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QA/QC-ed Groundwater Level Time Series in PLM-1 and PLM-6 Monitoring Wells, East River, Colorado (2016-2022)

This data set contains QA/QC-ed (Quality Assurance and Quality Control) water level data for the PLM1 and PLM6 wells. PLM1 and PLM6 are location identifiers used by the Watershed Function SFA project for two groundwater monitoring wells along an elevation gradient located along the lower montane life zone of a hillslope near the Pumphouse location at the East River Watershed, Colorado, USA. These wells are used to monitor subsurface water and carbon inventories and fluxes, and to determine the seasonally dependent flow of groundwater under the PLM hillslope. The downslope flow of groundwater in combination with data on groundwater chemistry (see related references) can be used to estimate rates of solute export from the hillslope to the floodplain and river. QA/QC analysis of measured groundwater levels in monitoring wells PLM-1 and PLM-6 included identification and flagging of duplicated values of timestamps, gap filling of missing timestamps and water levels, removal of abnormal/bad and outliers of measured water levels. The QA/QC analysis also tested the application of different QA/QC methods and the development of regular (5-minute, 1-hour, and 1-day) time series datasets, which can serve as a benchmark for testing other QA/QC techniques, and will be applicable for ecohydrological modeling. The package includes a Readme file, one R code file used to perform QA/QC, a series of 8 data csv files (six QA/QC-ed regular time series datasets of varying intervals (5-min, 1-hr, 1-day) and two files with QA/QC flagging of original data), and three files for the reporting format adoption of this dataset (InstallationMethods, file level metadata (flmd), and data dictionary (dd) files).QA/QC-ed data herein were derived from the original/raw data publication available at Williams et al., 2020 (DOI: 10.15485/1818367). For more information about running R code file (10.15485_1866836_QAQC_PLM1_PLM6.R) to reproduce QA/QC output files, see README (QAQC_PLM_readme.docx). This dataset replaces the previously published raw data time series, and is the final groundwater data product for the PLM wells in the East River. Complete metadata information on the PLM1 and PLM6 wells are available in a related dataset on ESS-DIVE: Varadharajan C, et al (2022). https://doi.org/10.15485/1660962. These data products are part of the Watershed Function Scientific Focus Area collection effort to further scientific understanding of biogeochemical dynamics from genome to watershed scales. 2022/09/09 Update: Converted data files using ESS-DIVE’s Hydrological Monitoring Reporting Format. With the adoption of this reporting format, the addition of three new files (v1_20220909_flmd.csv, V1_20220909_dd.csv, and InstallationMethods.csv) were added. The file-level metadata file (v1_20220909_flmd.csv) contains information specific to the files contained within the dataset. The data dictionary file (v1_20220909_dd.csv) contains definitions of column headers and other terms across the dataset. The installation methods file (InstallationMethods.csv) contains a description of methods associated with installation and deployment at PLM1 and PLM6 wells. Additionally, eight data files were re-formatted to follow the reporting format guidance (er_plm1_waterlevel_2016-2020.csv, er_plm1_waterlevel_1-hour_2016-2020.csv, er_plm1_waterlevel_daily_2016-2020.csv, QA_PLM1_Flagging.csv, er_plm6_waterlevel_2016-2020.csv, er_plm6_waterlevel_1-hour_2016-2020.csv, er_plm6_waterlevel_daily_2016-2020.csv, QA_PLM6_Flagging.csv). The major changes to the data files include the addition of header_rows above the data containing metadata about the particular well, units, and sensor description. 2023/01/18 Update: Dataset updated to include additional QA/QC-ed water level data up until 2022-10-12 for ER-PLM1 and 2022-10-13 for ER-PLM6. Reporting format specific files (v2_20230118_flmd.csv, v2_20230118_dd.csv, v2_20230118_InstallationMethods.csv) were updated to reflect the additional data. R code file (QAQC_PLM1_PLM6.R) was added to replace the previously uploaded HTML files to enable execution of the associated code. R code file (QAQC_PLM1_PLM6.R) and ReadMe file (QAQC_PLM_readme.docx) were revised to clarify where original data was retrieved from and to remove local file paths.

