Methane emissions associated with the production, transport, and
use of oil and natural gas increase the climatic impacts of energy use;
however, little is known about how emissions vary temporally and with
commodity prices. We present airborne and ground-based data, supported by
satellite observations, to measure weekly to monthly changes in total
methane emissions in the United States' Permian Basin during a period of
volatile oil prices associated with the COVID-19 pandemic. As oil prices
declined from
Accurate quantification of methane (CH
The Permian Basin (Fig. 1) is the most productive oil basin in the USA and
rivals the Ghawar Field in Saudi Arabia for the global record (Jacobs,
2019). Although the first oil well was drilled in the Permian Basin nearly
100 years ago, the basin has experienced rapid growth in recent years as
directional drilling and hydraulic fracturing allowed for production from
unconventional reservoirs (Enverus, 2021). In 2019, the Permian Basin had
Regional map with outlines of the Permian Basin (orange), Delaware
and Midland subbasins (dashed green and purple), and the 100 km
In January 2020, oil prices declined as the COVID-19 pandemic triggered a global slowdown in oil and natural gas consumption; in March 2020, there was a rapid price drop when the oil oversupply was exacerbated by both the Organization of the Petroleum Exporting Countries (OPEC) failing to reach a deal to cut production and global oil storage capacity reaching its limit (Reed and Krauss, 2020). Spot prices for the US oil benchmark, known as West Texas Intermediate – Cushing (WTI-Cushing), varied dramatically during this period; price per barrel was relatively stable at USD 50–60 for most of 2019, declined to USD 20 by late April 2020, briefly dropped below zero on 20 April, and then recovered to USD 40 by early July (USEIA, 2020b). Natural gas spot prices (Henry Hub) were less volatile during this period (USD 1.50–2.00 per million British Thermal Units), continuing a gradual downward trend since late 2018 (USEIA, 2020a). In the Permian Basin, oil price is a stronger driver of well development than natural gas price since many operators view oil as the primary product. Lower commodity prices reduce investment in new well and infrastructure development; in the Permian Basin, the number of active drilling rigs, which had averaged over 400 from April 2019 to March 2020, dropped below 200 by early May and reached a minimum of 123 in September (Baker-Hughes, 2020) (Fig. 2).
We hypothesize that the rapid drop in oil price would be affiliated with a concomitant reduction in methane emissions due to lower rates of well development and a subsequent decline in oil and natural gas production. The postulated causal mechanism for this relationship is the effect of associated natural gas production from new wells on midstream infrastructure throughput. During periods of higher commodity prices, the rapid growth in natural gas production likely exceeds the capacity of the midstream pipelines, compressor stations, and processing plants that deliver natural gas to market, leading to associated gas flaring and anomalous conditions such as over-pressurization that increase emissions. Such trends were observed in an earlier drilling slowdown in the Bakken region, another US unconventional oil formation (Enverus, 2021) (Fig. F1). However, this effect might have been countered in the Permian Basin if lower profit margins led operators to allocate fewer resources to infrastructure maintenance and emissions mitigation, or similarly, restrictions due to COVID-19 reduced the number of field staff performing tasks such as leak detection and repair (LDAR) (Gould et al., 2020).
Weekly count of active drilling rigs by type in the Permian Basin between July 2019 and August 2020 (Baker Hughes, 2020).
In January 2020, we began quantifying O&G methane emissions at varying
spatiotemporal scales within the Permian Basin with a concentrated effort
within a 100 km
Between January and August 2020, we used two inversion approaches to
quantify total methane emission flux from the study area at a weekly to
monthly frequency. The first approach used aircraft-based instruments to
measure atmospheric boundary layer (ABL) methane concentration ([CH
We also evaluated satellite-based remote sensing observations of column
methane enhancement (
An atmospheric reanalysis similar to the system used in previous studies
(Barkley et al., 2019, 2017) was used to create simulated
regional atmospheric [CH
Only atmospheric [CH
Note that the emissions magnitude from the preliminary [CH
The total CH
On each flight day, two laps consisting of a box enclosing the 100 km
[CH
To test the uncertainty of the emission rate solution for each flight day, a
1000-iteration Monte Carlo uncertainty assessment was performed, adjusting
various parameters to test how they impacted the solution. Through the
iterations, we examine the impact of various possible sources of error,
including uncertainty in the background, uncertainty in the assumed
influence from sources outside the domain, and uncertainty in the
atmospheric transport. For uncertainty in the background, we select a random
percentile between the 5th and 15th to use as the methane background
in a flight lap. For uncertainty in sources outside of the domain that are
subtracted from the observations, we multiply the “other” enhancement
tracer by a random factor between 0.5 and 1.5 to account for the possibility
that regional emissions may be incorrect. For uncertainty in the transport,
the time of the observations is adjusted by
Comparison between modeled and observed differences in the maximum
and minimum daily CH
Tower and aerial emission estimates from the 100 km
Numerical estimates of CH
TROPOMI observations of topography-corrected methane column
enhancements over the Permian Basin, from January to June 2020.
