transcanada’s risk management system for pipeline ... · 2 pipeline risk & integrity...
TRANSCRIPT
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TransCanada’s Risk Management System for Pipeline Integrity Management
Warren Peterson
Louis Fenyvesi
CORS
March 19, 2009
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Pipeline Risk & Integrity Management Enabler
The PRIME project was started in 1998 to develop a Risk Management process for Pipeline Integrity and the infrastructure necessary to support it.
Through the PRIME project, the following items and processes were developed/acquired:
• Facilities and integrity data model.
• System wide facility data.
• A GIS system.
• PRIME Process: The Risk Management and Decision Analysis process used to develop TransCanada’s Integrity Programs.
• PRIME Risk Models: The Hazard, Consequence, Risk Assessment and Decision Analysis Models used to execute the PRIME Process.
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PRIME Process
The PRIME Process is a risk-based decision making process used to develop and evaluate the majority of maintenance programs:
• MFL In-Line Inspections
• Hydrostatic Tests
• Condition Monitoring Investigations & Repairs
• Discrete Pipe Replacement/Recoating.
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Risk-Based Program Development
PRIME Process Flow Diagram
UnacceptableNot EnoughInformation
Analyze Risks
1. Hazard Identification2a. Consequence Analysis
2b. Hazard Frequency Analysis3. Risk Analysis
Audit Results
Data Management
Risk ControlCondition Monitoring Evaluate RiskAcceptability
Pipeline Surveillance
StakeholderParticipation
Acceptable
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Decision Making Framework
PRIME contains a framework for evaluating risk acceptability that provides:
• Common Goals
• Common Measures
• Common Decision Criteria
…to facilitate decision making
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Pipeline Maintenance Goals
A Risk Management methodology should flow from the goals of a company’s pipeline maintenance program.
Decision Criteria should reflect and be directly traceable to the company’s goals.
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Pipeline Maintenance Goals
TransCanada’s Pipeline Maintenance Goals include:
1. Provide an adequate level of safety to the public and employees.
2. Maintain lowest long-term operating and capital costs, except where there is conflict the above goal.
…among others
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Measures of Safety
Goal: 1. Safety of Public and Employees
Measure: Individual Risk
Individual risk is a measure of the total risk faced by a risk receptor from all potential risk sources measured as an annual risk of fatality.
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Measures of Safety - Individual Risk
Individual Risk can be calculated both for known population and generically.
• Specific population data can quickly become ‘out-of-date’.
• Generic or ‘inherent’ individual risk can be used to establish and maintain a ‘baseline’ level of safety for a pipeline.
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Measures of Safety -Inherent Individual Risk
‘Inherent’ individual risk assumes constant occupation by a single individual on top of the right-of-way.
Main variable is failure frequency.
Each meter of ROW is evaluated independently.
Individual Risk is calculated for each meter (Risk Source) of P/L relative to a specific point on the ROW (Risk Receptor).
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48”
36”
Point on ROW under analysis
Pipe beyond these points do not have an
effect on the point under evaluation.
∫+
−
××=X
X
xFatalityIgnitionx dxRRPPFRiskIndividual ))',((
The sum of the risk from each meter of pipe highlighted gives
the Individual Risk for the point on the ROW below.
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Safety Decision Criteria
Goal: 1. Safety of Public and Employees
Measure: Individual Risk
Decision Criteria: MIACC Land Use Guidelines
MIACC (Major Industrial Accidents Council of Canada) published risk-based land use guideline in the early 1990’s.
Land uses types have been interpreted in the context of pipeline class location definitions.
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Class I Equivalent Class II
EquivalentClass III & IV
Equivalent
Risks exceeding the risk acceptance threshold for the pipeline’s
corresponding class must be reduced to a level below that threshold.
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Safety Decision Criteria
Goal: 1. Provide an adequate level of safety to the public and employees.
Measure: Individual Risk measure of the annual risk of fatality. Inherent risk and risk to known receptors.
Decision Criteria: MIACC Land Use Guidelines define ‘an adequate level of safety’.
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Financial Measures
Goal: 2. Lowest long-term operating and capital costs
Measure: ‘Value Ratio’ VR
Key to achieving low long-term costs is considering both the cost of pipeline incidences and the cost to mitigate risk.
VR generated on a project by project basis.
VR = Risk Reduced ($) / Cost of Project ($)
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Financial Measures -Calculating ‘Risk Reduced’
A pipeline failure can generate a variety of consequences.
• Consequences are measured as:
• A short-term direct financial loss.
• A longer term indirect financial loss.
• Losses to the company or society that are not financial in nature.
