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At least 937 records · Page 52

Near-field non-radial motion generation from underground chemical explosions in jointed granite

Here, this paper describes analysis of non-radial ground motion generated by chemical explosions in a jointed rock formation during the Source Physics Experiment (SPE). Such motion makes it difficult to discriminate between various subsurface events such as explosions, implosions (i.e. mine collapse) and earthquakes. We apply 3-D numerical simulations to understand experimental data collected during the SPEs. The joints are modelled explicitly as compliant thin inclusions embedded into the rock mass. Mechanical properties of the rock and the joints as well as the joint spacing and orientation are inferred from experimental test data, and geophysical and geological characterization of the SPE site which is dominantly Climax Stock granitic outcrop. The role of various factors characterizing the joints such as joint spacing, frictional properties, orientation and persistence in generation of non-radial motion is addressed. The joints in granite at the SPE site are oriented in nearly orthogonal directions with two vertical sets dipping at 70–80 degrees with the same strike angle, one vertical set almost orthogonal to the first two and one shallow angle joint set dipping 15 degrees. In this study we establish the relationship between the joint orientation and azimuthal variations in the polarity of the observed shear motion. The majority of the shear motion is generated due to the effects of non-elastic sliding on the joints near the source, where the wave can create significant shear stress to overcome the cohesive forces at the joints. Near the surface the joints are less confined and are subject to sliding when the pressure waves are reflected. In the far field, where the cohesive forces on the joints cannot be overcome, additional shear motion can be generated due to elastic anisotropy of the rock mass given by preferred spatial orientations of compliant joints.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Wabash CarbonSAFE (Subtask 3.1 - Application of the NRAP Tools to the Wabash CarbonSAFE Site for Risk Assessment Associated with Geologic Carbon Storage Activities)

This report documents a risk assessment of CO 2 containment loss and induced shear failure due to geologic carbon storage at the Wabash CarbonSAFE site. The operator, Wabash Valley Resources, has proposed adapting the onsite integrated gasification combined cycle (IGCC) facilities to produce hydrogen and injecting the byproduct CO 2 stream into the subsurface Potosi dolomite formation. The purpose of this study is to assess (1) CO 2 sequestration performance relative to the CarbonSAFE goals of storing 50 Mt over 30 years, (2) the risk of containment loss due to leakage along a wellbore and into an overlying aquifer, and (3) the state of stress and risk of reactivating existing fractures. This study relied upon the initial site characterization work performed by the Illinois State Geologic Survey (ISGS) along with analogue data collected from other carbon sequestration projects in the region.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Characterization of Mineralogy Across Vesta

Dawn VIR spectra are characterized by pyroxene absorptions and no clear evidence for abundant other minerals are observed at the scale of the present measurements. Even though Vesta spectra are dominated by pyroxenes, spectral variation at regional and local scales are evident and distinct color units are identified. Although almost all of the surface materials exhibit spectra like those of howardites, some large units can be interpreted to be material richer in diogenite (based on pyroxenes band depths and band centers) and some others like eucrite-rich howardite units. VIR data strongly indicate that the south polar region (Rheasilvia) has its own spectral characteristics, indicating the presence of Mg-pyroxene-rich terrains (diogenite-like), while the equatorial areas have swallower band depths and average band centers at slightly longer wavelengths, consistent with more eucrite rich materials. Vesta surface shows considerable diversity at smaller scales (tens of km), in terms of spectral reflectance and emission, band depths and slopes. Many bright and dark spots are present on Vesta. Dark spots have low reflectance at visible wavelengths and are spectrally characterized by shallower 1 and 2 micron bands with respect the surrounding terrains. Bright materials have high reflectance and are often spectrally characterized by deep pyroxenes absorption bands. Vesta presents complex geology/topography and the mineral distribution is often correlated with geological and topographical structures. Ejecta from large craters have distinct spectral behaviors, and materials exposed in the craters show distinct spectra on floors and rims. VIR reveals the mineralogical variation of Vesta s crustal stratigraphy on local and global scales. Maps of spectral parameters show surface and subsurface unit compositions in their stratigraphic context. The hypothesis that Vesta is the HED parent body is consistent with, and strengthened by, the geologic and spectral context for pyroxene distribution provided by Dawn.

