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At least 1,009 records · Page 56

Accelerating geostatistical modeling using geostatistics-informed machine Learning

Ordinary Kriging (OK) is a popular geostatistical algorithm for spatial interpolation and estimation. The computational complexity of OK changes quadratically and cubically for memory and speed, respectively, given the number of data. Therefore, it is computationally intensive and also challenging to process a large set of data, especially in three-dimensional (3D) cases. This paper develops a geostatistics-informed machine learning (GIML) model to improve the efficiency of OK by reducing the number of points required to be estimated using OK. Specifically, only a very few of the unknown points are estimated by OK to get the weights and estimations, which are used as the training dataset. Moreover, the governing equations of OK are used to guide our proposed machine learning to better reproduce the spatial distributions. Our results show that the proposed GIML can reduce the computational time of OK by at least one order of magnitude. The effectiveness of the GIML is evaluated and compared using a 2D case. Furthermore, we demonstrate its efficiency and robustness by considering a different number of training samples on various 3D simulation grids.

58 GEOSCIENCES↗

The appearance of plasticity on the blocks surfaces in geological media

In present the elasticity and plasticity are absolutely different models of solids, which are not relate to each other. The experimental observations show, that the plasticity arrives and localizes on the surfaces of structures, which contain solid samples. The transition in special state, where a small part of solid volume is in plastic state, while the main part of volume is in elastic state not be describe by classical continuum Cauchy and Poisson model. This classical model requires two alternative states. Either is elastic state in the all volume or plastic one for all elementary volume too. However, the structured model of space gives us a possibility to describe this complicate state. In this paper shown that the sliding surfaces divided to each other by distances equal to the average sizes of microstructures, in the contrary of classical plasticity, where they have not characteristic distance. The energy of plastic transition is very small, because the main part of volume is elastic body. This description means the smooth transition from elasticity to plasticity in vicinity of sliding surfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Geologic studies of outer solar system satellites: Iapetus and Europa

A model of regolith evolution on bodies subjected to an asymmetric impact flux is presented. The general effect of an asymmetric impact flux is ballistic diffusion of regolith from areas of high impact flux to areas of lower flux. The effect is most pronounced on low gravity bodies where ejecta travel distances are large, and on bodies with strong flux asymmetries. It may be especially important on Iapetus, where retrograde debris from Phoebe striking the leading hemisphere may produce a flux asymmetry as large as 100 to 1 from apex to antapex. We find that the net amount of material transported by ballistic diffusion is inversely proportional to satellite density. Theoretical calculations and Voyager observations support the view that tidal heating is sufficient to maintain a liquid layer throughout the history of Europa. Photosynthetic, thermal, electrical, and chemical energy sources are considered. The calculations suggest that there may be regions on Europa, very limited in space and time, with physical conditions that are within the range of adaptation of life on Earth. Calculations for the electrical currents within Europa for a thick ice crust are very small.

Squyres, S. W.↗

The Value of Reversible Carbon Storage in a Zero-Emissions World

Atmospheric carbon dioxide removal (CDR) is required to stabilize global temperature. CDR can be achieved via ecosystem-based approaches that are cost-effective but reversible (e.g., soil and forest management) or by more durable but expensive approaches (e.g., direct air capture coupled with geologic storage). Here, we examine trade-offs between these approaches, focusing on timing, climate impacts, and cost. We simulated reversible carbon accrual for a range of CDR contract structures using a general minimalist model of ecosystem carbon cycling, and parameterized it to simulate US agricultural soil management─specifically cover cropping─as a case study. We then quantified the resulting impact on atmospheric carbon and global temperature using a climate model emulator. We find that maintaining a patchwork of reversible CDR projects by replacing lapsed projects with new projects can reduce warming by 22–195 μ°C in 2100 and that the magnitude of this cooling effect depends on how effectively the patchwork is maintained. Long-term maintenance of reversible CDR projects requires institutional stability that cannot be guaranteed over multiple decades. Consequently, effective CDR ultimately requires replacing reversible projects with durable projects. To address this problem, we modeled the cost of replacing reversible agricultural soil CDR with geologic CDR. We found that using reversible CDR as a bridge to durable CDR is potentially more cost-effective as a global cooling strategy (0.20–0.81 billion USD per μ°C avoided) than perpetual maintenance of reversible CDR (0.32–1.31 billion USD per μ°C avoided) or an immediate transition to durable CDR (1.37–2.19 billion USD per μ°C avoided). However, we emphasize that institutional commitments to maintain reversible CDR projects cannot be guaranteed. Reliance on reversible CDR as a bridge to durable CDR therefore carries an unknown amount of risk and will only function if efforts to maintain reversible CDR are robust.

