pipeline leak detection eric penner josh stephens 4/30/09
TRANSCRIPT
PIPELINE LEAK DETECTION
Eric Penner
Josh Stephens
4/30/09
OVERVIEW
IntroductionMethods of
Leak Detection
Cost Comparison
Introduction
WHERE ARE PIPELINES LOCATED?
Roughly 500,000 miles of pipeline in US 300,000 miles of gas
pipeline 200,000 miles of oil
pipeline
About 1.2 million miles of pipeline in the world Russia and Canada are
next two on list with ~250,000 miles and 100,000 miles of pipeline, respectively
DIFFERENT PIPELINE SYSTEMS
SIGNIFICANT INCIDENTS
Significant incidents meet any of the following conditions as defined by the PHMSA Fatality or injury requiring hospitalization $50,000 or more in total costs, measured in 1984
dollars Highly volatile liquid releases of 5 bbls or more or
other liquid releases of 50 bbls or more Any liquid releases resulting in an unintentional fire or
explosion
SIGNIFICANT INCIDENTS 1988-2008
WHAT ARE THE PRIME CAUSES? Excavation damage is the number one cause Most experts regard corrosion as second leading
cause, feeling that a strong portion of those under the “All Other Causes” heading are corrosion related as well
Methods of Leak Detection
HARDWARE LEAK DETECTION
Generally good sensitivity Able to detect large and
small leaks quickly Leak location can be
estimated via instrumentation
Previous two points help minimize environmental and economic impact in event of leak
High level of instrumentation Installation and
maintenance costs can be relatively high
Complex installations Considerable
amount of below surface activity
Pros Cons
IN BRIEF: ACOUSTIC EMISSIONS Method relies on
escaping fluid giving off a low frequency acoustic signal
Acoustic sensors placed around entire length of pipeline to monitor interior pipeline noise Baseline or “acoustic
map” created Deviation from
baseline triggers system alarm
IN BRIEF: VAPOR SENSOR METHOD
Vapor sensing tube placed along entire length of pipeline Tube is permeable
to material being transported
If leak occurs, some material diffuses into tube
Test gas is pumped through and analyzed for vapors of pipeline fluid
IN BRIEF: ULTRASONIC FLOW METER
Generates an axial sonic wave in pipe wall Difference in time for wave to travel upstream and
downstream allows for computation of flow rate Relies on mass flow balance
FIBER OPTIC SENSING: BASICS Probes placed along
pipeline every 0.5 meters
Escaping hydrocarbons change surrounding temperature Liquid leaks ↑ T Gas leaks ↓ T (Joule
Thompson effect) Scattered light
analysis Raman (intensity
based) Brillouin (frequency
based)
Measurement Performance
Sensitivity 50 ml/min
Leak Size Magnitude estimated
Leak Location Within 1 meter
Detection Time 30 seconds to 5 minutes
Cost 1200 km single pipeline
Roughly the distance from Houston to El Paso ~$18 million in equipment costs alone
Figure does not include installation Conclusion: fiber optic leak detection
requires a sizeable upfront investment
PERFORMANCE AND COST
SOFTWARE LEAK DETECTION
- Instrumentation is used to measure internal parameters of the pipeline
- What methods are available?
1. Balancing Systems2. Pressure Analysis3. Generalized
Likelihood Ratio
BALANCING SYSTEMS Basic principle is conservation of mass
Basic line balance does not compensate for changes in line pack due to pressure, temperature, or product composition
Volume balance is an enhanced, automated technique, which does account for line pack correction by assessing changes in volume due to temperature and/or pressure variations using SCADA (Supervisory Control and Data Acquisition)
. .
( ) ( ) 0LI O
dMM t M t
dt
MI MO
Steady State assumed
Stream 1 and 2 measured Discrepancy in flow measurement
WHY PRESSURE MEASUREMENTS?
Sensor 1 Leak Sensor 2
Case 1 0.4 0 0
Case 2 0 0.4 0
Case 3 0 0 -0.4
BALANCING SYSTEMS
Example: 1250 m pipeline Can identify leaks as small as 5% of flow Flow metering at the end of each pipeline
segment will not identify location of leak Cannot distinguish leak from bias Cannot find location of leak Cost: ~ $200,000
MI MO
PRESSURE ANALYSIS How is this implemented?
Pressure indicators segmenting pipeline
Changes in flow produce changes in pressure transients Propagate through the system
until steady-state is reached
SCADA values used to calculate theoretical hydraulic profile or baseline
PRESSURE ANALYSIS
Limitations Not only leaks cause
disturbances in pressure changes (junctions, nodes, bends)
Presence of a leak can be determined from specific deviation or combinations of several deviations
Example: 1250 m long pipeline
Leaks as small as 5% of nominal liquid flow
Located with an error smaller than 5 meters
Cost: ~ $200,000 Cannot distinguish a
leak from a bias
GENERALIZED LIKELIHOOD RATIO Statistical method modeled after flow conditions
in pipeline Mathematical model used that describes effects of
leaks and biases on the flow process Detects leaks in pipeline branch, location in the
branch, and magnitude of the leak. Identifies various types of gross errors
GLR for Gross Error IdentificationProcess ModelSteady state model without leak
is a measurement vector is the true value of state variables is the vector of random error
= constraint matrix
Measurement Bias Model
b is the bias of unknown magnitude in instrument I = is a vector with unity in position i
vxz z
iebvxz
ie
0AxA
Azr
0rE
'AQAVrCov
xv
0 jmbAx
jm
S. Narasimhan and R.S.H. Mah. "Generalized Likelihood Ratio Method for Gross Error Identification." AIChe Journal 33, No.9(1987): 1514-1519.