• In order to produce the VR measure, non-financial losses need to be mapped to an equivalent dollar loss
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Financial Measures -Calculating ‘Risk Reduced’
Major consequence categories are:
• Direct Financial Impact
• Cost of repair.
• Purchase of linepack.
• Indirect Financial Impact
• Fines
• Proving the integrity or ‘fitness for service’ of the affected pipeline.
• Longer term impact to the company’s image or ability to do business.
• Community or regulatory relationship.
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Financial Measures -Calculating ‘Risk Reduced’
Major consequence categories are:
• Customer Impact
• Financial loss incurred by the customer
• Through-put restriction
• Impact to Firm Service contracts
• Third-Party Impact
• Property Damage
• Court Settlements
• Environmental Impact
• Fines and Penalties
• Site Restoration Costs
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Financial Measures -Calculating ‘Risk Reduced’
The total consequence of a pipeline failure is the sum of the consequences calculated under the previous five categories.
The total failure frequency of a pipeline is the sum of the annual per meter failure frequencies contributed by each applicable hazard.
Risk = Total Consequence X Total Failure Frequency
Units of $/m*yr.
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Financial Measures -Calculating ‘Risk Reduced’
The risk reduction benefit of a pipeline maintenance project requires risk to be calculated for both the ‘as is’ or base case and the ‘after maintenance’ or remaining risk case.
∑ ∑= =−=
m
i mainingti
n
t Baseti RRReducedRisk1 )(Re,1 )(, ))((
m is the affected length of pipe.
n is the number of years over which
the project will have a measurable
benefit.
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Financial Decision Criteria
Goal: 2. Maintain lowest long-term operating and capital costs, except where there is conflict with the first two goals.
Measure: VR
Decision Criteria: VR’s greater than one represent projects whose cost is justified based on an expectation of future aversion of loss.
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Example
Evaluating a 35km NPS 36 Class I pipe.
Analysis Steps:
• Individual Risk is calculated and evaluated against acceptance criteria.
• Projects are identified that mitigate safety risk to an acceptable level.
• Project with most beneficial VR implemented.
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Individual Risk Example
1.00E-08
1.00E-07
1.00E-06
1.00E-05
1.00E-04
1.00E-03
1.00E-02
1.00E-01
1.00E+00
0 5000 10000 15000 20000 25000 30000 35000
Chainage
Individual Risk
These areas exceed
safety criteria and
require mitigation.
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Pipeline Maintenance Options Cost Risk Reduction IPV
Hydrostatic Test $900,000 $5,300,000 5.89
Traps + In-Line Inspection + Digs $2,000,000 $2,300,000 1.15
Pipe Recoating (~5 km) $5,100,000 $2,200,000 0.43
Pipe Replacement (~5 km) $8,700,000 $2,500,000 0.29
Example - Alternative Analysis
The following four options were identified as being able
to reduce the safety risk to an acceptable level.
The VR analysis identifies hydrostatic testing as
providing the greatest risk reduction value.
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Risk Based Decision Framework
This framework for quantitative risk-based decision making provides:
• Consistent decision making
• Clear relationship between company goals, risk measures, and decision criteria
• Prioritizes safety
• Facilitates alternative analysis
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Risk Analysis - Hazard Identification
Focused on hazards that are a relevant to the TransCanada system, including:
• Corrosion
• Mechanical Damage
• Stress Corrosion Cracking
• Geotechnical - Slope Movement
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Corrosion Management
The primary method for addressing the hazard of external corrosion is through MFL In-Line Inspection and Defect Management
• Majority of the system can be inspected
• ILI provides the most accurate information on External Corrosion of any available technique
• MFL data is still an indirect measurement
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Standard Industry Practice
Standard industry practice is to excavate MFL defects based on deterministic depth and failure pressure criteria. TransCanada’s are:
• Depth > 70%
• Failure Pressure < 1.25(MOP)
Deterministic criteria implicitly accounts for uncertainty by increasing conservatism
Goal is to restore original design factor and prevent pipeline incidents
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1.25 x MOP
MOP
0
1
2
3
4
5
6
7
8
9
10
0 50 100 150 200 250 300 350 400
Defect Length (mm)
Defect Depth (mm)
Deterministic Criteria
Pass
Fail
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Probabilistic Criteria
1.25 x MOP
MOP
0
1
2
3
4
5
6
7
8
9
10
0 50 100 150 200 250 300 350 400
Defect Length (mm)
Defect Depth (mm)
Area = Failure Probability
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Calculating Defect Failure Probability
Defect Risk Management Process:
• Probabilistically quantify:
• depth error
• length error
• growth rate
• As applicable
• Identify failure probability through simulation
• Simulation Size Depends on Desired Accuracy
• Assess defect acceptability (Risk Management Process)