carbon capture and storage↗

High resolution identification and quantification of diffuse deep groundwater discharge in mountain rivers using continuous boat-mounted helium measurements

Discharge of deeply sourced groundwater to streams is difficult to locate and quantify, particularly where both discrete and diffuse discharge points exist, but diffuse discharge is one of the primary controls on solute budgets in mountainous watersheds. The noble gas helium is a unique identifier of deep groundwater discharge because groundwater with long residence times is commonly enriched in helium. In this study, a portable mass spectrometer was used to measure longitudinal variation in dissolved helium concentrations in two mountainous rivers at high spatial resolution not feasible with traditional sampling techniques. Helium profiles were then simulated using a mass-balance model to quantify longitudinal variation in groundwater discharge to the receiving rivers. Results indicate helium concentrations were enriched by multiple orders of magnitude above atmospheric equilibrium in both rivers and that this persisted for up to 18 km below observed pulse inputs in the Colorado River. Helium mass-balance models match observed longitudinal patterns with the exception of sharp initial increases in helium observed in the rivers. Increased longitudinal groundwater discharge rates correspond to mapped geologic structures in both watersheds that likely transport deep geothermal water. Models show variable sensitivity to spatial assignment of input variables representing the groundwater source, illustrating the importance of collecting data from discrete groundwater discharges where possible. The methodology shows promise for field experiments designed to assess air–water exchange rates and to quantify total groundwater discharge from a combination of discrete and diffuse sources.

Deep groundwater↗

Aseismic crustal deformation in the Transverse Ranges of southern California

Using geodetic data at a plate boundary, the subsurface displacements that accompany plate motion were modeled as the sum of rigid block motion and the elastic effects of frictional drag between blocks in a model consisting of 12 blocks and 27 rectangular fault patches. The block motion inferred from the geodetic data has the same order of magnitude as the geologic estimates, and for many faults the agreement was excellent. The model implies about 20 mm/y of crustal shortening normal to the trend of the San Andreas fault.

Cheng, Abe↗

Predicting Flow in Fracture Networks With Quantum Algorithms

Uncertainty quantification plays a crucial role in the modeling of subsurface flow. For instance, uncertainties in the properties of geologic fracture networks significantly impact flow, requiring numerous simulations to accurately estimate quantities of interest. However, each simulation is computationally expensive because it requires solving a large linear system to capture features that involve both small and large fractures. An example is in percolation, where the interaction of many small fractures (which cumulatively can have a large surface area) with the rock matrix must be modeled precisely. Quantum computing is an emerging tool with the potential to address this issue. Quantum algorithms offer a significant speedup in solving linear systems, achieving efficiencies that are challenging to match with classical approaches. These classical approaches include direct solvers, such as LU decomposition, and iterative methods, notably preconditioned conjugate gradient, commonly used in subsurface modeling to solve large sparse systems. However, applying quantum algorithms to geologic fracture flow requires careful attention to algorithmic and problem-specific constraints to fully realize this quantum advantage. In this work we describe a quantum algorithm for generalized Monte Carlo applications with a quadratic speedup over the classical approaches which can be combined with the quantum speedup, currently under investigation, for solving quantum linear systems for subsurface flow. We show that for quantum algorithms the computational cost of estimating a quantity of interest for a statistical ensemble of networks is roughly the same as that of a single realization, essentially implying that one can get uncertainty quantification for free.

58 GEOSCIENCES↗

Shape of the ocean surface and implications for the Earth's interior: GEOS-3 results

A new set of 1 deg x 1 deg mean free air anomalies was used to construct a gravimetric geoid by Stokes' formula for the Indian Ocean. Utilizing such 1 deg x 1 deg geoid comparisons were made with GEOS-3 radar altimeter estimates of geoid height. Most commonly there were constant offsets and long wavelength discrepancies between the two data sets; there were many probable causes including radial orbit error, scale errors in the geoid, or bias errors in altitude determination. Across the Aleutian Trench the 1 deg x 1 deg gravimetric geoids did not measure the entire depth of the geoid anomaly due to averaging over 1 deg squares and subsequent aliasing of the data. After adjustment of GEOS-3 data to eliminate long wavelength discrepancies, agreement between the altimeter geoid and gravimetric geoid was between 1.7 and 2.7 meters in rms errors. For purposes of geological interpretation, techniques were developed to directly compute the geoid anomaly over models of density within the Earth. In observing the results from satellite altimetry it was possible to identify geoid anomalies over different geologic features in the ocean. Examples and significant results are reported.