De Sanctis, M. C.↗

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↗

Quantifying Community Assembly Processes and Identifying Features that Impose Them

Across a set of ecological communities connected to each other through organismal dispersal (a ‘meta-community’), turnover in composition is governed by (ecological) Drift, Selection, and Dispersal Limitation. Quantitative estimates of these processes remain elusive, but would represent a common currency needed to unify community ecology. Using a novel analytical framework we quantitatively estimate the relative influences of Drift, Selection, and Dispersal Limitation on subsurface, sediment-associated microbial meta-communities. The communities we study are distributed across two geologic formations encompassing ~12,500m3 of uranium-contaminated sediments within the Hanford Site in eastern Washington State. We find that Drift consistently governs ~25% of spatial turnover in community composition; Selection dominates (governing ~60% of turnover) across spatially-structured habitats associated with fine-grained, low permeability sediments; and Dispersal Limitation is most influential (governing ~40% of turnover) across spatially-unstructured habitats associated with coarse-grained, highly-permeable sediments. Quantitative influences of Selection and Dispersal Limitation may therefore be predictable from knowledge of environmental structure. To develop a system-level conceptual model we extend our analytical framework to compare process estimates across formations, characterize measured and unmeasured environmental variables that impose Selection, and identify abiotic features that limit dispersal. Insights gained here suggest that community ecology can benefit from a shift in perspective; the quantitative approach developed here goes beyond the ‘niche vs. neutral’ dichotomy by moving towards a style of natural history in which estimates of Selection, Dispersal Limitation and Drift can be described, mapped and compared across ecological systems.

ecological drift↗

Discovering hidden geothermal signatures using non-negative matrix factorization with customized k-means clustering

Discovery of hidden geothermal resources is challenging. It requires the mining of large datasets with diverse data attributes representing subsurface hydrogeological and geothermal conditions. The commonly used play fairway analysis approach typically incorporates subject-matter expertise to analyze regional data to estimate geothermal characteristics and favorability. We demonstrate an alternative approach based on machine learning (ML) to process a geothermal dataset from southwest New Mexico (SWNM). The study region includes low- and medium-temperature hydrothermal systems. Several of these systems are not well characterized because of insufficient existing data and limited past explorative work. This study discovers hidden patterns and relations in the SWNM geothermal dataset to improve our understanding of the regional hydrothermal conditions and energy-production favorability. This understanding is obtained by applying an unsupervised ML algorithm based on non-negative matrix factorization coupled with customized k-means clustering (NMFk). NMFk can automatically identify (1) hidden signatures characterizing analyzed datasets, (2) the optimal number of these signatures, (3) the dominant data attributes associated with each signature, and (4) the spatial distribution of the extracted signatures. Here, in this study, NMFk is applied to analyze 18 geological, geophysical, hydrogeological, and geothermal attributes at 44 locations in SWNM. Using NMFk, we find data patterns and identify the spatial associations of hydrothermal signatures within two physiographic provinces (Colorado Plateau and Basin and Range) and two sub-regions of these provinces (the Mogollon-Datil volcanic field and the Rio Grande rift) in SWNM. The ML algorithm extracted five hydrothermal signatures in the SWNM datasets that differentiate between low (<90°C) and medium (90-150°C)-temperature hydrothermal systems. The algorithm also suggests that the Rio Grande rift and northern Mogollon-Datil volcanic field are the most favorable regions for future geothermal resource discovery. NMFk also identified critical attributes to identify medium-temperature hydrothermal systems in the study area. The resulting NMFk model can be applied to predict geothermal conditions and their uncertainties at new SWNM locations based on limited data from unexplored regions. The code to execute the performed analyses as well as the corresponding data can be found at https://github.com/SmartTensors/GeoThermalCloud.jl.

