Hybrid Systems for Pipeline monitoring Leak Detection

ICEPIM 2015International Conference on Pipeline Integrity management

Hybrid Systems for Pipeline monitoring & Leak y y p gDetection

K V Siva Rao, Vice PresidentM.S.R.K. Bose, Project ManagerEnergy Solutions International

Introduction

RTTM f Pi li I i M i i• RTTM support for Pipeline Integrity Monitoring

• RTTM methodology

• Other Leak Detection Methods• Other Leak Detection Methods

• Best Fit of the Methods

• Hybrid Leak Detection Systemy y

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Pipelines – lifelines of energy security of India

• 15,340 km Gas pipeline, 14,083 km product pipelines and 9460 km crude pipelines [ PPAC R t J 15]9460 km crude pipelines [source: PPAC, Report Jan 15]

• Growing concerns over pipeline safety

• Loss of integrity by ways of leaks

• Leaks can be due to third party interference, joint failure, pipe material failure, ground movements, etcmaterial failure, ground movements, etc

• What ever the reason, leaks to be detected timely for


immediate action

RTTM support for Pipeline Integrity monitoring

• Leak Prevention with advanced features (Look Ahead and P di i M d l )Predictive Models)

• Leak Detection and Location with state of the art transient model based methodsmodel based methods

• Leak Mitigation – minimizing the consequences of a leak by prompt and clear detection and location

• RTTM significantly helps to improve pipeline integrity


RTTM based leak detection method

• Real Time Transient Model

• Recognized as most sophisticated method

• Proven track record to support pipeline integrity monitoring

• Vital support to operation & maintenance

• Extended Applications more than just a leak detection system


How Does an RTTM support pipeline control room

Step 1. Create a mathematical model of the pipelineStep 2. Get field data from SCADAStep 3. Run a Real-Time simulation of the pipelineStep 4. Real-time model provides operational overview and alarmsStep 5. Use Real-Time state to run a look-ahead simulationStep 6. Use Real-Time state to run predictive simulationsStep 7. Use Predictive model + Nominations to analyze feasibilityStep 8. Use Trainer model to train operatorsp p ppp p pp p ppp pp y yp p

Graphical

Q

P

pConfigurator

Real-TimeSCADA Real-time data Real Time Look-Ahead

LeakDetection

Real TimeDatabase

SCADA Real time dataModel

Look AheadModel

PredictiveModel

Scenario

PT

QPT

QS

TrainerModel

NomsModel

Nominations

Scenario


ModelScore

How does an RTTM detects leak?

Leak Detection and LocationPR

Qin

(model)Driven by P and T Measurements

Q(measured) Qout

(measured)The Volume Balance (VB) is calculated as:

VB = FB – PRwhere,

VB = Volume Balance (m^3/hr)VB = Volume Balance (m^3/hr)

FB = Flow Balance (m^3/hr) (Qin – Qout)

PR = Packing Rate (m^3/hr) (Model)


RTTM LEAK DETECTION ‐ Flow Balance (FB)

Qin (measured)

Qout(measured)

FB = Qin – Qoutwhere,

FB = Flow Balance (m^3/h)

Qin = Measured INFLOW (m^3/h)

Qout = Measured OUTFLOW (m^3/h)Qout = Measured OUTFLOW (m^3/h)


RTTM LEAK DETECTION – Packing Rate (PR)

PR(calculated by the model based on pressure measurementspressure measurements, temperature measurements, and fluid properties)

PR (m^3/hr)Packing Rate means how much volume (m^3) is added or removed from a pipe segment, during a time period (hr). It is evident that under steady flow conditions PR should be 0, since volume remains constant


Statistical Line Balance method (SLB)

• Application of statistical analysis to the accumulated product gain/loss (imbalance)gain/loss (imbalance)

• Accumulation of flow measurementsAccumulation of flow measurements

• Balancing of net metered volume over a period of time

• Time integral of flow balance


Instrument Deviation Analysis (IDA)

• Rapid detection of large leaks (ruptures)