54 ENVIRONMENTAL SCIENCES↗

Findings from the NETL Well Integrity Workshop: Insights for multiple subsurface energy operations

Wells are a core aspect of subsurface energy infrastructure. Ensuring the resilience of that infrastructure relies on the integrity of wells as engineered pathways that safely extract, inject, and store fluids in the subsurface. To identify areas where focused research can yield new insights to improve integrity and extend the operational life of wells, the United States (US) Department of Energys (DOE) National Energy Technology Laboratory (NETL) organized and hosted a workshop on well integrity research needs in May and June of 2021. The three-day workshop consisted of six technical sessions and 18 presentations from international well integrity experts on topics of geologic storage of carbon dioxide, natural gas, and hydrogen, as well as hydrocarbon and geothermal energy production. There were over 350 registrants from more than 10 countries, 4 major oil & gas companies, 14 US states, 8 US DOE National Laboratories, US Departments of Interior, Transportation, and Energy, and regulators from eight of ten US Environmental Protection Agency (EPA) regions and US EPA headquarters. Through presentations, moderated discussions, and an attendee survey several important areas for future research were identified. In this presentation, we highlight the findings of the NETL well integrity workshop and discuss future well integrity research needs.

carbon capture utilization and storage (CCUS)↗

Utah FORGE: Well 16B(78)-32 Drilling Data

This drilling data for Utah FORGE well 16B(78)-32 include a well survey, core summary, mud and mud temperature logs, daily reports of the drilling process, and additional data from the Pason oil and gas company. Well 16B(78)-32 serves as the production well for reservoir creation, fluid circulation, and demonstration of heat extraction for the FORGE project. It has been drilled as a doublet approximately 300 feet parallel to and above the injection well 16A(78)-32. The proposed total depth was 10,658 feet, which was exceeded. Spudding began on April 26th, 2023. As of June 20th, 2023, the total depth measured 10,947 feet and the vertical depth measured 8,357 feet. Drilling included the trial use of insulated drill pipe (IDP) from Eavor Technologies, which was considered a success. IDP restricts counter-current heat transfer between drilling fluid inside the drill string and hotter returning fluid in the annulus, thereby ensuring the bottomhole assembly (BHA) remains submerged in cool fluid. Eavor rented 350 joints of IDP to FORGE which were run in two consecutive BHAs at the well. The results of this trial are included here.

15 GEOTHERMAL ENERGY↗

Air quality impacts from the development of unconventional oil and gas well pads: Air toxics and other volatile organic compounds

Unconventional oil and natural gas development (UOGD) has expanded rapidly across the United States in recent decades and raised concerns about associated air quality impacts. While significant effort has been made to quantify methane emissions, relatively few observations have been made of Volatile Organic Compounds (VOCs), especially during drilling and completion of new wells. Extensive air monitoring during development of several large, multi-well pads in Broomfield, Colorado, in the Denver-Julesburg Basin, provides a novel opportunity to examine changes in local air toxics and other VOC concentrations during well drilling and completions and production. These operations offer an especially useful case to study as several management practices were implemented to reduce emissions (e.g., electrified, grid-powered drill rigs and closed loop fluid handling systems to reduce truck traffic and limit fluid handling on the pad). With simultaneous measurements of methane and 50 VOCs from October 2018 to December 2022 at as many as 19 sites near well pads, in adjacent neighborhoods, and at a more distant reference location, we identify impacts from each phase of well development and production. Use of weekly, time-integrated canisters, a Proton Transfer Reaction Mass Spectrometer (PTR-MS), continuous photoionization detectors (PID) to trigger canister collection upon detection of VOC-rich plumes, and an instrumented vehicle, provided a powerful suite of measurements to characterize both transient plumes and longer-term changes in air quality. Prior to the start of well development, VOC gradients were small across Broomfield. Once drilling commenced, concentrations of oil and gas (O&G) related VOCs, including alkanes and aromatics, increased around active well pads. Concentration increases were clearly apparent during certain operations, including drilling, coil tubing/millout operations, and production tubing installation. Emissions of C 8 –C 10 n-alkanes during drilling operations highlighted the importance of VOC emissions from synthetic drilling mud chosen to reduce odor impacts. More than 90 samples were collected of transient plumes. Using composition measurements, meteorological data, and information about well pad activities, these plumes were connected with specific UOGD operations including drilling, flowback, and production equipment maintenance. The chemical signatures of these plumes differed by operation type (e.g., C 8 –C 10 n-alkanes constituted a larger fraction of measured VOCs in drilling-related plumes). Concentrations of individual, oil and gas-related VOCs in these plumes were often several orders of magnitude higher than in background air, with maximum ethane and benzene concentrations of 79,600 and 819 ppbv, respectively. Because these plumes typically impact a monitoring site for just several minutes, they are easily missed by slower-responding instruments. Study measurements highlight future emission mitigation opportunities during UOGD operations, including better control of emissions from shakers that separate drill cuttings from drilling mud, production separator maintenance operations, and periodic emptying of sand cans during flowback operations.

