Red Hen Systems develops hardware and software for airborne and ground-based emissions detection surveys. They surveyed parts of Pennsylvania in 2014 using a helicopter equipped with sensors including a gas analyzer. Their goal was to quantify potential methane emissions from abandoned oil/gas wells and pipelines. They developed an algorithm to classify methane concentration points without user input. It extracts features from concentration data and uses techniques like wavelet analysis and principal component analysis. It defines significant points of interest, determines boundaries between concentrations, and reduces cluster overlap. Their source finding method uses sensor locations and wind direction to project emission sources onto pipeline and well pad infrastructure, locating sources within 5 feet of accuracy. The presentation concluded the method was adopted as an industry standard.

1. Automated concentration point
classification and source finding
in helicopter-based methane
emissions detection surveys
Bogdan Besfamylnyy
Technical Manager, Red Hen Systems,LLC.

2. Who is Red Hen Systems, LLC(RHS)?
o Develop and manufacture data multiplexing
hardware for data and media collection surveys
o Airborne and ground-based emissions detection
survey provider
o Leader in media geotagging, surveying and
mapping
o Cusomized mapping software and hardware
provider for digital video and audio
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3. Maps
Fort
Collins,CO
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4. 185,000 miles
Liquid petroleum pipelines
2,000,000 miles
Gas distribution pipelines
320,000 miles
Gas transmission pipelines
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5. Airborne Vehicle ATV UAV
Long range
(500 miles/day)
Remote pipelines
& facilities
Medium range
(400 miles/day)
Urban pipelines
& facilities
Short range
(200 miles/day)
Rural pipelines
& facilities
Short range
(100 miles/day*)
Remote pipelines
& Facilities
Moving Platforms

6. Equipment Workflow
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Proprietary
Data
Multiplexing
Hardware
Color
or
Infrared Camera Video
Streams
with
Inertial Measurement
Unit(IMU)
Mounted
Temperature
Humidity
Air pressure
Anemometer
Sensors
GPS
or
Sub-meter
GPS
Unit
Combustible
Gas Analyzers

7. Airborne Fugitive Gas Detection Survey
•Perfect moving platform for
surveying many miles of
pipeline infrastructure
•The best platform for
reaching infrastructure in
hard to access or high
concequence areas
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Combustible
Gas Analyzer
Paired OGI,
Color Video
and IMU
Atmospheric
Sensors

8. Ground-based Fugitive Gas Detection Survey
•Identifies fugitive gas
emissions from the ground
•Can be used to locate pipe
with magnetometer units
on board
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Combustible
Gas Analyzer
Portable
Methane
Detector Vehicle Methane
Detector
Magnetometer

9. Scope of the Survey
•In August 2014, Red Hen Systems, LLC (RHS), in collaboration with
National Energy Technology Laboratory (NETL) surveyed parts of the
state of Pennsylvania.
• The objective was to quantify potential methane fugitive emissions
associated with abandoned oil/gas wells and natural gas
transmission pipelines.
•Survey areas included 17.66 km2 in Hillman State Park in western
Pennsylvania, 37.73 km2 in Oil Creek State Park in northwestern
Pennsylvania, and a survey block of 28.74 km2 and 220 km of a
natural gas pipeline corridor in Susquehannock State Forest in
north-central Pennsylvania

10. Methods
•A fully articulated rotor system helicopter was equipped with a
proprietary survey package consisted of a color video camera,
proprietary video multiplexer and a combustible gas analyzer.
•The surveying mission lasted for 9 days, with the collection of 169,168
data entries to process.
•In addition to the helicopter mounted sensors, a ground level weather
station was set up in a central location within each of the three survey
areas to monitor temperature, relative humidity, wind direction, wind
speed and barometric pressure with one minute time resolution.

11. Problem
•No industry standard for classifying fugitive gas
concentrations
•Existing methods for classifying concentration
intervals were based on statistical analysis,
introducing data skewing bias
•No confidence level information was available to
measure the success of the classification
•No way of projecting concentration data acquired
aerially on the infrastructure on the ground

12. Approach
We devised an algorithm that extracted key behavioral features from
methane concentration distribution provided by Combustible Gas
Analyzer in Parts Per Million(PPM).
Wavelet Analysis (frequency domain analysis)
oShort-Time Fourier Transform (STFT)
oContinuous Wavelet Transform (CWT) and Morlet Energy Vector
Distribution
Principal Component Analysis (PCA by Singular Value Decomposition)
oProjection of Morlet Energy Vectors on 40% of Eigen-space.

13. Significant Feature Extraction
Short-Time Fourier Transform

14. Significant Feature Extraction
Continuous Wavelet Transform

15. Significant Feature Extraction
Projection of Morlet Energy Vectors on Eigen-
spaces

16. Steps to Classify Distribution of
Methane Concentrations
•Defining Points of Interest (POI)
1. Maxima of each energy vector’s distribution is determined
2. K-NN voting heuristic is incorporated to determine most significant POIs
3. The value of K is determined by a Peak Determination heuristic
•Determining Boundary by the POIs
1. Most significant POIs are bounded by creating Lower Hull of a Convex Polygon
•Reduction of misclassification by QDA (Quadratic Discriminant Analysis)
1. Clusters’ overlap are minimized
2. Likelihood of a concentration point to be in certain cluster is maximized.

17. Defining Points of Interest

18. Defining Boundaries for POIs

19. Reduction of Cluster Overlap using QDA

20. Classification Results
•Algorithmic approach identifying
concentration intervals of interest,
requiring no input from the user.
Hence, no skewing bias
•Provides confidence level for each of
the classified points

21. Source Finding
•Using the GPS coordinates of the pipeline or well
pads, the coordinates of the moving surveying
platform with the wind direction angle to form a
triangle the sides of which projected on the
pipeline infrastructure indentifying the segment
where the source is.

22. Source Finding Pipeline
•Using the GPS coordinates of the
pipeline or well pads, the
coordinates of the moving surveying
platform with the wind direction
angle to form a triangle the sides of
which projected on the pipeline
infrastructure indentifying the
segment where the source is,
accuracy of +-5 feet
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23. Source Finding Well Pads
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24. Conclusion
•We devised a turn-key solution for concentration
point classification from combustible gas analyzes
requiring no input from the user other than the
output log from the analyzer.
•Adopted as an industry standard by Colorado
based operators and NETL
•Highly accurate source pinpointing solution
identifying emission sources on the pipeline and
well pad infrastructures

25. Thanks!
Any questions?
You can find me at bog@redhensystems.com
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