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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Sequential Fracture Activation and Stress Evolution During EGS Stimulation at Utah FORGE Revealed by Waveform Cross‐Correlation

Mapping fracture networks in Enhanced Geothermal Systems (EGS) is essential for optimizing reservoir performance, yet complex fracture evolution during stimulation remains difficult to resolve. This study examines the evolution of microseismicity and fracture networks during stage 3 of the 2022 EGS stimulation at the Utah Frontier Observatory for Research in Geothermal Energy site. We map the fracture network represented by 20 clusters of seismic events identified by waveform similarities with cross-correlation. We characterize their geometric properties such as strike, dip, length, and width, and analyze the time evolution of activated fractures. The results reveal a systematic fracture evolution: early activation of pre-existing natural fractures, complex network development during peak injection, and continued activation of less favorably oriented fractures post-injection. Magnitude calibration using the Principal Component Analysis of cross-correlated waveforms improves relative amplitude measurements, refining estimations of the Gutenberg-Richter b-values with spatial variations in b-values suggesting stress re-distribution across the stimulated area. Analysis of the stress state of selected fractures further shows that fractures requiring higher excess pore pressure primarily activate at the end of injection and post-injection, highlighting stress transfer due to pore pressure as a dominant triggering mechanism. These findings provide insights into fracture propagation, stress evolution, and seismic hazard assessment in EGS reservoirs.

Asirifi, Richard [Texas A & M Univ., College Stati↗
DOE OSTI2022

A Dataset of 3D Structural and Simulated Transport Properties of Complex Porous Media

Physical processes that occur within porous materials have wide-ranging applications including - but not limited to - carbon sequestration, battery technology, membranes, oil and gas, geothermal energy, nuclear waste disposal, water resource management. The equations that describe these physical processes have been studied extensively; however, approximating them numerically requires immense computational resources due to the complex behavior that arises from the geometrically-intricate solid boundary conditions in porous materials. Here, we introduce a new dataset of unprecedented scale and breadth, DRP-372: a catalog of 3D geometries, simulation results, and structural properties of samples hosted on the Digital Rocks Portal. The dataset includes 1736 flow and electrical simulation results on 217 samples, which required more than 500 core years of computation. This data can be used for many purposes, such as constructing empirical models, validating new simulation codes, and developing machine learning algorithms that closely match the extensive purely-physical simulation. This article offers a detailed description of the contents of the dataset including the data collection, simulation schemes, and data validation.

3D images↗
DOE OSTI2024

Fluid inertia controls mineral precipitation and clogging in pore to network-scale flows

Mineral precipitation caused by fluid mixing presents complex control and predictability challenges in a variety of natural and engineering processes, including carbon mineralization, geothermal energy, and microfluidics. Precipitation dynamics, particularly under the influence of fluid flow, remain poorly understood. Combining microfluidic experiments and three-dimensional reactive transport simulations, we demonstrate that fluid inertia controls mineral precipitation and clogging at flow intersections, even in laminar flows. We observe distinct precipitation regimes as a function of Reynolds number (Re). At low Reynolds numbers (Re < 10), precipitates form a thin, dense layer along the mixing interface, which shuts precipitation off, while at high Reynolds numbers (Re > 50), strong three-dimensional flows significantly enhance precipitation over the entire intersection, resulting in rapid clogging. When injection rates from two inlets are uneven, flow symmetry-breaking leads to unexpected flow bifurcation phenomena, which result in enhanced concurrent precipitation in both downstream channels. Finally, we extend our findings to rough channel networks and demonstrate that the identified inertial effects on precipitation at the intersection scale are also present and even more dramatic at the network scale. This study sheds light on the fundamental mechanisms underlying mixing-induced mineral precipitation and provides a framework for designing and optimizing processes involving mineral precipitation.

