Variability in Spatially and Temporally Resolved Emissions and Hydrocarbon Source Fingerprints for Oil and Gas Sources in Shale Gas Production Regions

Methods for Spatial Extrapolation of Methane Measurements in Constructing Regional Estimates from Sample Populations

Methane emission estimates for oil and gas facilities are typically based on estimates at a subpopulation of facilities, and these emission estimates are then extrapolated to a larger region or basin. Basin-level emission estimates are then frequently compared with basin-level observations. Methane emissions from oil and gas systems are inherently variable and intermittent, which make it difficult to determine whether a sample population is sufficiently large to be representative of a larger region. This work develops a framework for extrapolation of emission estimates using the case study of an operator in the Green River Basin. This work also identifies a new metric, the capture ratio, which quantifies the extent to which sources are represented in the sample population, based on the skewness of emissions for each source. There is a strong correlation between the capture ratio and extrapolation error, which suggests that understanding source-level emissions distributions can mitigate error when sample populations are selected and extrapolating measurements. The framework and results from this work can inform the selection and extrapolation of site measurements when developing methane emission inventories and establishing uncertainty bounds to assess whether inventory estimates are consistent with independent large spatial-scale observations.

Toward Multiscale Measurement-Informed Methane Inventories: Reconciling Bottom-Up Site-Level Inventories with Top-Down Measurements Using Continuous Monitoring Systems

Government policies and corporate strategies aimed at reducing methane emissions from the oil and gas sector increasingly rely on measurement-informed, site-level emission inventories, as conventional bottom-up inventories poorly capture temporal variability and the heavy-tailed nature of methane emissions. This work is based on an 11-month methane measurement campaign at oil and gas production sites. We find that operator-level top-down methane measurements are lower during the end-of-project phase than during the baseline phase. However, gaps persist between end-of-project top-down measurements and bottom-up site-level inventories, which we reconcile with high-frequency data from continuous monitoring systems (CMS). Specifically, we use CMS to (i) validate specific snapshot measurements and determine how they relate to the temporal emission profile of a given site and (ii) create a measurement-informed, site-level inventory that can be validated with top-down measurements to update conventional bottom-up inventories. This work presents a real-world demonstration of how to reconcile CMS rate estimates and top-down snapshot measurements jointly with bottom-up inventories at the site level. More broadly, it demonstrates the importance of multiscale measurements when creating measurement-informed, site-level emission inventories, which is a critical aspect of recent regulatory requirements in the Inflation Reduction Act, voluntary methane initiatives such as the Oil and Gas Methane Partnership 2.0, and corporate strategies.

Tiered Leak Detection and Repair Programs at Simulated Oil and Gas Production Facilities: Increasing Emission Reduction by Targeting High-Emitting Sources

Distributions of methane emission rates originating from oil and gas production facilities are highly skewed and span 6-8 orders of magnitude. Traditional leak detection and repair programs have relied on surveys with handheld detectors at intervals of 2 to 4 times a year to find and fix emissions; however, this approach may lead unintended emissions to be active for the same interval independently of their magnitude. In addition, manual surveys are labor intensive. Novel methane detection technologies offer opportunities to further reduce emissions by quickly detecting the high-emitters, which account for a disproportionate fraction of total emissions. In this work, combinations of methane detection technologies with a focus of targeting high-emitting sources were simulated in a tiered approach for facilities representative of the Permian Basin, a region with skewed emission rates where emissions above 100 kg/h account for 40-80% of production site-wide total emissions, which include sensors on satellites, aircraft, continuous monitors, and optical gas imaging (OGI) cameras, with variations on survey frequency, detection thresholds, and repair times. Results show that strategies that quickly detect and fix high-emitting sources while decreasing the frequency of OGI inspections, which find the smaller emissions, achieve higher reductions than quarterly OGI and, in some cases, reduce emissions further than monthly OGI.

Assessing Detection Efficiencies for Continuous Methane Emission Monitoring Systems at Oil and Gas Production Sites

Continuous monitoring systems, consisting of multiple fixed sensors, are increasingly being deployed at oil and gas production sites to detect methane emissions. While these monitoring systems operate continuously, their efficiency in detecting emissions will depend on meteorological conditions, sensor detection limits, the number of sensors deployed, and sensor placement strategies. This work demonstrates an approach to assess the effectiveness of continuous sensor networks in detecting infinite-duration and fixed-duration emission events. The case studies examine a single idealized source and a group of nine different sources at varying heights and locations on a single pad. Using site-specific meteorological data and dispersion modeling, the emission detection performance is characterized. For these case studies, infinite-duration emission events are detected within 1 h to multiple days, depending on the number of sensors deployed. The percentage of fixed-duration emission events that are detected ranged from less than 10% to more than 90%, depending on the number of sources, emission release height, emission event duration, and the number of sensors deployed. While these results are specific to these case studies, the analysis framework described in this work can be broadly applied in the evaluation of continuous emission monitoring network designs.

