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At least 199 records · Page 11

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗

A multiphysics coupling framework for exascale simulation of fracture evolution in subsurface energy applications

Predicting the evolution of fractured media is challenging due to coupled thermal, hydrological, chemical and mechanical processes that occur over a broad range of spatial scales, from the microscopic pore scale to field scale. We present a software framework and scientific workflow that couples the pore scale flow and reactive transport simulator Chombo-Crunch with the field scale geomechanics solver in GEOS to simulate fracture evolution in subsurface fluid-rock systems. This new multiphysics coupling capability comprises several novel features. An HDF5 data schema for coupling fracture positions between the two codes is employed and leverages the coarse resolution of the GEOS mechanics solver which limits the size of data coupled, and is, thus, not taxed by data resulting from the high resolution pore scale Chombo-Crunch solver. The coupling framework requires tracking of both before and after coarse nodal positions in GEOS as well as the resolved embedded boundary in Chombo-Crunch. We accomplished this by developing an approach to geometry generation that tracks the fracture interface between the two different methodologies. The GEOS quadrilateral mesh is converted to triangles which are organized into bins and an accessible tree structure; the nodes are then mapped to the Chombo representation using a continuous signed distance function that determines locations inside, on and outside of the fracture boundary. The GEOS positions are retained in memory on the Chombo-Crunch side of the coupling. The time stepping cadence for coupled multiphysics processes of flow, transport, reactions and mechanics is stable and demonstrates temporal reach to experimental time scales. The approach is validated by demonstration of 9 days of simulated time of a core flood experiment with fracture aperture evolution due to invasion of carbonated brine in wellbore-cement and sandstone. We also demonstrate usage of exascale computing resources by simulating a high resolution version of the validation problem on OLCF Frontier.

97 MATHEMATICS AND COMPUTING↗

Characterizing Natural Organic Matter Transformations by Microbial Communities in Terrestrial Subsurface Ecosystems: A Critical Review of Analytical Techniques and Challenges

Determining the mechanisms, traits, and pathways that regulate microbial transformation of natural organic matter (NOM) is critical to informing our understanding of the microbial impacts on the global carbon cycle. The capillary fringe of subsurface soils is a highly dynamic environment that remains poorly understood. Characterization of organo-mineral chemistry combined with a nuanced understanding of microbial community composition and function is necessary to understand microbial impacts on NOM speciation in the capillary fringe. We present a critical review of the popular analytical and omics techniques used for characterizing complex carbon transformation by microbial communities and focus on how complementary information obtained from the different techniques enable us to connect chemical signatures with microbial genes and pathways. This holistic approach offers a way forward for the comprehensive characterization of the formation, transformation, and mineralization of terrestrial NOM as influenced by microbial communities.

59 BASIC BIOLOGICAL SCIENCES↗

Surface and subsurface oceanographic features drive forage fish distributions and aggregations: Implications for prey availability to top predators in the US Northeast Shelf ecosystem

Abstract Forage fishes are a critical food web link in marine ecosystems, aggregating in a hierarchical patch structure over multiple spatial and temporal scales. Surface‐level forage fish aggregations (FFAs) represent a concentrated source of prey available to surface‐ and shallow‐foraging marine predators. Existing survey and analysis methods are often imperfect for studying forage fishes at scales appropriate to foraging predators, making it difficult to quantify predator–prey interactions. In many cases, general distributions of forage fish species are known; however, these may not represent surface‐level prey availability to predators. Likewise, we lack an understanding of the oceanographic drivers of spatial patterns of prey aggregation and availability or forage fish community patterns. Specifically, we applied Bayesian joint species distribution models to bottom trawl survey data to assess species‐ and community‐level forage fish distribution patterns across the US Northeast Continental Shelf (NES) ecosystem. Aerial digital surveys gathered data on surface FFAs at two project sites within the NES, which we used in a spatially explicit hierarchical Bayesian model to estimate the abundance and size of surface FFAs. We used these models to examine the oceanographic drivers of forage fish distributions and aggregations. Our results suggest that, in the NES, regions of high community species richness are spatially consistent with regions of high surface FFA abundance. Bathymetric depth drove both patterns, while subsurface features, such as mixed layer depth, primarily influenced aggregation behavior and surface features, such as sea surface temperature, sub‐mesoscale eddies, and fronts influenced forage fish diversity. In combination, these models help quantify the availability of forage fishes to marine predators and represent a novel application of spatial models to aerial digital survey data.

