternal damage( hese threereasons are responsible for pipe line corrosion and this may give rise to corrosion 4pits4

developing along the line( hese are small in nature and could be responsible for material

imbalances over a period of time( 5ery accurate flo# metering can be used to detect this as

discussed in the ne%t section( &brasive fluids or dust-laden gas streams can give rise to pipe line#ear( &gain, this is a slo# process, but should a #eak spot develop 6more often than not close to a

change in direction or section7 then a pipe break may occur very rapidly and totally une%pectedly(

peration outside design guidelines is more common than is realied, as operators seek to use theline for as many fluids as possible( If the line is designed for a certain ma%imum temperature and

pressure, then operation at higher pressure and8or higher temperature could lead to spontaneousfailure( he problem could be compounded if the line has a large but unkno#n amount of

corrosion(

!nintentional third party damage may occur if e%cavation or building occurs near buried lines(

+ore often than not the right-of-#ays are not clearly marked and lines are sometimes broken by

bulldoers or similar plant machinery possibly #ith fatal results( &n e%ample occurred in .est

5irginia in 19:0 #hen a /;-in( natural gas line #as punctured by an e%cavator and product leakedslo#ly into a nearby supermarket during the night( he building #as totally destroyed early ne%t

morning by a massive e%plosion caused by a staff member lighting a cigarette( Such an occurrence

could have been avoided by some form of leak detection on the line(

Intentional damage unfortunately is on the increase and pipe lines carrying flammable or high

value products make ideal targets( &larm systems linked to block valves can help to minimie the

amount of product released as a result of sabotage, so again certain lines are instrumented #ith the

intention of reducing the effects of planned terrorism(

he costs of failure to detect leaks also fall into four main areas3

• )oss of life and property

• Direct cost of lost product and line do#ntime

• <nvironmental cleanup costs

•

Possible fines and legal suits

hese are all self e%planatory, #ith the most costly of these being the last, although any of the fourareas could be very e%pensive( he sie of claims can run into many millions of dollars, so the cost

of fitting and operating leak detection systems is often insignificant compared #ith the costs of

failure of the line(

It is this background that is causing operators and designers to turn to on-line integrity monitoringsystems and the ne%t section of the paper looks at the more basic methods(



Simple Leak Detection Systems

he most basic method of leak detection involves either #alking, driving, or flying the pipe lineright-of-#ay to look for evidence of discoloration of vegetation near the line or actually hear or

see the leak( ften 4unofficial4 pipe line monitoring is performed by people living nearby #ho can

inform the operator of a problem #ith the line(

he most cost effective #ay to detect leaks in non-flammable products is to simply add an odorantto the fluid( his requires some care in selection, as frequently the odorant has to be removed

before the transported fluid can be used( rganic compound make the most useful odoriers,

especially #hen the fluid being carried has no natural smell of its o#n( & good e%ample is carbon

mono%ide, a highly to%ic but odorless gas #hich is often pumped in large quantities bet#eenchemical plants( Chemicals such as mercaptans 6rotten egg smell7 or rimethylamine 6rotten fish

smell7 can be added in small quantities to enable any leak to be located by smell( he disadvantage

of such a method is that if the leak occurs in an area of no population the leak #ill go undetectedunless the line is #alked regularly by pipe line surveillance cre#s carrying suitable 4sniffer4

detectors( hus to the apparent lo# costs of this method have to be added the costs of removing

the odorant and maintain staff to check the line at frequent intervals( he location of a leak is alsodependent on prevailing #eather conditions( Strong #inds may disperse the smell and atmospheric

inversions may given an incorrect location of the leak and the uncertainty of relying on this

method alone is high( *evertheless, it is a useful method if used in con=unction #ith othertechniques(

Simple line flo# balances are frequently used to check for gross imbalances over hourly or daily

bases( his method may identify that a leak is present but flo#meters at each end of the line #ill

not identify the leak location( & line pressure measurement system #ill be required in con=unction#ith the flo#meters to establish that the pressure gradient has changed from the no-leak situation(

he method is useful, ho#ever, in identifying the e%istence of corrosion pits as the outputs of the

flo#meters at each end of the line #ill consistently diverge if flo# in the line is maintainedconstant( If line flo# rate varies #ith time, then imbalances are more difficult to detect, since theflo#meter outputs may vary nonlinearly #ith flo# rate or may have different flo# characteristics

from each other(

& loss of product #ill be identified simply as the different bet#een the steady state inventory ofthe system and the instantaneous inlet and outlet flo#s( +athematically this is3