Atmospheric mole fraction measurements of CH
CH
Unlike the aircraft mass balance observations, which are collected on days
when meteorological conditions are ideal for measuring emissions from the
study domain, the tower dataset is continuous, and many days may not be
suitable for calculating an emission rate from the study domain. The most
useful tower observations for solving for emissions within the study domain
are those whose enhancements are influenced primarily by sources within the
study domain and contain minimal enhancements from sources outside of the
domain. We select for these conditions by retaining days when
Temporal variation in methane emissions and crude oil price.
Number of new well pads constructed per month between 1 August 2019 and 31 July 2020 in the full Permian Basin and our 10 000 km
VIIRS-derived gas flaring in the study region.
We use column-averaged dry-air methane mixing ratios (XCH
We calculate the daily methane enhancements over the Permian Basin from
topography-corrected XCH
Repeating our analysis with the background defined at the 25th
percentile level (rather than the 10th), we find that trends are
insensitive to the percentile value used. Furthermore, the trends are not
explained by seasonal changes in wind speed across the Permian Basin. Higher winds
could lead to lower enhancements, but data from the NASA GEOS-FP (Lucchesi, 2013)
meteorological reanalysis product indicate that the daily wind speed
averaged over the full Permian Basin domain, in the lowest 3 km of the
atmosphere, during the 6 h closest to TROPOMI observation time
(15:00–21:00 UTC), decreased from a mean of 7.02 m s
Figure 3 presents the daily difference between the highest and lowest
observed CH
Figure 4 presents a time series of CH
Combining the monthly tower and aircraft-based estimates with reported gas
production (Enverus, 2021), we calculate a March 2020 loss rate of
3.3 % of total gas production (95 % CI range: 2.7 %–4.0 %), which is slightly
lower but within the uncertainty of previously reported basin-wide estimates
from 2018–2019 (3.7
In the full Permian Basin, orbital observations of XCH
Figure 5d shows frequency distributions of methane column enhancements
observed by TROPOMI in January, February, April, and May 2020. For these
monthly curves, we restrict our attention to a smaller Permian Basin domain that
closely bounds the methane hotspots seen over the Delaware and Midland
subbasins (dashed lines in Fig. 5a, b; 31–34
Well pad development in the study area proceeded at an average rate of 71 new sites per month between August 2019 and March 2020 and then dropped to a monthly average of 24 sites between April and July 2020 (Appendix C, Fig. 7). The number of well completions per month declined from 188 to 115 between January and April 2020 (Enverus, 2021); completion counts are higher than well pad development rates due to multiple wells being located on a single pad. After rising steadily throughout 2019, oil and gas production peaked in March 2020 and then declined 9 % and 8 %, respectively, in April. Based on adjusted, incomplete production data for May and June, gas production stayed relatively steady after April, while oil production dropped an additional 3 % (Appendix E). The relative decline in oil and natural gas production between March and April 2020 was much greater among wells in the first 2 months of production, decreasing 50 % and 45 %, for oil and gas, respectively (Appendix E).
