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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 OSTI2023

Semi-Analytical Leakage Solutions for Aquifers (SALSA) v1

SALSA is a semi-analytical modeling tool that can provide assessments of pressure perturbations and brine leakage because of fluid injection and extraction activities in sedimentary basins. Sedimentary basins typically contain vertical sequences of near-horizontal aquifers separated by less-permeable aquitards. In the context of geologic carbon sequestration (GCS), while aquitards are relied upon to contain injected buoyant free-phase CO2 and limit inter-aquifer brine flow, the large number of leaky wells (e.g., unused/unsuccessful exploration wells, or improperly plugged water or oil/gas wells) that are present in sedimentary basins creates concerns for potential leakage and groundwater contamination. The mathematical theory and solution method included in SALSA is presented in our recent manuscript under review. SALSA is the first to account for the coupled leakage through aquitards and leaky wells, with geologic pressurization sources. SALSA based on semi-analytical solutions can be computationally very efficient for problems containing many injection and leaky wells in multilayered sedimentary systems, compared to any numerical simulation software requiring local mesh refinement around each well to obtain accurate results. Therefore, stakeholders (e.g., regulators, operators) for site screening, injection and post-injection pressure behavior and assessing leakage risks can use SALSA as a fast-predictive tool in GCS applications in multilayered aquifer systems.

Cihan, Abdullah↗
DOE OSTI2025

Continuous surface-to-distributed acoustic sensor snapshots explain reactivation of individual natural fractures during an unconventional reservoir stimulation

ABSTRACT Fiber-optic sensing technologies allow petroleum engineering teams to detect hydraulic fracture interaction with boreholes during unconventional reservoir stimulation. In combination with high-repeatability seismic sources, the same distributed acoustic sensors (DASs) enable vertical seismic profiling (VSP) of the fracture evolution away from the boreholes. We discovered clear signatures of seismic scattering on activated fractures during nine days of continuous seismic monitoring of the fracturing stages at the Austin Chalk/Eagle Ford Field Laboratory. The present study applies a novel approach for quantitative analysis of the scattering events in terms of the evolution of the geometry and elastic stiffness of individual fractures. Our characterization strategy sequentially refines the fracture models: from a stack of 1D soft layers to 3D rectangular inclusions. First, we estimate the number of fracture locations and reflectivity using a modified sparse-spike deconvolution of the stacked VSP traces. The fracture set consists of five fractures spaced by 15–30 m with a reflectivity of approximately 1%. Then, we develop a scattering integral method to refine these estimates along with an inversion of the fracture top and bottom for each monitoring vintage. We find that, initially, some of the fractures are located above the monitoring fiber with the height of approximately 100 m. Then we integrate the seismic interpretation with the low-frequency DAS and pressure and microseismic monitoring to reconstruct the activation process of the fractures. Most likely, some of the natural fractures slowly grew downward to the monitoring fiber as a result of fluid injections in the stimulated well. This led to bright strain anomalies but did not trigger seismicity. The top of the fractures remained almost constant and were limited by a lithologic boundary/stress barrier. To our knowledge, this is the first time VSP data enabled tracking of the fracture evolution with such high spatial and temporal resolution, which was previously only available for crosswell surveys and at a much smaller scale.

Glubokovskikh, Stanislav↗
DOE OSTI2013

DTS Raw Data Guelph, Ontario Canada

Unprocessed active distributed temperature sensing (DTS) data from 3 boreholes in the Guelph, ON Canada region. Data from borehole 1 was collected during a fluid injection while data from boreholes 2 and 3 were collected under natural gradient conditions in a lined borehole. The column labels/headers (in the first row) define the time since start of measurement in seconds and the row labels/headers (in the first column) are the object IDs that are defined in the metadata. Each object ID is a sampling location whose exact location is defined in the metadata file. Data in each cell are temperature in Celsius at time and sampling location as defined above.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Geothermal Reservoir Simulation Results in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy

This dataset contains input data, code, ReadMe files, output data, and figures that summarize the results of a stochastic analysis of geothermal reservoir production from two potential geothermal reservoirs that were evaluated for the Cornell University Deep Direct-Use project. These potential reservoirs are the Trenton-Black River (TBR) from 2.27-2.3 km depth, and basement rocks from 3.0-3.5 km depth and 3.5-4.0 km depth. Several utilization scenarios consisting of different injection fluid temperatures and flow rates were evaluated for each reservoir. Uncertainty in geologic properties, thermal properties, economic costs, and utilization efficiencies were evaluated using a Monte Carlo analysis of the reservoir simulations. Some reservoir simulations of the TBR were completed using the TOUGH2 software, as implemented in PetraSIM. The PetraSIM run files and associated data are provided with this submission. All other reservoir simulations were completed using the GEOPHIRES software, with some modifications to complete the uncertainty analyses. ReadMe files that describe additions to GEOPHIRES, the GEOPHIRES input data, and the output data are all provided, and references are provided to the code repository. Figures that summarize the reservoir heat production, temperature drawdown, and the probability of meeting targeted building heating demands with the produced heat and fluid temperatures are provided.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Thermal-Hydrological-Mechanical Modelling of Stockton University Reservoir Cooling System, Large Scale Grid