his last term can be calculated as the average of the integrated inlet and outlet flo#s in simplesystems, but as #ill be seen later in this paper, the value of this term can be calculated more

accurately and easily in real time as a function of several variables(



&nother method is based on detecting the noise associated #ith or generated by a leak( here are

many instances #here fluid flo# can generate vibrations at frequencies in e%cess of /; k$( hesefrequencies are in the ultrasonic range but can be made portable so that pipe line cre#s can clamp

a transducer at any point along the line to check for noise( By noting the signal strength, the source

of the leak can be pinpointed(

& similar technique, though based on a different principle, is the acoustic 4#avealert4 monitor,more correctly called a negative pressure #ave detector( his is a pieoelectric sensor that gives an

output #hen dynamically stressed( .hen a leak occurs there is a sudden drop in pressure at the

leak follo#ed by rapid line repressuriation a fe# milliseconds later( he lo# pressure #avemoves a#ay from the leak in both directions at the speed of sound( he pipe #alls act as a

#aveguide so that this rarefaction #ave can travel for great distances, attenuating in amplitude as

it does so( Sensors placed at distances along the line can be triggered as the #ave passes and the

location of the leak can be calculated from the line conditions and the internal timing devices inthe instrument(

Such devices are particularly useful in identifying large breaks in lines very rapidly, since the

transient #ave typically moves 1 mile in > seconds in gases and almost 1 miles per second inliquids( ?esponse is therefore on the order of a fe# seconds depending on the positioning of thetransducers( @igure 1 sho#s one adaptation #here the instrument can be made to cancel line noise

and use the full measuring capability of the sensor for signal detection( here is the problem

setting the background threshold correctly, as this may be affected by the location of theinstrument in relation to bends, valves, pumps, regulators, etc( <%perience has sho#n that the

installation is also critical to reliable performance, and there is also a dependence on the ?eynolds

number of the flo#( Both of these affect the number of 4false alarms4 from the instrument(

Fi#ure 1. *egative pressure #ave detector 6acoustic monitor7

Pig Based Monitoring Systems



Pipe line pigs are frequently used for pipe line commissioning, cleaning, filling, de#a%ing,

batching, and more recently pipe line monitoring( his last type of pig can be designed to carry a#ide range of surveillance and monitoring equipment and can be used at regular intervals to check

internal conditions rather than continuously monitoring the line( Data, ho#ever, can be built up

over a period of time to provide a history of the line( his information can be used to predict or

estimate #hen maintenance, line cleaning, or repairs are required( If a leak is detected, for

e%ample, by flo# meter imbalance, the location can be found by using a pig #ith acousticequipment on board( his #ill alarm #hen the detection equipment output reaches a ma%imum

and the precise location of the pig can be confirmed by radio transmitters also mounted on board(

Pigs require tracking because they may become stuck, at a point of debris build-up, for e%ample(

Pigging should be carried out at a steady speed, but occasionally the pig may stop and start,

particularly in smaller lines( Information on #hen and #here the pig stops is therefore important in

interpreting the inspection records( Pig tracking is not ne# and many such proprietary systemse%ist( In the best systems, ho#ever, a picture of the line is often programmed in so that outputs

from =unctions, valves, cross-overs, and other geometries act as an aid to location( Pig tracking can

make use of the acoustic methods discussed earlier( .hen the sealing cups at the front of the pig

encounter a #eld, vibrational or acoustic signals are generated( <ach pipe line therefore has itscharacteristics sound pattern( #hen a crack occurs this pattern changes form the no-leak case and

the location can be found from direct comparison( he technology has become so advanced thatinformation on dents, buckles, ovality, #eld penetration, e%pansion, and pipe line footage can be

generated(

he equipment is often simple, consisting of sensor, conditioning, and amplifier circuits and

suitable output and recording devices( Such a device developed by British Aas is sho#n in @igure/( he range of detection is dependent on the pipe line diameter and the type of pig( perational

data have sho#n that light pigs in a /;; mm line can be detected at a range of : km, increasing to

:; km for a heavy pig in a 9;; mm line( &s the signals travel at acoustic velocity this means a

signal from a pig at :; km range #ill take 19; seconds to be picked up( Such technology is no# becoming routine in both offshore gas and onshore liquid lines(