• Analysis of instrument measurements

• Doesn’t rely on real time model

• Can run independently parallel to other methods


P ‐Wave

• Detects negative pressure wave produced by a leak

• Requires high frequency sampling of pressure transmitters

• Leak location from time of arrival of pressure wave at each end

• Signal acquisition must synchronized


Summary of Key Leak Detection Methods

• Real time transient model (RTTM)– Sophisticated system modelling hydraulic changes in the line andSophisticated system modelling hydraulic changes in the line and

recalculating change in pack at each time step compared to volume balance

• Statistical Line Balance (RTTM + SLB)Statistical Line Balance (RTTM SLB)– It is a Compensated Volume Balance leak detection methodology that

applies statistical analysis to the accumulated product gain/loss (imbalance) within the pipeline system.

• Instrument Deviation Alarms (IDA)– Uses changes in measured pressure and flow to evaluate and detect

leaks.

• Negative pressure wave (PWAVE)– Monitors pressure at various points available via the SCADA and uses

event detection to correlate a leak


e e t detect o to co e ate a ea

Best Fit

Technique Suitability Requirements

Hi fidelity leak detection

Theft Detection

Flow, pressure and temperature at various points

Good data backbone

Real Time Transient Model

Theft Detection

Lines where the RTTM is implemented to support operations.

Good location

Good data backbone

Fluid property data

Detailed configuration

Detailed tuning

Statistical Line BalanceLeak detection for challenging conditions

Small leaks over long time periods

Measurement of flow in and flow out

Good data backbone

Flow measurementRate of change alarms Rapid leak detection, no location

Good data backbone

Instrument Deviation AlarmsRapid Rupture Detection without accurate location

Flow, pressure and temperature at various points

Good data backboneInstrument quality monitoring required

Detailed tuning

Fast leak detection

Secondary LDSPressure sensors at various points via the SCADA/DCS


PWAVE Very good location

Rapid Rupture Detection without accurate location

Location in shut in conditions

SCADA/DCS

Good data backbone

Hybrid Leak Detection System

• Single leak detection solution insufficient in certain regionsSingle leak detection solution insufficient in certain regions

• The industry is looking to check all the boxes

– Sensitivity, Reliability, Accuracy, Robustnessy, y, y,

• Hybrid leak detection

– In simplest form multiple systems with separate alarms

– In a more complex form integration of multiple systems

• Each type of system has advantages and disadvantages

– Benefits when CPM systems integrate with internal methods

– Benefits when integrated with third party external solutions


Correlation of two leak detection systems

9

10

Imbalance B exceeded threshold but imbalance A is

Both imbalances exceeded threshold. This is probably leak or theft.

7

8threshold, but imbalance A is mirrored. This is probably not a leak or theft, but it could be a large

4

5

6

mba

lance

2

3

4Im

Threshold A

0

1

2Imbalance A

Threshold B

Imbalance B

Imbalance A exceeds threshold as it is rising, this is probably not a leak but an example of poor threshold tuning


0 2 4 6 8 10 12 14 16 18 20Time

Expected best hybrid system

• Being the RTTM having proven track record and extended applications it is obvious to have RTTM as first component inapplications, it is obvious to have RTTM as first component in any hybrid system

• Proposed system:

»RTTM + SLB

»RTTM + IDA

»RTTM + P Wave


Example Hybrid system

• Alyeska

– The TAPS system is a 1000 mile pipe crossing the Central Arctic herd on the North Slope and the Nelchina Herd in the Copper River basin of Alaska. It transports crude oil and can often suffer slack line flow issues due to the current flow rate being significantly lower than the design flow rate.

– As the pipeline crosses through the wilderness the operating company is mandated to use multiple forms of leak detection.

Th t E S l ti l k d t ti fi ti i l ti– The current Energy Solutions leak detection configuration is a real time transient model (RTTM), statistical model (IDA), and a statistically modified line balance approach (SLB).


Q&A

Thank You!


Hybrid Systems for Pipeline monitoring Leak Detection

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