54 ENVIRONMENTAL SCIENCES↗

Wildfires increasingly threaten oil and gas wells in the western United States with disproportionate impacts on marginalized populations

The western United States is home to most of the nation’s oil and gas production and, increasingly, wildfires. Here, we examined historical threats of wildfires for oil and gas wells, the extent to which wildfires are projected to threaten wells as climate change progresses, and exposure of human populations to these wells. From 1984 to 2019, we found that, cumulatively, 102,882 wells were located in wildfire burn areas, and 348,853 people were exposed (resided within ≤ 1 km). During this period, we observed a 5-fold increase in the number of wells in wildfire burn areas and a doubling of the population within 1 km of these wells. These trends are projected to increase by late century, likely threatening human health. Approximately 2.9 million people reside within 1 km of wells in areas with high wildfire risk, and Black, Hispanic, and Native American people have disproportionately high exposure to wildfire-threatened wells.

02 PETROLEUM↗

Unlocking Solutions: Innovative Approaches to Identifying and Mitigating the Environmental Impacts of Undocumented Orphan Wells in the United States

In the United States, hundreds of thousands of undocumented orphan wells have been abandoned, leaving the burden of managing environmental hazards to governmental agencies or the public. These wells, a result of over a century of fossil fuel extraction without adequate regulation, lack basic information like location and depth, emit greenhouse gases, and leak toxic substances into groundwater. For most of these wells, basic information such as well location and depth is unknown or unverified. Addressing this issue necessitates innovative and interdisciplinary approaches for locating, characterizing, and mitigating their environmental impacts. Our survey of the United States revealed the need for tools to identify well locations and assess conditions, prompting the development of technologies including machine learning to automatically extract information from old records (95%+ accuracy), remote sensing technologies like aero-magnetometers to find buried wells, and cost-effective methods for estimating methane emissions. Notably, fixed-wing drones equipped with magnetometers have emerged as cost-effective and efficient for discovering unknown wells, offering advantages over helicopters and quadcopters. Efforts also involved leveraging local knowledge through outreach to state and tribal governments as well as citizen science initiatives. These initiatives aim to significantly contribute to environmental sustainability by reducing greenhouse gases and improving air and water quality.

54 ENVIRONMENTAL SCIENCES↗

Chemical Characterization of Natural Gas Leaking from Abandoned Oil and Gas Wells in Western Pennsylvania

The U.S. Environmental Protection Agency estimates that there are over 3.2 million abandoned wells in the United States. Studies conducted on gas emissions from abandoned wells have been limited to methane, a powerful greenhouse gas, due to concerns regarding climate change. However, volatile organic compounds (VOCs), including benzene, a known human carcinogen, are known to be associated with upstream oil and gas development and hence could also be released when methane is emitted to the atmosphere. In this investigation, we analyze gas from 48 abandoned wells in western Pennsylvania for fixed gases, light hydrocarbons, and VOCs and estimate associated emission rates. We demonstrate that (1) gas from abandoned wells contains VOCs, including benzene; (2) VOCs are emitted from abandoned wells, the magnitude of which depends on the flow rate and concentration of VOCs in the gas stream; and (3) nearly one-quarter of abandoned wells are located within 100 m of buildings, including residences, in Pennsylvania. Together, these observations indicate that further investigation is necessary to determine whether emissions from abandoned wells pose an inhalation risk to people living, working, or congregating near abandoned wells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tunable coherent mixed-dimensional perovskite heterojunctions and quantum wells grown from solution

Coherent heterojunctions, quantum wells and multiple quantum wells are needed for high-performance devices; these are generally grown via a dedicated vapour phase epitaxy process. Here we demonstrate the growth of coherent perovskite heterojunctions and quantum wells made of mixed-dimensional perovskites using a solution process. By exploiting the solubility difference of methylammonium (MA + ) and 4-(aminomethyl)piperidinium (4AMP 2+ ), we assemble layered perovskites with different layer numbers. The resulting 4AMP-MA n–1 Pb n I 3n+1 materials each with different layer numbers or bandgaps form quantum wells. Heterojunctions and quantum wells made of 4AMP-MA 2 Pb 3 I 10 (n = 3) and 4AMP-MAPb 2 I 7 (n = 2) with various barrier thickness are tailored by the solution temperature profile during crystal growth. Multiple quantum wells have been formed by cycling temperature profiles. The planar heterojunction and quantum wells have lattice matching without interfacial defects, and exhibit strong thermal stability. Type I band alignment at the n = 2/n = 3 heterojunction is confirmed by both computation and optical studies. In conclusion, this study opens a new direction for the development of sophisticated perovskite heterojunction and quantum well devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Evaluating Production Implications of Pressure Maintenance in Unconventional Oil and Gas Wells using a Machine Learning Modeling Approach: Case Study in the Permian Basin