54 ENVIRONMENTAL SCIENCES↗

Time-lapse VSP integration and calibration of subsurface stress field utilizing machine learning approaches: A case study of the morrow B formation, FWU

This study aims to develop a methodology for calibrating subsurface stress changes through time-lapse vertical seismic profiling (VSP) integration. The selected study site is a region around the injector well located within Farnsworth field unit (FWU), where there is an ongoing CO 2 -enhanced oil recovery (EOR) operation. In our study, a site-specific rock physics model was created from extensive geological, geophysical, and geomechanical characterization through 3D seismic data, well logs, and core assessed as part of the 1D MEM conducted on the characterization well within the study area. Here, the Biot-Gassmann workflow was utilized to combine the rock physics and reservoir simulation outputs to determine the seismic velocity change due to fluid substitution. Modeled seismic velocities attributed to mean effective stress were determined from the geomechanical simulation outputs, and the stress-velocity relationship developed from ultrasonic seismic velocity measurements. A machine learning-assisted workflow comprised of an artificial neural network and a particle swarm optimizer (PSO) was utilized to minimize a penalty function created between the modeled seismic velocities and the observed time-lapse VSP dataset. The successful execution of this workflow has affirmed the suitability of acoustic time-lapse measurements for 4D-VSP geomechanical stress calibration pending measurable stress sensitivities within the anticipated effective stress changes and the availability of suitable and reliable datasets for petroelastic modeling. © 2023 Society of Chemical Industry and John Wiley & Sons, Ltd.

58 GEOSCIENCES↗

Geophysical methods reveal the soil architecture and subsurface stratigraphic heterogeneities across land-lake interfaces along Lake Erie

Abstract Purpose The land-lake interface is a unique zone where terrestrial and aquatic ecosystems meet, forming part of the Earth’s most geochemically and biologically active zones. The unique characteristics of this interface are yet to be properly understood due to the inherently high spatiotemporal variability of subsurface properties, which are difficult to capture with the traditional soil sampling methods. Geophysical methods offer non-invasive techniques to capture variabilities in soil properties at a high resolution across various spatiotemporal scales. Methods We combined electromagnetic induction (EMI), electrical resistivity tomography (ERT), and ground penetrating radar (GPR) with data from soil cores and in situ sensors to investigate hydrostratigraphic heterogeneities across land-lake interfaces along the western basin of Lake Erie. Results EMI revealed high spatial heterogeneities in ECa distribution across the land-lake interfaces, with higher values in the wetland and transition zones compared to the upland zone. Soil ECa maps matched soil maps from a public database with the hydric soil units delineated as high conductivity zones (ECa > 40 mS/m). ERT and GPR showed vertical variation in soil properties with clear stratigraphic boundaries, and correlation of ERT profiles with lithologs from piezometers revealed the stratigraphic units of silt–clay and till sequence down to 3.5 m depth which are consistent with the surficial geology of the study area. Conclusions These results validate the use of multiple geophysical methods for extrapolating soil properties and mapping stratigraphic structures at land-lake interfaces, thereby providing the missing information required to improve the earth system model (ESM) of coastal interfaces.