Fi#ure $. 4Intelligent4 pipe line monitoring pig( Courtesy British Aas Corp(

Computer!ased Monitoring Systems



It is in computer-based systems that the greatest amount of data can be gathered, processed,

analyed, and acted upon in the shortest period of time( Programs can calculate the inventory ofthe line at any time and compare this #ith accurate measurements at any section in the system(

he effects of pressure and temperature on line dimensions, for e%ample, can be calculated to

provide an accurate estimate of the mass of fluid in the line( Data from a #ide range of

instruments can be transmitted by telemetry, radio, or phone links to a central computer #hich

monitors the 4health4 of the line continuously( By changing programs and subroutines, a vastamount of functions and tasks can be accomplished very easily and cost effectively(

he many functions that can be performed by computer-based systems include not only leakdetection but also3

• Pig tracking

• Batch tracking of fluids

• Inventory accounting

• n-line flo# compensation

• Instrument data and malfunction checking, etc(

Such systems have very rapid response and have the advantage of multiple inputs being re#ired

before leaks are declared( hus some systems can run for short outage periods #ith no loss of

integrity( hey are often comple% and costly to install but once the initial capital investment has been made running costs are lo#( he first section in the detailed revie# of such systems looks at

the phenomena that need to be modeled #hen a leak occurs(

Pipe Line Leak Phenomena

.hen a leak occurs in a pipe line the measured pressure do#nstream of the leak falls but the

pressure at the same location is predicted to rise( he first is not difficult to understand as the line

is depressuriing as mass leaves through the leak( he second effect can be e%plained as follo#s(he equations presented later in the paper predict pressure based on measured flo# or flo# based

on measured pressure( &s mass leaves the system through the leak hole, a reduced flo# at thedo#nstream end is compared to the inlet flo#( he may not have chanted and so to balance the

system, the equations predict a do#nstream presser rise( In physical terms the model thinks the

line is 4packing4 and total system inventory is increasing( here is therefore a divergence bet#eenmeasured and modeled pressure(

he same is true of flo# changes, but here the inlet flo# could increase due to lo#er pipe flo#

resistance bet#een meter and leak #hile the section outlet flo# #ill fall as mass leave through the

leak instead of passing through the meter( hus a real imbalance #ill result( he model ho#ever

#ill sho# an inconsistency since the pressure comparison #ill indicate line packing and the flo#comparison a line unpacking( If selected pressure and flo# imbalance limits are e%ceeded than

leak is declared( he magnitude of the leak is predicted from the flo# imbalance and the location

from the pressure profile imbalance and the flo# leak indicators( he impact of instrumentaccuracy on the predicted location is discussed later in the paper( It is vitally important to good

leak siing and location to have the best pipe line instrumentation possible to minimie

uncertainty(



Background Philosophy of Pipe Line Modeling

?eal time modeling is a technique that uses the full data gathering capabilities of modern digitalsystems and the computational po#er of small computers to give accurate 4snapshots4 of the pipe

line( he #hole system is under the control of a SC&D& package of programs, #hich poll the data

stations on the line, process the data, control the running of the transient pipe line model and

activate the alarm and leak location routines( In addition to these basic soft#are modules, morecomple% systems might include a predictive model to analye 4#hat if4 operating scenarios,

provide an optimiation route for least-cost operating strategies or include a separate man8machine

interface for the model system(

he SC&D& interface is responsible for acquiring the data from the SC&D& system and relatingthem to the model representation of the line( &s a point in the system #here t#o large and

independently developed systems =oin, this can be the source of many problems in the

implementation of the real time modeling( nce the measurement data have been obtained, noisefiltering and plausibility checking can be performed prior to running of the model( he model is

the mathematical representation of the pipe line and #ill include such features as elevation data,

diameters, valve and pump locations, changes of direction and the location or cross-overs and =unctions( he model provides data on the flo# conditions #ithin the line at intervals bet#een

seconds and minutes, depending on operational needs(

.ith the data available from both the measurement system and the pipe line model, the real time

applications modules are run( hese are the leak detection and location routines in the conte%t ofintegrity monitoring( he leak detection module functions by computing the difference bet#een

the modeled flo#s and pressures and the measured values at tall points #here measurements not

already used as boundary conditions are located( Because the model accounts for normal transientoperations, these differences #ill be small under normal conditions( .hen a leak is present, the

differences become larger since the model system does not account for leakage( .hen these

differences e%ceed preselected values, a leak alarm is declared( Sophisticated voting schemes#hich require multiple leak indicators to be in alarm for several consecutive time intervals areused to reduce false alarms #hile maintaining lo# thresholds( ften a simple pipe line balance of

the type discussed earlier is used as a back-up to verify the transient model( ?esponse

characteristics are, ho#ever, much slo#er than the real time model(

nce the leak detection module declares a leak, the location routine is activated( he location is

calculated from the magnitude and distribution of the leak indicators( &s an e%ample, in a straight

pipe line #ith an upstream flo# discrepancy and a do#nstream pressure discrepancy as leak

indicators, it is an easy calculation to determine #here the leak must be such that the leak flo##hen added to the modeled flo# #ill produce the additional pressure drop observed at the

do#nstream end( Solutions for pipe net#orks are more complicated and unique locations do notal#ays e%ist( his might be the case #ith parallel looped lines, for e%ample( In this case all thecalculated locations should be checked(