This study implements the proprietary machine learning-based model (model) developed under the 2022 study titled “Evaluating the Impact of Proprietary Oil & Gas Data on Machine Learning Model Performance Using a Quasi-Experimental Analytical Approach” for forecasting unconventional oil and gas production using well data from the Permian Basin. The model, developed using an exclusive dataset that includes time series production data from an operator in the Permian Basin, is designed to jointly predict daily oil, gas, and water production for horizontal wells as a function of bottomhole pressure drawdown, spatial placement across the study domain, and well-completion attributes. In this study, the model was explicitly applied to explore its utility to evaluate the impact of varying drawdown strategies on the production forecast of a well in the Permian Basin dataset. Managing pressure drawdown has been identified as a way to improve estimated ultimate recovery (EUR) from unconventional shale wells due to the stress-dependent nature of fractures in shale reservoirs. Research has shown that applying a lower pressure drawdown helps to maintain the reservoir conductivity, resulting in higher productivity over the life of a well. Historic bottomhole pressure data from the well over time was used as a benchmark from which to set more and less aggressive pressure decline rates as bounding modeling cases. All pressure decline rates/strategies were forecasted over 5 years, and the model was used to generate oil, water, and gas prediction over the same timeframe. This report presents the results from the production forecast and discusses potential operational and economic implications, with contrasting perspectives between well productivity and profitability given typical oil and gas economics and the volatility in the oil and gas market.

02 PETROLEUM↗

Ultrafast optical switches using quantum wells

Colloidal quantum wells have discrete energy states and electrons in the quantum wells undergo interband and intersubband state transitions. The transmissivity of a colloidal quantum well may be tuned by actively controlling the states of the colloidal quantum wells enabling ultrafast optical switching. A primary excitation source is configured to provide a primary excitation to promote a colloidal quantum well from a ground state to a first excitation state. A secondary excitation source is configured to provide a secondary excitation to the colloidal quantum well to promote the colloidal quantum well from the first excitation state to the second excitation state with the first and second excitation states being subbands in the conduction band of the colloidal quantum well.

Diroll, Benjamin↗

FECM/NETL Unconventional Shale Well Economic Model (UShWEM)

FECM/NETL Unconventional Shale Well Economic Model (UShWEM) is an Excel-based model that evaluates the economics of an unconventional shale well on a per-well and per-pad basis. The model calculates the net cash flow, internal rate of return (IRR), net present value (NPV), earnings before interest, taxes, depreciation, and amortization (EBITDA), payout month and year, and breakeven price (for either oil- or gas-wells). The model can be used to estimate the economics of a well or pad over its lifetime (development through site reclamation) based on (1) the capital and operating costs associated with well/pad development and operations, (2) the revenue associated with oil, gas, and condensate production streams, and (3) accounting for relevant tax policies and asset depreciation applicable for oil and gas operations. The main input for the model is the completion design and production data. Key financial considerations in the model include oil, gas, and condensate market prices, tax-related settings, royalty rates, the discount rate, minimum economic hurdle (IRR) [if performing break-even analysis], and project contingency. The financial consideration can be adjusted to reflect the level of granularity the user requires as input when calculating the economics for a well or pad development. In addition, the model affords users the option to provide their user inputs for all cost categories considered. As a result, the model can be used to generate a multitude of scenario cases for sensitivity analysis of the various financial considerations, as well as production and cost profiles. To make this seamless, the model has the capability for key economic outputs to be exported in large batches through macros-enabled functions on its “Model Output Summary” and “Multi-Well Cost Analysis. The spreadsheet model includes macros and user-defined functions, so the user must enable Excel’s macro capability for the model to function correctly.