54 ENVIRONMENTAL SCIENCES↗

Revealing the Subsurface Basal $\langle$a$\rangle$ Dislocation Activity in Magnesium Through Lattice Rotation Analysis

A method was proposed in this study to reveal the subsurface basal dislocation activity in Mg-Y alloy and determine the corresponding Burgers vector. This is achieved by correlating the slip directions of dislocations to the lattice rotation represented by the {0001} pole figure. The identified basal slip system by this approach was verified by micro-Laue diffraction. This method can be applied as a complementary method to the conventional slip trace analysis to study the dislocation behavior of Mg alloys.

36 MATERIALS SCIENCE↗

Solubility controls on plutonium and americium release in subsurface environments exposed to acidic processing wastes

To identify the role of waste composition and sediment interactions in controlling Pu and Am mobility in contaminated sediments at Hanford, a legacy nuclear site, Pu and Am concentrations in solutions equilibrated with contaminated sediments from beneath the 216-Z-9 (Z-9) Trench were compared to the solubilities of PuO 2 materials, synthesized by methods representative of the disposed wastes, in the absence of sediments. Furthermore, this work shows that the solubilities of PuO 2 materials synthesized by different methods, and with varying particle sizes, agree with PuO 2 (am,hyd), although dissolution kinetics differed between materials. According to saturation index (SI) calculations, PuO 2 (am,hyd) is likely also controlling Pu release from sediments under conditions where phosphate concentrations are low. However, both Pu-phosphate and Am-phosphate phases, identified in SI calculations and by high resolution transmission electron microscopy, play roles in controlling release in low pH, high phosphate, shallow sediments just below the Z-9 Trench. The elevated phosphate is likely due to decomposition of tributyl phosphate from waste solutions over time. Sediments from deeper in the subsurface beneath the Z-9 Trench are less acidic and contain less phosphate, with Pu solubility likely controlled by PuO 2 (am,hyd) that precipitated following neutralization of the acidic waste stream. Controls on Am concentrations in deeper sediments are more complex and potentially involve sediment adsorption and/or release from Pu (1-x) Am x O 2 following Am in-growth. The concentrations of both Pu and Am were elevated in the colloidal fraction associated with shallow sediments, but not in PuO 2 experiments, suggesting the presence of Pu/Am pseudocolloids (e.g., Pu/Am associated with mineral colloids). However, Pu and Am association with the colloidal size fraction was not observed in deeper sediments, suggesting transport of Pu and Am to these depths beneath the Z-9 Trench was not due to colloidal transport.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Surface and subsurface characterization of laser-interference structured Ti6Al4V

Ti6Al4V specimens were exposed to high-energy laser pulses of 1.24 J/cm 2 fluences per pulse using a two-beam optical configuration to attain laser-interference. In addition to the formation of periodic surface textures by laser-interference, scanning electron microscope (SEM) images demonstrated several microstructural changes on the surface processed. Moreover, the surface and subsurface of Ti6Al4V specimens were characterized for the as-received and laser-interference processed conditions using x-ray photoelectron spectroscopy (XPS) and electron energy dispersive spectroscopy (EDS). The XPS data showed that this laser technique is effective at removal of surface contaminants for Ti6Al4V. The XPS analysis also revealed the formation of an oxy-nitride layer on the laser treated material. Finally, the microstructure analysis indicates that grain refinement, dendrite and twin structures were found near the surface due to laser processing.

36 MATERIALS SCIENCE↗

Long-term CRISPR locus dynamics and stable host-virus co-existence in subsurface fractured shales