The components of the real time modeling system "ork together toreduce the large #olumes of ra" data from the data acquisitionsystem to a much smaller num!er of parameters and alarms thatare more meaningful to pipe line operations$ %n the case ofintegrity monitoring& this means leak e#ents that could not !e

detected !y inspection of the measured data can !e found andisolated quickly and relia!ly$ Basic Pipe Line Modeling Equations

he transient pipe line flo# model is the heart of a pipe line modeling system( he modelcomputes the state of the pipe line at each time interval for #hich data are available( he state of

the pipe line is defined as a set of pressures, temperatures, flo#s, and densities that described the

fluids being transported at all points #ithin the system( hese quantities are found as the solutionto a set of equations #hich describe the behavior of the pipe line system( hese basic equations are

the continuity equation, the +omentum equation, the <nergy equation, and an equation of state(

he continuity equation enforces the conservation of mass principle( Simply stated, it requires that

the difference in mass flo# into and out of a section of pipe line is equal to the rate of change ofmass #ithin the section( his can be e%pressed mathematically by the relation3

he momentum equation describes the force balance on the fluid #ithin a section of pipe line( It

requires that any unbalanced force result in an acceleration of the fluid element( In mathematical

form, this is3

he energy equation states that the difference in the energy flo# into and out of a section equalsthe rate of change of energy #ithin the section( he equation is3

hese three are the basic one dimensional pipeflo# equations are present in one form or another in

all transient pipe models( .hat is needed to solve them, ho#ever, is a relation bet#een the pressure, density, and temperature for the fluid - an equation of state(



he state equation depends on the type of fluid being modeled, as no one equation fully describes

the variety of products that are shipped in pipe lines( Some of the forms in use include a bulkmodulus type of relation of the form3

his is normally used for liquids that can be regarded as incompressible( he bulk modulus B and

the thermal e%pansion coefficient a can be constant or functions of temperature and8or pressuredepending on the application( @or light hydrocarbon gases a basic equation such as P r % ? % %

is appropriate, #here 6the compressibility7 is a kno#n function of temperature and pressure(

@or reasonable ranges of temperature and pressure a function of the form3

may be adequate( @or conditions #here fluids are transported at or near the critical point, a moresophisticated correlation is required to obtain the required accuracy but there is still a large

uncertainty in the true density under these operating conditions and they should be avoided

#herever possible( +any real time systems have been installed on lines carrying ethylene, butane, propane, and )*A8)PA products and have used the Benedict-.ebb-?ubin correlation as modified

by Starling 6commonly called the B.?S equation7 #ith reasonable results( &lternatively, tables

such as *-19 or special correlations such as the *BS ethylene equation can be used, but thisincreases the comple%ity of the programming(

& further complication arises if the product is not uniform throughout the system( his can occurdue to batching of fluids or from varying inlet conditions( he first is more common #here

different products are shipped in a common line( he properties are essentially discontinuousacross the interface of the t#o fluids, but can be considered as uniform #ithin batches( he basic

problem here is to keep tack of the location of the interface( Systems #ith continuous variations in

inlet conditions occur in both liquid and gas systems( he variations can result from mi%ing offluids of slightly different composition or from large variations in supply conditions(

he governing equations presented are non-linear partial differential equations #hich are not

suitable for machine computation( hey have to be solved by implicit or e%plicit finite difference

techniques or the method or characteristics( f these the implicit method seems the most

appropriate, as the other t#o methods could give rise to mathematical instabilities if the #rongtimestep or distance interval is used(