Science & Technology - Other Topics↗
DOE OSTI2024

Inertia-induced mixing and reaction maximization in laminar porous media flows

Solute transport and biogeochemical reactions in porous and fractured media flows are controlled by mixing, as are subsurface engineering operations such as contaminant remediation, geothermal energy production, and carbon sequestration. Porous media flows are generally regarded as slow, so the effects of fluid inertia on mixing and reaction are typically ignored. Here, we demonstrate through microfluidic experiments and numerical simulations of mixing-induced reaction that inertial recirculating flows readily emerge in laminar porous media flows and dramatically alter mixing and reaction dynamics. An optimal Reynolds number that maximizes the reaction rate is observed for individual pore throats of different sizes. This reaction maximization is attributed to the effects of recirculation flows on reactant availability, mixing, and reaction completion, which depend on the topology of recirculation relative to the boundary of the reactants or mixing interface. Recirculation enhances mixing and reactant availability, but a further increase in flow velocity reduces the residence time in recirculation, leading to a decrease in reaction rate. The reaction maximization is also confirmed in a flow channel with grain inclusions and randomized porous media. Interestingly, the domain-wide reaction rate shows a dramatic increase with increasing Re in the randomized porous media case. This is because fluid inertia induces complex three-dimensional flows in randomized porous media, which significantly increases transverse spreading and mixing. This study shows how inertial flows control reaction dynamics at the pore scale and beyond, thus having major implications for a wide range of environmental systems.

Chen, Michael A. (ORCID:0000000294614710)↗
DOE OSTI2024

Physics-informed neural networks for heterogeneous poroelastic media

This study presents a novel physics-informed neural network (PINN) framework for modeling poroelasticity in heterogeneous media with material interfaces. The approach introduces a composite neural network (CoNN) where separate neural networks predict displacement and pressure variables for each material. While sharing identical activation functions, these networks are independently trained for all other parameters. To address challenges posed by heterogeneous material interfaces, the CoNN is integrated with the Interface-PINNs (I-PINNs) framework (Sarma et al., Comput. Methods Appl. Mech. Eng. 429: 117135, 2024), allowing different activation functions across material interfaces. Further, this ensures accurate approximation of discontinuous solution fields and gradients. Performance and accuracy of this combined architecture were evaluated against the conventional PINNs approach, a single neural network (SNN) architecture, and the eXtended PINNs (XPINNs) framework through two one-dimensional benchmark examples with discontinuous material properties. The results show that the proposed CoNN with I-PINNs architecture achieves an RMSE that is two orders of magnitude better than the conventional PINNs approach and is at least 40 times faster than the SNN framework. Compared to XPINNs, the proposed method achieves an RMSE at least one order of magnitude better and is 40% faster.

42 ENGINEERING↗
DOE OSTI2023

Environmental risks and opportunities of orphaned oil and gas wells in the United States

Abstract Hundreds of thousands of documented and undocumented orphaned oil and gas wells exist in the United States (U.S.). These wells have the potential to contaminate water supplies, degrade ecosystems, and emit methane and other air pollutants. Thus, orphaned wells present risks to climate stability and to environmental and human health, which can be reduced by plugging. To quantify environmental risks and opportunities of well plugging at the national level, we analyze data on 81 857 documented orphaned wells across the U.S. We find that > 4.6 million people live within 1 km of a documented orphaned well. 35% of the documented orphaned wells are located within 1 km of a domestic groundwater well, yet only 8% of the wells have groundwater quality data within a 1 km radius. Methane emissions from the documented orphaned wells represent approximately 3%–6% of total U.S. methane emissions from abandoned oil and gas wells, but this estimate is based on measurements at < 0.03% of U.S. abandoned wells. 91% of the documented orphaned wells overlie formations favorable for geologic storage of carbon dioxide and hydrogen, meaning that orphaned well plugging can reduce leakage risks from future storage projects. Finally, we estimate plugging costs for documented orphaned wells to exceed the $4.7 billion federal funding by 30%–80%, emphasizing the importance of prioritizing federal spending on wells with large remediation benefits. Overall, environmental monitoring data are not extensive enough to quantify risks, especially those related to air and water quality and human health. Plugging orphaned wells can provide opportunities for geologic storage of carbon dioxide and hydrogen and geothermal energy development, thereby facilitating efforts to transition to net-zero energy systems. Our analysis on environmental risks and opportunities of orphaned wells provides a framework that can be used to manage the millions of documented and undocumented orphaned wells in the U.S. and abroad.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

High-resolution Bayesian spatial autocorrelation (SPAC) quasi-3-D Vs model of Utah FORGE site with a dense geophone array

SUMMARY We expand the application of spatial autocorrelation (SPAC) from typical 1-D Vs profiles to quasi-3-D imaging via Bayesian Monte Carlo inversion (BMCI) using a dense nodal array (49 nodes) located at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) site. Combinations of 4 and 9 geophones in subarrays provide for 36 and 25 1-D Vs profiles, respectively. Profiles with error bars are determined by calculating coherency functions that fit observations in a frequency range of 0.2–5 Hz. Thus, a high-resolution quasi-3-D Vs model from the surface to 2.0 km depth is derived and shows that surface-parallel sedimentary strata deepen to the west, consistent with a 3-D seismic reflection survey. Moreover, the resulting Vs profile is consistent with a Vs profile derived from distributed acoustic sensing (DAS) data located in a borehole at the FORGE site. The quasi-3-D velocity model shows that the base of the basin dips ∼22° to the west and topography on the basement interface coincident with the Mag Lee Wash suggests that the bedrock interface is an unconformity.