15 GEOTHERMAL ENERGY↗

Physical, Hydraulic, and Transport Properties of Sediments and Engineered Materials Associated with Hanford Immobilized Low-Activity Waste

Current plans for treatment and disposal of immobilized low-activity waste (ILAW) from Hanford’s underground waste storage tanks include vitrification and storage of the glass waste form in a nearsurface disposal facility. This Integrated Disposal Facility (IDF) is located in the 200 East Area of the Hanford Central Plateau. Performance assessment (PA) of the IDF requires numerical modeling of subsurface flow and reactive transport processes over very long periods (thousands of years). The models used to predict facility performance require parameters describing various physical, hydraulic, and transport properties. This report provides updated estimates of physical, hydraulic, and transport properties and parameters for both near- and far-field materials, intended for use in future IDF PA modeling efforts. Previous work on physical and hydraulic property characterization for earlier IDF PA analyses is reviewed and summarized. For near-field materials, portions of this document and parameter estimates are taken from an earlier data package. For far-field materials, a critical review is provided of methodologies used in previous data packages. Alternative methods are described and associated parameters are provided.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

The benefit of brightness temperature assimilation for the SMAP Level-4 surface and root-zone soil moisture analysis

The Soil Moisture Active Passive (SMAP) Level-4 (L4) product provides global estimates of surface soil moisture (SSM) and root-zone soil moisture (RZSM) via the assimilation of SMAP brightness temperature (Tb) observations into the NASA Catchment Land Surface Model (CLSM). Here, using in situ measurements from 2474 sites in China, we evaluate the performance of soil moisture estimates from the L4 data assimilation (DA) system and from a baseline “open-loop” (OL) simulation of CLSM without Tb assimilation. Using random forest regression, the efficiency of the L4 DA system (i.e., the performance improvement in DA relative to OL) is attributed to eight control factors related to the CLSM as well as τ–ω radiative transfer model (RTM) components of the L4 system. Results show that the Spearman rank correlation (R) for L4 SSM with in situ measurements increases for 77 % of the in situ measurement locations (relative to that of OL), with an average R increase of approximately 14 % (ΔR=0.056). RZSM skill is improved for about 74 % of the in situ measurement locations, but the average R increase for RZSM is only 7 % (ΔR=0.034). Results further show that the SSM DA skill improvement is most strongly related to the difference between the RTM-simulated Tb and the SMAP Tb observation, followed by the error in precipitation forcing data and estimated microwave soil roughness parameter h. For the RZSM DA skill improvement, these three dominant control factors remain the same, although the importance of soil roughness exceeds that of the Tb simulation error, as the soil roughness strongly affects the ingestion of DA increments and further propagation to the subsurface. For the skill of the L4 and OL estimates themselves, the top two control factors are the precipitation error and the SSM–RZSM coupling strength error, both of which are related to the CLSM component of the L4 system. Finally, we find that the L4 system can effectively filter out errors in precipitation. Therefore, future development of the L4 system should focus on improving the characterization of the SSM–RZSM coupling strength.

Jianxiu Qiu↗

Selected Area Manipulation of MoS 2 via Focused Electron Beam-Induced Etching for Nanoscale Device Editing

