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At least 109 records · Page 6

Geometrical-Based Generative Adversarial Network to Enhance Digital Rock Image Quality

X-ray microcomputed tomography (micro-CT) is a common tool for the study of porous media structures and properties. High-quality micro-CT data are required to accurately capture pore structures. Acquiring high-quality micro-CT data, however, is not always possible, owing to application limitations and experimental constraints. Therefore, we propose a geometrical-based generative adversarial network (GAN) to rapidly restore noisy micro-CT images to their clean counterparts. The training data and related ground-truth (GT) data are scanned for 7 min and 9.5 h, respectively. To evaluate the performance of the geometrical-based GAN, a 6003 voxel image that has never been used for training is reconstructed and compared with the corresponding GT image. Histogram matching and linear normalization are implemented to adjust the histogram of the reconstructed image to that of the GT image. A watershed-based segmentation method is then applied to delineate pore and solid phases. Lastly, we measure the Minkowski functionals and petrophysical properties, including absolute permeability, pore size distribution, drainage capillary pressure-saturation curve, and imbibition relative permeability, to estimate the physical accuracy of the denoised image. The results show that the proposed geometrical-based GAN can accurately restore noisy micro-CT data. By reducing the scanning time from 9.5 h to 7 min, the expenditure of collecting micro-CT can be decreased significantly. This is particularly important for applications where time-lapse images of a dynamic process are required, high-throughput imaging is necessary for real-time data analysis, or where the quantification of large sample volumes is required.

58 GEOSCIENCES↗

ESIAS Pseudocode

The Explosive Shock Image Analysis System (ESAIS) is designed to provide a semiautomated quantitative analysis of fast-frame imagery taken during the detonation of high explosive (HE) rate sticks. ESIAS does this by assisting the user in identifying the HE stick geometry on the image (i.e., sides of the undetonated HE stick, detonation front, an axial reference point to assist in the inter-comparison of images); scaling the images based on the known diameter of the undetonated HE stick; identifying the profiles of various surfaces resulting from the detonation process such as the shock wave and product gases or the outer pipe surface; calculating the detonation speed of the HE by tracking the distance it travels between two images with a known time lapse between the images; and determining the slit velocities resulting from the detonation. ESIAS will also import scope traces from oscilloscopes and assist in identifying the time of arrival of significant peaks.

97 MATHEMATICS AND COMPUTING↗

Image Processing Pipeline for Fluoroelastomer Crystallite Detection in Atomic Force Microscopy Images

Phase transformations in materials systems can be tracked using atomic force microscopy (AFM), enabling the examination of surface properties and macroscale morphologies. In situ measurements investigating phase transformations generate large datasets of time-lapse image sequences. The interpretation of the resulting image sequences, guided by domain-knowledge, requires manual image processing using handcrafted masks. Here this approach is time-consuming and restricts the number of images that can be processed. Her in this study, we developed an automated image processing pipeline which integrates image detection and segmentation methods. We examine five time-series AFM videos of various fluoroelastomer phase transformations. The number of image sequences per video ranges from a hundred to a thousand image sequences. The resulting image processing pipeline aims to automatically classify and analyze images to enable batch processing. Using this pipeline, the growth of each individual fluoroelastomer crystallite can be tracked through time. We incorporated statistical analysis into the pipeline to investigate trends in phase transformations between different fluoroelastomer batches. Understanding these phase transformations is crucial, as it can provide valuable insights into manufacturing processes, improve product quality, and possibly lead to the development of more advanced fluoroelastomer formulations.

36 MATERIALS SCIENCE↗

Phase II Field Demonstration at Lansing Smith Generating Plant, Southport, Florida (Final Report)