Geochemistry & Geophysics↗
DOE OSTI2021

Experimental study correlating damage and permeability in concrete using confined, flattened Brazilian disks

This research experimentally studies coupled hydro-mechanical relationships using flattened Brazilian disks under confinement, with concurrent permeability measurements and acoustic emission monitoring. A series of tests are performed on concrete, as representative samples of brittle geo-materials, under a range of confining stresses between 2.76 and 13.79 MPa. Acoustic emission data is used to quantify damage and identify damage thresholds. Damage is then correlated to pre-peak changes in permeability. The advancement of models that couple transport properties to mechanical responses are of interest in the fields of carbon sequestration, hydrofracking, production of geothermal energy, induced seismicity, and underground nuclear waste storage, and these experiments validate a novel experimental approach towards investigating hydro-mechanical relationships.

Boyce, S.↗
DOE OSTI2024

Introduction to special section: Induced seismicity

Induced seismicity refers to earthquakes related to anthropogenic activities such as wastewater disposal, hydraulic fracturing, and geothermal energy production. In Oklahoma, wastewater disposal is considered to have caused more than 100 earthquakes of magnitude 4 and above (M4+) since 2010. Similarly, over 50 such events have been recorded in the Permian Basin of Texas and New Mexico. Additionally, some of these earthquakes have magnitudes exceeding 5.0, including a magnitude 5.8 event in Pawnee, Oklahoma, in a magnitude 5.6 event in the Peace River Oil Sands Area in Alberta, and a magnitude 5.4 event in the Delaware Basin of Texas.

58 GEOSCIENCES↗
DOE OSTI2020

Using geodetic data in geothermal areas

Geodetic observations, often in conjunction with other data, provide a cost-effective means for identifying and characterizing geothermal resources. Here, a review of the various methods reveals how the technology for measuring deformation has advanced considerably in the past few decades. Currently, interferometric synthetic aperture radar is the method of choice for monitoring deformation at a geothermal field. A discussion of geodetic monitoring at The Geysers geothermal field, California, illustrates some of the progress made and the challenges that remain.

58 GEOSCIENCES↗
DOE OSTI2020

US Geothermal Electricity and Heat Market Analysis and Report

The power production data from FY19 is provided for U.S. geothermal power plants. The spreadsheet includes the plant name and type, nameplate capacity, summer capacity, winter capacity, and net generation for each power plant.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

GeoThermalCloud framework for fusion of big data and multi-physics models in Nevada and Southwest New Mexico

Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information about SmartTensors can be found at the SmartTensors Github Repository and the SmartTensors page at LANL.gov. Links to these pages are included in this submission. GeoThermalCloud.jl is a repository containing all the data and codes required to demonstrate applications of machine learning methods for geothermal exploration. GeoThermalCloud.jl includes: - site data - simulation scripts - jupyter notebooks - intermediate results - code outputs - summary figures - readme markdown files GeoThermalCloud.jl showcases the machine learning analyses performed for the following geothermal sites: - Brady: geothermal exploration of the Brady geothermal site, Nevada - SWNM: geothermal exploration of the Southwest New Mexico (SWNM) region - GreatBasin: geothermal exploration of the Great Basin region, Nevada Reports, research papers, and presentations summarizing these machine learning analyses are also available and will be posted soon.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Utah FORGE Updated Well, Well Pad, and Seismic Station GPS Coordinates December, 2021

This is a CSV spreadsheet containing UTM and Latitude and Longitude coordinates and elevations for Wells 78-32, 78B-32, 56-32, 58-32, 68-32, and 16A(78)-32 and seismic stations BOR1, BOR2, BOR3, FOR1, FOR2, FOR5, FOR6, FOR 7, FOR8, FORK, FORU, FORW, and FORB. These are from a GPS survey conducted by the Utah Geological Survey completed in December, 2021.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Laboratory Drilling Test Data of PDC bits with Sierra White Granite Rock