Process Leak ModelA mass flow leak in process unit (node) j of unknown magnitude b can be modeled by;
the elements of vector correspond to the total mass flow constraint associated with node j
Procedure for single gross error
When there is no gross error;
GLR for Gross Error IdentificationIf a gross error due to a bias of magnitude b is present in measurement I, then;
If a gross error due to process leak in magnitude b is present in node j, then;
When a gross error due to a bias or process leak is present;
let μ be the unknown expected value of r, we can formulate the hypotheses for gross error detection as
Ho: is the null hypothesis that no gross errors are present and H1: is the alternative hypothesis that either a leak or a measurement bias is present.
b and fi are unknown parameters. b can be any real number and fi will be referred to as a gross error vectors from the set F
iAebrE
imbrE
j
i
i
i
m
Aef
where
fbrE
For a bias in measurement i
For a process leak in node j
ifbH
H
:
0:
1
0
mjnimAeF ji ...1,...1:,
GLR for Gross Error IdentificationWe will use the likelihood ratio test statistics to test the hypothesis by:
The expression on the right hand side is always positive. The calculation can be simplified by the calculation by the test statistics, T as:
rVr
fbrVfbr
Hr
Hr
ii
fbii
1'
1'
0
1
5.0exp
5.0expsup
Pr
Prsup
ii
fbfbrVfbrrVrT
j
1'1'
,supln2
b
rVffVfbiii
111
iii
ii
i
ii
fVfC
rVfd
CdT
1'
1'
2
iiTT sup
The maximum likelihood estimate :
Substituting in the test statistics equation and denoting T by Ti:
Where:
This calculation is performed for every vector fi in set F and the test statistics T is:
b
GLRMechanical Energy balance
Without leak
Liquids
Gases
With leak of magnitude b and location lb
Liquids
Gases
)(21 GfPP ),,(21 blbGfPP
Miguel J. Bagajewicz and Emmanuel Cabrera. "Data Reconciliation in Gas Pipeline Systems." Ind. Eng. Chem. Res 42, No.22(2003): 1-11
)(21 GfPP ),,(21 blbGfPP
GLR
Problem formulation
Without Error:
Subject to:
With Error:
Subject to:
So:0,, outiini GG
12~
12~
*)(*)( ii PiiGii
i SPPSGGMin
)(,, GfPP outiini
0,, bGG outiini
),,(,, boutiini lbGfPP
12~
12~
*)(*)( ii PiiGii
i SPPSGGMin
GLR IMPLEMENTATION
Leak detection procedure: Hypothesize leak in every branch and solve data reconciliation
problem
Obtain GLR test statistic for each branch objno_leak –objwith_leak_k
Determine the maximum test statistic objno_leak - objwith_leak_k
We compare the max test statistic with the chosen threshold value: Max{objno_leak – objwith_leak_k}> threshold value: leak is identified and located in the branch corresponding to the maximum test statistic
NOTE: Assuming only one possible error
SAMPLE PIPELINE NETWORK
SIMULATION PROCEDURE - LEAK IN PIPE 1
Calculator
Leak simulated in Pipe 1
Optimizer
SIMULATION RESULTS- LEAK IN PIPE 1
Leak Simulated
Pipe 1
Location(m) 4000
Magnitude(kg/s) 4.915
Measured Flow 15.482
Measured Pressure (KPa) 2420.3
Estimated Magnitude(kg/s) 4.640
Estimated Location(m) 4048
PipeBest
Objective function
1 15.9834
2 18.0199
3 60.4256
4 60.7056
5 21.3695
6 16.8630
7 78.68648 81.06509 123.2020
SIMULATION PROCEDURE - LEAK IN PIPE 8
Leak simulated in Pipe 8
SIMULATION RESULTS- LEAK IN PIPE 8
Leak Simulated
Pipe 8
Location(m) 450
Magnitude(kg/s) 2.611
Measured Flow 4.946
Measured Pressure (kPa) 2160.1
PipeBest
Objective function
1 126.6782 97.4383 101.8644 123.7105 126.4476 126.4477 63.2948 0.1519 159.922
Estimated Magnitude(kg/s) 2.609
Estimated Location(m) 450
GENERALIZED LIKELIHOOD RATIO
ResultsMore accurate to do GLR in Pro II as
opposed to ExcelFor a system with a single gross error, GLR
can distinguish between a bias and a leak Procedure more complex for multiple gross errors
Accuracy of the method increases with increasing magnitude of simulated bias
Cost Comparison
ECONOMIC VALUE Which method is the most economic? Cost = L + P + M + F Where
L is the value of product lost due to leaksP is the value of lost production (ie, that value
of product that would have been shipped if a leak and shut down of the pipeline had not occurred)
M is the maintenance and installation cost of detection equipment
F is the value of fines levied for leaks
CALCULATING L (PRODUCT LOST DUE TO LEAK)
Average leak size PHMSA data provided an average leak size
Adjusted average leak size for sensitivity of detection method Detecting smaller leaks reduces average leak size
Accounted for frequency of leaks being different Detecting smaller leaks results in more detected
