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Practical appliction of API 1149 &1155
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Practical Application of API 1149 and 1155
Dan Nagala – UTSIJoey Verret – LOOP LLC
Presentation Overview
LOOP Leak Detection Study BackgroundAPI 1149 OverviewAPI 1149 Application to LOOP PipelineAPI 1155 OverviewAPI 1155 Application to LOOP ProjectConclusions
What is LOOP?
Louisiana Offshore Oil Port! Supertanker offloading facility located 18
miles off the Louisiana coast in the Gulf of Mexico
! 45 mile long 48” diameter pipeline! Underground storage onshore in salt dome
caverns! Delivery to various refineries
LOOP Main Oil LineMarine Terminal
Underground StorageCaverns
FlowTemperaturePressureDensityViscosityAir Temp.
TemperaturePressure
TemperaturePressure
FlowTemperaturePressure
Sea Level
+ 115 ft
- 117 ft
- 1 ft+ 6 ftWater Temp.
Water Temp.
Ground Temp.
21 miles 24 miles
Fourchon BoosterStation
LOOP Pipeline Operations
48 different crude oil typesAPI gravity range of 20 to 50Viscosity range of 2-300 centipoiseBatch temperature range of 62 to 120 deg. F60,000 bbl/hr avg. flow rate (89,000 max)580 psi platform discharge pressureFive 16-in. and two 10-in. turbine metersEach meter is proved twice daily
Leak Detection Study Background
Legacy Leak Detection System! Modest Sensitivity! Frequent False Alarms! Poor Operator Interface! Lack of Analytical Tools
Results: Pipeline Controllers Loss ofConfidence in System
Background
Feasibility Study! API 1149 utilized to
! Project improvement of pipeline leak detection performance
! Justify further investment and investigation! API 1155 utilized to
! Determine actual system performance on the LOOP Pipeline from a set of available systems on the market
API 1149 OverviewTheoretical analysis of detectable leak sizesAttempts to quantify what effects variable uncertainties have on Leak Detection performance based on:! Pipeline physical characteristics! Instrumentation accuracy
Assumes Mass-Balance techniqueMost applicable to steady-state flowAssumes simplistic transient operationsResults can vary based on coefficients used to determine uncertainties
1149 Assumptions
Steady-State Flow! Flow measurement
uncertainty! Pressure and
temperature uncertainty along pipeline
Transient Flow! Additional linefill
uncertainty caused by a specific transient
LD Sensitivity > Flow Measurement Uncertainty+ Linefill Uncertainty
1149 Equation
Observations:! Flow Uncertainty is constant over time! Linefill Uncertainty diminishes over time
(uncertainties due to inaccurate pressure and temperature profiles along the pipeline)
( )2
2out
2in
flowrate pipeline
rateleak
Flowrate Timety UncertainLinefill ty UncertainFlowty UncertainFlow
×∆++≥
1149 Equation
Therefore:! Short-term: LD sensitivity is more dependent on
meter accuracy and the degree you can accurately determine temperature* and pressure along the linefill
! Long-term: LD sensitivity converges to meter accuracy
( )2
2out
2in
flowrate pipeline
rateleak
Flowrate Timety UncertainLinefill ty UncertainFlowty UncertainFlow
×∆++≥
API 1149 Coefficient Comparisons
Leak Detection SensitivityFlow Uncertainty 0.0003 Temp Uncertainy 0.35 Press Uncertainty 2.6
M i ni mum Det ect i on T i me
1149 Tr ansient 1149 Steady State
Leak Detection SensitivityFlow Uncertainty 0.0003 Temp Uncertainy 2.0 Press Uncertainty
2.6
Minimum Detection Time
Det
ecta
ble
Leak
Siz
e
1149 Transient 1149 Steady State
Leak Detection SensitivityFlow Uncertainty 0.002 Temp Uncertainy 0.35 Press Uncertainty 2.6
Mi ni mum Det ect i on T i me
1149 Tr ansi ent 1149 Steady State
Leak Detection SensitivityFlow Uncertainty 0.0003 Temp Uncertainy 0.35 Press Uncertainty 10.0
M in imu m D e t e c t io n T im e
1149 Tr ansient 1149 Steady State
Performance Projection
Legacy leak detection system performance compared to 1149 calculated performance
Leak Detection Sensitivity
Increasing Detection Time
Incr
easi
ng L
eak
Size
1149 Transient 1149 St eady St at e LOOP Legacy Leak Det
API 1155 OverviewStandardized process for the evaluation of Software Based Leak Detection SystemsOff-line model based analysis of leak detection performanceBased on physical pipeline characteristics and actual operating data collected from the pipeline operationsAnalysis limited to a manageable subset of the pipeline network
Process FundamentalsSix steps executed in part by the pipeline company and by one or more software vendors
1. Gather information and define the physicalpipeline characteristics
2. Collect data samples and build case files3. Specify performance metrics4. Transmit information to vendors for evaluation5. Perform data analysis (vendor)6. Interpret vendor results
Step 1. Gather Information and Define the Physical Pipeline Characteristics
Characterize the pipeline! Detailed definition of the pipeline topology through
a keyword oriented definition file! Contains a structured definition of a single
pipeline, network of pipelines or subset of the network
! General Syntax! Keyword, followed by specific information related to the
keyword
Step 1. Gather Information and Define the Physical Pipeline
Benefits:Provides one standard format for pipeline characterization for all vendorsKeyword format is comprehensive and robust
Challenges:Data collection can be time-consumingBooster station configuration was tediousVendor compatible data formats (metering data)
2. Collect Data Samples and Build Case Files
Each data set is defined by two files produced by the pipeline company! Case File - Informational “Read Me” file
containing a description of the operational data contained in the data file and its relationship to the configuration