Viruses are the most ubiquitous biological entities on Earth. Even so, elucidating the impact of viruses on microbial communities and associated ecosystem processes often requires identification of unambiguous host-virus linkages-an undeniable challenge in many ecosystems. Subsurface fractured shales present a unique opportunity to first make these strong linkages via spacers in CRISPR-Cas arrays and subsequently reveal complex long-term host-virus dynamics. Here, we sampled two replicated sets of fractured shale wells for nearly 800 days, resulting in 78 metagenomes from temporal sampling of six wells in the Denver-Julesburg Basin (Colorado, USA). At the community level, there was strong evidence for CRISPR-Cas defense systems being used through time and likely in response to viral interactions. Within our host genomes, represented by 202 unique MAGs, we also saw that CRISPR-Cas systems were widely encoded. Together, spacers from host CRISPR loci facilitated 2,110 CRISPR-based viral linkages across 90 host MAGs spanning 25 phyla. We observed less redundancy in host-viral linkages and fewer spacers associated with hosts from the older, more established wells, possibly reflecting enrichment of more beneficial spacers through time. Leveraging temporal patterns of host-virus linkages across differing well ages, we report how host-virus co-existence dynamics develop and converge through time, possibly reflecting selection for viruses that can evade host CRISPR-Cas systems. Together, our findings shed light on the complexities of host-virus interactions as well as long-term dynamics of CRISPR-Cas defense among diverse microbial populations.

59 BASIC BIOLOGICAL SCIENCES↗

Selecting representative geological realizations to model subsurface CO 2 storage under uncertainty

Carbon capture and storage (CCS) is one of the quickest and most effective solutions for reducing carbon emissions. The majority of subsurface storage occurs in saline aquifers, for which geological information is lacking which in turn results in geological uncertainty. To evaluate uncertainty in CO 2 injection projections, the use of multiple geological realizations (GRs) has been practiced very commonly. In this approach, hundreds or thousands of high-resolution GRs is used that quickly becomes computationally expensive. This issue can be addressed with representative geological realizations (RGRs) that preserve the uncertainty domain of the ensemble GRs. Here, in this study, we propose the use of unsupervised machine learning (UML) frameworks, including dissimilarity measurement, dimensionality reduction, clustering and sampling algorithms ta select a predetermined number of RGRs. We compare the simulation outputs of the RGR sets and the ensemble using the Kolmogorov–Smirnov (KS) test to select the best UML. The UML frameworks and their associated selection processes are evaluated using a saline aquifer with a single CO 2 injection well and 200 GRs with varying uncertain petrophysical characteristics. The best UML framework is selected to use only 5% of the GRs while maintaining the uncertainty domain of the ensemble GRs. In addition, the best UML framework is tested using a saline aquifer with three CO 2 injection wells and varied GRs. The results show that our proposed UML framework can be used to choose RGRs, capturing the whole uncertainty domain. Our approach leads to a significant reduction in the computational cost associated with scenario testing, decision-making, and development planning for CO 2 storage sites under geological uncertainty.

58 GEOSCIENCES↗

Comparison of machine learning and electrical resistivity arrays to inverse modeling for locating and characterizing subsurface targets

Here, this study evaluates the performance of multiple machine learning (ML) algorithms and electrical resistivity (ER) arrays for inversion with comparison to a conventional Gauss-Newton numerical inversion method. Four different ML models and four arrays were used for the estimation of only six variables for locating and characterizing hypothetical subsurface targets. The combination of dipole-dipole with Multilayer Perceptron Neural Network (MLP-NN) had the highest accuracy. Evaluation showed that both MLP-NN and Gauss-Newton methods performed well for estimating the matrix resistivity while target resistivity accuracy was lower, and MLP-NN produced sharper contrast at target boundaries for the field and hypothetical data. Both methods exhibited comparable target characterization performance, whereas MLP-NN had increased accuracy compared to Gauss-Newton in prediction of target width and height, which was attributed to numerical smoothing present in the Gauss-Newton approach. MLP-NN was also applied to a field dataset acquired at U.S. DOE Hanford site.