Mesh, properties, initial conditions, injection/withdrawal rates for modeling thermal, hydrological, and mechanical effects of fluid injection to and withdrawal from ground for Stockton University reservoir cooling system (aquifer storage cooling system), Galloway, New Jersey, on large scale grid, with some results. First simulation of J.T. Smith, E. Sonnenthal, P. Dobson, P. Nico, and M. Worthington, 2021. Thermal-hydrological-mechanical modeling of Stockton University reservoir cooling system, Proceedings of the 46th Workshop on Geothermal Reservoir Engineering, Stanford University, SGP-TR-218, from which Figures 1-5 pertain.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

EGS Collab Experiment 2: Continuous Active Source Seismic Monitoring (CASSM)

The dataset contains continuous active-source seismic monitoring (CASSM) data collected during EGS Collab Experiment 2, conducted from February to September 2022 at the Sanford Underground Research Facility in Lead, South Dakota. This experiment aimed to investigate enhanced geothermal systems through high-pressure fluid injections at depths of 1200-1500 meters. The seismic monitoring system included 16 three-component piezoelectric accelerometers and 24 hydrophones installed in boreholes around the injection zones, recording signals from piezoelectric seismic sources. Data were acquired using both continuous and triggered recording systems, with sampling rates of up to 100 kHz. The raw data are organized by timestamps and stored in .dat format, with accompanying log files. Calibration certificates for selected accelerometers are provided to aid in correcting sensor responses, though users are advised to consider possible effects of enclosures and installation on sensor performance. Users are strongly advised to consult the accompanying report, which outlines the experimental setup, data acquisition, sensor specifications, and recording systems.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Wastewater Disposal Has Not Significantly Altered the Regional Stress State in Southern Kansas

Wastewater disposal is primarily responsible for the increased seismicity rate since ~2013 in southern Kansas. Previous work that used shear-wave splitting (SWS) in southern Kansas interpreted an ~90° temporal rotation in the fast polarization direction and attributed it to increased pore pressures resulting from fluid injection. However, this interpreted rotation coincided with a change in the stations used to make the SWS measurements. We investigate the temporal variability of fast azimuths in southern Kansas by making SWS measurements on earthquake families with similar source–receiver paths recorded on a stable local seismic network. We select high-quality SWS measurements by investigating the stability of results across 65 different frequency bands between 0.5 and 15 Hz. We find that the fast polarization direction in southern Kansas is relatively constant with an average east-northeast (~N79°E) orientation between 2014 and 2017. Our fast polarization measurements are primarily a reflection of the maximum principal horizontal stress direction (SHmax). We observe a slight spatial change in SHmax to the northeast (~N55°E) near the Nemaha ridge in Oklahoma. However, we do not observe any significant temporal rotation of SHmax or variation in delay time (i.e., crack density) in southern Kansas, contrary to the earlier study. The previously interpreted ~90° rotation may either be a reflection of a very local stress change or a misinterpretation of SWS results potentially due to the use of inconsistent source–receiver paths. Our SWS measurements cover the period of peak wastewater disposal and seismicity rates and suggest an absence of significant temporal rotations in the local anisotropy and stress orientations associated with wastewater disposal.

Geochemistry & Geophysics↗
DOE OSTI2012

Locating Microearthquakes In The Salton Sea Geothermal Field, California

We report the results of a 6-month microearthquake study of the Salton Sea Geothermal Field, California. This active geothermal field is also seismically active due to the flow of fluids through pre-existing fractures of rocks in the subsurface which can cause faults to slip. Locating these seismic events within the geothermal field enables researchers to determine whether the earthquakes are anthropogenic or tectonic from the nearby Brawley Seismic Zone. We analyzed November 2009 to April 2010 seismic waveform data retrieved from a network of continuously recording seismometers covering an area of 10 km 2 . 2,271 microearthquake hypocenters were processed out of 2,609 total recorded events and their locations suggest the majority could be at approximately the same depth as the fluid injection wells.