Sheriff, Alana↗

Inter-well connectivity detection in CO 2 WAG projects using statistical recurrent unit models

Routine well-wise injection and production measurements contain significant information on subsurface structure and properties. Data-driven technology that interprets surface data into subsurface structure or properties can assist operators in making informed decisions by providing a better understanding of field assets. Our machine-learning framework is built on the statistical recurrent unit (SRU) model and interprets well-based injection/production data into inter-well connectivity without relying on a geologic model. We test it on synthetic and field-scale CO 2 EOR projects utilizing the water-alternating-gas (WAG) process. SRU is a special type of recurrent neural network (RNN) that allows for better characterization of temporal trends, by learning various statistics of the input at different time scales. In our application, the complete states (injection rate, pressure and cumulative injection) at injectors and pressure states at producers are fed to SRU as the input and the phase rates at producers are treated as the output. Once the SRU is trained and validated, it is then used to assess the connectivity of each injector to any producer using permutation variable importance method, wherein inputs corresponding to an injector are shuffled and the increase in prediction error at a given producer is recorded as the importance (connectivity metric) of the injector to the producer. This method is tested in both synthetic and field-scale cases. The validation of the proposed data-driven inter-well connectivity assessment is performed using synthetic data from simulation models where inter-well connectivity can be easily measured using the streamline-based flux allocation. The SRU model is shown to offer excellent prediction performance on the synthetic case. Despite significant measurement noise and frequent well shut-ins imposed in the field-scale case, the SRU model offers good prediction accuracy, the overall relative error of the phase production rates at most producers ranges from 10% to 30%. It is shown that the dominant connections identified by the data-driven method and streamline method are in close agreement. This significantly improves confidence in our data-driven procedure. The novelty of this work is that it is purely data-driven method and can directly interpret routine surface measurements to intuitive subsurface knowledge. Furthermore, the streamline-based validation procedure provides physics-based backing to the results obtained from data analytics. This study results in a reliable and efficient data analytics framework that is well-suited for large field applications.

42 ENGINEERING↗

Bound and Continuum Intersubband Transitions in Colloidal Quantum Wells

Quantum well intersubband transitions are critical for quantum cascade lasers and infrared photodetectors. Control of band offsets allows bound-to-bound intersubband transitions, with confinement of both initial and final states, and bound-to-continuum transitions, in which only the initial state is energetically confined within the potential well. Both types of transitions are also achieved in colloidal CdSe wells by changing the heterostructure shell. Bare wells have narrow intersubband transitions spanning the near-infrared spectrum following effective mass predictions. Atomically precise core/shells enable a readily adjusted potential well for electrons. For CdSe/ZnS, bound-to-bound transitions are narrow and redshift with shell thickness. By contrast, broad bound-to-continuum absorptions are found in CdSe/CdS. Due to small conduction band offsets, higher conduction band states of the well are more delocalized into the CdS shell. In conclusion, these measurements provide unique data to understand the electronic structure of colloidal quantum wells and chart a path to atomically precise optoelectronic materials for the mid-infrared.

colloidal atomic layer deposition↗

Basin-scale analysis of Mokelumne River Formation for multi-well CO 2 injection

Large-scale carbon sequestration will likely require multiple projects injecting CO 2 into the same subsurface formation, raising concerns about safe operation and efficient use of storage capacity. This study evaluates the long-term response of the Mokelumne River Formation in California’s Sacramento Basin to multi-megaton CO 2 injection using three geologic models of the formation and the open-source simulator GEOS. The analysis focuses on three aspects of reservoir performance: (1) average pressure increase and dissolved CO 2 mass after 30 years for varying well counts and injection rates, (2) pressure interference in a multi-well configuration, and (3) dynamic storage capacity with identification of overpressure-prone regions. The results show that average formation pressure increases linearly with injected mass, while CO 2 dissolution exhibits mixed scaling: approximately linear with the number of wells but sublinear with injection rate, indicating that distributing injection across more wells enhances dissolution more effectively than increasing per-well rates. Pressure-interference effects are significant, with lower-permeability conditions delaying their onset but amplifying their magnitude at later times. Dynamic capacity, defined by the first occurrence of pressure exceeding the local overburden-based limit anywhere in the formation, varies across geologic models and assumed overburden pressure gradients. A lower fidelity geologic model predicts nearly twice the storage capacity of the two higher fidelity models, which consistently estimate approximately 1 Gt under the upper-bound overburden pressure gradient considered for the Sacramento Basin. In all model scenarios, overpressure develops away from injection wells, particularly in higher-elevation regions, highlighting the importance of basin-scale modelling for identifying risks beyond the immediate well vicinity.

