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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

University of Hawai‘i, Shallow Geothermal Resources: Energy Technology Innovation Partnership Project (Final Report)

Scientists at Lawrence Berkeley National Laboratory (Berkeley Lab) have teamed up with the University of Hawai‘i at Manoa (UH Manoa) through the U.S. Department of Energy’s Energy Technology Innovation Partnership Project to evaluate the technological and market feasibility of shallow geothermal heat exchanger (GHE) technology. UH requested this analysis to evaluate opportunities in building cooling, energy efficiency, and emissions reduction applications in Hawai‘i. UH has an abundance of geologic and geothermal data and is looking to the national labs’ expertise to execute this analysis. UH is also interested in investigating policy, regulatory, and business conditions advantageous for implementation of a pilot project and more broad deployment of this technology in Hawai‘i. In many locations around the world, the demands for heating and cooling are roughly balanced over the course of the year, so GHEs do not cause significant long-term changes in subsurface temperature. This is not the case in Hawai’i, where the demand for heating is very small, meaning that, over time, GHEs will add heat to the subsurface. If temperatures increase significantly, GHE systems will not work as designed. Regional groundwater flow has the potential to sweep heated water away from boreholes, thereby maintaining the functionality of the GHE system. Significant regional groundwater flow requires two things: a sufficiently large driving hydraulic head gradient (usually closely related to surface topography), and sufficient porosity and permeability to enable groundwater to flow in large enough quantities to enable near-borehole temperatures to be maintained at ambient values. Hawai‘i’s volcanic terrain offers ample surface topographic variation. The lava itself shows an extremely large range of porosity and permeability, so sites with large enough values of these properties must be selected. Numerical modeling of coupled groundwater and heat flow can be used to determine how large is large enough. Primarily, closed-loop systems have been investigated. Other options considered are open-loop systems and using cool seawater as the chilling source. Project work investigated the feasibility of GHE technology at two scales. At the island scale, GIS layers of various attributes relevant for GHE were combined to develop an overall favorability map for employing GHE in Hawai‘i. At the local scale, a hydrogeologic model for the subsurface component of a closed-loop system was developed for the Stan Sheriff Center at the UH Manoa campus. This site is considered promising because the rock below and immediately downgradient of the borefield is highly permeable, consisting of a subsurface karst system (limestone containing high-permeability open channels), which is underlain by a thick, high-permeability fractured basalt. Moreover, the site is near the base of the Ko‘olau Range, providing a large hydraulic head gradient. Thus, groundwater flow through the site is expected to be large, enabling efficient removal of heated groundwater. A full-GHE-system model of the site was also developed, with a simplified representation of the subsurface, in which groundwater flow is not considered and heat transfer is purely by conduction. Using the building cooling load data provided by UH, simulation results show that with groundwater flow present, a GHE can operate successfully for at least 10 years, but with no groundwater flow, the subsurface begins to heat up after only one year of operation, making the GHE unviable within 2-6 years. The team also developed a techno-economic model for this site to compare the cost of cooling using a GHE system with the costs of operating the current air-conditioning system. The GHE system is advantageous economically if favorable tax incentives and interest rates can be obtained.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Web-Based Tools for Data-Informed Remedy Optimization: Software Theory and User Guide