58 GEOSCIENCES↗
DOE OSTI2011

Mapping Diffuse Seismicity for Geothermal Reservoir Management with Matched Field Processing: Year 2 Report

Detecting and locating seismic events in managed underground geothermal reservoirs can become increasingly difficult during certain reservoir management operations. For example, during fluid injection procedures, large numbers of microearthquakes frequently occur during a relatively short amount of time. On seismic records, these events can overlap or have poor signal-to-noise ratios (SNR). This can obscure the onset of smaller signals and complicate the picking of seismic phases needed for earthquake location algorithms. To accurately illuminate the active areas of the underground reservoir through time however, a complete earthquake catalog down to very small magnitudes is necessary. To aid in the seismic characterization of reservoir fracture networks, we propose to complement traditional earthquake detection and location techniques with the empirical matched field processing (MFP) method. The principle of the empirical MFP method is to calculate propagation from source to receivers for pre-existing events, also called master templates. Then MFP matches the spatial structure of incoming seismicity observed by a network of sensors to master templates keyed to potential event locations. We demonstrate that empirical MFP can complement existing catalogs and techniques by using archived seismic information to increase earthquake catalog completeness. We identify and construct representative master templates using the Southern California Earthquake Data Center (SCEDC) earthquake catalog and archived waveform data of events originating within the Salton Sea Geothermal Field (SSGF). We identify 231 master events that have good quality seismic records at four or more seismic stations. We apply the empirical MFP method to continuous seismic data collected at the SSGF between November 2009 and December 2010. The MFP method successfully identified 5357 local events, while the original catalog only reported 1536 events. This increase in the number of events allows us to better determine the active fractures of the geothermal reservoir. We model the Coulomb stress change due to events between M2 – M3.5 that occurred during the January 2010 seismic swarm. Our results show a good correlation between regions of increased Coulomb stress change due to double-couple shear events on faults and the locations of subsequent microseismicity. In addition, we investigate the lower event detection magnitude threshold of our surface network using the MFP method. It clearly shows the event detection threshold is extended to include many smaller earthquakes with magnitudes down to M0.0. Therefore, we believe that the empirical MFP method, when combined with conventional methods, significantly improves network detection capabilities.

15 GEOTHERMAL ENERGY↗
DOE OSTI2013

High Fidelity Computational Analysis of CO2 Trapping at Pore Scales (Final Technical Report)

With an alarming rise in carbon dioxide (CO2) emission from anthropogenic sources, CO2 sequestration has become an attractive choice to mitigate the emission. Some popular storage media for CO 2 are oil reservoirs, deep coal-bed, and deep oceanic-beds. These have been used for the long term CO 2 storage. Due to special lowering viscosity and surface tension property of CO 2 , it has been widely used for enhanced oil recovery. The sites for CO 2 sequestration or enhanced oil recovery mostly consist of porous rocks. Lack of knowledge of molecular mobility under confinement and molecule-surface interactions between CO2 and natural porous media results in generally governed by unpredictable absorption kinetics and total absorption capacity for injected fluids, and therefore, constitutes barriers to the deployment of this technology. Therefore, it is important to understand the flow dynamics of CO 2 through the porous microstructures at the finest scale (pore-scale) to accurately predict the storage potential and long-term dynamics of the sequestered CO 2 . This report discusses about pore-network flow modeling approach using variational method and analyzes simulated results this method simulations at pore-scales for idealized network and using Berea Sandstone CT scanned images. Variational method provides a promising way to study the kinetic behavior and storage potential at the pore scale in the presence of other phases. The current study validates variational solutions for single and two-phase Newtonian and single phase non-Newtonian flow through angular pores for special geometries whose analytical and/or empirical solutions are known. The hydraulic conductance for single phase flow through a triangular duct was also validated against empirical results derived from lubricant theory.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

A microseismic workflow for managing induced seismicity risk as CO 2 storage projects

It is well established that fluid injection has the potential to induce earthquakes—from microseismicity to large, damaging events—by altering state-of-stress conditions in the subsurface. While induced seismicity has not been a major operational issue for carbon storage projects to date, a seismicity hazard exists and must be carefully addressed. Two essential components of effective seismic risk management are (1) sensitive microseismic monitoring and (2) robust data interpretation tools. This report describes a novel workflow, based on advanced processing algorithms applied to microseismic data, to help improve management of seismic risk. This workflow has three main goals: (1) to improve the resolution and reliability of passive seismic monitoring, (2) to extract additional, valuable information from continuous waveform data that is often ignored in standard processing, and (3) to minimize the turn-around time between data collection, interpretation, and decision-making. These three objectives can allow for a better-informed and rapid response to changing subsurface conditions.

58 GEOSCIENCES↗
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↗