In order for the transient pipe line model to compute the state along the line at the end of each time

interval, a set of initial conditions and a set of boundary conditions are required( he initialconditions specify the state at the beginning of the time interval and are normally the last set of

data from the model( & steady state model must be used to generate an initial state #hen the model

is started from rest, a so-called 4cold start(4 In this case a period of time must elapse before the pipe line model truly represents the actual state of the line( his time period allo#s any transient



conditions present and not represented by the steady state model to die out( Aenerally, less

compressible systems #ill cold start faster than the more compressible ones, but the actual time forthe transient model to be activated depends on the application( his may typically be on the order

of E; minutes for a gas pipe line(

he boundary conditions required by the model are taken from measured data along the line( @or

each point #here fluids enter the system, its temperature, fluid type or composition, and either aflo# or a pressure is required( @or any equipment in the system that affects or controls the line, a

suitable boundary condition must also be given( @or a gas compressor for e%ample, either its

suction pressure, flo# rate or discharge pressure must be specified( &dditional measurements areused by the applications modules, generally by comparing their values to the corresponding model

calculations(

Basic Pipe Line Modeling Equations

he transient pipe line flo# model is the heart of a pipe line modeling system( he model

computes the state of the pipe line at each time interval for #hich data are available( he state ofthe pipe line is defined as a set of pressures, temperatures, flo#s, and densities that described thefluids being transported at all points #ithin the system( hese quantities are found as the solution

to a set of equations #hich describe the behavior of the pipe line system( hese basic equations are

the continuity equation, the +omentum equation, the <nergy equation, and an equation of state(

he continuity equation enforces the conservation of mass principle( Simply stated, it requires thatthe difference in mass flo# into and out of a section of pipe line is equal to the rate of change of

mass #ithin the section( his can be e%pressed mathematically by the relation3

he momentum equation describes the force balance on the fluid #ithin a section of pipe line( Itrequires that any unbalanced force result in an acceleration of the fluid element( In mathematical

form, this is3

he energy equation states that the difference in the energy flo# into and out of a section equals

the rate of change of energy #ithin the section( he equation is3



hese three are the basic one dimensional pipeflo# equations are present in one form or another inall transient pipe models( .hat is needed to solve them, ho#ever, is a relation bet#een the

pressure, density, and temperature for the fluid - an equation of state(

he state equation depends on the type of fluid being modeled, as no one equation fully describes

the variety of products that are shipped in pipe lines( Some of the forms in use include a bulkmodulus type of relation of the form3

his is normally used for liquids that can be regarded as incompressible( he bulk modulus B andthe thermal e%pansion coefficient a can be constant or functions of temperature and8or pressure

depending on the application( @or light hydrocarbon gases a basic equation such as P r % ? % %

is appropriate, #here 6the compressibility7 is a kno#n function of temperature and pressure(

@or reasonable ranges of temperature and pressure a function of the form3

may be adequate( @or conditions #here fluids are transported at or near the critical point, a more

sophisticated correlation is required to obtain the required accuracy but there is still a large

uncertainty in the true density under these operating conditions and they should be avoided

#herever possible( +any real time systems have been installed on lines carrying ethylene, butane, propane, and )*A8)PA products and have used the Benedict-.ebb-?ubin correlation as modified

by Starling 6commonly called the B.?S equation7 #ith reasonable results( &lternatively, tables

such as *-19 or special correlations such as the *BS ethylene equation can be used, but thisincreases the comple%ity of the programming(

& further complication arises if the product is not uniform throughout the system( his can occur

due to batching of fluids or from varying inlet conditions( he first is more common #here

different products are shipped in a common line( he properties are essentially discontinuousacross the interface of the t#o fluids, but can be considered as uniform #ithin batches( he basic

problem here is to keep tack of the location of the interface( Systems #ith continuous variations in

inlet conditions occur in both liquid and gas systems( he variations can result from mi%ing offluids of slightly different composition or from large variations in supply conditions(

he governing equations presented are non-linear partial differential equations #hich are not

suitable for machine computation( hey have to be solved by implicit or e%plicit finite difference



techniques or the method or characteristics( f these the implicit method seems the most

appropriate, as the other t#o methods could give rise to mathematical instabilities if the #rongtimestep or distance interval is used(