Here we demonstrate direct-write patterning of single and multilayer MoS 2 via a focused electron beam-induced etching (FEBIE) process mediated with the XeF 2 precursor. MoS 2 etching is performed at various currents, areal doses, on different substrates, and characterized using scanning electron and atomic force microscopies as well as Raman and photoluminescence spectroscopies. Scanning transmission electron microscopy reveals a sub-40 nm etching resolution and the progression of point defects and lateral etching of the consequent unsaturated bonds. The results confirm that the electron beam-induced etching process is minimally invasive to the underlying material in comparison to ion beam techniques, which damage the subsurface material. Single-layer MoS 2 field-effect transistors are fabricated, and device characteristics are compared for channels that are edited via the selected area etching process. The source–drain current at constant gate and source–drain voltage scale linearly with the edited channel width. Moreover, the mobility of the narrowest channel width decreases, suggesting that backscattered and secondary electrons collaterally affect the periphery of the removed area. Focused electron beam doses on single-layer transistors below the etching threshold were also explored as a means to modify/thin the channel layer. The FEBIE exposures showed demonstrative effects via the transistor transfer characteristics, photoluminescence spectroscopy, and Raman spectroscopy. While strategies to minimize backscattered and secondary electron interactions outside of the scanned regions require further investigation, here, we show that FEBIE is a viable approach for selective nanoscale editing of MoS 2 devices.

36 MATERIALS SCIENCE↗

Phylogenetic beta diversity in bacterial assemblages across ecosystems: deterministic versus stochastic processes

Increasing evidence emerged for non-random spatial distributions for microbes, but the underlying processes resulting in microbial assemblage variation among and within Earth’s ecosystems is still lacking. For instance, some studies showed that the deterministic processes by habitat specialization are important, while other studies hold that bacterial communities are assembled by neutral forces. Here we examine the relative importance of deterministic and stochastic processes for bacterial communities from subsurface environments, as well as stream biofilm, lake water, lake sediment and soil using pyrosequencing of 16S rRNA gene. We show that there is a general pattern in phylogenetic signal in species niches across recent evolutionary time for all studied habitats, enabling us to infer the influences of community assembly processes from patterns of phylogenetic turnover in community composition. The phylogenetic dissimilarities among habitat types were significantly higher than within them, and the communities were clustered according to their original habitat types. For communities within habitat types, the highest phylogenetic turnover rate through space was observed in subsurface environments, followed by stream biofilm on mountainsides, whereas the sediment assemblages across regional scales showed the lowest turnover rate. Quantifying phylogenetic turnover as the deviation from a null expectation suggested that measured environmental variables imposed strong selection on bacterial communities for nearly all sample groups, and for three sample groups, that spatial distance reflects unmeasured environmental variables that impose selection, as opposed to spatial isolation. Such characterization of spatial and environmental variables proved essential for proper interpretation of partial mantel results based on observed beta diversity metrics. In summary, our results clearly indicate a dominant role of deterministic processes on bacterial assemblages and highlight that bacteria show strong habitat associations that have likely emerged through evolutionary adaptation.

Bacteria↗

Electronic structure and surface properties of MgB 2 (0001) upon oxygen adsorption [Electronic structure and surface properties of MgB2: oxygen adsorption on MgB2(0001)]

Here, we use density-functional theory to investigate the bulk and surface properties of MgB 2 . The unique bonding structure of MgB 2 is investigated by Bader's atoms-in-molecules, charge density difference, and occupancy projected band structure analyses. Oxygen adsorption on the charge-depleted surfaces of MgB 2 is studied by a surface potential energy mapping method, reporting a complete map including low-symmetry binding sites. The B-terminated MgB 2 (0001) demonstrates reconstruction of the graphenelike B layer, and the reconstructed geometry exposes a threefold site of the subsurface Mg, making it accessible from the surface. Detailed reconstruction mechanisms are studied by simulated annealing method based on ab initio molecular dynamics and nudged elastic band calculations. The surface clustering of B atoms significantly modifies the B 2p states to occupy low energy valence states. The present paper emphasizes that a thorough understanding of the surface phase may explain an apparent inconsistency in the experimental surface characterization of MgB 2 . Furthermore, these results suggest that the surface passivation can be an important technical challenge when it comes to development of a superconducting device using MgB 2 .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

SMART – A Comprehensive Research and Development Program to Demonstrate Application of Machine Learning for Supporting CCS Deployment

Presentation material for a paper presented at the GHGT-17 conference, Calgary, Canada, October 20-24, 2024. The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.