Reconciling Multiple Methane Detection and Quantification Systems at Oil and Gas Tank Battery Sites

Emission rates were estimated for >100 oil and gas production sites with significant liquid-handling equipment (tank battery sites) in the Permian Basin of west Texas. Emission estimates based on equipment counts and emission factors, but not accounting for large uninventoried emission events, led to ensemble average emission rates of 1.8-3.6 kg/h per site. None of the site-specific emission estimates for individual sites, based on equipment counts, exceeded 10 kg/h. On-site drone-based emission measurements led to similar emission estimates for inventoried sources. Multiple aircraft measurement platforms were deployed and reported emissions exceeding 10 kg/h at 14-27% of the sites, and these high-emission rate sites accounted for 80-90% of total emissions for the ensemble of sites. The aircraft measurement systems were deployed asynchronously but within a 5 day period. At least half of the sites with emission rates above 10 kg/h detected by aircraft had emissions that did not persist at a level above 10 kg/h for repeat measurements, suggesting typical high-emission rate durations of a few days or less for many events. The two aircraft systems differed in their estimates of total emissions from the ensembles of sites sampled by more than a factor of 2; however, the normalized distributions of emissions for sites with emission rates of >10 kg/h were comparable for the two aircraft-based methods. The differences between the two aircraft-based platforms are attributed to a combination of factors; however, both aircraft-based emission measurement systems attribute a large fraction of emissions to sites with an emission rate of >10 kg/h.

Multiscale Methane Measurements at Oil and Gas Facilities Reveal Necessary Frameworks for Improved Emissions Accounting

Methane mitigation from the oil and gas (O&G) sector represents a key near-term global climate action opportunity. Recent legislation in the United States requires updating current methane reporting programs for oil and gas facilities with empirical data. While technological advances have led to improvements in methane emissions measurements and monitoring, the overall effectiveness of mitigation strategies rests on quantifying spatially and temporally varying methane emissions more accurately than the current approaches. In this work, we demonstrate a quantification, monitoring, reporting, and verification framework that pairs snapshot measurements with continuous emissions monitoring systems (CEMS) to reconcile measurements with inventory estimates and account for intermittent emission events. We find that site-level emissions exhibit significant intraday and daily emission variations. Snapshot measurements of methane can span over 3 orders of magnitude and may have limited application in developing annualized inventory estimates at the site level. Consequently, while official inventories underestimate methane emissions on average, emissions at individual facilities can be higher or lower than inventory estimates. Using CEMS, we characterize distributions of frequency and duration of intermittent emission events. Technologies that allow high sampling frequency such as CEMS, paired with a mechanistic understanding of facility-level events, are key to an accurate accounting of short-duration, episodic, and high-volume events that are often missed in snapshot surveys and to scale snapshot measurements to annualized emissions estimates.

A Methane Emission Estimation Tool (MEET) for predictions of emissions from upstream oil and gas well sites with fine scale temporal and spatial resolution: Model structure and applications

In comparing observation based methane emission estimates for oil and gas well sites to routine emissions reported in inventories, the time scale of the measurement should match the time scale over which the inventoried emissions are estimated. Since many measurements are of relatively short duration (seconds to hours), a tool is needed to estimate emissions over these time scales rather than the annual totals reported in most emission inventories. This work presents a tool for estimating routine emissions from oil and gas well sites at multiple time scales; emissions at well sites vary over time due to changes in oil and gas production rates, operating practices and operational modes at the sites. Distributions of routine emissions (expected and inventoried) from well sites are generally skewed, and the nature and degree to which the distributions are skewed depends on the time scales over which emissions are aggregated. Abnormal emissions can create additional skew in these distributions. At very short time scales (emissions aggregated over 1 min) case study distributions presented in this work are both skewed and bimodal, with the modes depending on whether liquid storage tanks are flashing at the time of the measurement and whether abnormal emissions are occurring. At longer time scales (emissions aggregated over 1 day) distributions of routine emissions simulated in this work can have multiple modes if short duration, high emission rate events, such as liquid unloadings or large abnormal emissions, occur at the site. Multiple applications of the methane emission estimation tool (MEET), developed in this work, are presented. These results emphasize the importance of developing detailed emission inventories, which incorporate operational data, when comparing measurements to routine emissions. The model described in this work supports such comparisons and is freely available.