The Final Technical Report: Field Test Design and Pressure Management Strategies for Phase II Field Demonstration of Optimal Pressure Control, Plume Management, and Produced Water Strategies presents the culmination of multi-year efforts under the U.S. Department of Energy’s Brine Extraction and Storage Test (BEST) program, led by EPRI in partnership with Gulf Power at the Plant Smith site near Panama City, Florida. The project was designed to evaluate and demonstrate the technical feasibility of managing subsurface pressures and fluid movement associated with large-scale CO₂ injection, using low-salinity water as a proxy fluid. Through a combination of field injection testing, reservoir modeling, and optimization studies, the research team developed and refined active and passive brine extraction strategies aimed at controlling injection-induced pressure buildup, mitigating risks of fault activation, and managing plume migration. The field demonstration incorporated a new injection well (TIW-2), a new monitoring/extraction well (TEMW-A), and an existing well (TIW-1) repurposed for passive pressure relief. Complementary geophysical monitoring was designed to track plume development and evaluate the effectiveness of pressure management strategies. The report details the integrated workflow encompassing wellfield development, regulatory permitting, model calibration, and survey design. It includes a comprehensive electromagnetic (EM) modeling and inversion study used to develop a cost-effective, time-lapse geophysical monitoring plan capable of imaging the evolving low-salinity plume within the highly saline Lower Tuscaloosa formation. Reservoir simulation results guided the design of the 17-month injection program and the timing of active extraction to maintain formation pressures below a hypothetical fault reactivation threshold. Supporting analyses evaluated potential injectivity risks related to clay fines migration and geochemical incompatibility, identifying practical mitigation measures such as salinity and pH control. The final design recommends a series of crosswell EM surveys—conducted before, during, and after injection—as the most effective and economical approach for plume imaging, supplemented by continuous downhole pressure and flow monitoring. Collectively, the study provides a field-ready framework for cost-effective pressure management and monitoring in support of future CO₂ storage projects.

01 COAL, LIGNITE, AND PEAT↗

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects

Researchers at New Mexico Tech, Los Alamos National Laboratory (LANL), Sandia National Laboratory (SNL), and other collaborators are developing a methodology to improve characterization of stress in the subsurface by means of a model-based inversion of reservoir engineering data, time lapse seismic measurements, and microseismicity. Historically, various geophysical techniques have been used in efforts to understand the state of stress in the subsurface through direct and indirect imaging of stress sensitive features (faults and fractures) and observations of transient stress related observations (time variant elastic moduli and microseismicity). Standard direct and indirect techniques for seismic fault and fracture imaging suffer from detectability limits due to reliance on high data quality and multiplicity. Variations in effective elastic properties from inversion of high quality seismic (Vertical Seismic Profile (VSP)) data may be used to infer stress near the wellbore through integration with independent experimental characterization of the stress-velocity relationship. Given a sufficiently robust observation network, microseismic emissions may be inverted to characterize focal mechanisms which, together with supporting assumptions and constraints, inform estimates of in-situ stress. While each of these techniques contributes in part to the characterization of stress within limited spatial and temporal domains, no one method provides an unambiguous stress measurement or a predictive capability over a site scale spatial extent. Challenges associated with solution non-uniqueness, measurement ambiguity, and irregular sampling may be greatly minimized through combination of one or more of independent measurements within a common framework in which realistic geological, hydrodynamic, geomechanical, and seismological constituent process models may act as constraints.

02 PETROLEUM↗

Enhanced Manganese Oxidation at the Biofilm–Fluid Interface Drives Pore-Scale Patterns in Mineral Precipitation

Microbial oxidation of manganese (Mn) from aqueous Mn(II) to solid-phase Mn(III, IV) minerals catalyzes Mn(II) removal in natural and engineered porous systems. However, little is known about the spatiotemporal evolution of Mn biomineralization in confined spaces that experience simultaneous Mn(II) delivery and Mn oxide precipitation. Here, we combine time-lapse microscopy, image analysis, and mass spectrometry to quantify the extent and rate of Mn biomineralization by Pseudomonas putida GB-1 in an optically transparent two-dimensional porous medium. We found that Mn(II) oxidation initially occurred within biofilms but shifted over time toward the edges of biofilms in contact with pore fluid. Minerals precipitated outside of the initial biofilm footprint likely due to surface-mediated oxidation of Mn(II) by nascent biogenic Mn oxides, reinforcing a gradient in mineral accumulation from the Mn(II) source near the reactor inlet to the outlet. The rate of mineral precipitation outside the biofilm footprint surpassed the rate of mineral accumulation inside biofilms within 6 h and accounted for two-thirds of the total Mn oxide mass in the pore space at the end of the experiment. This work advances a mechanistic understanding of coupled biotic and abiotic Mn oxidation in porous environments while providing a novel platform to quantify microbe-mineral-fluid interactions.