This file contains unprocessed drilling data tests on Sierra White Granite (SWG) using two new PDC bits. The tests were conducted at Sandia National Laboratories (SNL) in the Hard Rock Drilling Facility (HRDF). The collected data includes ROP data at rotational speeds of 80, 120, and 160 RPMs, with incremental weight on bit (WOB) up to 5100 lbs. The diameter of the 4-bladed and 5-bladed PDC bits was 3 3/4" and supplied by National Oilwell Varco (NOV). Five tests modes were conducted for both bits, which are as follow: (1) Rigid configuration, with no vibration compliance (2) Flywheel configuration (3) Torsional compliance configuration (4) Axial Compliance configuration (5) Combined Axial and Torsional compliance configuration Note: the WOB and torque in the drilling data should be calibrated by zeroing the WOB and torque when the drill bit tags the rock sample.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

INGENIOUS Thermal Conductivity Measurement Source Categorization

Thermal conductivity (TC) data taken for different wells at a specified drill depth. This is an abridged version of the complete SMU heat flow database, downloaded from the SMU node of the NGDS at the beginning of INGENIOUS (approximately April 2021), and filtered to the INGENIOUS study area. This National Geothermal Data System (NGDS) project aggregates geothermal data collected and curated by the SMU Geothermal Laboratory and its partner organizations. All columns in this database are the same as the SMU database, except for 2 additions associated with this project. Repeated columns are for data correlation purposes. Column descriptions and data types are the same as previous iterations of the SMU database. The new values that are the addition are two new columns developed as part of the INGENIOUS project: INGENIOUS TC Value | INGENIOUS notes INGENIOUS notes are individual notes that were written for specific data points during the analysis process. There are not always notes associated with each input value. INGENIOUS TC Value includes 4 values: 1. Assumed Measured These are values that are assumed to be measured thermal conductivity values, either within a specific well or within the same study region. Many of these have either a published reference, a reported standard deviation, or a unique thermal conductivity value. 2. Data release - assumed measured These are values in the SMU database that are from proprietary data that were added to the SMU database and are labeled as data release for their reference. These values were searched for in person at the SMU Geothermal Laboratory as well as virtual examination of data available on the NGDS. For many of these, there are reported thermal conductivity values associated with the heat flow data in the database, but no specific table or reference to measurements in the original data release files. 3. Known measured These are values that have a reported measurement, either as an original file in the SMU data files on the NGDS or a reported table in a publication. In the rare circumstances, Maria Richards or David Blackwell confirmed measurement. Confirmation of measurement would be written in the INGENIOUS notes column. 4. Unmeasured Unmeasured values are those that are known to be unmeasured, either estimated from another report or no information given. In the SMU database, there are wells that have a heat flow but no thermal conductivity. These are categorized as unmeasured. There are also heat flow values that are stated to have estimated or generalized average thermal conductivity values for the region and rock type. Because these are known to be unmeasured, they are categorized as such. 5. Blank Blank values are either A quality or X quality. These quality values are stated in the INGENIOUS notes. These values were not going to change associated with the heat flow analysis, so these were not examined.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Purdue University: Results of B-Value Tests for Rock Saturation

This dataset includes an Excel file with the results of B-value tests to determine the magnitude of the back pressure required for full saturation of Sierra White granite samples. Test were conducted on cylindrical rock specimens of Sierra White granite in a custom water pressurized chamber. Dimensions and properties of Sierra White granite specimens are summarized in the PDF file. The PDF file also includes a description of the B-value tests, experimental procedure, and results.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Utah FORGE - Development of a Reservoir Seismic Velocity Model and Seismic Resolution Study

This is data from and a final report on the development of a 3D velocity model for the larger FORGE area and on the seismic resolution in the stimulated fracture volume at the bottom of well 16A-32. The velocity model was developed using RMS velocities of the seismic reflection survey and seismic velocity logs from borehole measurements as an input model. To improve the accuracy of the model in the shallow subsurface, travel times phase arrivals of the direct propagating P-waves were determined from the seismic reflection data, using PhaseNet, a deep-neural-network-based seismic arrival time picking method. The travel times were subsequently inverted using the input velocity model. The seismic resolution study used borehole and surface seismic sensors as well as the seismicity observed during the April 2022 stimulation experiment to estimate the seismic resolution in the activated fracture reservoir. The data contain a 3D P- and S-wave velocity model for the larger FORGE area.

15 GEOTHERMAL ENERGY↗