leaks
0 10 20 30 40 50 60 70 800
0.2
0.4
0.6
0.8
1
1.2
f(x) = 0.000000046484 x⁴ − 0.00000799418 x³ + 0.000454454 x² − 0.0118664 x + 1.04382R² = 0.992481733299527
Correction Factor for Leak Frequency
Smallest Leak Detected
Corr
ecti
on F
acto
r
0 10 20 30 40 50 60 70 800
200400600800
1000120014001600
f(x) = − 0.0000511551 x⁴ + 0.00903263 x³ − 0.514984 x² + 13.8861 x + 1147.64R² = 0.994198831330397
Adjusted Average Leak Size
Smallest Leak Detected (bbl)
Aver
age
Leak
Size
(bbl
)
CALCULATING L (PRODUCT LOST DUE TO LEAK)
Price of oil and natural gas Difficult to accurately predict either Oil price varied between $40-$80 Natural gas price varied between $4-$12
Clean up costs due to leak included Range from $700 to $5,000 per bbl
CALCULATING P (LOST VALUE PRODUCT TRANSPORTED)
Not the same as leak loss Calculated the value lost via shut down of
pipeline to fix leaks The value of what could have been transported
during that down time Amount flowing through pipeline: API
Recommended best practices
CALCULATING M (MAINTENANCE) AND F (FINES)
Maintenance assumed to be 5% of Base Cost for each method
Fines EPA fines the costliest Cost per bbl estimate
Clean Air Act Clean Water Act Industry examples
This estimate multiplied by leak size under each method to calculate the corresponding fine
METHODOLOGY GLR compared with Ultrasonic, Volume
Balance, and Pressure Analysis Methods Pressure analysis methods grouped together
since there is no significant change in base cost or implementation among them
Excel database created to compare methods Cost of crew, instrumentation, and different
levels of tuning required were taken into account for each model
Various companies were contacted to estimate cost of different detection schemes
METHODOLOGY Simulations were run for varying nominal
pipe diameters 2 to 8 inches for gathering/distribution networks 12 to 24 inches for single pipeline
Multiple scenarios tested for each Range of values used for price of oil, natural gas,
and for leak clean up Pipeline length varied from 0.1 to 10,000 miles Time for repair of leak assumed to be the same
for all methods
6” Nominal Diameter: Oil
20” Nominal Diameter: Oil
20” Nominal Diameter: Natural Gas
Example 8000 mi pipeline ~ $1 million in cost
difference between Ultrasonic and GLR
CONCLUSION
GLR showed to be the most economic for both single pipelines and gathering/distribution networks This held true for oil as well as natural gas GLR shows more separation from the other
methods in the case of oil, due to the higher product value
Implementing GLR results in less fines and less lost production
QUESTIONS
HARDWARE COMPARISONMethod Power Size
Estimate of Leak
Location Smallest Leak (gas)
Smallest Leak
(liquid)
Response Time
Acoustic Emissions
1 false alarm / year Not provided +/- 30 m
Hole 2-10% of pipeline
dia.
1-3% nominal flow of pipeline
15 seconds to 1 minute
Fiber Optic Sensing
Reportedly no false alarms
Indicates whether leak is large, medium,
or small1 m 50 ml/min
30 seconds to 5 minutes
Vapor Sensing
Reportedly no false alarms
Indicates whether leak is large, medium,
or small
0.5% of monitored
area 100 l/hr 1 l/hr 2-24 hours
Ultrasonic Flow Meters
Reportedly no false alarms
Indicated by difference in
mass flow measurements (0.15% nominal flow smallest)
Known to be
between two
ultrasonic meters
0.15% of nominal flow Near real time
CORROSION PREVENTION Corrosion-related cost to the pipeline industry is
approximately $5.4 to $8.6 billion annually Cathodic protection is required on all interstate
pipelines and has been for decades Technique uses a constant low voltage electrical
current run through the pipeline to counteract corrosion – corrosion can create a galvanic cell
Pipeline coating is the other common corrosion prevention
PIGS AND SMART PIGS
• Pigs are cylinder shaped plugs of the same diameter as the pipe
• Smart pigs are fitted with electronic sensors that can help locate pipeline wall weaknesses prior to a leak appearing
• Both scrape build-up off the interior wall of the pipeline, which also helps prevent corrosion
TRANSIENT FLOW Advanced fluid mechanics
and hydraulic modeling are used to simulate pipeline internal conditions
How is this implemented? Pressure and flow
measurements input to simulation
Pressure-flow profiles created
Predicts size and location of leaks by comparing measured data to predicted data Detectable leaks were
greater than 2% for liquid and 10% for gas