Biofilms↗

Real Time 3D Observations of Portland Cement Carbonation at CO2 Storage Conditions

Depleted oil reservoirs are considered a viable solution to the global challenge of CO 2 storage. A key concern is whether the wells can be suitably sealed with cement to hinder the escape of CO 2 . Under reservoir conditions, CO 2 is in its supercritical state, and the high pressures and temperatures involved make real-time microscopic observations of cement degradation experimentally challenging. Here, we present an in situ 3D dynamic X-ray micro computed tomography (μ-CT) study of well cement carbonation at realistic reservoir stress, pore-pressure, and temperature conditions. The high-resolution time-lapse 3D images allow monitoring the progress of reaction fronts in Portland cement, including density changes, sample deformation, and mineral precipitation and dissolution. By switching between flow and nonflow conditions of CO 2 -saturated water through cement, we were able to delineate regimes dominated by calcium carbonate precipitation and dissolution. For the first time, we demonstrate experimentally the impact of the flow history on CO 2 leakage risk for cement plugging. In-situ μ-CT experiments combined with geochemical modeling provide unique insight into the interactions between CO 2 and cement, potentially helping in assessing the risks of CO 2 storage in geological reservoirs.

58 GEOSCIENCES↗

Vegetation Warming Experiment: Chamber and ambient plot digital camera imagery for vegetation phenology, Utqiagvik (Barrow), Alaska, 2019

Time lapse photography of experimental plots within five warming chambers (ZPWs) and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Images were recorded from 21 June to 25 September, 2019 to capture vegetation dynamics during the growing season. Vegetation phenology, including green up and senescence were captured. Images were recorded daily at 30 minute intervals, from 09:00 - 16:30 Alaska daylight time (AKDT, UTC-8), using Wingscapes TimelapseCam cameras. The target species was Eriophorum angustifolium. Image files (.jpg) captured by Wingscapes TimelapseCams, compressed as zip files. Additional information in *.pdf and *.csv files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Vegetation Warming Experiment: Chamber and ambient plot digital camera imagery for vegetation phenology, Utqiagvik (Barrow), Alaska, 2021

Time lapse photography of experimental plots within five warming chambers (ZPWs) and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Images were recorded from 17 June to 19 September, 2021 to capture vegetation dynamics during the growing season. Vegetation phenology, including green up and senescence were captured. Images were recorded daily at 30 minute intervals, from 09:00 - 16:30 Alaska daylight time (AKDT, UTC-8), using Wingscapes TimelapseCam Pro cameras. The target species was Carex aquatilis. Individual jpg images from each camera have been combined in zip format. The data package includes a metadata document with example fields of view from each camera (*.pdf). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Vegetation Warming Experiment: Chamber and ambient plot digital camera imagery for vegetation phenology, Utqiagvik (Barrow), Alaska, 2018

Time lapse photography of experimental plots within five warming chambers (ZPWs) and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Images were recorded from 17 June to 24 September, 2018 to capture vegetation dynamics during the growing season. Vegetation phenology, including green up and senescence were captured. Images are *.jpg files recorded daily at 30 minute intervals, from 11:00 - 14:30 Alaska daylight time (AKDT, UTC-8), using Wingscapes TimelapseCam cameras. The target species was Arctagrostis latifolia. Additional information in *.pdf and *.csv files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Vegetation Warming Experiment: Chamber and ambient plot digital camera imagery for vegetation phenology, Utqiagvik (Barrow), Alaska, 2017

Time lapse photography (*.jpg) of experimental plots within five warming chambers (ZPWs) and paired control plots located on the Barrow Environmental Observatory (BEO), Barrow (now Utqiagvik), Alaska. Images were recorded from 21 June to 18 September, 2017 to capture vegetation dynamics during the growing season. Vegetation phenology, including green up and senescence were captured. Images were recorded daily at 30 minute intervals, from 11:00-14:30 Alaska daylight time (AKDT, UTC-8), using Wingscapes TimelapseCam cameras. The target species was Petasites frigidus. Also included multiple metadata files including reporting formats as *.pdf and *.csv files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Amino mapping: possibility to visualize amino-N compounds in the rhizosphere of Zea Mays L.