This report documents the development and application of two web-based decision-support tools for pump-and-treat (P&T) groundwater remediation systems: PTOLEMY (Pump-and-Treat Optimized Location Evaluation to Maximize Yields) and OPTIMA (Optimization for Pump-and-Treat Implementation, Management, & Assessment). These tools enhance remedy design and management by leveraging advanced computational methods – specifically deep learning and multi-objective optimization – within a user-friendly platform. By integrating data-driven models with established hydrogeological knowledge, PTOLEMY and OPTIMA enable more efficient evaluation of well placement and operational strategies, helping site managers balance multiple remediation objectives under complex conditions. Both tools are implemented as modules within the SOCRATES (Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites) web platform, which provides data access, visualization, and analytics to support remedy optimization across sites in the U.S. Department of Energy Office of Environmental Management complex. PTOLEMY is a rapid screening module designed to identify promising locations for new extraction wells. It employs a multi-channel three-dimensional convolutional neural network (MC3D-CNN) trained on high-fidelity simulation data to predict the relative performance (in terms of contaminant mass recovery) of potential well sites. Through an interactive web interface, PTOLEMY visualizes the probability of high performance across a site, highlighting areas where an extraction well is likely to yield above-threshold contaminant removal over a multi-year period. PTOLEMY’s map-based displays and exportable results support transparent communication of screening analyses. By focusing attention on the most favorable candidate locations, the tool augments traditional engineering judgment and physics-based modeling, providing a data informed basis for subsequent detailed evaluations. OPTIMA is a multi objective optimization module designed to find wellfield layouts and operating schedules that meet various cleanup goals. It quickly evaluates thousands of candidate setups – combinations of well locations, timing, and rates – and returns a small set of best trade-off options for comparison. At its core, OPTIMA uses a U-Net-based surrogate model – a deep-learning emulator of a groundwater flow and transport simulator – to dramatically accelerate scenario evaluations. Coupling this fast surrogate with the NSGA-II (Non-dominated Sorting Genetic Algorithm II) evolutionary algorithm, OPTIMA explores a wide decision space of well locations and schedules to identify Pareto-optimal solutions that trade off key objectives (e.g., minimizing cleanup time, maximizing contaminant mass removal, and minimizing plume extent). The tool outputs a family of optimal configurations and visualizes their trade-offs (Pareto frontiers of cleanup metrics and maps of optimized well placements). Site managers can use these results to understand the range of viable strategies and to select candidate designs for more detailed verification. OPTIMA is currently under active development and not yet fully released; this guide provides early documentation to support planning and gather user feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Geologic Seawater Air Conditioning (GeoSWAC) System: Resource Assessment and Techno-Economic Evaluation in Puerto Rico

Puerto Rico's hot, humid climate drives a high and persistent demand for cooling, straining an aging and fuel-dependent energy grid while increasing peak electricity loads. Much of this challenge stems from inefficient air-conditioning systems operating in buildings without passive cooling design, making cooling both costly and vulnerable to disruption - especially during hurricanes. To address these issues, researchers evaluated a new alternative called Geologic Seawater Air Conditioning (GeoSWAC), which uses inland wells connected to naturally cold, deep seawater. By avoiding long offshore pipelines and energy-intensive refrigeration cycles, GeoSWAC can cut electricity use by 75-90%, reduce environmental impacts, and operate more reliably during power outages. A case study at the University of Puerto Rico's Rio Piedras campus found that GeoSWAC could deliver significantly lower levelized costs of cooling, reduced operational expenses, and improved water conservation compared to the campus's existing chilled-water plant. The system offers key advantages - including access to a constant cold heat sink, low pumping requirements, and enhanced resilience - for coastal regions such as Puerto Rico, the broader Caribbean, and Florida. However, its effectiveness depends heavily on site-specific geological conditions, such as subsurface connectivity and aquifer characteristics, which require detailed investigation. Future research should refine hydrogeological models, conduct performance and economic analyses, and address regulatory and permitting frameworks to support broader adoption of this promising technology.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

The ParFlow Sandtank: An interactive educational tool making invisible groundwater visible

Physical aquifer models are a highly effective teaching tool for hydrology education, however they come with inherent limitations that include the high cost to purchase, the static configuration of the model materials, the time required to visualize hydrogeological phenomena, and the effort to reset and clean them over time. To address these and other limitations, we have developed an interactive computer simulation of a physical aquifer model called the ParFlow Sandtank. In this gamified interface, users run the simulation using a familiar web-app like interface with sliders and buttons while learning real hydrologic concepts. Our user interface allows participants to dive into the world of hydrology, understanding assumptions about model parameters such as hydraulic conductivity, making decisions about inputs to groundwater aquifer systems such as pumping rates, visualizing outputs such as stream flow, transport, and saturation, and exploring various factors that impact real environmental systems such as climate change. The ParFlow Sandtank has already been used in a variety of educational settings with more than 9,000 users per year, and we feel this emerging educational tool can be used broadly in educational environments and can be scaled-up to provide greater accessibility for students and educators. Here we present the capabilities and workflow of the ParFlow Sandtank, two use cases, and additional tools and custom templates that have been developed to support and enhance the reach of the ParFlow Sandtank.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Radionuclide Transport Simulations Supporting Proposed Borehole Waste Disposal in Israel

