nagala verret 2002

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

QQ

×∆++≥

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

QQ

×∆++≥

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


Mi ni mum Det ect i on T i me

1149 Tr ansi ent 1149 Steady State


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:

nagala verret 2002

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