Leak Detection Performance

Leak Detection Performance

Pipeline Safety Trust Conference

November 17 & 18, 2011

New Orleans, Louisiana

Why Leak Detection?

Why Leak Detection? (Contd)

Minimize the volume of lost fluid Reduce risk of fire, explosion or other safety hazards Protect the company

Minimize cleanup costs with an early response to a leak warning

Protect reputation Demonstrable acceptance of responsibility by

executing a proactive leak detection program

Always increasing regulatory interest in pipeline integrity programs; including leak detection

November 17 & 18, 2011Pipeline Safety Trust

2011 Pipeline Safety Conference3

History

Manual pressure/flow readings and evaluation

Voice communication between the field and any center of responsibility that may exist, or with other stations along the line

Familiarity with the pipeline behavior by controllers and technicians was critical

Right-of-way observation including walk-overs and fly-overs were among few leak detection options



Automated Measurements

Proprietary logging systems and SCADA

Transmitter and meter technology

Automation tools and products that acquire accurate information about hydraulic behavior

Tools to assist in evaluating the relationships among measurements



Leak Detection Performance

From the former API 1155 (Evaluation Methodology for Software Based Leak Detection Systems): The system correctly indicates that there is no leak The system correctly indicates that there is a leak The system incorrectly indicates that there is a leak

(false alarm) The system incorrectly indicates that there is no leak

(failure to detect)

Definitions absorbed into API RP-1130 (Computational Pipeline Monitoring for Liquid Pipelines)

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Performance Metrics

Sensitivity – Combination of the size of a detectable leak and the time required to detect it

Reliability – A measure of the system’s ability to accurately assess whether a leak exists or not

Accuracy – The ability of a system to estimate leak parameters such as leak flow rate, total volume lost, and leak location

Robustness – The ability of a system to continue to function during unusual hydraulic conditions or when data is compromised



Meter-Based Leak Detection

Most widely used method on long haul pipelines Requires meters at all entry and exit points Achievable sensitivity limited by meter accuracy Some methods can be implemented in SCADA; or are

options with SCADA products Some products are stand-alone and driven by SCADA data Alarm thresholds must tolerate and expect the imbalance

in meter readings as the line packs and unpacks Leak evaluation algorithms that correlate actual changes

in linepack with meter imbalance provide the best performance



API 1149 Performance Predictions

Predicts the theoretical best performance possible with configured uncertainties No margin for false alarm prevention Temperature uncertainty and related changes in

density during transit is largest influence on performance Not uncertainty in measurement, but uncertainty in

temperature profile along the line One type of leak detection system can more accurately

estimate the temperature profile than other systems



Definitions

Dry Volume – Volume of the pipeline at atmospheric pressure and a reference temperature

Linepack – The incremental quantity of fluid in the line in addition to the dry volume influenced by pressure and fluid temperature Linepack is heavily influenced by temperature’s effect

on fluid density as is pressure, but often to a lesser degree

Profile – Value of a parameter over the length of the pipeline segment



Definitions (cont)

Uncertainty – Potential error in measurements that must be expected and accounted for; also the degree to which something is unknown and must be estimated or assumed based on somewhat related measurements.

Real-Time Transient Model (RTTM) – Accurately tracks fluid temperature/density profiles with consideration of pressure in order to reduce uncertainty in the linepack



Meter Quality vs. Performance

Influence of Meter Quality on Performance

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Detection Time

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Meter-Based Leak Basics

Flow/Pressure/Temperature measurements only at segment end-points

Metered flow accuracy important for high sensitivity

Fluid density (molecules/mass per unit volume) varies significantly with temperature Warm fluid is less dense; Cold fluid is more dense Temperature/density profile uncertainty is the most

limiting factor in leak detection for some pipelines



Volumetric Flow Measurement

Benefits of volumetric (not corrected for temperature and pressure) flow measurement Barrel-to-barrel assessment tolerates differences in

density at injection and delivery points Tolerates switching injection sources of different

temperatures Useful on short lines with small changes in

temperature/density during transmission Not useful where temperature/density profiles are

significant due to heat loss



Net barrel Flow Measurement

Benefits of net (corrected for temperature and pressure) flow measurement Useful for custody transfer Under steady-state conditions, fluid injected at lower

density will balance with delivered fluid at higher density Injections at slightly higher volumetric flow balances

with deliveries at lower volumetric flow Assumes a stable temperature/density profile



Net Flow Measurement Issues

Transient conditions thwart many algorithms involving net flow measurements Line packing and unpacking still result in an

apparent net flow imbalance as with basic volume balance methods

Net barrel flow measurements aggravate simple balance algorithms where a difference in density exists at injection and delivery points except under steady-state stable conditions



Natural Flow Imbalance

Difference in injected fluid density and delivered fluid density Gradual change in fluid density during transit