A scientific collaboration between the U.S. and Israel is underway to assess the suitability of a potential site for subsurface radioactive waste disposal in the Negev Desert, Israel. The Negev Desert has several favorable attributes for geologic disposal, including an arid climate, a deep vadose zone, interlayered low-permeability lithologies, and carbonate rocks with high uranium-sorption potential. These features may provide a robust natural barrier to radionuclide migration. Geologic and laboratory characterization data from the Negev Desert are incorporated into multiphase flow and transport models, solved using PFLOTRAN, to aid in site characterization and risk analysis that will support decision-making for waste disposal in an intermediate-depth borehole design. The lithology with the greatest uranium sorption potential at the site is phosphorite. We use modeling to evaluate the ability of this layer to impact uranium transport around a proposed disposal borehole. The current objective of the simulations is focused on characterizing hypothetical leakage from waste canisters and subsequent uranium migration under three infiltration scenarios. Here, we describe a hydrogeologic model based on data from a local exploratory borehole and present results for uranium flow and transport simulations under varying infiltration scenarios. We find that under the current climate conditions, it is likely that uranium will remain in the near-field of the borehole for thousands of years. However, under a hypothesized extreme climate scenario representing an increase in infiltration by a factor of 300x above present-day values, uranium may break through the phosphorite layer and exit the base of the model domain (~200 m above the water table) within 1000 years. Simulation results have direct implications for the planning of nuclear waste disposal in the Negev Desert, and specifically in intermediate-depth boreholes.

58 GEOSCIENCES↗
DOE OSTI2025

Permeability Prediction Using Vision Transformers

Accurate permeability predictions remain pivotal for understanding fluid flow in porous media, influencing crucial operations across petroleum engineering, hydrogeology, and related fields. Traditional approaches, while robust, often grapple with the inherent heterogeneity of reservoir rocks. With the advent of deep learning, convolutional neural networks (CNNs) have emerged as potent tools in image-based permeability estimation, capitalizing on micro-CT scans and digital rock imagery. This paper introduces a novel paradigm, employing vision transformers (ViTs)—a recent advancement in computer vision—for this crucial task. ViTs, which segment images into fixed-sized patches and process them through transformer architectures, present a promising alternative to CNNs. We present a methodology for implementing ViTs for permeability prediction, its results on diverse rock samples, and a comparison against conventional CNNs. The prediction results suggest that, with adequate training data, ViTs can match or surpass the predictive accuracy of CNNs, especially in rocks exhibiting significant heterogeneity. This study underscores the potential of ViTs as an innovative tool in permeability prediction, paving the way for further research and integration into mainstream reservoir characterization workflows.

58 GEOSCIENCES↗
DOE OSTI2021

New insights into the drainage of inundated ice-wedge polygons using fundamental hydrologic principles

Abstract. The pathways and timing of drainage from the inundated centers of ice-wedge polygons in a warming climate have important implications for carbon flushing, advective heat transport, and transitions from methane to carbon dioxide dominated emissions. Here, we expand on previous research using a recently developed analytical model of drainage from a low-centered polygon. Specifically, we perform (1) a calibration to field data identifying necessary model refinements and (2) a rigorous model sensitivity analysis that expands on previously published indications of polygon drainage characteristics. This research provides intuition on inundated polygon drainage by presenting the first in-depth analysis of drainage within a polygon based on hydrogeological first principles. We verify a recently developed analytical solution of polygon drainage through a calibration to a season of field measurements. Due to the parsimony of the model, providing the potential that it could fail, we identify the minimum necessary refinements that allow the model to match water levels measured in a low-centered polygon. We find that (1) the measured precipitation must be increased by a factor of around 2.2, and (2) the vertical soil hydraulic conductivity must decrease with increasing thaw depth. Model refinement (1) accounts for runoff from rims into the ice-wedge polygon pond during precipitation events and possible rain gauge undercatch, while refinement (2) accounts for the decreasing permeability of deeper soil layers. The calibration to field measurements supports the validity of the model, indicating that it is able to represent ice-wedge polygon drainage dynamics. We then use the analytical solution in non-dimensional form to provide a baseline for the effects of polygon aspect ratios (radius to thaw depth) and coefficient of hydraulic conductivity anisotropy (horizontal to vertical hydraulic conductivity) on drainage pathways and temporal depletion of ponded water from inundated ice-wedge polygon centers. By varying the polygon aspect ratio, we evaluate the relative effect of polygon size (width), inter-annual increases in active-layer thickness, and seasonal increases in thaw depth on drainage. The results of our sensitivity analysis rigorously confirm a previous analysis indicating that most drainage through the active layer occurs along an annular region of the polygon center near the rims. This has important implications for transport of nutrients (such as dissolved organic carbon) and advection of heat towards ice-wedge tops. We also provide a comprehensive investigation of the effect of polygon aspect ratio and anisotropy on drainage timing and patterns, expanding on previously published research. Our results indicate that polygons with large aspect ratios and high anisotropy will have the most distributed drainage, while polygons with large aspect ratios and low anisotropy will have their drainage most focused near their periphery and will drain most slowly. Polygons with small aspect ratios and high anisotropy will drain most quickly. These results, based on parametric investigation of idealized scenarios, provide a baseline for further research considering the geometric and hydraulic complexities of ice-wedge polygons.