Abstract Understanding N uptake by plants, the N cycle, and their relationship to soil heterogeneity has generated a great deal of interest in the distribution of amino-N compounds in soil. Visualization of the spatial distribution of amino-N in soil can provide insights into the role of labile N in plant-microbial mechanisms of N acquisition and plant N uptake, but until now, it has remained technically challenging. Here, we describe a novel technique to visualize the amino-N distribution at the root-soil interface. The technique is based on time-lapse amino mapping (TLAM) using membranes saturated with the fluorogenic OPAME reagent (O-phthalaldehyde and β-mercaptoethanol). OPAME in the membrane reacts with organic compounds containing a NH 2 functional group at the membrane-soil interface, generating a fluorescent product visible under UV light and detectable by a digital camera. The TLAM amino-mapping technique was applied to visualize and quantify the concentration of amino-N compounds in the rhizosphere of maize (Zea MaysL.). A ten times greater amino-N concentration was detected in the rhizosphere compared to non-rhizosphere soil. The high content of amino-N was mainly associated with the root tips and was 3 times larger than the average amino-N content at seminal roots. The amino-N rhizosphere was 2 times broader around the root tips than around other parts of the roots. We concluded that TLAM is a promising approach for monitoring the fate of labile N in soils. However, the technique needs to be standardized for different soil types, plant species, and climate conditions to allow wider application.

Agriculture↗

Three‐Dimensional Permeability Inversion Using Convolutional Neural Networks and Positron Emission Tomography

Abstract Quantification of heterogeneous multiscale permeability in geologic porous media is key for understanding and predicting flow and transport processes in the subsurface. Recent utilization of in situ imaging, specifically positron emission tomography (PET), enables the measurement of three‐dimensional (3‐D) time‐lapse radiotracer solute transport in geologic media. However, accurate and computationally efficient characterization of the permeability distribution that controls the solute transport process remains challenging. Leveraging the relationship between local permeability variation and solute advection behavior, an encoder‐decoder based convolutional neural network (CNN) is implemented as a permeability inversion scheme using a single PET scan of a radiotracer pulse injection experiment as input. The CNN can accurately capture the 3‐D spatial correlation between the permeability and the radiotracer solute arrival time difference maps in geologic cores. We first test the inversion accuracy using synthetic test datasets and then test the accuracy on a suite of experimental PET imaging datasets acquired on four different geologic cores. The network‐predicted permeability maps from the geologic cores are used to parameterize forward numerical models that are directly compared with the experimental PET imaging data. The results indicate that a single trained network can generate robust 3‐D permeability inversion maps in seconds. Numerical models parameterized with these permeability maps closely capture the experimentally observed solute arrival time behavior. This work provides an unprecedented approach for efficiently characterizing multiscale permeability heterogeneity in complex geologic samples.

54 ENVIRONMENTAL SCIENCES↗

Modeling root system growth around obstacles

State-of-the-Art models of Root System Architecture (RSA) do not allow simulating root growth around rigid obstacles. Yet, the presence of obstacles can be highly disruptive to the root system. We grew wheat seedlings in sealed petri dishes without obstacle and in custom 3D-printed rhizoboxes containing obstacles. Time-lapse photography was used to reconstruct the wheat root morphology network. We used the reconstructed wheat root network without obstacle to calibrate an RSA model implemented in the R-SWMS software. The root network with obstacles allowed calibrating the parameters of a new function that models the influence of rigid obstacles on wheat root growth. Experimental results show that the presence of a rigid obstacle does not affect the growth rate of the wheat root axes, but that it does influence the root trajectory after the main axis has passed the obstacle. The growth recovery time, i.e. the time for the main root axis to recover its geotropism-driven growth, is proportional to the time during which the main axis grows along the obstacle. Qualitative and quantitative comparisons between experimental and numerical results show that the proposed model successfully simulates wheat RSA growth around obstacles. Our results suggest that wheat roots follow patterns that could inspire the design of adaptive engineering flow networks.

59 BASIC BIOLOGICAL SCIENCES↗

Direct observation of C 3 S particle dissolution using fast nano X-ray computed tomography

