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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Summary of Externally-Driven Cavern Oil Mixing Research at SNL Including Work Performed at ASU/Notre Dame and UMass-Dartmouth

Sandia National Laboratories is investigating oil mixing in underground storage caverns as part of the Strategic Petroleum Reserve (SPR) program. Oil mixing in caverns can be classified as internally - driven or externally driven. In externally - driven mixing, which is addressed in this report, processes external to the cavern and the underground environment such as the introduction and removal of fluids can cause mixing of the oil. Miscible and immiscible mixing processes are discussed. As part of this investigation, research into the fundamental mixing processes for layered caverns has been conducted by Professor H.J.S. Fernando and associates at Arizona State University (ASU) (2006 - 2009) and at the University of Notre Dame (2010 - 2012) for miscible mixing from jets. Additional research for immiscible mixing at an interface due to fluid injection was conducted at the University of Massachusetts - Dartmouth. The results of the research conducted at Sandia National Laboratories and at ASU/Notre Dame and UMass - Dartmouth are summarized in this report.

02 PETROLEUM↗
DOE OSTI2022

Combustion Kinetics Model Development & Fluid Property Experimental Investigation For Improved Design Of Supercritical CO 2 Power Cycle Components

Supercritical carbon dioxide (sCO 2 ) cycles are being investigated for the future of power generation and will contribute to a carbon-neutral future to combat the effects of climate change. These direct-fired closed cycles will produce power without adding significant pollutants to the atmosphere. For such cycles to be efficient, they will need to operate at significantly higher pressures (e.g., 300 atm for Allam Cycle) than existing systems (typically less than 40 atm). There is limited knowledge on combustion at these high pressures and with a high dilution of carbon dioxide. Also, various experimental and computational investigations and model developments have been performed by the University of Central Florida (UCF), Embry-Riddle Aeronautical University (ERAU), and Stanford University (S.U.) to improve the current knowledge base and support the design and development of sCO 2 combustors. This project's technical aspects include chemical kinetics development, fundamental sCO 2 combustion, combustion model and sub-model development, supercritical fluid injection characterization, and heat transfer characterization.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Identification of Faults Susceptible to Induced Seismicity Final Report

The primary objective of this project (referred to as the State of Stress project or SoS project) was to predict the presence of faults susceptible to movement in the presence of fluid injection as a consequence of vertical pressure migration from the storage unit to the crystalline basement. These faults included those difficult to resolve with traditional interpretations of surface seismic: faults with no or minimal offset, faults in the crystalline basement where no seismic reflectors are present, subseismic faults (due to size), and faults undetected (e.g., due to unfavorable orientation with surface seismic survey).

25 ENERGY STORAGE↗
DOE OSTI2024

A Complete Machine-Learning-Based Workflow to Illuminate Earthquake Processes

Under this grant we developed, tested, and made available, machine learning models to improve the tasks in the earthquake monitoring workflow (Figure 1). We implemented these models as a part of an end-to-end workflow for seismic network processing and demonstrated, in a variety of settings, that these methods generalize and that they result in dramatically more comprehensive earthquake catalogs. These catalogs illuminate earthquake processes in detail and to an extent that had previously not been possible, and they do so for both tectonic seismicity and seismicity induced by fluid injection related to unconventional hydrocarbon development. This report summarizes the results from the 15 publications that resulted from this grant. Those contributes are divided into: (1) the development of specific tasks related to monitoring (7 publications), (2) the organization of those tasks into workflows for seismic monitoring (2 publications), and (3) applications of those workflows to data (6 publications).