CO2 geologic storage↗

Data and Model-Driven Decision Support for Environmental Management of a Chromium Plume at Los Alamos National Laboratory - 13264

A series of site investigations and decision-support analyses have been performed related to a chromium plume in the regional aquifer beneath the Los Alamos National Laboratory (LANL). Based on the collected data and site information, alternative conceptual and numerical models representing governing subsurface processes with different complexity and resolution have been developed. The current conceptual model is supported by multiple lines of evidence based on comprehensive analyses of the available data and modeling results. The model is applied for decision-support analyses related to estimation of contaminant- arrival locations and chromium mass flux reaching the regional aquifer, and to optimization of a site monitoring-well network. Plume characterization is a challenging and non-unique problem because multiple models and contamination scenarios are consistent with the site data and conceptual knowledge. To solve this complex problem, an advanced methodology based on model calibration and uncertainty quantification has been developed within the computational framework MADS (http://mads.lanl.gov). This work implements high-performance computing and novel, efficient and robust model analysis techniques for optimization and uncertainty quantification (ABAGUS, Squads, multi-try (multi-start) techniques), which allow for solving problems with large degrees of freedom. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

SMART – A Comprehensive Research and Development Program to Demonstrate Application of Machine Learning for Supporting CCS Deployment

The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.

Siriwardane, Hema↗

Mars 2001 Lander Mission: Measurement Synergy Through Coordinated Operations Planning And Implementation

The 2001 Mars Surveyor Program Mission includes an orbiter with a gamma ray spectrometer and a multispectral thermal imager, and a lander with an extensive set of instrumentation, a robotic arm, and the Marie Curie Rover. The Mars 2001 Science Operations Working Group (SOWG) is a subgroup of the Project Science Group that has been formed to provide coordinated planning and implementation of scientific observations, particularly for the landed portion of the mission. The SOWG will be responsible for delivery of a science plan and, during operations, generation and delivery of conflict-free sequences. This group will also develop an archive plan that is compliant with Planetary Data System (PDS) standards, and will oversee generation, validation, and delivery of integrated archives to the PDS. In this report we cover one element of the SOWG planning activities, the development of a plan that maximizes the scientific return from lander-based observations by treating the instrument packages as an integrated payload. Scientific objectives for the lander mission have been defined. They include observations focused on determining the bedrock geology of the site through analyses of rocks and also local materials found in the soils, and the surficial geology of the site, including windblown deposits and the nature and history of formation of indurated sediments such as duricrust. Of particular interest is the identification and quantification of processes related to early warm, wet conditions and the presence of hydrologic or hydrothermal cycles. Determining the nature and origin of duricrust and associated salts is -very important in this regard. Specifically, did these deposits form in the vadose zone as pore water evaporated from soils or did they form by other processes, such as deposition of volcanic aerosols? Basic information needed to address these questions includes the morphology, topography, and geologic context of landforms and materials exposed at the site, together with quantitative information on material mineralogy, chemistry, and physical properties (rock textures; soil grain size and shape distributions; degree and nature of soil induration; soil magnetic properties). The calibration targets provide radiometric and mineralogical control surfaces. The magnets allow observations of magnetic phases. Patch plates are imaged to determine adhesive and abrasive properties of soils. Coordinated mission planning is crucial for optimizing the measurement synergy among the packages included on the lander. This planning has already begun through generation of multi-sol detailed operations activities. One focus has been to develop a scenario to use the arm to dig a soil trench to a depth of tens of centimeters. The activity will be monitored through use of Pancam and RAC to ensure nominal operations and to acquire data to determine subsurface physical properties (e.g., angle of repose of trench walls). Pancam and Mini-TES observations would also provide constraints on mineralogy and texture for the walls and bottom of the trench during excavation. If desired, soils excavated at depth could be deposited on the surface and Mossbauer and APXS measurements could be acquired for these materials. Soil samples from various depths would be delivered to MECA for characterization of aqueous geochemistry and physical properties of soil grains, particularly size, shape, and hardness. These physical properties would be determined by optical and atomic force microscopy. When completed, detailed information of soil properties as a function of depth would be obtained. These various data sets would constrain our understanding of whether or not there are systematic variations in soil characteristics as a function of depth. These variations might be related, for example, to evaporative moisture losses and formation of salt deposits, thereby indicating water transport processes occurred fairly recently. Many other value-added measurement scenarios are being developed. For example, characterizing the nature and dynamics of dust deposition will be done using MIP/DART to provide deposition rates, Pancam and RAC imaging of lander and rover surfaces to extrapolate these measurements to other areas, and a variety of measurements to determine if the bulk loose soil has the same characteristics as dust that accumulates during the mission. Bedrock geology of the site is primarily an APEX-focus setting, mineralogy, and texture, and APXS data to be we interest will be to determine the extent to which rock hydrothermal processes, given that APEX is the precursor 4 and 2005 rover missions. Additional information is contained in the original.