The three flare surveys between February and June 2020 consistently found
that 11 % of flares had combustion issues, with 5 % unlit and emitting
hydrocarbons. Even when using conservative assumptions of higher combustion
efficiency, we estimate a basin-wide flare combustion efficiency of 93 %,
with the remaining gas (assuming 80 % methane content) being emitted to
the atmosphere (Appendix B). Satellite observations of radiant heat indicate
that flared gas volumes were cut in half from 7.6 to 3.2 Bcf (
The pandemic-associated oil price crash provided an unexpected opportunity
to assess temporal variability in methane emissions during a period of
volatile oil prices and associated operational changes. In support of our
hypothesis that methane emissions would decline with oil price, we observed
a threefold reduction in Permian Basin study area methane emissions that
was strongly correlated to the average daily oil price. Between Q1 and Q2
2020, Permian Basin oil and natural gas production dropped about 12 % and
8 % respectively; the magnitude of change for oil and gas production was
similarly about 11 % and 9 % within the 100 km
Lower oil prices directly led to reduced emissions by decreasing well
development activities, as we observed for rig count, new site construction,
and well completions following the price crash. Well development activities
are an intermittent source of methane emissions, particularly completion
flowback, the typically multiday period following hydraulic fracturing when
fluids, excess proppant, and entrained gas are expelled from the wellbore
(Allen et al., 2013). We estimate that the
The observed twofold reduction in flared gas volumes between January and
April 2020 was likely the result of the large drop in associated gas
production from new wells. Unconventional wells tend to have high initial
gas production followed by steep declines. With lower rates of well
development and new gas production in the area, competition for limited gas
pipeline capacity likely was abated, leading to less flaring of stranded
associated gas. Assuming a combustion efficiency of 93 %, we estimate
flare-related methane emissions in our study area were approximately 8 and 3 Mg CH
Our estimates of well completion and flare-related methane emissions account for less than 20 % of the observed total reduction between pre-crash and minimum price conditions; therefore, we theorize that the primary driver of emission reductions is indirect improvements to the performance of the midstream gathering and processing system resulting from reduced inputs of gas from new wells. This result suggests that the high methane emission rate observed in the Permian Basin in recent years is in large part due to insufficient capacity of midstream infrastructure for handling and delivering rapidly growing rates of natural gas production (Zhang et al., 2020). The drastic decline in flared associated gas volumes during the oil price crash suggests that the reduction in new gas production relieved midstream capacity issues. A similar pattern was observed in the Bakken formation during the oil price decline of 2015–2016: price drops caused only a small decrease in total production but a large decrease in drilling and flaring rates (Appendix F). Our study provides the first direct evidence of reduced methane emissions resulting from an apparent abatement of infrastructure capacity limitations.
The high methane emission rate observed in the Permian Basin during periods of higher oil commodity prices is likely a consequence of associated gas production increasing at a faster rate than midstream infrastructure capacity for sending gas downstream. This leads to both intentional flaring of stranded gas and fugitive emissions from anomalous conditions related to excess gas throughput (e.g., pressure relief venting). Our observations of emissions declining concurrently with new well development suggest that methane emissions could be mitigated in the Permian Basin and similar oil-producing fields by better aligning development rates of wells and midstream infrastructure. For example, regulations could prohibit the drilling of wells in areas without sufficient capacity to transport newly produced associated gas to market. Our findings suggest that policies which tie the maximum rate of well development to infrastructure capacity, in addition to other approaches such as requiring high-frequency or continuous monitoring to detect large emission sources (Alvarez et al., 2018), can facilitate lower methane emissions that reduce the climatic impact of oil and gas production.
We assess the monthly trends in the volumes of natural gas flared in the
study region using nighttime fire and flare data observed by the Visible
Infrared Imaging Radiometer Suite (VIIRS) instrument aboard the Suomi
National Polar-orbiting Partnership satellite. Specifically, we use the
VIIRS NightFire V3.0 data product to support our analysis (Elvidge et
al., 2013) For the study region and for the period between January 2019 and
June 2020, we retrieved 49 885 individual VIIRS detections for which it was
possible to estimate flaring source temperatures based on Planck curve
fitting of the source radiances (Elvidge et al., 2013). During this
period, the mean VIIRS-derived source temperature was 1869 K. The histogram
of source temperatures is shown in Fig. 8b, indicating a strong gas flaring
signal in the characteristic temperature regime of between 1400 and 2500 K.
Elvidge et al. (2015) developed a correlation between the VIIRS-derived
radiant heat and reported gas flared volumes and derived the relationship:
We compiled a list of potential locations of recently active flares in the
Permian Basin (Delaware and Midland subbasins) based on a geospatial
analysis of the SkyTruth Global Flaring Dataset, which is derived from heat
sources detected by the Visible Infrared Imaging Radiometer Suite (VIIRS)
instrument on the NOAA Suomi NPP satellite; SkyTruth has applied several
filters to the VIIRS data including removing heat sources
LSI performed three surveys of the potential flare locations during the weeks of 17 February, 23 March, and 22 June 2020 (EDF, 2020). At each potential flare location, LSI determined if one or more flares was present at the spatial coordinates, and if so, it observed the flare(s) for operational status. For flares with apparent combustion issues, LSI recorded 30–60 s of infrared and visual video footage of the flare plume to provide visual evidence of flare status. For each flare, LSI assigned a qualitative assessment of the apparent flare status at the time of survey from four categories: inactive and unlit with no emissions (inactive); active, lit, and operating properly (operational); active and lit but with operational issues such as incomplete combustion or excessive smoke (malfunction); or active, unlit, and venting methane (unlit). For survey 1, LSI observed 337 flares from the random selection of potential locations. For surveys 2 and 3, a random subset of the 337 flares was selected for resurvey, prioritizing locations that had previously observed issues. We observed similar flare performance in each of the three surveys: 11 % of active flares had observed malfunctions, including 5 % that were unlit and venting (Table B1).