58 GEOSCIENCES↗
DOE OSTI2024

SMART Deliverable 6.1.2a: Application of the ORION tool to the IBDP Carbon Storage Site

Forecasting and managing potential induced seismic activity is one of the challenges facing commercialscale geologic carbon sequestration (GCS), as well as other geologic energy extraction and byproduct disposal technologies. Historically, the process to develop robust, science-based forecasts of induced seismicity has required an integrated effort from experts in seismology, geomechanics, and reservoir engineering to manage data, develop and evaluate models of subsurface processes, and to calibrate and interpret the results from a range of models to understand site behavior relative to prescribed standards and in the context of uncertainty in geologic characterization data, forecasting models, and operational scenario uncertainty. The Operational Forecasting of Induced Seismicity (ORION) toolkit is an open-source, observation-based forecasting toolkit that is being co-developed by two U.S. DOE-funded initiatives: the National Risk Assessment Partnership (NRAP) and the Scienceinformed Machine Learning for Accelerating Real Time Decisions in Subsurface Applications (SMART) Initiative. ORION is designed to provide functionality to support decision making about seismic hazard analysis and risk management for GCS stakeholders ranging from the public to site operators to expert seismologists. The tool, which is written as open-source code in the Python programming language, is composed of a desktop graphical user interface (GUI) and an underlying forecasting engine. The forecasting engine uses available reservoir properties, well and fluid injection scenario details, and observed seismic catalog data as inputs to produce a set of temporal and spatio-temporal seismic forecasts.

58 GEOSCIENCES↗
DOE OSTI2024

Machine Learning and Data Science to Advance Laboratory Earthquake Prediction and Illuminate the Mechanics of Precursors to Failure

Earthquakes represent one of our greatest natural hazards and in recent years human induced seismicity is adding to the threat. Even a modest improvement in the ability to forecast devastating large earthquakes or smaller shallow events associated with fluid injection could save thousands of lives and billions of dollars. Current efforts to forecast earthquakes are limited by knowledge of earthquake physics and hampered by a lack of reliable lab or field observations. However, recent work has provided a critical opportunity for advancement. We have found: 1) clear and consistent precursors prior to earthquake-like failure in the laboratory and 2) that lab earthquakes can be predicted using machine learning (ML). These works show that stick-slip failure events –the lab equivalent of earthquakes– are preceded by a cascade of micro-failure events that radiate elastic energy in a manner that foretells catastrophic failure. Remarkably, ML predicts the fault zone stress state, the failure time and in some cases the magnitude of lab earthquakes. In addition, the observations include clear precursors to failure in the form of changes in fault zone properties prior to lab earthquakes. Precursors have been observed in previous laboratory studies but their origin is poorly understood and their possible connection to ML based earthquake prediction is unknown. The work conducted under our project has dramatically expanded these efforts. We have developed an integrated data science approach to illuminate the physics of earthquake precursors and lab earthquake prediction. Our work has accelerated the development of ML, artificial intelligence (AI), and related data science approaches by providing massive data sets that are tightly connected to critical scientific problems and by bringing together leading subject matter experts and data scientists. Earthquake physics involves phenomena that are far from equilibrium. Our work has leveraged data science methods to illuminate these phenomena and investigate how they relate to earthquake prediction. In addition to a large database with many types of labeled events that is available to everyone, our work has advanced the fundamental understanding of seismic forecasting, earthquake physics, and fault rheology

58 GEOSCIENCES↗
DOE OSTI2019

How far can it go?: Determining the reach of induced seismicity

Induced seismicity is a unique societal and intellectual challenge in the solid Earth sciences. Societally, induced seismicity provides an opportunity to harness the advances of earthquake science to directly reduce hazard. Intellectually, induced seismicity provides a partially controlled, field-scale experiment that allows us to investigate otherwise inaccessible processes. The dramatic increase in induced earthquakes in the 21st century requires rising to both aspects of the challenge. A key issue is establishing general trends of induced seismicity. Fluid injection activity has led to several recent moderate magnitude earthquakes and many detailed studies are available (Bao and Eaton, 2016; Ellsworth, 2013; Kim et al., 2018; Weingarten et al., 2015; Yeck et al., 2017). However, a generalized understanding has been difficult to reach in part because of the variety of potential observables and variables. Some efforts at generalizing behavior have focused on magnitudes or seismicity rate (Bachmann et al., 2011; Galis et al., 2017; Gischig and Wiemer, 2013; McGarr, 1976, 2014; Shapiro et al., 2010). Others have examined migratory behavior (Bourouis and Bernard, 2007; Shapiro and Dinske, 2009; Shapiro et al., 2002). We expand on these results and focus on the spatial distribution of induced events, which has rarely been examined quantitatively. We find that the spatial decay of earthquakes from injection wells is a particularly powerful tool for accessing physics and comparing the factors that exert the most significant control on the resulting seismicity (Goebel and Brodsky, 2018).