Chapman, M. E.↗

Value of abstraction in performance assessment – When is a higher level of detail necessary?

In this study, different approaches in performance assessment (PA) of the long-term safety of a repository for radioactive waste were examined. This investigation was carried out as part of the DECOVALEX-2023 project, an international collaborative effort for research and model comparison. One specific task of the DECOVALEX-2023 project was the Salt Performance Assessment Modelling task (Salt PA), which aimed at comparing various models and methods employed in the performance assessment of deep geological repositories in salt. In the context of the Salt PA task, three distinct teams from SNL (United States), Quintessa Ltd (United Kingdom), and GRS (Germany) examined the consequences of employing different levels of abstractions when modelling the repository's geometry and implementing various features and processes, using the example of a simple hypothetical repository structure in domal salt. Each team applied their own tools: PFLOTRAN (SNL), QPAC (Quintessa) and LOPOS (GRS). These differ essentially regarding numerical concept and degree of detail in the representation of the underlying physical processes. The discussion focused on when simplifications can be appropriately applied and what consequences result from them. Furthermore, it was explored when and if a higher level of fidelity in geometry or physical processes is required.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

GDSA Framework Development and Process Model Integration FY2021

The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Spent Fuel & Waste Disposition (SFWD) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and highlevel nuclear waste (HLW). A high priority for SFWST disposal R&D is disposal system modeling (DOE 2012, Table 6; Sevougian et al. 2019). The SFWST Geologic Disposal Safety Assessment (GDSA) work package is charged with developing a disposal system modeling and analysis capability for evaluating generic disposal system performance for nuclear waste in geologic media.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Impacts of elevated dissolved CO 2 on a shallow groundwater system: Reactive transport modeling of a controlled-release field test

We report one of the risks that CO 2 geological sequestration imposes on the environment is the impact of potential CO 2 /brine leakage on shallow groundwater. The reliability of reactive transport models predicting the response of groundwater to CO 2 leakage depends on a thorough understanding of the relevant chemical processes and key parameters affecting dissolved CO 2 transport and reaction. Such understanding can be provided by targeted field tests integrated with reactive transport modeling. A controlled-release field experiment was conducted in Mississippi to study the CO 2 -induced geochemical changes in a shallow sandy aquifer at about 50 m depth. The field test involved a dipole system in which the groundwater was pumped from one well, saturated with CO 2 at the pressure corresponding to the hydraulic pressure of the aquifer, and then re-injected into the same aquifer using a second well. Groundwater samples were collected for chemical analyses from four monitoring wells before, during and after the dissolved CO 2 was injected. In this paper, we present reactive transport models used to interpret the observed changes in metal concentrations in these groundwater samples. A reasonable agreement between simulated and measured concentrations indicates that the chemical response in the aquifer can be interpreted using a conceptual model that encompasses two main features: (a) a fast-reacting but limited pool of reactive minerals that responds quickly to changes in pH and causes a pulse-like concentration change, and (b) a slow-reacting but essentially unlimited mineral pool that yields rising metal concentrations upon decreased groundwater velocities after pumping and injection stopped. During the injection, calcite dissolution and Ca-driven cation exchange reactions contribute to a sharp pulse in concentrations of Ca, Ba, Mg, Mn, K, Li, Na and Sr, whereas desorption reactions control a similar increase in Fe concentrations. Finally, after the injection and pumping stops and the groundwater flow rate decreases, the dissolution of relatively slow reacting minerals such as plagioclase drives the rising concentrations of alkali and alkaline earth metals observed at later stages of the test, whereas the dissolution of amorphous iron sulfide causes slowly increasing Fe concentrations.

58 GEOSCIENCES↗

Uranium (VI) Adsorbate Structures on Portlandite [Ca(OH)2] Type Surfaces Determined by Computational Modelling and X-ray Absorption Spectroscopy