Arvidson, R.↗

Lunar and Planetary Science XXXVI, Part 12

Topics discussed include: The Ancient Lakes in Hellas Basin Region as Seen Through the First Year of Mars Express HRSC-Camera; DISR Observations of Craters at Titan at the Huygens Landing Site: Insights Anticipated; The Sun s Dust Disk - Discovery Potential of the New Horizons Mission During Interplanetary Cruise; Evidence for Aqueously Precipitated Sulfates in Northeast Meridiani Using THEMIS and TES Data; Integrated Spectroscopic Studies of Anhydrous Sulfate Minerals; Venusian Channel Formation as a Subsurface Process; Reexamination of Quartz Grains from the Permian-Triassic Boundary Section at Graphite Peak, Antarctica; Observations of Calcium Sulfate Deposits at High Latitudes by OMEGA/Mex at Km/Pixel Resolutions; Observations of the North Permanent Cap of Mars in Mid-Summer by OMEGA/MEX at km per Pixel Resolutions; Classification and Distribution of Patterned Ground in the Southern Hemisphere of Mars Genesis: Removing Contamination from Sample Collectors; Thermal Characterization of Fe3O4 Nanoparticles Formed from Poorly Crystalline Siderite; Hydrogen Abundances in Metal Grains from the Hammadah Al Hamra (HaH) 237 Metal-rich Chondrite: A Test of the Nebular-Formation Theory; REE and Some Other Trace Elements Distributions of Mineral Separates in Atlanta (EL6); The Composition and Origin of the Dewar Geochemical Anomaly; Asteroid Modal Mineralogy Using Hapke Mixing Models: Testing the Utility of Spectral Lookup Tables; and The Huygens Mission at Titan: Results Highlights. (sup 182)Hf-(sup 182)W Chronometry and an Early Differentiation in the Parent Body of Ureilites Ground Penetrating Radar in Sedimentary Rocks Mars, Always Cold, Sometimes Wet: New Constraints on Mars Denudation Rates and Climate Evolution from Analog Studies at Haughton Crater, Devon Island, High Arctic Europa s Porous Ice Rheology and Implications for Ice-penetrating Radar Scattering Loss Surface Generated Cracks on Europa

Source record↗

Updated Subsurface Data Base For Bear Creek Valley, Chestnut Ridge, And Parts Of Bethel Valley On The U.S. Department of Energy Oak Ridge Reservation