54 ENVIRONMENTAL SCIENCES↗

Gas diffusion through variably-water-saturated zeolitic tuff: Implications for transport following a subsurface nuclear event

Noble gas transport through geologic media has important applications in the characterization of underground nuclear explosions (UNEs). Without accurate transport models, it is nearly impossible to distinguish between xenon signatures originating from civilian nuclear facilities and UNEs. Understanding xenon transport time through the earth is a key parameter for interpreting measured xenon isotopic ratios. One of the most challenging aspects of modeling gas transport time is accounting for the effect of variable water saturation of geological media. In this study, we utilize bench-scale laboratory experiments to characterize the diffusion of krypton, xenon, and sulfur hexafluoride (SF6) through intact zeolitic tuff under different saturations. Here, we demonstrate that the water in rock cores with low partial saturation dramatically affects xenon transport time compared to that of krypton and SF6 by blocking sites in zeolitic tuff that preferentially adsorb xenon. This leads to breakthrough trends that are strongly influenced by the degree of the rock saturation. Xenon is especially susceptible to this phenomenon, a finding that is crucial to incorporate in subsurface gas transport models used for nuclear event identification. We also find that the breakthrough of SF6 diverges significantly from that of noble gases within our system. When developing field scale models, it is important to understand how the behavior of xenon deviates from chemical tracers used in the field, such as SF6 (Carrigan et al., 1996). These new insights demonstrate the critical need to consider the interplay between rock saturation and fission product sorption during transport modeling, and the importance of evaluating specific interactions between geomedia and gases of interest, which may differ from geomedia interactions with chemical tracers.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Environmental impact of solution pH on the formation and migration of iron colloids in deep subsurface energy systems

Deep subsurface stimulation processes often promote fluid-rock interactions that can lead to the formation of small colloidal particles that are suspected to migrate through the rock matrix, partially or fully clog pores and microfractures, and promote the mobilization of contaminants. Thus, the goal of this work is to understand the geochemical changes of the host rock in response to reservoir stimulation that promote the formation and migration of colloids. Two different carbonate-rich shales were exposed to different solution pHs (pH = 2 and 7). In this study, iron and other mineral transformations at the shale-fluid interface were first characterized by synchrotron-based XRF mapping. Then, colloids that were able to migrate from the shale into the bulk fluid were characterized by synchrotron-based extended X-ray absorption structure (EXAFS), scanning electron microscopy (SEM), and single-particle inductively coupled plasma time-of-flight mass spectrometry (sp-icpTOF-MS). When exposed to the pH = 2 solution, extensive mineral dissolution and secondary precipitation was observed; iron-(oxyhydr)oxide colloids colocated with silicates were observed by SEM at the fluid-shale interfaces, and the mobilization of chromium and nickel with these iron colloids into the bulk fluid was detected by sp-icpTOF-MS. Iron EXAFS spectra of the solution at the shale-fluid interface suggests the rapid (within minutes) formation of ferrihydrite-like nanoparticles. Thus, we demonstrate that the pH neutralization promotes the mobilization of existing silicate minerals and the rapid formation of new iron colloids. These Fe colloids have the potential to migrate through the shale matrix and mobilize other heavy metals (such as Cr and Ni, in this study) and impacting groundwater quality, as well produced waters from these hydraulic fracturing operations.

54 ENVIRONMENTAL SCIENCES↗

Initial Laboratory Measurements Probing Hydrogen Interactions with Eagle Ford Shale and Pyrite: Potential Implications for Subsurface Hydrogen Storage

Hydrogen (H 2 ) has the potential to be a transformative technology as an enabler to a low-carbon future and promoter of renewable energy. When H 2 is injected and stored in the subsurface, it has the potential to interact with the caprock (usually shale) which overlies and seals the storage reservoir. Here, this study examines geochemical reactions or changes in surface morphology to Eagle Ford Shale, a proxy for caprock, upon exposure to H 2 at 50°C and 10.3 MPa. Reactions were also performed with N 2 to provide an experimental control. Scanning Electron Microscopy with Energy Dispersive Spectroscopy (SEM-EDS), Atomic Force Microscopy (AFM), and Optical Photothermal-Infrared (O-PTIR) Spectroscopy were applied to quantify changes on the microscale and nanoscale level. Fluid chemistry changes were monitored with Ion Chromatography (IC) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Exposure of Eagle Ford Shale to H 2 gas alone did not result in any alterations to the shale chemically or any changes in the surface morphology. Exposure of Eagle Ford Shale to both H 2 and water as well as N 2 and water resulted in changes to the surface morphology because of gypsum dissolution and reprecipitation, thus indicating that H 2 is not necessary to promote changes. Pure pyrite was the most reactive with H 2 possibly resulting in a reduction to pyrrhotite. These initial studies suggest that the extent of reactions activated by hydrogen with caprock are minor under the temperature and pressure conditions that would represent underground hydrogen storage.