In order for the transient pipe line model to compute the state along the line at the end of each time

interval, a set of initial conditions and a set of boundary conditions are required( he initial

conditions specify the state at the beginning of the time interval and are normally the last set ofdata from the model( & steady state model must be used to generate an initial state #hen the model

is started from rest, a so-called 4cold start(4 In this case a period of time must elapse before the

pipe line model truly represents the actual state of the line( his time period allo#s any transientconditions present and not represented by the steady state model to die out( Aenerally, less

compressible systems #ill cold start faster than the more compressible ones, but the actual time for

the transient model to be activated depends on the application( his may typically be on the order

of E; minutes for a gas pipe line(

he boundary conditions required by the model are taken from measured data along the line( @or

each point #here fluids enter the system, its temperature, fluid type or composition, and either a

flo# or a pressure is required( @or any equipment in the system that affects or controls the line, asuitable boundary condition must also be given( @or a gas compressor for e%ample, either itssuction pressure, flo# rate or discharge pressure must be specified( &dditional measurements are

used by the applications modules, generally by comparing their values to the corresponding model

calculations(

%mpact of %nstrument Accuracy

he performance of real time pipe line monitoring systems is limited primarily by the accuracy of

the instrumentation installed on the line( o estimate the performance of the leak detection and

location routines, it is important to under the effect of measurement uncertainty on the model and

the real time applications module( +easurement uncertainty is composed of bias and randomcomponents( he first is usually a fi%ed error bet#een the indicated and true values but this could

change #ith time as components #ear( he second is temporal and possibly spatial fluctuation of

the output about its mean value( @ortunately there are techniques that can be employed #ithin the

soft#are to largely mitigate the effects of bias, but care should be e%ercised as this is not al#aysthe case(

)eak detection and location both use differences bet#een the measured values and the modeled

values to discern leak characteristics( he measured values could contain both bias and8or randomerrors as discussed( he model values, because they are driven by the measured values as

boundary conditions, also include error terms #hich are less obvious( Because of these errors the

difference in the model and measured values, or leak indicators, #ill not normally be ero but #illfluctuate about some non-ero mean( his mean value determined by observation during periods



#hen no leak is present and is attributed to bias errors in the measuring system( By subtracting this

from the leak indicators, the bias component can be eliminated( he leak detection then #ill be afunction of the measurement precision errors(

Problems #ith this technique arise #hen dealing #ith pipe lines #hose operations change

substantially from time to time( &n e%ample #ould be a liquid line operating intermittently( By

monitoring differences in this #ay, the instruments contributing to the error are not identified(Because fluid flo# in a pipe line is governed by highly non-linear relationships, fi%ed errors in the

boundary conditions can cause variable differences in the leak indicators #hen the pipe line

operation changes( &s an e%ample, consider a steady state pipe line that is driven by pressuredifference bet#een upstream and do#nstream boundary points( he leak indicator is the difference

in the measured and modeled flo#( 6*ote that a transient model #ould have a flo# difference at

each end of the pipe line(7 he true value of the data for this pipe line is an upstream pressure of

1,;;; units #ith a pressure drop of 1;; units for a flo# of 1;; units( he model of this system isthen described by the equation3

P1 - P/ ;(;1 F/

If a 12 pressure error is introduced into the upstream pressure, the modeled flo# becomes 1;>

and a difference of > units bet#een measured and modeled flo# #ould sho# up in the leakindicators( &s long as the flo# stays near this value, the error in the leak indicator #ill remain

nearly constant( @or instance, an actual flo# of :; units #ould result in a modeled flo# of :G

units( hus the effects of the bias error in the pressure measurement can be substantially mitigated by subtracting > units from the leak indicator( his is termed the leak indicator 4offset4(

*o# assume the line is shut do#n( he 1; unit pressure measurement error causes the flo# to

compute a flo# of E1 units( &fter applying the offset, the value of the leak indicator still remains

at />( In general, a line that undergoes large and rapid changes in operation #ill be affected by

instrument bias errors( he more common case of lines that operate #ithin relatively narro# bounds, or that change operations slo#ly so that the offset can be automatically ad=usted, #ill only

be affected by the precision error of the measurements(

+easurement errors impact leak detection by limiting the sie of the leak that can be detected bythe monitoring system( he problem comes in finding a threshold value for each alarm in the

system( @or a simple system that operates #ithin narro# bounds, this can be as simple as the offset

previously discussed( he values of the leak indicators 6no# after the offset has been removed7can be observed during normal operation and the appropriate alarm values set( @or more

complicated systems, the thresholds can be set in a more rigorous #ay( he pipe line hydraulic

equations can be used to determine the sensitivity of each leak indicator to the measurement at

each boundary point( he error, #hether bias or precision, of each boundary point can beestimated from kno#ledge of the transducers and the data gathering equipment installed on the

pipe line( he error in the boundary instruments times the sensitivity of the leak indicator to the

boundary point #ill give the threshold required to prevent normal noise in the measurement valuefrom being interpreted as a leak( !sing the root sum square as a result of combining the threshold

for each boundary point #ith the error for the leak indicator's comparison measurement, a

threshold for the leak indicator can be calculated on-line( his 4auto tuning4 of the leak indicatoris found in the more advanced systems commercially available(