To estimate methane emissions from flaring, we used our qualitative flare
performance data and conservatively high assumptions about the combustion
efficiency of operational, malfunctioning, and unlit flares to estimate
overall combustion efficiency, and then we applied combustion efficiency to
estimated flared volumes in 2019 based on an analysis of VIIRS data
(Appendix B). We assume that operational flares perform at the EPA default
combustion efficiency of 98 % (USCFR, 2016). The 5 % of
flares that were unlit and venting were assumed to have a combustion
efficiency of 0 %. The 6 % of flares that were lit with apparent
combustion issues were assumed to have 90 % combustion efficiency. If we
assume flared gas volumes are proportional to the observed fraction of
flares by performance, then the overall combustion efficiency of active
flares in the Permian Basin is 93 %, which means 7 % of flared methane
is emitted. Applying 93 % combustion efficiency to the 280 Bcf (
EPA publishes two separate estimates of Permian Basin flaring methane emissions,
which incorporates the 98 % combustion efficiency but different gas flared
data. The 2020 greenhouse gas inventory (USEPA, 2020a) reports 2018
Permian Basin methane emissions of 12 100 Mg CH
The operational performance of Permian Basin flares as observed during three helicopter-based infrared optical gas imaging surveys.
We mapped new well pad construction in the Permian Basin using a two-step machine learning and remote sensing approach. First, well pad candidates were identified in satellite imagery with a convolutional neural network (CNN) model in individual scenes. The model predictions were then compared between the beginning and end of each month to identify the locations of newly constructed well pads. Second, by differencing before and after model outputs, persistent false-positives in the model were removed. The resulting model was deployed on imagery over the Permian Basin on a monthly cadence between 1 August 2019 and 1 July 2020.
We assessed the monthly trends in new well pad construction in the Permian Basin using a combination of satellite imagery from the European Space Agency Sentinel-2 satellite (ESA, 2020) and the National Aeronautics and Space Administration (NASA) Landsat-8 satellite (USGS, 2020). Imagery from Sentinel-2 has a pixel resolution of 10 m, sufficient to clearly identify well pads, and is collected approximately once every 5 d for any location, providing an average of six collects per month. While this is generally sufficient for monthly monitoring, some areas experience high cloud cover in all the scenes, causing well pads to be missed. Imagery from Landsat-8 was used to fill in for such cloudy scenes. Despite the slower 16 d revisit rate and coarser (30 m) pixel resolution of Landsat-8, well pads are still easily detectable. The combined use of these two satellites provided at least one cloud-free scene for all of the Permian Basin for each month within the time period we monitored. We use six spectral bands from both Sentinel-2 and Landsat-8: “red”, “green”, “blue”, “NIR”, “SWIR1”, and “SWIR2”.
New well pad construction was detected in a two-step approach. Well pad
candidates were first identified with a convolutional neural network (CNN)
model in individual scenes. The model predictions were compared between the
beginning and end of each month, and new well pads were identified. Well
pads were detected using a semantic segmentation approach. We used a UNet
architecture with a six-band input layer with shape
The model was trained on a ground-truth dataset taken from well pads
detected with a separate machine learning model run on high-resolution
(1.5 m) imagery. We generated
To further remove false positives, we require that new well pad candidates should not have existed in multiple months leading up to the construction date and should continue to exist for several months after. We thus used the 3 months before and the 2 months after to remove candidates that fail this condition. While the 10 m resolution of the imagery makes it difficult to confirm with certainty that candidates contain oil and gas infrastructure, we suspect that the Permian Basin region is unlikely to experience a high volume of unrelated ground clearing for development. We confirm this with manual inspection; see details below.