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

A Workflow for Characterizing Legacy Wells as Potential Leakage Pathways for Integration to NRAP-Open-IAM

Carbon capture and storage is a crucial component of climate change mitigation strategies, involving the capture of carbon dioxide (CO2) from point sources and its injection into permeable subsurface formation. Many suitable CO2 storage sites coincide with legacy wells since the conditions that kept hydrocarbons in-situ for thousands of years are also ideal for storage of carbon dioxide. To protect underground sources of drinking water (USDW) during greenhouse gas injection, the Environmental Protection Agency (EPA) mandates area of review evaluations. These evaluations ensure that drinking water sources would not be contaminated by injected fluids. They include identification of legacy wellbores, integrity assessments, and implementing any necessary corrective action. Previous assessment approaches of legacy wells include high-level scoring of regional data and well construction and abandonment evaluation. This work describes a novel methodology that evaluates well construction and abandonment, ranks them based on complexity, and performs a risk assessment with NRAP-Open-IAM. A workflow of the methodology is presented, highlighting its capabilities and limitations.

Wise, Jarrett↗
DOE OSTI2024

Closing the Loop Between In Situ Stress Complexity and EGS Fracture Complexity (Quarterly Research Performance Progress Report: Q3Y3)

As part of Task 1, we have started by testing our modeling capabilities by reproducing isothermal DFIT simulations presented in the literature. To start, we have been working towards adjusting numerical parameters to reproduce DFIT tests with different fracture geometries. Then, we have focused modeling the DFIT conducted at well 58-32 (cycle 4 in zone 2). Specifically, we have carefully analyzed the influence of the aperture-contact stress relationship and investigated how two different laws affect model results. We have also introduced thermal effects in the model and rerun the simulations to estimate the effect of cooling on the DFIT response. Due to the small amount of fluid injected during a DFIT, thermal effects seem to be moderate.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Subsurface Aggregation of Cationic Friction Reducers: Cause and Prevention

The purpose of this work was to identify the cause of a gelatinous aggregation of friction reducers that was found post-fracturing by RWS operators. RWS sent us samples which we analyzed by scanning electron microscope (SEM). Laboratory experiments were performed to identify the cause of the aggregations and propose a method of preventing them from forming. We concluded that cationic friction reducers were crosslinking with clays, and that this could be prevented by using higher-salinity injection fluid. The results of this study help promote recycling of produced water.

geochemistry↗
DOE OSTI2025

Technical Report on Subsurface Monitoring of the Brady Hot Spring Geothermal Site, Nevada, based upon Full Waveform Inversion