08 HYDROGEN↗

CO 2 Hydrogenation on Pd(111): The Role of Subsurface Hydrogen and Surface Defects

Palladium-based catalysts are often used in carbon dioxide (CO 2 ) hydrogenation reactions with different possible reaction pathways producing methanol, methane, formic acid, or carbon monoxide. We used ambient pressure X-ray photoelectron spectroscopy (AP-XPS) to understand the surface reaction mechanism of CO 2 hydrogenation on Pd(111). AP-XPS results show that the order in which the reactants are introduced yields different initial surface species. In a CO 2 and H 2 mixture, carbonaceous species (CH x , C*, PdC x ) are formed upon heating Pd(111) at 400 K and above. In addition, a Pd(111) sample pre-exposed to an elevated pressure of H 2 followed by evacuation to ultrahigh vacuum (UHV) can store enough hydrogen atoms in the subsurface and bulk to provide a hydrogen source for the CO 2 hydrogenation reaction to occur when exposed to CO 2 gas alone. In conclusion, the formation of carbonaceous species likely occurs through the decomposition of a transient CH x O intermediate facilitated by low-coordinated sites and surface defects.

36 MATERIALS SCIENCE↗

Domain-Dependent Electronic Properties of 2D Copper Boride Synthesized from Reversible Subsurface Diffusion on Cu(111)

Emerging boron-based 2D materials hold properties with potential applications ranging from electronic devices to catalysis and energy storage. Using physical vapor deposition, 2D copper borides are formed on Cu(111) at elevated temperatures. However, the as-prepared surfaces often contain boron clusters that compromise structural homogeneity, and the dynamics of their formation is not yet fully understood. Through in situ low-energy electron microscopy (LEEM), Auger electron spectroscopy (AES), and scanning tunneling microscopy/spectroscopy (STM/STS), we show that cluster-free 2D CuB x is synthesized via reversible subsurface diffusion of boron atoms. The resolved regular atomic structure aligns with the previously calculated Cu 8 B 14 model. In a rare case, possibly due to surface strain and a change of orientation, a second domain of CuB x was observed with a pronounced change in electronic properties, yet electronic states remain delocalized in both domains. In conclusion, these findings demonstrate the sensitivity of electronic properties to domain structure and highlight a potential opportunity to tune 2D CuB x for diverse applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Surface Methane Concentrations Along the Mid-Atlantic Bight Driven by Aerobic Subsurface Production Rather Than Seafloor Gas Seeps

Relatively minor amounts of methane, a potent greenhouse gas, are currently emitted from the oceans to the atmosphere, but such methane emissions have been hypothesized to increase as oceans warm. Here, we investigate the source, distribution, and fate of methane released from the upper continental slope of the U.S. Mid-Atlantic Bight, where hundreds of gas seeps have been discovered between the shelf break and ~1,600 m water depth. Using physical, chemical, and isotopic analyses, we identify two main sources of methane in the water column: seafloor gas seeps and in situ aerobic methanogenesis which primarily occurs at 100–200 m depth in the water column. Stable isotopic analyses reveal that water samples collected at all depths were significantly impacted by aerobic methane oxidation, the dominant methane sink in this region, with the average fraction of methane oxidized being 50%. Due to methane oxidation in the deeper water column, below 200 m depth, surface concentrations of methane are influenced more by methane sources found near the surface (0–10 m depth) and in the subsurface (10–200 m depth), rather than seafloor emissions at greater depths.

54 ENVIRONMENTAL SCIENCES↗