This document summarizes research on using ground penetrating radar (GPR) to detect leaks in water pipe networks. It discusses the objectives of assessing GPR's limitations for leak detection through numerical simulations, laboratory experiments, and a field application. The numerical simulations showed that water content most impacts GPR signal reflection and leak detection. Laboratory tests identified discontinuities in pipe and plate reflections indicating a leak location. However, the field application difficulties detecting known pipes and the leak directly. Overall, the research aims to better understand GPR for leak detection but encounters challenges with soil conditions and complex real-world environments.

1. LEAKAGE DETECTION IN WATER PIPE NETWORKS USING
GROUND PENETRATING RADAR (GPR)
Professor: Sébastien LAMBOT Student: Dai SHI
19th June 2013

2. CONTEXT
MAJOR CURRENT LEAK DETECTION TECHNIQUES
OBJECTIVES
PROCESS STEPS
NUMERICAL SIMULATION
LAB EXPERIMENT
FIELD APPLICATION
CONCLUSION AND PERSPECTIVE

3. WHY ARE WE INTERESTED IN WATER LEAKAGE?
In developed countries 20-30% leakage of total
water produced
In Wallonia, ~15-20% of unsold water is due to
leakage
In developing countries, the leakage represents
> 50%
Economic reasons
Public health safety
Natural resource conservation
Can be reduced via adequate detection techniques
Water Supply Compagny of Nanjing, China

4. LEAK DETECTION PROCEDURE
SECTORIZATION
ACCURATE LOCALIZATION
1.WATER AUDIT
2. SECTORIAL LEAK DETECTION
3. ACCURATE LOCALIZATION & REPAIR
REPAIR
MINIMUM NIGHT FLOW
MONITORING
ANOMALY DETECTION
WATER PIPE
NETWORK
MAPPING
FLOW MEASUREMENTS DATA TRANSFER

5. CONTEXT
MAJOR CURRENT LEAK DETECTION TECHNIQUES
OBJECTIVES
PROCESS STEPS
NUMERICAL SIMULATION
LAB EXPERIMENT
FIELD APPLICATION
CONCLUSION AND PERSPECTIVE

6. MAJOR CURRENT LEAK DETECTION TECHNIQUES
Leak noise correlatorAcoustic
Other techniques
Gas tracer
Thermography
Smartball
Listening rod Ground microphone
Sewerin, Gütersloch,
Germany

7. Methods Pipe materials
Asbestos
cement
Metal
(Iron & Steel)
Plastic
Listening devices ± ✓ ±
Leak noise
correlator
X ✓ ±
Gaz tracer ± ✓ ✓
Thermography X ✓ X
ADEQUACY OF LEAK DETECTION METHODS FOR
VARIOUS TYPES OF PIPES

8. GROUND PENETRATING RADAR (GPR)
Principle
Emits electromagnetic microwaves and records the reflected signal from subsurface
Advantages
✓ Nondestructive method
✓ High resolution images of subsurface
✓ Independent of the pipeline material
✓ Can detect objects, changes in material and voids
✓ Good penetration depth
Major limitation
X Data processing and interpretation
X Signal attenuation with conductive soil

9. SPECIFIC OBJECTIVES
1. 2D Numerical simulation and analysis
Simulate different key parameters
Evaluate the sensitivity of GPR to different parameters
Obtain a first visualization of a leak’s radar signature
2. Laboratory testing
Measure an artificial leaky pipeline with GPR in sand
Analyze 2D and 3D images
3. Field application
Measure a pre-located leak with GPR in an urban area
Discuss the applicability and limitations of GPR
Complexity
GENERAL OBJECTIVE
Assess the limitations of GPR for leak detection and test deployment routines

10. CONTEXT
MAJOR CURRENT LEAK DETECTION TECHNIQUES
OBJECTIVES
PROCESS STEPS
NUMERICAL SIMULATION
LAB EXPERIMENT
FIELD APPLICATION
CONCLUSION AND PERSPECTIVE

11. Hydrus 2D
Water content
Θ (x, z, t)
GprMAX 2D
Input
Domain geometry
Flow and transport
parameters
(e.g. main processes,
time information)
Domain properties
(e.g. soil texture )
Initial conditions
(e.g. water content)
Boundary conditions
(e.g. flow type)
Output
Input
Permittivity
ε (x, z, t)
Conductivity
σ (x, z, t)
Output
GPR signal reflection data
Model geometry

12. Model design
Antenna frequency
400 [MHz]
Water content
Soil moisture (t0 : dry)
Parameters
Simulation time : 1 day and 1 week
Leak type : TOP
1.2 m
Simulation domain: 6 m x 4 m
Pipe diameter : 0.09 m
Soil type: sand
Pipe type: PVC
Pipe position: x = 3 m, 1.2 depth
1.2 m
Surface
reflection
Pipe reflection
GPR reflection

13. TOP leak after 1 day
INITIAL SITUATION
Configuration 1
Surface
reflection
Pipe reflection
Pipe reflection

14. TOP leak after 1 week
INITIAL SITUATION
Configuration 1 (Field)
Surface
reflection
Pipe reflection
Pipe reflection
Attenuation of reflection

15. SYNTHESIS
 Water content has the most impact on the reflected signal
and significantly influences the detection performance
 400 MHz antenna is a good trade-off between resolution
and penetration depth to detect a pipe with 0.09 m outer
diameter at depth of 1.2 m
 It is difficult to determine visually the type and extent of a
leak from the reflected signal