Modeling air emissions from complex facilities at detailed temporal and spatial resolution: The Methane Emission Estimation Tool (MEET)

Recent attention to methane emissions from oil and gas infrastructure has increased interest in comparing measurements with inventory emission estimates. While measurement methods typically estimate emissions over a few periods that are seconds to hours in length, current inventory methods typically produce long-term average emission estimates. This temporal mis-alignment complicates comparisons and leads to underestimates in the uncertainty of measurement methods. This study describes a new temporally and spatially resolved inventory emission model (MEET), and demonstrates the model by application to compressor station emissions - the key facility type in midstream natural gas operations The study looks at three common facility measurement methods: tracer flux methods for measuring station emissions, the use of ethane-methane ratios for source attribution of basin-scale estimates, and the behavior of continuous monitoring for leak detection at stations. Simulation results indicate that measurement methods likely underestimate uncertainties in emission estimates by failing to account for the variability in normal facility emissions and variations in ethane/methane ratios. A tracer-based measurement campaign could estimate emissions outside the 95% confidence interval of annual emissions 30% of the time, while ethane/methane ratios could be mis-estimated by as much as 50%. Use of MEET also highlights the need to improve data reporting from measurement campaigns to better capture the temporal and spatial variation in observed emissions.

Projecting the Temporal Evolution of Methane Emissions from Oil and Gas Production Basins

The methane emission intensity (methane emitted/gas produced or methane emitted/methane produced) of individual unconventional oil and gas production sites in the United States has a characteristic temporal behavior, exhibiting a brief period of decrease followed by a steady increase, with intensities after 10 years of production reaching levels that are 2-10 times the 10 year production-weighted average. Temporal patterns for methane emission intensity for entire production regions are more complex. Historical production data and facility data were used with a detailed basin-wide methane emission model to simulate the collective behavior of tens of thousands of wells and associated midstream facilities. For production regions with few to no new wells being brought to production, and existing wells having reached a mature stage, as in the Barnett Shale production region in north central Texas, the methane emission intensity gradually increases, as natural gas production decreases faster than emissions decrease, following the general pattern exhibited by individual wells. In production regions that are rapidly evolving, either with large numbers of new wells being put into production or with the introduction of source-specific regulations, the behavior is more complex. In the Eagle Ford Shale, which has had both a large number of new wells and the introduction of source-specific regulations, the methane emission intensity stays within relatively narrow bounds but the distribution of sources varies. As source distributions vary, basin-wide propane-to-methane and ethane-to-methane emission ratios vary, impacting methods used in source attribution.

A Searchable Database for Prediction of Emission Compositions from Upstream Oil and Gas Sources

Atmospheric emissions from oil and gas production operations are composed of multiple hydrocarbons and can have large variations in composition. Accurate estimates of emission compositions are needed to estimate the fate and impacts of emissions and to attribute emissions to sources. This work presents a database, constructed with empirical data and thermodynamic models, that can be queried to estimate hydrocarbon compositions from emission sources present at oil and gas production sites. The database can be searched for matches using between two and seven well parameters as query inputs (gas-to-oil ratio, API gravity, separator pressure, separator temperature, methane molar fraction in produced gas, ethane molar fraction of produced gas, and propane molar fraction in produced gas). Database query performance was characterized by comparing returns from database queries to a test data set. Application of the database to well parameters for tens of thousands of wells in the Barnett, Eagle Ford, and Fayetteville production regions demonstrates variations in emission compositions. Ethane to methane ratio varies by more than an order of magnitude from well to well and source to source. VOC to methane ratios are comparable in variability to ethane to methane ratios for most emission sources, but have a higher variability for emissions from flashing of liquid hydrocarbon tanks.