The CNN and change detection pipeline was run over the Permian Basin on monthly imagery composites between 1 August 2019 to 1 July 2020. The deployment was done using the Descartes Labs platform. Tiled imagery was drawn on the fly, model inference was performed in a cloud-native Kubernetes infrastructure, and results were stored in the commercial cloud. Finally, the authors manually verified the candidates for each month.
The change detection analysis has a precision of
Examples of image–target pairs: (left) Sentinel-2 RGB imagery (ESA, 2020) and (right) ground truth.
CNN model example, showing Sentinel-2 imagery (left; ESA, 2020) and model output heatmap over the same area (right).
Left to right: before (1) and after (2) medium-resolution imagery (ESA, 2020); same area in model output: (3) before, (4) after, (5) difference, and (6) detected new well pads.
Example of an area where new development was found, before (left) and after (right) shown in Sentinel-2 imagery (ESA, 2020). Points in yellow indicate the locations of new well pad development.
Well completion flowback refers to the unconventional well development
period following hydraulic fracturing in which water, proppant, and
entrained natural gas flow out of the wellbore to prepare a well for
production (Allen et al., 2013). As of 2015, US
federal regulations require all oil and gas wells except exploratory and
low-pressure wells to utilize reduced emission completions (RECs), which
separate the natural gas and send to a pipeline as soon as technically
feasible (USEPA, 2019); occasionally, flaring or a combination of REC and
flaring is used to partially control emissions. Previous research has
demonstrated that RECs control flowback emissions by an average of 99 %
(Allen et al., 2013). To estimate monthly
completion-related methane emissions within our 100 km
Estimate of Permian Basin well completion emission factors based on US EPA Greenhouse Gas Reporting Program data.
The number of monthly well completions in the study area dropped from 188 in
January to 115 in April and then to a minimum of 29 in June 2020 (Table D2).
Based on our first approach, January and April 2020 completion-related
actual emissions were 3.6 and 2.2 Mg CH
Estimate of average monthly potential completion-related emissions from our study area from January 2019–September 2020 based on initial gas production data and the assumption of 4 d completion duration.
Production quantities of oil and gas from individual wells are reported to
public state databases (RRC, 2020; NMOCD, 2020); however, the
best results are achieved by analyses from an external database (Enverus,
2021), which filters and aggregates all of the publicly available datasets
from all reporting agencies. Oil and natural gas production data from New
Mexico are updated on a monthly cadence, while data from Texas are updated
twice each month but still only at monthly resolution. Time series of oil and
natural gas production within the greater Permian Basin and 100 km
Monthly time series of oil
Monthly time series of active wells
Number of wells drilled versus fraction of total gas production flared in the Bakken region (North Dakota, USA) from 2012–2017. Similar to trends observed in the Permian, there was a strong correlation between wells drilled and fraction of gas flared with both values decreasing rapidly when oil prices crashed in 2014.
Data are available for download at
DRL, BH, ARB, MK, EAK, AJM, and SPH contributed to study conceptualization. DRL, BH, RG, MO, KR, ZRB, KJD, NLM, VCM, SJR, SC, MLS, DJJ, LS, DVV, AD, XR, NS, and KTS contributed to methods development and data analysis. DRL, BH, MO, ZRB, KJD, MLS, DJV, and KTS wrote the original draft and all authors reviewed and edited the article.
Adam R. Brandt, Eric A. Kort, Mary Kang, and Anthony J. Marchese serve on the PermianMAP scientific advisory panel. Authors declare no other competing interests.
The authors thank Beth Trask, Colin Leyden, Jon Goldstein, Louise White, Caleb Berman, and the entire PermianMAP team for their contribution to the project. We are grateful to Ramon Alvarez, Maureen Lackner, Ricardo Esparza, Ilse Aben, and Bram Maasakkers for providing comments. We are grateful to Niall Armstrong for piloting the research aircraft and Leak Surveys, Inc. for performing the flare performance surveys. The PermianMAP project, which includes the aerial, tower, and flare survey data, is grateful for the support of Bloomberg Philanthropies, Grantham Foundation for the Protection of the Environment, High Tide Foundation, the John D. and Catherine T. MacArthur Foundation, and Quadrivium. Computations for this research were performed on The Pennsylvania State University's Institute for Computational and Data Sciences' Roar supercomputer. We thank Carlsbad Caverns National Park for hosting a methane instrument used in the tower analysis.
The PermianMAP project has been supported by Environmental Defense Fund and its donors; the work at Harvard University was supported by NASA Carbon Monitoring System.
This paper was edited by Bryan N. Duncan and reviewed by two anonymous referees.