16. CONTEXT
MAJOR CURRENT LEAK DETECTION TECHNIQUES
OBJECTIVES
PROCESS STEPS
NUMERICAL SIMULATION
LAB EXPERIMENT
FIELD APPLICATION
CONCLUSION AND PERSPECTIVE

17. Vivaldi antenna
OPERATION STEPS
MATERIALS

18. LABORATORY EXPERIMENT : 2D IMAGE ACQUISITION
Hole location
1.5 m
1 m
Scan area
Scan directions
Scan during the leak (2 hours)
Number of scans: 38
Far field (i.e., 25 cm above surface) & Near field
1.5 m
0.2 m
Copper area
1 m

19. 19
Surface reflection
Pipe
line
Longitudinal section (Far field)
Copper reflection
Surface reflection
Pipe hyperbola
Transversal section (Far field)
Copper reflection

20. LABORATORY EXPERIMENT : 2D IMAGE ACQUISITION
Hole location
1.5 m
1 m
Scan area
Scan directions
Scan during the leak (2 hours)
Number of scans: 38
Far field (i.e., 25 cm above surface) & Near field
1.5 m
0.2 m
Copper area
1 m

21. 21
Surface reflection
Pipe line
Longitudinal section (Far field)
Copper reflection

22. LABORATORY EXPERIMENT : 3D IMAGE ACQUISITION
Scan before and after leak
Number of scans: 101
Far field (i.e., 25 cm above surface)
1.5 m
1 m
1.5 m
1 m
Transversal scan area
0.2 m
Scan direction
Copper area

23. 3D IMAGE OF INITIAL DRY CONDITIONS
Surface reflection
Pipe reflection
Copper reflection

24. 3D IMAGE OF POST-LEAK CONDITIONS
Surface reflection
Pipe reflection
Copper plate reflection
Attenuation
Leak location

25. SYNTHESIS
 Soil homogeneity and a priori knowledge about the leak
configuration ease the image interpretation step
 Different reflections (e.g., surface, pipe and copper plate) are
identifiable in dry conditions
 An interruption of pipe and copper plate reflection continuity in the
2D longitudinal image (after 20 minutes) and the 3D image (after
leak) due to the leak was observed

26. CONTEXT
MAJOR CURRENT LEAK DETECTION TECHNIQUES
OBJECTIVES
PROCESS STEPS
NUMERICAL SIMULATION
LAB EXPERIMENT
FIELD APPLICATION
CONCLUSION AND PERSPECTIVE

27. STUDY AREA
DESCRIPTION
Water supply
system
Drain system
Drain system

28. SCAN STEPS
y
x 33 X
21 X
0,0

29. RESULTS

30. Water supply pipe
reflection (?)
Transition between 2 media
reflection (?)

31. No Name Detection
1 Leak area ✓
(metal plate only)
2 Manhole ✓
3 Floor drain ✓
4 Floor drain
connection
X
5 Water supply pipe Maybe
(to be verified)
6 Water connection X
7 Sewer X (?)
8 Sewer connection X
9 Sewer gallery X
DETECTABILITY OF VARIOUS COMPONENTS

32. SYNTHESIS
 The metal objects (e.g., manhole, floor drain and metal valve cover) on the road
were easily detected since the metal is a perfect reflector
 The water supply pipe was not detected in a continuous manner, its reflection is
supposed to be observed in 3 transversal scans in hyperbolic shape, despite the
fact that the pipe is made of cast iron
 Since the leak area had been reworked, it is difficult to identify 2 unexpected
reflections
 The leak was not directly detected

33. CONCLUSION
Numerical analysis
 The water content is the most limiting factor for detection
 A plastic pipe of 0.09 m outer diameter at 1.2 m of depth is detectable
in leak conditions
 It is difficult to classify the type of the leak
 It is possible to determine the signal attenuation by observing the
whole sequence of images (dry to saturated soil)
Laboratory testing
 Leak can be detected by observing the discontinuity of the pipe and
the copper plate reflections in longitudinal scans of 2D images and in
3D images (dry to wet soil)
Field validation
 Difficulty to detect pipes and no insight regarding the leak

34. PERSPECTIVES
 Smart water monitoring with
 Online database of the measurement conditions (e.g., weather
conditions, pipe characteristics, GPR antenna frequency used,
etc.)
 Exchange information between GPR operators & SWDE (e.g.,
leak location and area, pipe configuration, soil type, feed back of
measurements results, etc.) → ensure a gain in time to identify
leak conditions suitable for GPR detection
 Improved protocol with
 Standardization between numerical simulations and the lab
experiment
 Development of image processing to classify radar images
 Filtering of near field antenna effects, including antenna medium
coupling, for improved subsurface imaging

35. EXAMPLE OF ANTENNA FILTERING
Far-field initial image Enhanced image
Antenna filtering
Range gain

36. Special thanks go to the Water Supply Company of Wallonia (SWDE)
Persons I would like to THANK
Prof. Sébastien LAMBOT
Prof. Alain HOLEYMAN
GPR ASSISTANCE
Mohamed MAHMOUDZADEH
Laurence MERTENS
Albéric DE COSTER
HYDRUS-2D ASSISTANCE
Félicien MEUNIER
EQUIPMENT ASSISTANCE
Frédéric LAURENT & Sébastien FRANCOIS
ACKNOWLEDGEMENTS