Abilities to accurately characterize the subsurface in a geothermal setting is key to assess and support production. An important element of geothermal reservoir monitoring is also the ability to investigate fluid transport within fracture network. This report focuses on improving subsurface imaging and monitoring in geothermal settings using full waveform inversion based on the adjoint method and time-lapse imaging. To assess our method, we rely on a dense seismic dataset collected in 2016 at the Brady Hot Springs geothermal site in Nevada for the DOE-funded project Poroelastic Tomography by Adjoint Inverse Modeling of Data from Seismology, Geodesy, and Hydrology. This dataset captures subsurface changes across four stages of geothermal power plant operations, which involve varying rates of fluid injection and extraction. Two velocity models were previously derived from this dataset using different methods: one based on travel times and another on sweep interferometry. Our first step is to refine these models using adjoint tomography, which has been applied successfully at global and regional-scales but is less common at the reservoir-scale. Two approaches are then explored for time-lapse analysis: directly comparing refined tomographic models from different stages or backpropagating waveform differences relative to a baseline tomographic model. The main take away is that both approaches highlight similar reservoir behaviors, but the latter approach is more computationally effective in capturing small-scale changes in subsurface properties. For this work, we leverage the use of Salvus (www.mondaic.com), an end-to-end seismic imaging solution, relying on the spectral element method to compute forward and adjoint simulations, and developed by Mondaic Ltd. It includes integrated workflow management that handles waveform and metadata, launches simulations, computes waveform misfits and adjoint sources, and iterates for model updates by nonlinear optimization.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Coupled Investigation of Fracture Permeability Impact on Reservoir Stress and Seismic Slip Behavior (Final Technical Report)

Enhanced Geothermal Systems (EGS) produce clean energy by circulating fluid through hot rock deep underground and bringing that heat to the surface to generate electricity. For this process to work reliably, fluids must be able to move efficiently through networks of natural or engineered fractures in the rock. Enhancing and maintaining subsurface permeability over time is essential for sustainable energy production. However, fluid injection changes the underground temperature, pressure, rock stress, and chemistry, which can alter permeability and sometimes trigger earthquakes. Predicting these interconnected processes remains a key challenge. To address this, we combined high-temperature laboratory experiments with high-fidelity simulations to better understand how fractures in geothermal reservoirs evolve over time. Our experiments measured how fractures respond to stress, slip, slip rate, and chemical reactions under geothermal conditions. These data were integrated into coupled thermal-hydrological-mechanical-chemical and earthquake (THMC+E) models tailored to the Utah FORGE site. The validated modeling framework improves predictions of reservoir performance and seismic response and helps guide operational decisions. This work reduces technical risk and strengthens the scientific foundation needed to make geothermal energy a reliable and scalable clean energy resource.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Scientific Exploration of Induced SeisMicity and Stress (SEISMS)

Several major fault-drilling projects have captured the interseismic and postseismic periods of earthquakes. However, near-field observations of faults immediately before and during an earthquake remain elusive due to the unpredictable nature of seismicity. The Scientific Exploration of Induced SeisMicity and Stress (SEISMS) workshop met in March 2017 to discuss the value of a drilling experiment where a fault is instrumented in advance of an earthquake induced through controlled fluid injection. The workshop participants articulated three key issues that could most effectively be addressed by such an experiment: (1) predictive understanding of the propensity for seismicity in reaction to human forcing, (2) identification of earthquake nucleation processes, and (3) constraints on the factors controlling earthquake size. A systematic review of previous injection experiments exposed important observational gaps in all of these areas. The participants discussed the instrumentation and technological needs as well as faults and tectonic areas that are feasible from both a societal and scientific standpoint.

58 GEOSCIENCES↗
DOE OSTI2015

Code Comparison Study Fosters Confidence in the Numerical Simulation of Enhanced Geothermal Systems

Numerical simulation has become a standard analytical tool for scientists and engineers to evaluate the potential and performance of enhanced geothermal systems. A variety of numerical simulators developed by industry, universities, and national laboratories are currently available and being applied to better understand enhanced geothermal systems at the field scale. To yield credible predictions and be of value to site operators, numerical simulators must be able to accurately represent the complex coupled processes induced by producing geothermal systems, such as fracture aperture changes due to thermal stimulation, fracture shear displacement with fluid injection, rate of thermal depletion of reservoir rocks, and permeability alteration with mineral precipitation or dissolution. A suite of numerical simulators was exercised on a series of test problems that considered coupled thermal, hydraulic, geomechanical, and geochemical (THMC) processes. Problems were selected and designed to isolate selected coupled processes, to be executed on workstation class computers, and have simple but illustrative metrics for result comparisons. This paper summarizes the initial suite of seven benchmark problems, describes the code comparison activities, provides example results for problems and documents the capabilities of currently available numerical simulation codes to represent coupled processes that occur during the production of geothermal resources. Code comparisons described in this paper use the ISO (International Organization for Standardization) standard ISO-13538 for proficiency testing of numerical simulators. This approach was adopted for a recent code comparison study within the radiation transfer-modeling field of atmospheric sciences, which was focused on canopy reflectance models. This standard specifies statistical methods for analyzing laboratory data from proficiency testing schemes to demonstrate that the measurement results do not exhibit evidence of an unacceptable level of bias.