Portlandite [Ca(OH) 2 ] is a potentially dominant solid phase in the high pH fluids expected within the cementitious engineered barriers of Geological Disposal Facilities (GDF). This study combined X-ray Absorption Spectroscopy with computational modelling in order to provide atomic-scale data which improves our understanding of how a critically important radionuclide (U) will be adsorbed onto this phase under conditions relevant to a GDF environment. Such data are fundamental for predicting radionuclide mass transfer. Surface coordination chemistry and speciation of uranium with portlandite [Ca(OH) 2 ] under alkaline groundwater conditions (ca. pH 12) were determined by both in situ and ex situ grazing incidence extended X-ray absorption fine structure analysis (EXAFS) and by computational modelling at the atomic level. Free energies of sorption of aqueous uranyl hydroxides, [UO 2 (OH) n ] 2–n (n = 0–5) with the (001), (100) and (203) or (101) surfaces of portlandite are predicted from the potential of mean force using classical molecular umbrella sampling simulation methods and the structural interactions are further explored using fully periodic density functional theory computations. Although uranyl is predicted to only weakly adsorb to the (001) and (100) clean surfaces, there should be significantly stronger interactions with the (203/101) surface or at hydroxyl vacancies, both prevalent under groundwater conditions. The uranyl surface complex is typically found to include four equatorially coordinated hydroxyl ligands, forming an inner-sphere sorbate by direct interaction of a uranyl oxygen with surface calcium ions in both the (001) and (203/101) cases. In contrast, on the (100) surface, uranyl is sorbed with its axis more parallel to the surface plane. The EXAFS data are largely consistent with a surface structural layer or film similar to calcium uranate, but also show distinct uranyl characteristics, with the uranyl ion exhibiting the classic dioxygenyl oxygens at 1.8 Å and between four and five equatorial oxygen atoms at distances between 2.28 and 2.35 Å from the central U absorber. These experimental data are wholly consistent with the adsorbate configuration predicted by the computational models. These findings suggest that, under the strongly alkaline conditions of a cementitious backfill engineered barrier, there would be significant uptake of uranyl by portlandite to inhibit the mobility of U(VI) from the near field of a geological disposal facility.

36 MATERIALS SCIENCE↗

Geologic Characterization of the South Georgia Rift Basin for Source Proximal CO2 Storage

The project Geologic Characterization of the South Georgia Rift Basin for Source Proximal CO2 Storage is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The South Carolina Research Foundation and partners evaluated the feasibility of CCS in the Jurassic/ Triassic (J / TR) saline formations of the buried Mesozoic South Georgia Rift (SGR) Basin that extends from South Carolina into Georgia. The J / TR sequence, based on preliminary assessment of limited geologic and geophysical data, appears to have both the appropriate areal extent and multiple horizons to permanently and safely store CO2 The presence of several igneous rock layers within the sequence may potentially provide adequate seals to prevent upward CO2 migration into the Coastal Plain aquifer systems. Approximately 81 kilometers of 2-D seismic reflection data were collected by Bay Geophysical, Inc. to explore a portion of the SGR located in southern Georgia. The 81 kilometers were divided into two lines approximately 40.5 kilometers each, with Line 1 intersecting Georgia well GGS 3457. Line 2 intersects Line 1 at the southern portion of Line 1 to maximize the extent of coverage away from GGS-3457 (a deep well drilled in the 1980s for oil and gas exploration). This well had a set of usable logs, including gamma and neutron logs that provided promising results related to CO2 storage. Results showed sandstone with porosity values greater than 10 percent and a thickness of 120 meters. The design of the seismic shot was to extrapolate information away from the well and to better define the extent of the SGR and the necessary reservoir and caprock for a successful CO2 injection. A numerical simulation model of CO2 Injection and migration was developed based on the geology log for the GGS-3457 well. The simulation model was used to investigate the feasibility of injecting 30 million metric tons of CO2 into SGR J / TA sediments and integrity of the diabase layers as seals to prevent CO2 migration.

2-D seismic↗

The moon - Composition determined by nebular processes

The Ganapathy-Anders seven-component model is used as the basis for an analysis of conditions in the early solar nebula as they pertain to the formation of the moon. Calculations incorporating improved geological data and petrological constraints are presented in terms of a model moon which meets trace element restrictions and conforms to known parameters of heat flow, density, and moment of inertia ratio, ie., 40 ppb U, and a core of 2% by weight. It is noted that a melt of the model composition approximates that of Apollo 15 green glass, together with a residuum of olivine, plus 3-4% spinel.

Morgan, J. W.↗

Building a virtual planet

The virtual Planetary Laboratory (VPL) is a recently funded 5-yr project, which seeks toimprove our understanding of the range of plausible environments and the likely signatures for life on extrasolar terrestrial planets. To achieve these goals we are developing a suite of innovative modeling tools to simulate the environments and spectra of extrasolar planets. The core of the VPL IS a coupled radiative transfer/climate/chemistry model, which is augmented by interchangeable modules which characterize geological, exogenic, atmospheric escape, and life processes. The VPL is validated using data derived from terrestrial planets within our own solar system. The VPL will be used to explore the plausible range of atmospheric composittions and globally averaged spectra for extrasolar planets and for early Earth, and will improve our understanding of the effect of life on a planet's atmospheric spectrum and composition. The models will also be used to create a comprehensive spectral catalog to provide recommendations on the optimum wavelength range, spectral resolution, and instrument sensitivity required to characterize extrasolar terrestrial planets. Although developed by our team, the VPL is envisioned to be a comprehensive and flexible tool, which can be collaboratively used by the broader planetary science and astrobiology communities. This presentation will describe the project concept, the tasks involved, and will outline current progress to date. This work is funded by the NASA Astrobiology Institute.