This document represents a compilation of location, construction, and hydrologic information relating to boreholes, groundwater monitoring wells, and surface water locations that have been installed/established at the Y-12 National Security Complex (Y-12) through August 2013. To date, a total of 1422 boreholes and wells have been installed in and around the Y-12 area. Of those, 835 existing boreholes and wells continue to be utilized for groundwater monitoring programs, research, remedial investigations, plume characterization and delineation studies, and various other hydrogeologic endeavors. In addition, 215 surface water locations, such as rivers, streams, seeps, springs, lakes, ponds, and building sumps are included in this database. General data about boreholes and wells included in the database are survey coordinates, survey system, elevations, alternative names and well status. Surface water location information (Appendix I) includes name, alias, functional area, northing and easting coordinates, survey system, map number and sampling history. Tabulated construction data include total depth, completion method, borehole diameter, casing and screen materials, casing and screen diameters, casing and screen depths, filter pack depths, open-hole intervals, and open-hole diameters. Hydrogeological data summarized in this document include the aquifer monitored by the completion interval, depth to weathered and fresh bedrock, formations penetrated, well sampling history, and whether rock core and geophysical logs were obtained. This document (which is the sixth revision to Y/TS–881 and the ninth overall update of a previous compilation) is published on a regular basis by the Y-12 Groundwater Protection Program (GWPP), which serves as custodian of drilling records and well construction data for the network of wells and other groundwater monitoring stations at Y-12. The tabulations in this database are arranged in appendices of like information. An example application of the data compiled in this document would be the evaluation of the suitability of wells for continued use in groundwater investigations and monitoring studies. Other uses may include: the siting of hydrogeological characterization activities, background evaluations of sites prior to initiation of new drilling activities, and hydrogeological review of selected sites prior to the initiation of remedial actions or new construction activity. Existing boreholes, wells, and surface water locations are presented on a series of maps (Appendix K). Boreholes and wells that have been plugged and abandoned, destroyed, could not be located, or otherwise are of unknown status/condition appear on a second series of maps of identical coverage (Appendix L).

54 ENVIRONMENTAL SCIENCES↗

Devising a framework to Couple Electromagnetic Geophysical Measurements with Reservoir Simulations to Monitor CO2 Plume Movement

Monitoring CO2 plume movement and extent is critical to any CO2 utilization and storage (CCUS) project but can present significant challenges. Downhole measurements (such as cross-well seismic) can give the resolution needed to track the CO2 plume. That resolution comes at a significant expense in equipment and lost production time, and the resolution is only in the vicinity of that well. Surface seismic is less expensive but has decreasing resolution with depth and may not be sensitive to changes in the CO2 plume. Conversely, electrical conductivity has been shown to be correlated with changes in phase saturation associated with CCUS operations. A novel approach for subsurface monitoring that can be applied with minimal expense and operation disruption is charged wellbore casing controlled-source electromagnetics (CWC-CSEM). This technique injects electrical current into two legacy wells. Surface measurements of the induced electric and magnetic fields are obtained with distributed data loggers. Time-lapse measurements are sensitive to changes in CO2 plume movement, but inversion requires the application of prior knowledge from prior characterization efforts. We propose a methodology where simulations are used to inform CWC-CSEM inversion while simultaneously being validated. As such, uncertainty is reduced, and more robust flow models can be devised. A three-year study is underway at the Bell Creek Field in southeast Montana (DOE-NETL Project DE-FE0028320) to evaluate the effectiveness of CWC-CSEM on an active CO2-EOR operation. Determining the relationship between electrical resistivity and phase saturations, and coupling that to a reservoir model is the thrust of this project. Initially, the relative permeability/capillary pressure relationship and the compositional oil model were identified as model parameters with high uncertainty. To elucidate the impact of these uncertain parameters, simulations were run for ten years with a single five-spot pattern. Final water saturation distributions were converted into resistivity using Archie’s Law and available fluid sampling data to provide an exploration of the time lapse electromagnetic anomaly which can be anticipated using CWC-CSEM methods. This technique has promise as an inexpensive and accurate way to monitor CO2 injection in a CCUS site.

Moodie, Nathan↗