Basin-scale↗

Seismic monitoring of well integrity

Seismic tube waves, produced by flexure of the well boundary, pressure changes in the fluid in the well, and deformation of the material immediately surrounding the well, are particularly sensitive to variations in the state of the well. In this work, we evaluate a direct approach for generating and observing tube waves as a means of detecting well damage. While we find that it can be difficult to reliably excite observable tube waves without a very strong surface source, time-frequency techniques can be employed to increase the detectability of tube wave reflections. New technologies, particularly distributed acoustic sensing, hold great promise for evaluating well integrity by monitoring tube waves, temperature changes, and seismic noise due to well deformation and fluid leakage.

58 GEOSCIENCES↗

Procedure for locating oil and gas wells in the Appalachian Basin

Locating undocumented (or poorly documented) oil and gas wells for environmental assessment is often difficult. Remnant features that confirm the presence of a well (intact casing/wellhead, well bore, etc.) are typically less than a meter in size and often are obscured from direct observation on the ground or from the air (by dense vegetation, for example). To efficiently find such features, it is useful to first systematically compile publicly available digital data at progressively smaller scales prior to embarking on field campaigns. Further, the information presented here describes the procedure developed and used by the U.S. Department of Energy's National Energy Technology Laboratory to locate potential oil and gas well sites for follow-up field verification and characterization. Digital data are first compiled from national and state resources such as well location/production databases, historical topographic maps, historical aerial photographs, and LiDAR data. Although each data set is likely to be incomplete or inaccurate to some extent, combining the data resources using geographic information system technology can generate potential well site targets with a higher degree of confidence, which improves the efficiency of fieldwork activities. This workflow was developed in the Appalachian Basin region, and although certain aspects may be unique, the general process would be applicable to locating undocumented wells in other regions.

54 ENVIRONMENTAL SCIENCES↗

Hydraulic Testing of the Lost Lake Aquifer Near Recovery Well RWM001R

An aquifer pumping test was conducted on the Lost Lake Aquifer Zone (LLAZ) at the recently installed recovery well RWM001R in accordance with the approved test plan (Dixon, 2024). The objective of the testing was to determine baseline well performance parameters and aquifer hydraulic conductivity. This testing consisted of two step-drawdown tests to determine well performance properties and two constant pumping rate aquifer tests with recovery periods to determine aquifer hydraulic properties. Well performance parameters determined included specific capacity, well efficiency, and head loss coefficients. The results of the step-drawdown testing are presented in Tables ES1 and ES2 whereas the results of the constant pumping rate testing are presented in Table ES3. The average specific capacity of RWM001R operating at pump capacity (~54 gpm) was 2.2 gpm/ft using data from the final step of both tests. The average well efficiency determined from both step-drawdown tests was 56% using data from the final step of both tests. For both step-drawdown tests, well efficiency was inversely related to the pumping rate with the average efficiency decreasing from approximately 79% to 56%. Aquifer head loss coefficients from both tests were comparable (Table ES2).

54 ENVIRONMENTAL SCIENCES↗

Orphaned oil and gas well methane emission rates quantified using Gaussian plume inversions of ambient observations

Abstract. Annually, ∼ 3.6 million abandoned oil and gas wells in the US emit a combined ∼ 2.6 Tg methane (CH4), adversely affecting climate and regional air quality. However, these estimates depend on emission factors derived from measuring subpopulations of wells that vary by orders of magnitude due to very limited field sampling and poorly characterized distributions. Currently, US protocols to remediate orphaned wells lacks standardized quantification methods needed to both prioritize plugging and account for emission reductions. Therefore, sensitive, reliable, affordable, and scalable CH4 flux quantification methods are needed. We report the use of a simple Gaussian plume method where the dispersion parameters are constrained by in situ ground measurements of CH4 concentration at four locations 7.5–49 m downwind of the orphan well as well as local winds to estimate the leak rate from an orphan well. We derive a flux of 10.53 ± 1.16 kg CH4 h−1 during a venting procedure in April 2023 that agrees with the directly measured volumetric flow rate of 9.00 ± 0.25 kg CH4 h−1. This is 71 % greater than the 5.3 kg CH4 h−1 flux measured 7 months prior. Additionally, we discovered a secondary leak through the surface casing inferred as 0.43–0.67 kg CH4 h−1 both by our ground Gaussian analysis and by transecting the plume with an uncrewed aerial system (UAS). We show that in situ determination of the dispersion parameters used in our Gaussian inversions allows us to measure methane emissions to 15 % accuracy, significantly reducing errors when compared to the standard practice of assuming stability class. Our results help develop simpler methods and protocols for robust orphan well emission quantification that can be used for reporting.

Follansbee, Emily↗