! Data File - Block or sequentially ordered ASCII text file containing captured (or simulated) data which is representative of actual pipeline operations
! 24 Hours minimum per sample set, 48+ recommended
2. Collect Data Samples and Build Case Files
Challenges:Data collection software requiredIdentifying appropriate operational windowsData integrity! timestamps! correction factors! consistency (system updates)
Leak simulation
Benefits:Only one set of data files is needed for all vendors
3. Specify Performance Metrics
Specification of pipeline company’s desired or expected levels of leak detection performanceGrouped into four performance classifications
• Reliability• Accuracy• Sensitivity• Robustness
Performance Metrics
Consistency of system to alarm actual leaks
Consistency of system to minimize false alarms
Critical to maintain operator confidence
Reliability
Ancillary information such as leak location, leak rate and total volume lost
Important information for notifications and response planning
Accuracy
Performance Metrics
Quantitative measure in terms of detection time versus leak size
Provides a baseline performance curve
Sensitivity
A measure of the leak detection system’s ability to continue to function and provide useful information, even under changing conditions of pipeline operation, or under other less than ideal operating conditions
Robustness
LOOP’s Performance Metric Ranking
4Accuracy
3Robustness
2Sensitivity
1Reliability
PriorityMetric
4. Transmit Information to Vendors for Evaluation
ASCII text files24 hour duration on the averageSix (6) different operational scenariosInternet e-mail used for delivery
5. Perform Data Analysis (Vendor)
Review the configuration, case file(s), and data set(s) prepared by the pipeline companyImport the configuration into their model(s)Tune the model with pipeline data samples Perform studies on all pipeline data sets and casesDemonstrate performance and discuss anomaliesPrepare final report describing analysis results and expected level of achievable performance
5. Perform Data Analysis (Vendor)
Flow rate data spikesProduct identification data
Problems Encountered:
6. Interpret Vendor Results
Visit each vendor to witness application execution! Provides an opportunity for the vendor to discuss analysis
difficulties and data anomalies face-to-face! Helps the pipeline company understand the complexities of
each system under consideration, and to see the application and its analysis tools in action on real data
Conduct visits after the vendor’s draft report is completed, but before a final version delivered
6. Interpret Vendor Results
Simulation runs of each data setDetermine sensitivity across all operational conditions
Interpret Vendor Results
Detection Time
Leak
Siz
e
API 1149
Vendor 1
Legacy System
Vendor 2
Vendor 3
Interpret Vendor Results
Identified system enhancements needed for certain operational conditions! Data timestamps! Meter flow rate calculations! PLC data filtering! Product data requirements! Projected degree of enhanced leak detection
sensitivity for incremental improvements in instrumentation accuracy
Benefits:
Interpret Vendor ResultsVendor Scorecard
Priority Category Vendor A Vendor B Vendor C1 Operator Ease of Use 4 2 32 Maintenance 5 3 33 Performance (Overall) 4 3 5--- Sensitivity 3 3 5--- Accuracy 4 4 5--- Reliability 4 2 5--- Robustness 4 3 54 Ease of Installation 4 3 25 Relative Cost 5 3 2--- Support & Analysis Tools 3 2 4--- Confidence 4 3 4
Totals ------ 29 19 23 Summary of Vendor Ranking Based on LOOP Criteria (5 = Best/Most Desirable, 1 = Worst/Least Desirable)
Final Vendor SelectionAPI 1155 should not be used as a vendor selection and contracting tool because:! Does not contain any project requirements specification! Does not contain any structure for solicitation of bids
Assuming that one or more methodologies are found to be appropriate for the subject pipeline(s)! Define the Leak Detection Project scope in terms of
implementation and delivery requirements! Solicit firm proposals from vendors, select and contract
Final Sensitivity Comparisons
Leak Detection Sensitivity
Increasing Detection Time
Incr
easi
ng L
eak
Size
LOOP Legacy Leak Det 1149 Transient 1149 St eady St at e New LOOP Leak Det
ConclusionsAPI 1149
Aids in the understanding of the effects of instrument uncertainties to leak detectionRelatively quick method to determine a very rough estimate of of mass-balance leak detection performance that can be achieved based on specific pipeline parameters and instrumentationResults can be useful in gaining confidence in vendor estimates of achievable performance
Benefits:
ConclusionsAPI 1149
Only considers leak detection via mass balance techniqueMore applicable to steady-state than to transient operating regimesOnly considers very basic transient estimationResults are based on a theoretical estimation of leak detection based on accumulation of measurement uncertaintiesResults can vary based on coefficients used to determine uncertainties, therefore should only be used as a basis for further, specific leak detection system testing
Shortcomings:
ConclusionsAPI 1155
Standard format for pipeline characterizationData sets represent true pipeline operationCustomer gets demonstrable performance projectionsSubstantial system configuration is complete! pipeline configuration! data
Operations related system enhancements can be identified in advanceProject implementation costs can be more accurately determined
Benefits:
ConclusionsAPI 1155
Pipeline data configuration is time-consumingAmount of work required of vendorsTest execution costly if many vendors are involvedMay not be cost effective for a single pipeline
Shortcomings:
?