Tricalcium silicate (C 3 S) occupies 50 % to 70 % of ordinary portland cement (OPC) by mass and it is an important component affecting the hydration of OPC [1], [2], [3], [4], [5], [6], [7]. Generally, the hydration of C 3 S is described by two processes: the dissolution of C 3 S particles and the precipitation of hydration products. While it is understood that the dissolution rates of C 3 S vary with time, more precise measurements are needed to understand this process. Many mechanisms have been proposed to explain the time-evolving dissolution rates of C 3 S [2]. The metastable barrier hypothesis suggests that a thin metastable layer of hydrates forms around the C 3 S particle surface and prohibits the access of grains to the aqueous solution [8], [9], [10], [11], [12]. The slow dissolution step hypothesis suggests that the increased ion concentration from the initial reaction delays the C 3 S dissolution [2], [13], [14], [15], [16], [17]. More recent publications suggest that C 3 S may react differently depending on the existence of crystallographic defects [18], [19], [20]. Etch pits are thought to open on the particle surface during the initial reaction and this contributes to the C 3 S dissolution [21], [22]. As hydrates precipitate and cover these highly reactive surfaces, hydration slows down and the induction period starts [18], [23], [24], [25], [26]. Many experiments have been conducted to test the aforementioned mechanisms. Some hydration studies utilize bulk measurements, such as isothermal calorimetry [27], [28], [29], pore solution analysis [30], quasi-elastic neutron scattering [31], and nuclear magnetic resonance spectroscopy [32], [33]. One limitation of these measurements is that they do not provide direct and detailed information on the individual C 3 S particles. Some other studies utilize imaging techniques, such as scanning electron microscopy (SEM) [34], [35], [36] and transmission electron microscopy (TEM) [37]. However, SEM/TEM cannot track the evolution of individual particles throughout hydration [34], [35], [38], [39], [40] and they do not give insights into the microstructure of materials before hydration [34], [35], [39]. This makes it challenging to draw strong conclusions from only SEM or TEM observations. Synchrotron X-ray tomography techniques have been used more broadly in recent years to study cement hydration. They are not only non-destructive but also able to image a sample in full 3D with resolutions that can reach from micron to nanoscale. Nano computed tomography (nCT) is one technique that has been applied to study cement hydration at the nanoscale [26], [41]. A typical nCT can reach a pixel size from 15 to 65 nm, providing enough detail for observing features <1 μm. However, nCT often takes >0.5 h to finish one scan. This makes the application of this technique on continuous scans for in-situ observations challenging. Fast X-ray computerized tomography (fCT) is another technique that has shown success in studying the time-evolving cement microstructures [20], [42], [43], [44], [45], [46], [47], [48], [49]. Due to the high flux of the X-ray beam from the synchrotron ring, fCT allows a scan to be captured within 1 min at a pixel size of 1 μm. This allows a paste sample to be continuously scanned during the hydration process. However, the micron-sized resolutions limit does not provide detailed insights for particles <5 μm [20], [49]. Fortunately, the combination of nCT and fCT has allowed the development of fast nano X-ray computed tomography (fnCT). fnCT can capture a 3D data set in <2 min at a pixel size of 50 nm. This makes this procedure an exciting method to evaluate hydrating pastes. fnCT collects multiple X-ray radiographs at various rotation angles and generates a 3D model of the scanned sample, which is also referred to as a 3D tomography [50], [51]. In one tomography, the X-ray absorptions of different components (e.g., C 3 S and hydrates) differ as functions of density and chemistry [52], [53]. These X-ray absorption contrasts can be used to extract detailed information about the 3D microstructure [26], [54], [55]. In this paper, fnCT is used to collect time-lapse tomographs of hydrating C 3 S paste from 18 min after mixing to 7 h of hydration. The bulk measurements of anhydrous C 3 S, as well as the microstructural changes of individual C 3 S particles, are directly observed, quantified, and discussed. The dissolution behavior of C 3 S particles at various size scales is systematically analyzed and compared. This work aims to find the relationship between the size of C 3 S particle sizes and their dissolution rates. This provides significant insights into the early-age hydration of C 3 S on length and time scales not previously possible. Because of the magnitude of the data and the substantial amount of observations, this work will solely focus on the change in the anhydrous particles. Changes in the hydration products will be reported in future work.

