safely managing the life cycle of pipelines

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Integrity ManagementIntegration vs Aggregation

• safely managing the life cycle of pipelines

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SGA Operating Conference
Integrity Management Integration vs Aggregation
July 19th, 2006
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Objectives

• Characteristics of an effective risk management
  program
• Applications of risk models
• Role of data integration
• Round Table topics
• Data integrity, How do we treat missing data?
• Including PM measures in risk model
• Specific threats SCC, Manufacturing your
  plan?

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Key Concepts

• Risk Assessment
• Formal process of determining the magnitude of
  threats and consequences
• Risk Management
• Process of selecting and implementing activities
  to mitigate risks to the system
• Integrity Management for HCAs
• Risk Results
• More than a number - expected loss to the Company

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Characteristics of an Effective Risk Assessment

• Thorough documentation
• Utilization of operational data and experience
• Accounts for PM activities in assessment of
  risk
• Serves a predictive function in susceptibility
  assessments and trending
• Enables what-if analyses on potential risk
  mitigation activities
• Allows segment / HCAs to be ranked and compared
• Enables sufficient resolution in segmentation to
  support analysis data and identify discrete
  high-risk sites
• Provides adequate basis for assigning defaults to
  missing data
• Does Not
• Predict the time, place or cause of the next
  failure

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Application of risk models

• Ranking HCAs
• Identifying effective PM measures
• Demonstrating the value of all integrity
  management efforts (risk reduction)
• Asset management decision making i.e. replace
  versus repair
• Evolution of model continuing to refine through
  calibration and benchmarking
• Understanding what a 6.2 out of 10 really means

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Validation

• Do the results make sense SMEs
• Is field information supporting ranking
• Field data is collected and feedback into the
  assessment
• Benchmarking and calibration what does a
  specific score mean?

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Data Integration

• Much more rigorous than data merging
• Common referencing system for all data sets
• Understanding data sets relative to each other
• Location of an anomaly (odometer) to a coating
  type (stationing) to a location of a house
  (GPS)
• Historical changes to pipeline centerline
• Synchronize the effects of changes between
  different datasets (i.e. pipe replacement)

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Crossings, casings, repairs, TP
Year, WT, Grade, Seam
Coating Type, Date
MOP, Hydrotest, SMYS
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Case Study

• The data
• Pipe 24 OD, 0.375 wt, X-45, single wrapped
  tape
• ILI Four dents less than 2 on top of pipe, 10
  apart with no metal loss
• Class 1 location in proximity to state HWY
  crossing.
• Ditch for HWY is maintained by state
• SME input is that the ditch was periodically
  cleaned out with backhoe.
• The findings
• Backhoe struck the pipe while clearing the ditch,
  only 6 of cover in the bottom of the ditch.

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Round Table Issues List

• Data Integrity
• How do we treat missing data?
• QC process for data sets
• Data integration how are we doing?
• Risk Treat Assessment
• SCC what is your plan?
• Manufacturing monitoring 5 previous years?
• Establishing a threshold - if scores arent zero?
• Including PM measures in risk model
• Interaction of threats

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General Discussion