astrobiology↗

Qualification of Numerical and Semi-Analytical Modeling Codes for Thermal Design of HLW Repository - 18455

Disposal in a geological repository is a viable option for safely isolating high-level radioactive waste. Thermal processes induced by decay heat from the radioactive waste may impact the integrity of the engineered barrier system, and may lead to fluid flow and transport; and the associated migration of radionuclides. This study looks at an analysis of thermal conduction for the emplacement of high-level waste in a repository located in bedded salt. The simulations used analytical and numerical methods to study conductive heat transport in a repository. This study concentrated on heat flow in a central waste package with contributions from adjacent waste packages and drifts. Of particular importance to this work is comparison of predictions of peak temperature at the drift wall and at the waste package surface using different solution methods. Simulation results of analytical and numerical modeling methods are compared. The results show that predictions of the codes were comparable under identical initial and boundary conditions. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Boosting Barlow Twins Reduced Order Modeling for Machine Learning‐Based Surrogate Models in Multiphase Flow Problems

Abstract We present an innovative approach called boosting Barlow Twins reduced order modeling (BBT‐ROM) to enhance the reliability of machine learning surrogate models for multiphase flow problems. BBT‐ROM builds upon Barlow Twins reduced order modeling that leverages self‐supervised learning to effectively handle linear and nonlinear manifolds by constructing well‐structured latent spaces of input parameters and output quantities. To address the challenge of high contrast data in multiphase flow problems due to injection wells and faults, we employ a boosting algorithm within BBT‐ROM. This algorithm sequentially trains a set of weak models (i.e., inaccurate models), improving prediction accuracy through ensemble learning. To evaluate the performance of BBT‐ROM, we conduct three three‐dimensional multiphase flow problems, including waterflooding and geologic carbon storage (GCS), with varying numbers of input parameter cases and model domain features. The results demonstrate that BBT‐ROM excels at predicting non‐wetting phase saturation (e.g., oil or saturation) and fluid pressure, with average relative errors ranging from 0.5% to 3%. Importantly, BBT‐ROM showcases robustness when faced with limited input parameter space during GCS testing.

58 GEOSCIENCES↗

BioRT-Flux-PIHM v1.0: a biogeochemical reactive transport model at the watershed scale

Watersheds are the fundamental Earth surface functioning units that connect the land to aquatic systems. Many watershed-scale models represent hydrological processes but not biogeochemical reactive transport processes. This has limited our capability to understand and predict solute export, water chemistry and quality, and Earth system response to changing climate and anthropogenic conditions. Here we present a recently developed BioRT-Flux-PIHM (BioRT hereafter) v1.0, a watershed-scale biogeochemical reactive transport model. The model augments the previously developed RT-Flux-PIHM that integrates land-surface interactions, surface hydrology, and abiotic geochemical reactions. It enables the simulation of (1) shallow and deep-water partitioning to represent surface runoff, shallow soil water, and deeper groundwater and of (2) biotic processes including plant uptake, soil respiration, and nutrient transformation. The reactive transport part of the code has been verified against the widely used reactive transport code CrunchTope. BioRT-Flux-PIHM v1.0 has recently been applied in multiple watersheds under diverse climate, vegetation, and geological conditions. This paper briefly introduces the governing equations and model structure with a focus on new aspects of the model. It also showcases one hydrology example that simulates shallow and deep-water interactions and two biogeochemical examples relevant to nitrate and dissolved organic carbon (DOC). These examples are illustrated in two simulation modes of complexity. One is the spatially lumped mode (i.e., two land cells connected by one river segment) that focuses on processes and average behavior of a watershed. Another is the spatially distributed mode (i.e., hundreds of cells) that includes details of topography, land cover, and soil properties. Whereas the spatially lumped mode represents averaged properties and processes and temporal variations, the spatially distributed mode can be used to understand the impacts of spatial structure and identify hot spots of biogeochemical reactions. The model can be used to mechanistically understand coupled hydrological and biogeochemical processes under gradients of climate, vegetation, geology, and land use conditions.

54 ENVIRONMENTAL SCIENCES↗