Projecting the Temporal Evolution of Methane Emissions from Oil and Gas Production Sites

Many recent studies have reported methane emissions from oil and gas production regions, often reporting results as a methane emission intensity (methane emitted as a percentage of natural gas produced or methane produced). Almost all of these studies have been instantaneous snapshots of methane emissions; however, total methane emissions from a production site and the methane emission intensity would be expected to evolve over time. A detailed site-level methane emission estimation model is used to estimate the temporal evolution of methane emissions and the methane emission intensity for a variety of well configurations with and without emission mitigation measures in place. The general pattern predicted is that total emissions decrease over time as production declines. Methane emission intensity shows complex behavior because production-dependent emissions decline at different rates and some emissions do not decline over time. Prototypical uncontrolled wet gas wells can have approximately half of their emissions over a 10 year period occur in the first year; instantaneous wellsite methane emission intensities range over a factor of 3 (0.62-2.00%) in the same period, with a 10 year production weighted-average lifecycle methane emission intensity of 0.79%. Including emission control in the form of a flare can decrease the average lifecycle methane emission intensity to 0.23%. Emissions from liquid unloadings, which are observed in subsets of wells, can increase the lifecycle methane emission intensity by up to a factor of 2-3, between 1.2 and 2.3%, depending on the characteristics of the unloadings. Emissions from well completion flowbacks raise the average lifecycle methane emission intensity from 0.79 to 0.81% for flowbacks with emission controls; for flowbacks with uncontrolled emissions, lifecycle methane emissions increase to 1.26%. Dry gas and oil wells show qualitatively similar temporal behavior but different absolute emission rates.

Congenital heart defects and intensity of oil and gas well site activities in early pregnancy

BACKGROUND

Preliminary studies suggest that offspring to mothers living near oil and natural gas (O&G) well sites are at higher risk of congenital heart defects (CHDs).

OBJECTIVES

Our objective was to address the limitations of previous studies in a new and more robust evaluation of the relationship between maternal proximity to O&G well site activities and births with CHDs.

METHODS

We employed a nested case-control study of 3324 infants born in Colorado between 2005 and 2011. 187, 179, 132, and 38 singleton births with an aortic artery and valve (AAVD), pulmonary artery and valve (PAVD), conotruncal (CTD), or tricuspid valve (TVD) defect, respectively, were frequency matched 1:5 to controls on sex, maternal smoking, and race and ethnicity yielding 2860 controls. We estimated monthly intensities of O&G activity at maternal residences from three months prior to conception through the second gestational month with our intensity adjusted inverse distance weighted model. We used logistic regression models adjusted for O&G facilities other than wells, intensity of air pollution sources not associated with O&G activities, maternal age and socioeconomic status index, and infant sex and parity, to evaluate associations between CHDs and O&G activity intensity groups (low, medium, and high).

RESULTS

Overall, CHDs were 1.4 (1.0, 2.0) and 1.7 (1.1, 2.6) times more likely than controls in the medium and high intensity groups, respectively, compared to the low intensity group. PAVDs were 1.7 (0.93, 3.0) and 2.5 (1.1, 5.3) times more likely in the medium and high intensity groups for mothers with an address found in the second gestational month. In rural areas, AAVDs, CTDs, and TVDs were 1.8 (0.97, 3.3) and 2.6 (1.1, 6.1); 2.1 (0.96, 4.5) and 4.0 (1.4, 12); and 3.4 (0.95, 12) and 4.6 (0.81, 26) times more likely than controls in the medium and high intensity groups.

CONCLUSIONS

This study provides further evidence of a positive association between maternal proximity to O&G well site activities and several types of CHDs, particularly in rural areas.

Use of Light Alkane Fingerprints in Attributing Emissions from Oil and Gas Production

Spatially resolved emission inventories were used with an atmospheric dispersion model to predict ambient concentrations of methane, ethane, and propane in the Eagle Ford oil and gas production region in south central Texas; predicted concentrations were compared to ground level observations. Using a base case inventory, predicted median propane/ethane concentration ratios were 106% higher (95% CI: 83% higher-226% higher) than observations, while median ethane/methane concentration ratios were 112% higher (95% CI: 17% higher-228% higher) than observations. Predicted median propane and ethane concentrations were factors of 6.9 (95% CI: 3-15.2) and 3.4 (95% CI: 1.4-9) larger than observations, respectively. Predicted median methane concentrations were 7% higher (95% CI: 39% lower-37% higher) than observations. These comparisons indicate that sources of emissions with high propane/ethane ratios (condensate tank flashing) were likely overestimated in the inventories. Because sources of propane and ethane emissions are also sources of methane emissions, the results also suggest that sources of emissions with low ethane/methane ratios (midstream sources) were underestimated. This analysis demonstrates the value of using multiple light alkanes in attributing sources of methane emissions and evaluating the performance of methane emission inventories for oil and natural gas production regions.