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					                Experience with
            Data Integration on the
          Alyeska Experience with Data
             Trans Alaska Pipeline
          Integration on Trans Alaska Pipeline




8/11/01                 Data Integration         1
TAPS Background

 800 Mile - Crude Oil Transmission Pipeline
     North Slope to Valdez Alaska
     48 “ Dia. 0.5” wall thickness
     Three Construction Modes to Consider
          376 Miles Conventional Below Ground pipeline
          420 Miles Above Ground to avoid unstable permafrost
          4 Miles Insulated/Refrigerated Buried

 System Startup - August 1977
     24 Yrs of Operation
     2.1 MMBPD Capacity, 1.0 MMBPD Throughput
     Over 13 B bbls transported


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TAPS ILI Background

 TAPS - History of In Line Inspection (ILI)
     Annual Inspections Since 1979
     58 Smart Pig Runs over operating life
     Both UT and MFL wall loss pigs used - UT is now primary tool
     Curvature/Deformation Pigs used
 Predominate Operating Risks Addressed by ILI
     Corrosion
     Settlement/Curvature
     Deformation/Third Party damage -
          During construction and operation




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Experience with Data Integration

  Data Integration Depends on Decisions Required
      Focus on Decision Support not just Data Management
  A Management System needed - to manage changes
  Decisions Based on Risk - Contain Uncertainty
      Decisions depend on defect type
          Corrosion, Dents, Curvature, Interaction of defects
      Decisions depend on pipeline location and data limitations
          High Risk v Normal Risk Locations
      Intervention Criteria Based on Risk
  Interaction with ILI Vendors a Must
  Pig Data Can Be Used to Assess Cathodic Protection

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Data Integration Description
 Oracle Data Base - Intranet Application- By Pipe Joint
    (Contains 105,000)
         Pipe Data - Grade, Thickness, MAOP, Hydrotest data, Bend data, Mode
         Pipe Features - Insulation, Casing, Coating, River Weights, etc,
         Hydraulics Data - Functional MOP
         Pig Data - Corrosion/Curvature/Deformation - Contains Graded, Not Raw Data,
         CP Data - CIS, CP Coupon Data

 Embeds Routine Queries and Decisions
      Corrosion Defect Evaluations, RSTRENG

 Outputs Routine Reports
      Ranking by penetration, bursting pressure, SF, Years to Dig, Etc.
      Integrated Data Displays - GIS not mandatory

 Contains Information needed for Maintenance Decisions

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Management System Elements

  A management system is needed to manage change
      Alyeska Integrity Management System (AIMS) has 5 elements
  Scope & Objectives defined
       Secure, readily accessible environment
      Allows Accurate and efficient maintenance decisions
       Distributes data in a single source
       Maintains a record of decisions made
  Procedures written
      Data Collection, Quality Assurance, Security etc.




8/11/01                        Data Integration                    6
Mgmt System Elements (Cont)
 Accountable Resources - Roles Defined
         Data Base Developer
         Data Base Administrator
         Data Owners, Data Entry
         System Users
         IT Maintenance Support

 Data Management Performance Measures established Based
  on Objectives
 Feedback Processes established
         AIMS Assessment - Improvement of Decision Support Management Plan
         Risk Assessment - Assess risks e.g. bad algorithm, data corruption, human error
         Technology Assessment - Take advantage of new technologies, i.e. GIS
         Compliance Assessment - Adapt to new regulations, new industry standards
         Business Assessment - Strategic planning and budgeting
8/11/01                                Data Integration                                 7
Defect Types and Failure Modes

 Corrosion
     Penetration
     Bursting
 Dents
     Outside Force/Third Party Damage - Top Half of Pipe
     Bottom Half of Pipe -
 Dents w Stress Riser (Metal Loss or Contact with Weld)
 Curvature and Curvature w Corrosion
     Straight Pipe
     Field Bends


8/11/01                      Data Integration               8
Risk Classification Sets Urgency
 Decisions depend on Risk
     Consequences depend on pipeline location
     Data Limitations increase risks (pig data, CP data)
 High Risk Areas - 6 different types
     DOT High Consequence Areas ~ 40 miles
          Locations where leak “Could Affect”
             • Commercially Navigable Waterways
             • High or Other Population Areas
             • Unusually Sensitive Areas - Endangered Species
     Other (Discretionary) High Consequence Areas ~ 20 miles
          Locations “Within”
             • Major Streams or Floodplains
             • Inaccessible Areas

8/11/01                            Data Integration             9
Action Urgency (Continued)

 High Risk Areas (Continued)
     Areas where Pig Performance is Limited ~ 15 miles
          Near Welds, 3D Bends, Slack Line, Wax affected locations
     Active Corrosion Areas - 9 miles
          Statistically Active Corrosion, High projected corrosion
     Areas with Limited Cathodic Protection - 5 miles
          Under Insulation, Shorted Casings, Known Disbonded Coatings
     Notably Corroded Areas - 1 mile
          High Probability of Exceedance, Potential for NAC, SCC, MIC

 Normal Risk Areas - Other areas not designated “High Risk”
     90/800 miles (11%) designated high risk



8/11/01                              Data Integration                    10
Intervention Criterion (Triage)

 No Action - Required
 Intervene - Corrective Maintenance within Year of
  Discovery1 or as required by regulation
     Expose pipe, evaluate defect, repair if necessary
     lower operating pressure
 Investigate - Predictive Maintenance within 3 Years
     Rank Severity based on all available data
     Expose pipe, evaluate and repair in order of Severity Rank
 Note1:
      Discovery Means - Data is available, of sufficient reliability, for an operator to
          clearly determine that intervention is required.


