Assessment of Methane Emissions from Oil and Gas Production Pads using Mobile Measurements

Abstract

A new mobile methane emissions inspection approach, Other Test Method (OTM) 33A, was used to quantify short-term emission rates from 210 oil and gas production pads during eight two-week field studies in Texas, Colorado, and Wyoming from 2010 to 2013. Emission rates were log-normally distributed with geometric means and 95% confidence intervals (CIs) of 0.33 (0.23, 0.48), 0.14 (0.11, 0.19), and 0.59 (0.47, 0.74) g/s in the Barnett, Denver-Julesburg, and Pinedale basins, respectively. This study focused on sites with emission rates above 0.01 g/s and included short-term (i.e., condensate tank flashing) and maintenance-related emissions. The results fell within the upper ranges of the distributions observed in recent onsite direct measurement studies. Considering data across all basins, a multivariate linear regression was used to assess the relationship of methane emissions to well age, gas production, and hydrocarbon liquids (oil or condensate) production. Methane emissions were positively correlated with gas production, but only approximately 10% of the variation in emission rates was explained by variation in production levels. The weak correlation between emission and production rates may indicate that maintenance-related stochastic variables and design of production and control equipment are factors determining emissions.

Constraining sector-specific CO<sub>2</sub> and CH<sub>4</sub> emissions in the US

“…Subsequent facility and on-road measurements elucidate why: a small number of malfunctioning facilities account for a large percentage of emissions. EFs that account for this skewed distribution are more consistent with regional top-down estimates (e.g., Brantley et al, 2014;Lavoie et al, 2015;Subramanian et al, 2015).…”

“…This strategy usually entails measuring trace gas mixing ratios from a ground-based vehicle either on public roads (e.g., Maness et al, 2015) or private roads in partnership with the facility owner (e.g., Roscioli et al, 2015). Existing studies often target oil and gas facilities (e.g., Roscioli et al, 2015;Brantley et al, 2014;Jackson et al, 2014;Lan et al, 2015;Mitchell et al, 2015;Subramanian et al, 2015) and mobile CO 2 emissions (e.g., Brondfield et al, 2012;Maness et al, 2015). In the case of oil and gas emissions, Brantley et al (2014) explain that mobile measurements capture an integrated plume that includes all leaks from a given facility but rarely indicate which components caused those leaks.…”

“…For example, facility-level observations provide the most insight into detailed emission processes from specific source sectors but can miss emission events or processes. Observations of oil and gas facilities provide a prime example; scientists may not know about some leaks and therefore may not measure them, other leaks may be in inaccessible locations (e.g., Subramanian et al, 2015), and the largest leaks often come from ephemeral equipment failures at a small number of facilities that are difficult to identify (e.g., Brantley et al, 2014;Allen, 2014;Allen et al, 2015). Cost also limits facility-level, continuous emission monitoring; it is typically only used for large point sources like power plants (National Research Council, 2010).…”

“…As a result, it is difficult to develop robust, national-scale EFs from a modestly sized sample of facilities (Allen, 2014). Furthermore, Brantley et al (2014) explain that these leaks do not correlate with production and can vary greatly in time. Different oil and gas drilling basins also have different overall leakage rates -from 0.3 % in Pennsylvania's Marcellus Shale region to 8.9 % in Utah's Uintah Basin (e.g., Karion et al, 2013Karion et al, , 2015Pétron et al, 2014;Peischl et al, 2015).…”

“…For example, emission factors for oil and gas operations are difficult to estimate because a small number of emitters often account for a large fraction of emissions (e.g., Allen, 2014;Allen et al, 2015;Brantley et al, 2014;Lan et al, 2015;Mitchell et al, 2015) and because there are so many points along the natural gas production, processing, transmission, and distribution cycle that leak methane (e.g., Kang et al, 2014;Allen et al, 2015;McKain et al, 2015;Subramanian et al, 2015;Zimmerle et al, 2015).…”