Harp, Dylan R. (ORCID:0000000197778000)↗
DOE OSTI2025

Transfer learning of neural surrogates on multifidelity groundwater simulations

Multifidelity data used in the paper published in Advances in Water Resources 206 (2025) 105140, https://doi.org/10.1016/j.advwatres.2025.105140 The code used to process the data is openly available on GitHub at https://github.com/Model-Reduction-and-UQ-Group/Transfer_Learning_K_reconstruction Computationally inexpensive surrogates of process-based models, such as deep neural networks, enable ensemble-based computations used in risk assessment, data assimilation, etc. However, generation of large datasets required to train a neural network can be as expensive as the ensemble simulations themselves. We ameliorate this challenge by using data from multifidelity (MF) groundwater simulations and transfer learning (TL) to reduce data generation costs while maintaining model accuracy. As a computational example, we train a deep convolutional neural network (CNN) to reconstruct permeability fields from saturation maps derived from a multiphase flow model. Starting with very low- and low-fidelity data generated on increasingly coarse meshes, we pretrain the CNN, followed by output-layer training and fine-tuning using only a limited number of high-fidelity samples. We demonstrate the surrogate’s robustness when interpreting low-quality inputs—such as interpolated maps or data affected by noise—which has strong implications for the applicability in practical hydrogeological scenarios. This multilevel MF-TL strategy achieves a favorable trade-off between computational efficiency and predictive accuracy, significantly outperforming high-fidelity-only approaches under the same computational budget.

Chiofalo, Alessia [University of Bologna] (ORCID:0↗
NASA NTRS1973

Capability of ERTS-1 imagery to investigate geological and structural features in a sedimentary basin (Bassin Parisien, France)

The author has identified the following significant results. The region covered by the MSS images has the benefit of complete geological mapping at scales of 1:80,000, 1:320,000, and 1:1,000,000. Comparison of imagery and exisiting geological maps, particularly the 1:1,000,000 scale, produces important information: (1) Good correspondence is seen between large units distinguished on the images and the concentric strata of the Jurassic, Cretaceous, and Paleocene on the map. (2) Comparison of MSS images with the hydrogeological map of the Parisian basin at 1:500,000 removes all ambiguity with regard to lithological variations. Among the many faults revealed, only three were considered: (1) the Metz; (2)Juranze; and (3) the double fault of the Marne. Imagery shows a conspicuous alignment of the Metz fault unknown until now and ending near Montereau against the group of north-south faults between Montargis and Bourbon l'Archambault. MSS images show that the Juranze fault divides beyond Brienne into two branches of equal importance. The northern one represents the known fault, the southern one was not known until now, but the convergence of the faults constitutes a tectonic trap. The double fault of the Marne is known for a total length of 50 km. ERTS-1 imagery suggest a prolongation toward the southeast which could bring its length to 110 km.

Weecksteen, G.↗
NASA NTRS1974

Preliminary results of ERTS-investigations by W-German investigations

Results are presented of West German investigations into multidisciplinary geoscientific experiments in central Germany and the Alps, and hydrogeological investigations in the Pampa of Argentina based on ERTS-1 data. The main goals of the investigation were achieved. The studies have given a good idea of the possibilities and limitations of ERTS imagery depending on the objectives in question and on the geographical conditions of the areas under investigation. Even in the well known region of central Europe, ERTS has proven its ability of improving present knowledge. In fields such as pollution monitoring and regional planning the satellite techniques should have distinct practical value. For any regional study of less known areas, the value of ERTS imagery can hardly be overestimated.