42 ENGINEERING↗

Economic and operational investigation of CO 2 sequestration through enhanced oil recovery in unconventional reservoirs in Colorado, USA

The ongoing CCUS commercial projects are highly relied on the support of government incentives due to massive capital investment. Here, this study analyzes the economics of carbon capture utilization and sequestration (CCUS) projects, shows a state-wide CCUS deployment exercise, followed by simulation results of enhanced oil recovery (EOR) based CO 2 storage in unconventional reservoirs. The comprehensive economic analysis of capture, transportation, sequestration costs, enhanced 45Q tax credits, and EOR revenue implies the practicality of CO 2 -EOR to offset the high CCUS costs. With the economics understanding, we study the top CO 2 sources, existing CO 2 pipelines, and sequestration sinks in the state of Colorado, USA. This paper next presents results from EOR simulation in one section of the unconventional Denver-Julesburg (DJ) Basin Niobrara and Codell reservoirs. The simulation model is based on a geological static model, incorporated with hydraulic fracture stimulation, history matched to production, and calibrated to the microseismic and time-lapse surface seismic data. The CO 2 -EOR simulation results show that oil production can be increased and more CO 2 stored with: a longer primary production period; the presence of a shut-in period; higher injection rates; and multi-well injectors. The modeling results show that about 7–10 Mscf of CO 2 will be stored when recovering 1 stb of EOR oil. By adding the enhanced oil revenue and the carbon credits together, it is estimated that the most economic case can generate $\$13$ MM when oil price is assumed to be $\$80$/stb, and the EOR oil revenue is 3.4 times greater than that generated from 45Q incentives. It corresponds to the scenario that a five-year primary production is followed by CO 2 injection into four wells with the sequence of injection (4 MMscf/day for 6 months), shut-in (6 months) and production (12 months). The best practices in this study will provide valuable insights for similar CCUS projects in other unconventional fields. Furthermore, this study defines a term named “Carbon Neutrality Index (CNI)” by comparing the amount of CO 2 stored with that burned by EOR oil. The CNI value of 0 indicates the enhanced oil is carbon neutral; a negative CNI value implies there is a net reduction in carbon emission. The 4-year huff-n-puff (HnP) simulation leads to a positive CNI value, indicating that the EOR oil generated in this process is not carbon neutral yet.

03 NATURAL GAS↗

Electrical Resistivity Tomography data from 2016 to 2018 at the Lower Montane site in the East River Watershed, Colorado

This dataset contains time-lapse Electrical Resistivity Tomography (ERT) data along a transect located on the northeast-facing hillslope at the lower montane site (Pumphouse site) in the upper East River Watershed. The monitoring dataset covers the period from November 2, 2016, to August 6, 2018. In addition, the archive also contains a baseline dataset from October 9, 2016. The ERT transect consisted of 128 electrodes with an electrode spacing of 1.25 m. The acquisition system was located in the middle of the transect, about 50 m on one side, and included an MPT (Multi-Phase Technologies) ERT system, a mini computer, and batteries with solar panels. Acquisition occurred daily under normal circumstances. The first 16 electrodes (from the upper end of the transect) could not be used after the cable was damaged during the 2017–2018 winter. Also, due to multiple failures in the power system, the temporal resolution of the data is much lower in 2018 compared to 2016 and 2017. The data have been processed and used in Dafflon et al., 2023, and the baseline dataset was used in Falco et al., 2019 (see reference list). This archive contains the measurements (ER.zip containing csv files) for each of the 326 acquisition times and a filtered version where only electrodes 17 to 128 are included (ERT_sm.zip containing csv files). The archive also contains the baseline dataset and two acquisitions with full reciprocals (ERT_RB.zip containing csv files), as well as all the raw MPT files (ERT_raw_MTP.zip). The geometry (electrode position and elevation) is provided in Universal Transverse Mercator (UTM) 13N Geoid2012AB in the file named ERT_Location.csv. The archive contains 1 *.csv data files, four *.zip files, and three metadata *.csv files. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗

Longitudinal Single‐Cell Imaging of Engineered Strains with Stimulated Raman Scattering to Characterize Heterogeneity in Fatty Acid Production

Abstract Understanding metabolic heterogeneity is critical for optimizing microbial production of valuable chemicals, but requires tools that can quantify metabolites at the single‐cell level over time. Here, longitudinal hyperspectral stimulated Raman scattering (SRS) chemical imaging is developed to directly visualize free fatty acids in engineered Escherichia coli over many cell cycles. Compositional analysis is also developed to estimate the chain length and unsaturation of the fatty acids in living cells. This method reveals substantial heterogeneity in fatty acid production among and within colonies that emerges over the course of many generations. Interestingly, the strains display distinct types of production heterogeneity in an enzyme‐dependent manner. By pairing time‐lapse and SRS imaging, the relationship between growth and production at the single‐cell level are examined. The results demonstrate that cell‐to‐cell production heterogeneity is pervasive and provides a means to link single‐cell and population‐level production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