benchmark problems↗
DOE OSTI2021

Recent Thermal and Hydraulic Stimulation Results at Raft River, ID EGS Site

The Raft River geothermal system, located 160 km northwest of Salt Lake City, Utah is the site of a Department of Energy Enhanced Geothermal System (EGS) stimulation demonstration project. The target well RRG-9 ST-1, is roughly 1.6 km (1 mile) south of the power plant. This well has undergone a series of thermal and hydraulic stimulation treatments. Furthermore, the well passes through approximately 1,524 m MD (5,000 ft. MD) of laterally discontinuous Quaternary and Tertiary volcanoclastic and volcanic rocks that unconformably overlie the Precambrian basement. The Elba Quartzite formation located in the Precambrian basement is the target zone for the stimulation program. Fluid injected into the well exits through a fracture zone in the Elba Quartzite at 1,567 m TVD (5,140 ft. TVD). In June 2013 low-rate stimulation began at RRG-9 ST-1 using injection water from the geothermal plant. The average injection rate, temperature, and well head pressure of the low-rate stimulation was 163 Lpm (43 gpm), 34°C, and 1,931kPa (280 psig), respectively. This injection continued through late August of 2013 when wellhead pressures were intentionally increased to approximately 5,516 kPa (800 psig) at approximately 984 Lpm (260 gpm). From September 12 to September 24, 2013 cold well water was injected. The average surface injection temperature was approximately 12°C. On September 25, 2013 injection of the warmer plant water was resumed. This was continued through the rest of 2013 and into 2014. Between April 1, 2014 and April 4, 2014, a higher rate hydraulic stimulation was conducted. Colder water (~10°C) was injected at rates of 20 bpm to 30 bpm (3,178 Lpm to 4,770 Lpm) at wellhead pressures of 5,861 kPa (850 psig) over approximately 24 hours. Microseismic activity was recorded near the Tertiary-Precambrian contact. Subsequently, injection of water from the plant was resumed. As of mid-January, 2015, over 666 million liters (176 million gallons) have been injected into the well. The fate of this water is the subject of ongoing numerical analyses and continuous site monitoring. Various analyses have been implemented to monitor and assess the ongoing stimulation program. Modified Hall plot analysis shows increasing conductivity and/or a decreasing skin factor around the wellbore. Since April, 2014, the injectivity index has increased significantly from 0.28 Lpm/kPa (0.5 gpm/psig) to 0.93 Lpm/kPa (1.7 gpm/psig).

enhanced geothermal system↗
DOE OSTI2018

Experimental Investigation of Time-Dependent Deformation of Fluid Disposal Reservoir Caprocks

For approximately the last two decades low-permeability formations have become a prominent research area because these are the target of unconventional oil shale exploration, and also the primary trapping mechanism for CO2 sequestration and other such subsurface storage. The objective of this research is focused on the sealing ability and induced seismic risk of such tight formations. Disposal of fluid into the subsurface alters the stress state in both the target reservoir and the surrounding formations from their initial in situ state. Therefore, caprocks must be able to deform and accommodate the altered stress and strain state while maintaining the integrity of the seal. The deformation induced in caprock formations often results in a decrease in the normal stress on faults and fractures, which may induce shear slip and therefore create the potential for induced seismicity and leakage. Deformations induced by fluid injection are generally not instantaneous, but typically occur gradually as a pressure front advances through the reservoir and caprock formations. As such, an injection program design can influence both the rate and magnitude of deformation and associated changes in stress. Many common caprock formation types, such as shales and evaporates, are prone to undergo time-dependent deformation such as viscoelastic and/or viscoplastic response. Both the magnitude of the time-dependent deformation and the associated characteristic time scale are important considerations for selecting or operating an injection site. This paper describes tests intended to characterize these effects using caprock samples from a variety of current or potential storage sites. Triaxial and load relaxation test data are presented and used to quantify the time-dependent deformation behavior of rocks with different textures and compositions.