8/11/01                                 Data Integration                                    11
Intervention Criterion (Cont)
                                                 High Risk                                        Normal Risk
    Defect Type                   Investigate                  Intervene                Investigate         Intervene
    Corrosion/Metal Loss
        Penetration          RWT < 65 % NWT             RWT < 60% NWT              RWT < 55 % NWT           RWT < 50% NWT
        Bursting             YTD <= M*Inspct Intvl      PRST REN < 95 % MOP        YTD <= 1*Inspct Intvl    PRST REN < 100 % MOP

    Dent/Ovality
        Top Half             Def > 0.75 in (1.5% Dia)   Fatigue Unacceptable       Def > 0.96 in (2% Dia)   Fatigue Unacceptable
        Bottom Half          Def > 2.88 in (6% Dia)     Fatigue Unacceptable       Def > 2.88 in (6% Dia)   Fatigue Unacceptable

    Dent w Stress Riser      Any Dent w Metal Loss      If no mitigating factors   Any Dent w Metal Loss    If no mitigating factors

    Curvature
        Straight Pipe        Curv > 70 % Kcr            Wave Form > .25 in         Curv > 85 % Kcr          Wave Form > .25 in
                             Delta Curv > 10 %          Delta Curv > 20 %          Delta Curv > 10 %        Delta Curv > 20 %
          Field Bends        Delta Curv > 10 %          Delta Curv > 20 %          Delta Curv > 10 %        Delta Curv > 20 %
                                                        Wave Form > .25 in                                  Wave Form > .25 in

    Curvature w Metal Loss
        Straight Pipe        Curv > 70 % Kcr            SAFE Unacceptable          Curv > 85 % Kcr          SAFE Unacceptable
                             Delta Curv > 10 %                                     Delta Curv > 10 %
                             RWT < 65 % NWT                                        RWT < 55 % NWT
                             YTD <= 2*Inspct Intvl                                 YTD <= 1*Inspct Intvl
          Field Bends        Delta Curv > 10 %          SAFE Unacceptable          Delta Curv > 10 %        SAFE Unacceptable
                             RWT < 65 % NWT                                        RWT < 55 % NWT
                             YTD <= M*Inspct Intvl                                 YTD <= 1*Inspct Intvl


8/11/01                                               Data Integration                                                                 12
Decision Process
                                                                          Decision Criteria
                CDM
                                                                          High Risk Areas,
           Corrosion Data         Vendor
                                                    Pig Data               Defect Types,
            Management          Interaction
                                                                             Intervention
              System
                                                                         Criterion, Min Digs

                                                Current Data

                                                  Start Pig
                     Previous                     Feature
                                                                       Criterion
                       Data                      Evaluation
                                                  Process




             No Action                             Feature
          Document Results                        Exceeds
            Update CDM              No
                                                Investigation
                                                  Criterion

                                                      Yes

          Corrective Action                       Feature
          Document Results                                                  Recommend
                                                  Exceeds
            Update CDM              Yes                          Yes         Corrective
                                                Intervention
                                                                            Maintenance
                                                  Criterion

                                                      No


                                                 Predictive
                                               Maintenance
                                              Ranking Process




           Predictive Action                         Is
          Document Results                                                  Recommend
                                                 Ranking<
             Update CDM             Yes                          Yes         Predictive
                                                Minimum No
                                                                            Maintenance
                                                    Digs




             No Action
          Document Results                                                   Conduct
            Update CDM                         No
                                                                            Maintenance




                                                                             Evaluate
                                                                         Lessons Learned         End
                                                                                               Process




8/11/01                                       Data Integration                                           13
Interaction Needs with ILI Vendors

  Raw data interpretation by
   Operator needed
  Pig Performance assessment
  Routine Coordination w Vendor
  Comparison between Field and
   Pig data

          Pig Run     Type    Begin        End        Deep     Length DEG RWT 85%M RSTRENG
          1998 NKK    UT     3168678.9 3168688.3 3168688.1      4.8    221   362   1004   984
          1997 NKK    UT     3168687.6 3168689.8 3168688.1      26.4   222   335   849    958
          1996 NKK    UT     3168687.5   3168693     3168688    66     226   362   869
    1994 Pipetronic   UT     3168687.6   3168693     3168688    64.8   211   382   905
    1992 Pipetronic MAG 3168687.9 316868802          3168688    3.6    212   370   1025
     Field Analysis          3168687.8 3168691.8 3168688.1      48     216   365   882    954
8/11/01                                  Data Integration                                 14
CP Mitigation Decisions

 Pig Data Can Be Used for more than dig decisions
 Statistically Active Corrosion -
      Based on 100 foot Moving Average Pig Call Depth
      Identifies “Statistically Active Corrosion” (3-10 mpy vs 0-3 mpy)
      May indicate need for CP Mitigation in spite of Good CP Data

 Projected Pig Features -
      “Years to Dig” Projected to determine number of corrosion investigations likely
       in future.
      Economic Model Compares Cost of Corrosion Investigations vs. Alternative
       Maintenance such as Additional CP or Coating Refurbishment.

 Corrosion Data Overlays - GIS like display
      Used to Display Relevant Corrosion Data in one source
      Supports corrosion decision making and planning


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Corrosion Data Overlays




8/11/01       Data Integration   16
Summary - Lessons Learned

 Data Integration Depends on Decisions Required
     Focus on Decision Support not just Data Management
 A Management System needed - to manage changes
 Decisions Based on Risk - Contain Uncertainty
     Decisions depend on defect type
          Corrosion, Dents, Curvature, Interaction of defects
     Decisions depend on pipeline location and data limitations
          High Risk v Normal Risk Locations
     Intervention Criteria Based on Risk
 Interaction with ILI Vendors a Must
 Pig Data Can Be Used to Assess Cathodic Protection

8/11/01                              Data Integration              17
8/11/01   Data Integration   18

				
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