&s an e%ample, consider the steady state pipe line used in the earlier paragraph( he sensitivity of

the modeled flo# to the upstream and do#nstream pressures area3

dF 8 dP1 -6dF 8 dP/7 >; 8 F

hus, at a flo# of 1;; units, the sensitivity of the flo# to either pressure #ould be ;(>, #ith a

decrease in the do#nstream pressure being equal to an increase in the upstream pressure( @or a12, or 1; unit error in the pressure, a > unit error in the flo# #ould be e%pected, #hich is

consistent #ith the previous results, he threshold required for this system #ould then be3

his sho#s that the required threshold for the system increases #ith decreasing flo#, #ith leak

detection being impossible at ero flo#( he overly stringent requirement at ero flo# is due to the

simplified model used( ther than that, the results are representative of the manner in #hich theleak thresholds must be ad=usted #hen large flo# variations occur in a pipe line(

+easurement uncertainty affects leak location by increasing the uncertainty in the calculated leak

position( )eaks are located in a line by discovering #here a leak of a given sie #ould need to belocated to best match the observed discrepancies in the leak indicators( Consider our steady state

model again( If there is a leak of /; units half#ay do#n the line so that the flo# is 1/; units

before and 1;; after the leak, then the pressure drop #ould be 1// units( his pressure drop #ouldcorrespond to a modeled flo# of 11;( his #ould result in discrepancies in the leak indicator at

both ends of the pipe at 1;( he leak location for a pressure-pressure boundary condition is given

by3

) % 6F/ 8 F1 H F/7

@or the condition given above, the correct location of half the pipe length is obtained( If, ho#everthe flo#meters have a / unit error such that the upstream leak indicator is 1/ and the do#nstream

indicator is :, the leak is located 0;2 do#n the pipe, and not half#ay( In a 1;; mile line this is an

error of 1; miles #hich is very significant(

.hen evaluating the effect of measurement uncertainty on leak detection or location, it is useful to

compare the uncertainty to the magnitude of the hydraulic events of interest( hus a pressure

transducer that is 12 accurate over a 1,>;; psi span is only E;2 accurate #hen the pressure drop

bet#een t#o closely spaced valve sites if >; psi( his is because the flo# is governed by pressuredifferences and not absolute pressures( )ike#ise a flo# meter that is /2 accurate in comparison to

its span is ;2 accurate for siing a E2 leak(

System Design Aspects and 'uidelines



he availability of leak alarm uptime depends heavily on the system design and the choice of

hard#are( Aenerally the more comple% the system, the greater the risk of leak indicator loss, butthe more accurate the location of the leaks( Design is therefore a compromise bet#een cost,

performance, and reliability( Consider a section of line sho#n in @igure E( @or the three simple

alarms of flo# imbalance, pressure imbalance, and acoustic alarms bet#een stations & and B or B

and C, the follo#ing components are needed3

+ass flo#3 / flo#meters, / pressure sensors, / temperature sensors, / ?!s, / communication

links, 1 computer 611 elements7

Pressure3 0 pressure sensors, 0 ?!s, 0 communications links, and 1 computer 61E elements7

&coustic3 / acoustic monitors, / ?!s, / communications links, and 1 computer 6 elements7

Fi#ure %. Schematic overvie# of pipe line computer-based monitoring system(

If combined hybrid alarms of flo#8acoustic, flo#8pressure, or pressure8acoustic are used then thenumber of components in the chain is increased( By summing the component availabilities for

each element, an uptake for each alarm can be estimated( @or e%ample, a flo#meter #ith a failure

of once in E years #ith a repair time of 0 hours has an availability factor of ;(999:> 6or 99(9:>27(

@rom such an analysis, the conclusion can be dra#n that the system should be made as simple as possible or instruments should be installed in duplicate to ma%imie alarm uptake( Section 9 also

sho#ed that instruments should be selected on performance and not on economic grounds( It is

better to install fe#er high performance instruments than numerous poor ones( Digital conversionalso requires attention( ften 1/ or 10 bit conversion is required to give the necessary accuracy of

data processing and usually double precision computation is also required( he use of standard

outputs should be made #herever possible( Custom designed electronics invariably lead to problems( he best guideline, ho#ever, is to seek users of pipe line monitoring systems to ask

their advice and e%perience #ith instruments and system components( Independent validation of



all information should be made #herever possible( Companies that supply such complete systems

usually have a client list and it is #orth spending time talking to these clients before the finaldesign specification is fi%ed(