Edelman, Eric↗
DOE OSTI2019

Numerical Simulation of Critical Factors Controlling Heat Extraction from Geothermal Systems Using a Closed-Loop Heat Exchange Method

Closed-loop heat exchange for geothermal energy production involves injecting working fluid down a well that extends through the geothermal resource over a significant length to absorb heat by conduction through the well pipe. The well then needs to return to the surface for energy recovery and fluid re-injection to complete the cycle. We have carried out mixed convective-conductive fluid-flow modeling using a wellbore flow model for TOUGH2 called T2Well to investigate the critical factors that control closed-loop geothermal energy recovery. T2Well solves a mixed explicit-implicit set of momentum equations for flow in the pipe with full coupling to the implicit three-dimensional integral finite difference equations for Darcy flow in the porous medium. T2Well has the option of modeling conductive heat flow from the porous medium to the pipe by means of a semi-analytical solution which makes the computation very efficient because the porous medium does not have to be discretized. When the fully three-dimensional option is chosen, the porous medium is discretized and heat flow to the pipe is by conduction and convection, depending on reservoir permeability and other factors. Simulations of the closed-loop system for a variety of parameter values have been carried out to elucidate the heat recovery process. To the extent that convection may occur to aid in heat delivery to the pipe, the permeability of the geothermal reservoir, whether natural or stimulated, is an important property in heat extraction. The injection temperature and flow rate of the working fluid strongly control the ultimate energy recovery. Pipe diameter also plays a strong role in heat extraction, but is correlated with flow rate. Similarly, the choice of working fluid plays an important role, with water showing better heat extraction than CO2 for certain flow rates, while the CO2 has higher pressure at the production wellhead which can aid in surface energy recovery. In general, we find complex interactions between the critical factors that will require advanced computational approaches to fully optimize.

Oldenburg, Curtis↗
DOE OSTI2024

A novel digital lifecycle for Material‐Process‐Microstructure‐Performance relationships of thermoplastic olefins foams manufactured via supercritical fluid assisted foam injection molding

Abstract This research significantly enhances the applicability of thermoplastic olefins (TPOs) in the automotive industry using supercritical N 2 as a physical foaming agent, effectively addressing the limitations of traditional chemical agents. It merges experimental results with simulations to establish detailed material‐process‐microstructure‐performance (MP2) relationships, targeting 5–20% weight reductions. This innovative approach labeled digital lifecycle (DLC) helps accurately predict tensile, flexural, and impact properties based on the foam microstructure, along with experimentally demonstrating improved paintability. The study combines process simulations with finite element models to develop a comprehensive digital model for accurately predicting mechanical properties. Our findings demonstrate a strong correlation between simulated and experimental data, with about a 5% error across various weight reduction targets, marking significant improvements over existing analytical models. This research highlights the efficacy of physical foaming agents in TPO enhancement and emphasizes the importance of integrating experimental and simulation methods to capture the underlying foaming mechanism to establish material‐process‐microstructure‐performance (MP2) relationships. Highlights Establishes a material‐process‐microstructure‐performance (MP2) for TPO foams Sustainably produces TPO foams using supercritical (ScF) N 2 with 20% lightweighting Shows enhanced paintability for TPO foam improved surface aesthetics Digital lifecycle (DLC) that predicts both foam microstructure and properties DLC maps process effects & microstructure onto FEA mesh for precise prediction

Engineering↗