1. This material is based upon work supported
by the National Science Foundation
under Grant No. EEC-0540832.
Tanvir Mangat,1
Dana Caulton,2
Levi M. Golston,2
Mark A. Zondlo2
1 – University of Massachusetts, Amherst MA, 01003
2 –Princeton University, Princeton NJ, 08540
www.mirthecenter.org
Spatial Analysis of Methane Emissions
from Natural Gas Well pads in the
Marcellus Shale Region
Spatial Analysis of Methane Emissions
from Natural Gas Well pads in the
Marcellus Shale Region
 Employed the Princeton Atmospheric Chemistry Mobile
Acquisition Node (PAC-MAN), equipped with LI-7500A and
the LI-7700 sensors, to spatially profile the CO2 and the CH4
concentrations, respectively.
 ~249 unique wells that stretched
across the states of West Virginia
and Pennsylvania were sampled.
Fig1(right):
PAC-MAN in
the field
with L-7700
and L-7500A
sensor
attached to
the roof rack
 From 2005 to 2013, dry natural gas production increased by
35% and is projected to comprise 31.3% of the entire U.S
energy production budget by the end of 2015.[1]
 Advances in drilling techniques have caused major boom in
the shale gas production which now constitutes 47% of total
dry natural gas production. [1]
 Fugitive methane emissions are a major concern due to
methane’s global warming potential being 28-34 times
higher than that of carbon dioxide. [2]
 In July 2015, we conducted a field study to quantify
methane leakage from natural gas well pads in the
Marcellus Shale.
 Leak rates from potential emission sources on these well
pads were examined using an inverse Gaussian plum model
along with sensitivity analysis for estimated leak height.
Motivation
References
[1] US Energy Administration 2015 Annual Energy Outlook.
http://www.eia.gov/forecasts/aeo/index.cfm (Accessed July 22, 2015).
[2] Stocker T, et al. (2013) in Climate Change 2013: The Physical Science Basis: Technical
Summary, eds Joussaume S, Penner J, Fredolin T (Cambridge University Press, New York),
Table 8.7
[3] U.S. Greenhouse Gas Inventory Report:1990-2013.
http://www.epa.gov/climatechange/ghgemissions/usinventoryreport.html (Accessed July
29,2015).
Methodology
Fig 2 (left):
The sonic
anemometer
used to
measure
atmospheric
turbulence
for the
intensive
sampling
sites
Fig 3 a,b,c: The methane concentrations observed near three well pads in
Southern and Southwestern Pennsylvania. The modeled wind direction on
the day and the time of the transects (shown as an arrow) aligns with the
location of the plume. The sites were chosen to analyze whether uncertainty
in the height of emission source has a significant effect on the emission rates
from the inverse Gaussian model.
A Case Study of 3 Well Pads
Potential Emission Sources
a b c
Fig 4a: Four Christmas trees on a well pad
connecting to the wellheads. Liquid unloading
events can cause fugitive methane leaks.
Fig 4b: GPU units separate the gas from
oil, water. Contain glycol pumps and
compressors that can release methane
Fig 4c:
Pneumatic
pumps
control the
flow, temp,
levels and
pressure of
liquid/gas.
a valve is
They release methane when
actuated.
Fig 4d:
Storage tanks
contain light
hydrocarbons
and VOC’s
that are
vented as
condensate
levels
fluctuate.
a b
c d
Results
Emission rate (metric ton/year)
Fig 5:EPA estimates of methane
emissions due to natural gas
production activities [3]
Fig 6: Variation in the height of
equipment affects the emission
rate by altering the
concentration data fitted in the
inverse Gaussian model
• Strong evidence (R2
>.99) that emission rates decrease
in the model as the source height increases.
• However, the sensitivity of emission rate (~2.2% on
logarithmic scale) is relatively insignificant.
• In future, the same methodology could be applied to a
compressor station or a drilling site because there is a
more diverse range of equipment and leak heights
compared to a well pad.
• A stronger alliance between the industry and the
scientific community is needed to pin point the
emission source and reap the mutual benefits of a
healthier environment and increased profits.
Conclusion
Equipment Height (ft)
Acknowledgements
Lars Wendt, Jessica Lu, Haley Lane, Stephanie Paredes
∆Emission rate/ft
Fig 8 (above): Regression
analysis of the well pads
with the source point
ranging from 0-24ft
Fig 9 (left): Regression
data scaled to a
logarithmic y-scale