.ith regard to instrumentation, flo#meters #ith the highest accuracy are required for mass

balance functions( Suitable types include turbine and displacement meters #ith pulse outputs(

rifice meters are not really suitable, since the best accuracy that can be obtained from a #ellmaintained system is around J12 of full scale( he correct choice of turbine by comparison is

J;(/>2 of reading or better(

De#elopment of Pipe Line Monitoring Systems

he speed of instrumentation development generally is rather frightening( he impact of micro-

electronics is still being felt some ten years after they first appeared, and ne# and improved

transducers #ith on-board 4intelligence4 are being sold in increasing numbers( &t the same timethe sie of computers is decreasing and the computating capability is increasing( Soft#are is also

advancing rapidly and the performance of modern flo# monitoring systems is becoming

dependent on the accuracy of the modeling equations( <quations of state and the behavior ofhydrocarbon mi%tures are not particularly advanced or #ell understood, and fundamental research

is required before the ne%t advance in this type of technology can proceed(

&ll of these points indicate that computer-based monitoring systems #ill become the standard

technique of operating and controlling pipe lines in the future( Control algorithms can beintegrated #ith the applications modules to produce a semi-intelligent complete integrity

monitoring scheme( &s e%perience in the design and operation of such systems gro#s they #ill be

applied #ith increasing confidence(

@uture systems #ill use a combination of the ne# technology discussed( his could includeinternal monitoring pigs and advanced pipe line models, both run from a central control room(

hus the internal and e%ternal state of the line could be checked simultaneously( Such technology

can enable safer and more economic operation of pipe lines to be carried out(

Conc&usion

he paper cannot do =ustice in such a short space, to the comple% and diverse sub=ect of leak

detection( Such systems have been in operation in many forms all over the #orld, but it is only

recently that environmental as #ell as economic factors have influenced their development(+odern digital systems are transforming operation and design, #ith many parallel functions being possible #ith a single system( here is no# a clear need to ensure complete integration of all

components in the system to guarantee safer and more accurate pipe line management( Instrument

selection is critical, as is the need to develop better thermodynamic models, for the ne%t generationof systems to become more reliable and accurate(

Re'erences



1( @urness, ?( &(, 4+odern Pipe )ine +onitoring echniques,4 Pipes and Pipelines

International , +ay-Kune, -11 and September-ctober, 10-1:, 19:>(/( +aillou%, ?( )( and van ?eet, K( D(, 4?eal ime ransient @lo# +odeling &pplications,4

PSIA &nnual +eeting , 19:E(

E( Covington, +( (, 4Pipe )ine ?upture Detection and Control,4 &S+< Paper :-P<->0,

19:(

0( Bernard, A( A(, 4<nergy Balance Derivation,4 C?C Bethany Internal ?eport, 19:/(>( &non, 4Pinpointing pigs in pipe lines,4 R & D Digest , :, 10-1>, British Aas Corporation,

19:G(G( @u=imori, *( and Sugaya, S(, 4& study of a leak detection based on in-out flo# difference

method,4 Proceedings of I+<" Symposium on @lo# +easurement and Control, pp( /;>-

/;9, okyo, Kapan, 199(( Ste#art, ( )(, 4perating e%perience using a computer model for pipe line leak detection,4

Journal of Pipelines, E, /EE-/E, 19:E(

(otation

& - cross-sectional areaB - fluid bulk modulusc - specific heat at constant volume

D - pipe line diameter

<P1 - uncertainty in upstream pressure measurement<P/ - uncertainty in do#nstream pressure measurement

<F - uncertainty in flo# measurement

g - gravitational accelerationh - elevation

) - pipe length

P - pressure

P; - reference or base pressureP1 - section upstream pressure

P/ - pipe line flo# rate

F - pipe line flo# rateF1 - upstream measured vs( modeled flo# discrepancy

F/ - do#nstream measured vs( modeled flo# discrepancy

? - gas constant - temperature

g - ground temperature

) - leak detection threshold levelo - reference or base temperature

t - time

! - heat transfer coefficient

5 - velocity - leak location

% - incremental distance along the pipe line

y - factor correlation coefficient - gas compressibility factor

alpha - coefficient of thermal e%pansion

p - density po - reference or base density

Leak Detection(Chapter 17)

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Transcript of Leak Detection(Chapter 17)