Muehlfeld, R.↗
NASA NTRS1973

Applications of thermal remote sensing to detailed ground water studies

Three possible applications of thermal (8-14 microns) remote sensing to detailed hydrogeologic studies are discussed in this paper: (1) the direct detection of seeps and springs, (2) the indirect evaluation of shallow ground water flow through its thermal effects on the land surface, and (3) the indirect location of small volumes of ground water inflow into surface water bodies. An investigation carried out with this purpose in an area containing a complex shallow ground water flow system indicates that the interpretation of the thermal imageries is complicated by many factors, among which the most important are: (1) altitude, angle of view, and thermal-spatial resolution of the sensor; (2) vegetation type, density, and vigor; (3) topography; (4) climatological and micrometeorological effects; (5) variation in soil type and soil moisture; (6) variation in volume and temperature of ground water inflow; (7) the hydraulic characteristics of the receiving water body, and (8) the presence of decaying organic material.

Souto-Maior, J.↗
NASA NTRS1974

Contribution of space platforms to a ground and airborne remote sensing programme over active Italian volcanoes

The author has identified the following significant results. A method has been suggested for the forecasting of the lateral eruptions of Mount Etna, through the multispectral analysis of the vegetation behavior. Unknown geological lineaments which seem to be related to deep crustal movements have been discovered using the ERTS-1 imagery. Results in the geological field were obtained in the study of the general structure of the Alpine range. In the field of official vegetation classification, ERTS-1 images were used for a preliminary study of rice fields in northern Italy. Very good experimental results have been obtained using the Skylab multispectral photographs. In the field of hydrogeology and soil type discrimination discoveries of unknown paleoriver beds have been made in the northeastern part of the Po Valley using the multispectral imagery of SL3. The superior resolution of Skylab was a fundamental element for the success of this investigation.

Cassinis, R.↗
NASA NTRS1975

Application of remote sensor data to geologic analysis of the Bonanza test site Colorado

Selected samples of anomalous surface features commonly associated with the various types of uranium deposits are presented and recommendations for sensor applications are given. The features studied include: epigenetic uranium ore roll type; precambrian basal conglomerate type; vein-type uranium deposits; pipe-structure or diatreme deposits; evaporitic uranium deposits. The hydrogeology of the Mosquito Range and the San Luis Valley is also examined.

Lee, K.↗
NASA NTRS1975

Application of Skylab imagery to some geological and environmental problems in Italy

Four topics are considered: regional geology of Sicily, volcanic surveillance in southern Italy, hydrogeology (with special regard given to the discovery and mapping of paleoriverbeds), and crop investigation. The discovery of unknown lineaments and structures in Sicily contributes to the geological knowledge of this region and in particular to the mechanical phenomena involving the upper part of the crust. An attempt was made to relate the status of vegetation surrounding Etna volcano to the magmatic gas escapes filtering through the soil. False-color Skylab images were used to analyze the vigor of the Etnean forestal belt vegetation canopy in order to map possible gas-vent ways as well as the 'active' microfractures. In northern Italy, buried channels were mapped in the Venetian Plain, and a tentative cost-benefit evaluation was done in the field of vegetational studies, both disease detection and species inventory were performed in the Po River Delta and in northwestern Italy.

Cassinis, R.↗
NASA NTRS1975

Water resources, summary

The application of remote sensing products to the development and understanding of water resources problems is considered. Geology and hydrogeology, analysis of watersheds, snow and ice, prediction of runoff from snowmelt, hydrologic land use classifications, soil moisture, evapotranspiration, flood hazards, and water quality surveys are among the topics discussed. Suggestions for further use of remotely sensed data are given along with increased user requirements.

Simons, D. B.↗
NASA NTRS1975

Red River chloride remote sensing study

Side looking radar, infrared thermal imagery and color photography, together with a few examples of black and white panoramic photos, are used to supplement information on the natural saline pollution problem that is hydrologically and geologically oriented. The study area was explored concurrently by ground methods and a reasonably good understanding of hydrogeological conditions has been achieved. Examples of the products acquired, their interpretation, and use techniques are included.

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