{ })Erri i(P(L ,AD (L,W))-P M)1
( ) I /N
i
p Rupture N>
==∑
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MFL Data – Depth Uncertainty
Depth Accuracy: +/- 10% 80% of the time
• Equivalent to a normal distribution with:
• Mean: 0%
• Standard Deviation: 7.8%
• More complex corrosion:
• Standard Deviation: 11%
• As more data is collected for a particular line, these statistics are updated
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MFL Data – Peak Depth Accuracy
0%
25%
50%
75%
100%
0% 25% 50% 75% 100%
MFL Reported Peak Depth
LPIT Measured Peak Depth
Forecast: Fitted Depth Error Distribution
0
1000
2000
3000
4000
5000
6000
7000
8000
-0.437108672-0.248762431 -0.06041619 0.127930052 0.316276293
Frequency
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MFL Data – Length Uncertainty
Length Accuracy: +/- 20mm 80% of the time
• Equivalent to:
• Mean: 0 mm
• Standard Deviation: 15.6 mm
• Also affected by complexity of the corrosion
• Clusters consisting of several boxes:
• Standard Deviation: 22 mm
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501 mm
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Signal Comparison
Estimating corrosion growth critical to determining when currently sub-critical defects will require repair
Corrosion growth rates estimated through a comparison of MFL signal data
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Segmenting Pipeline by Measured Growth
Growth
0
5
10
15
20
25
30
0 20000 40000 60000 80000 100000 120000 140000
Abs. Distance (m)
Growth (%w)
S1 S2 S3 S4 S5 S6 S7 S8 S9 S10S11S12S13 S14 S15 S16 S17
Histogram (S2)
0
10
20
30
40
50
0 3 6 9 12 15 18 21 24 27 30
Bin
Frequency
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Regression Tree Analysis
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Risk Acceptance – Individual Risk Criteria
48”
36”
Point on ROW under analysis –
Assumed constant occupation
Escape Distance: Pipe beyond these points do
not have an effect on the point under evaluation
( ( , '))
X
x Ignition Fatality x
X
IndividualRisk P P P R R dx
+
−
= × ×∫
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Correlation Results – Risk Based Digs
1.00
1.20
1.40
1.60
1.80
2.00
1.00 1.20 1.40 1.60 1.80 2.00
MFL Safety Factor (Relative to MAOP)
LPIT Safety Factor (Relative to MAOP)
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Risk Based Digs - Results
Increased Dig Program
• 27 Defects Deterministic -> 73 Defects Risk Based
Significant Defects Found and Repaired
• 18 Defects Deterministic -> 37 Defects Risk Based
Worst Defect Identified Through Risk Process
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Improving Rupture Frequency Trend1994
1996
1998
2000
2002
2004
Year
Frequency per km*yr
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Pipe Maintenance Program Spending Trend
1998 1999 2000 2001 2002 2003 2004 2005 2006
Maintenance Spending
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Conclusions
The PRIME process resulted in both:
• Significant cost savings relative to the industry standard approach
• Improving reliability and reduced risk exposure relative to the industry standard approach.
Provides a rationale for determining maintenance spending levels and allocating those resources
Provides a mechanism for continuous improvement through the incorporation of new quantitative information.
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Second Generation Pipeline Risk Management Why Upgrade?
Operating Experience
Scope
Regulatory Change
Scientific Advancement
Data Availability
Computing Power
Obsolescence and Support
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Operating Experience
Decision criteria dominated by two types of consequence
High dependence on data
• Physical and spatial attributes
• Maintenance data
• Third-party data sources (ILI, LPIT, Imagery, etc.)
• Industry statistics
Platform dependence is an issue (OS, desktop, network, related apps)
Ongoing technical support burdens
Limited ability to revise and enhance
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Scope
System growth, primarily through acquisitions
Support required for several pipelines in U.S.
Need for liquids pipeline support
Acquisition of off-shore facilities
Greater number of users; differing areas of expertise
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Regulatory Change
Changes to Canadian regulations
Introduction and Changes to U.S. regulations
Changes to Industry standards (CSA Z662 and ASME B31)
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Scientific Advancement
Improvements to existing engineering models
New engineering models
Capitalizing on previous R&D effort
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Data Availability
Electronic access to 3rd party information
Migration of old data
Industry adoption of standardized data structures (ISAT, PODS, etc.)
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Computing Power
Order of magnitude increase in desktop computing power
Order of magnitude increase in server/network throughput
Fewer compromises required
Better tools for development, deployment and support
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Obsolescence and Support
Tools (PERL SDK, Tk, ODBC)
Platform (PERL runtime, Windows XP, IE, Office 2003, Oracle)
Stand-alone versus I.S. support
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Thank you