Temperature/density profiles are poorly understood by most simple algorithms Profile changes shape with changes in flow rate Water crossings and occasionally wet soil increase

thermal conductivity



Meter-Based Leak Detection Limitations

Accounting for changes or disturbances in linepack Operational changes causes the line to pack or unpack

as a normal occurrence Short-term hydraulic disturbances (transients),

including changes in injection temperatures, and their effect on linepack must be tolerated or understood in short-term evaluation algorithms used in rapid assessments

Over extended periods any effects of transients are diluted; thus allowing good sensitivity by most meter-based solutions over long observation intervals



Key Concepts

Pressures and temperatures under steady-state conditions provide current linepack characteristics Divergence of meter readings (greater imbalance) should

be reflected in linepack changes as seen in pressures Transients disturb this information and can lead to

significant short-term linepack uncertainty Over long time intervals any observed variations in

linepack become insignificant compared to the quantity of fluid passing through the pipeline system

Long-term sensitivity settings do not require as much tolerance of linepack uncertainty as do short term leak detection thresholds



Linepack Estimation

Fluid density assumed to be an average of injection and delivery density Weighted average Custom algorithms for curve fitting

RTTM thermal models track fluid density along the line

Change in flow rate alters the temperature/density profile as a new quiescent state develops



Profiles

Temperature Occurs when injection and delivery temperatures differ Subject to heat transfer characteristics of environment Varies with flow rate / transit time

Pressure Varies as batched fluids of different characteristics travel

Varies as batches of different densities travel over mountains

Profiles are accurately tracked by Real-Time Transient Models

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Real-Time Transient Model

Most sophisticated volume/mass balance tool Includes a thermal model to increase the accuracy of

linepack evaluation, thus allowing a shorter detection time for a detectible leak

Tracks heat transfer along the line and develops accurate temperature/density profiles as step changes in flow rates or injection temperatures occur

Allows thermal model tuning to achieve the best performance by modeling the hydraulic behavior accurately

Automatic tuning capabilities Instrument sanity checking



RTTM Myths

Software is expensive Not significantly more expensive

Software requires special skills Training and full technical support is offered by vendors Knowledge of the pipeline physical details is needed

Software requires ongoing maintenance Not needed, once performance is satisfactory, but

further tuning is often performed to continually improve performance

Required if the pipeline network is changed



Static Pressure Testing

Extremely high sensitivity

Zero (0) flow results in zero (0) uncertainty in flow measurement

Works well in a relatively incompressible liquid environment

Requires pressure control equipment



Static Pressure Testing (contd)

Shut in under pressure at near operating pressure Monitor pressure decay for a period of time Drop pressure by half Monitor pressure decay for a period of time A consistent pressure decay rate indicates

decreasing density due to heat transfer A different pressure decay rate indicates a leak

whose rate is pressure dependent



Static Pressure Test Trends



Conclusion

Simple linepack assessment algorithms have a place where linepack is stable and linepack variations and uncertainty do not adversely affect leak assessment

RTTM technology significantly reduces linepack uncertainty in transient environments and enables leak detection approaching the limits imposed by meter accuracy

Static pressure testing is a useful integrity verification tool

Matching the proper tool to the pipeline’s operation is critical



Training & Response

A critical component of any pipeline integrity management program

Response protocol should be included in training and be enforced Controller can shut down the line on any suspicion of

a leak Details regarding actions, reporting, etc. No internal penalty for reasonable judgment

A culture focused on pipeline integrity management is critical



References

API 1130 – Computational Pipeline Monitoring for Liquid Pipelines

API 1149 – Pipeline Variable Uncertainties and Their Effects on Leak Detectability

API 1161 – Guidance Document for the Qualification of Pipeline Personnel

49 CFR Part 192 - TRANSPORTATION OF NATURAL AND OTHER GAS BY PIPELINE: MINIMUM FEDERAL SAFETY STANDARDS

49 CFR Part 195 - TRANSPORTATION OF HAZARDOUS LIQUIDS BY PIPELINE



Contact UTSI

UTSI - U.S. Headquarters

1560 West Bay Area BoulevardSuite 300Friendswood, Texas USA 77546

Telephone: +1 281 480 8786

Fax: +1 281 480 8008

Email: [email protected]

WWW: http://www.utsi.com

Daniel W. Nagala ([email protected])

President & CEO



UTSI - EuropeRaimundo Fernandez Villaverde

43, 6L

28003 Madrid, Spain

Telephone: +34 (91) 534 07 49

Fax: +34 (91) 535 42 57

Email: [email protected] WWW:

http://www.utsi.com

Catalina Frey ([email protected]) Senior Consultant

Daniel W. Nagala ([email protected])

President & CEO

mailto:[email protected]

http://www.utsi.com/



http://www.utsi.com/



Leak Detection Performance

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