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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Precise relative magnitude measurement improves fracture characterization during hydraulic fracturing

SUMMARY Microseismic monitoring is an important technique to obtain detailed knowledge of in-situ fracture size and orientation during stimulation to maximize fluid flow throughout the rock volume and optimize production. Furthermore, considering that the frequency of earthquake magnitudes empirically follows a power law (i.e. Gutenberg–Richter), the accuracy of microseismic event magnitude distributions is potentially crucial for seismic risk management. In this study, we analyse microseismicity observed during four hydraulic fracture treatments of the legacy Cotton Valley experiment in 1997 at the Carthage gas field of East Texas, where fractures were activated at the base of the sand-shale Upper Cotton Valley formation. We perform waveform cross-correlation to detect similar event clusters, measure relative amplitude from aligned waveform pairs with a principal component analysis, then measure precise relative magnitudes. The new magnitudes significantly reduce the deviations between magnitude differences and relative amplitudes of event pairs. This subsequently reduces the magnitude differences between clusters located at different depths. Reduction in magnitude differences between clusters suggests that some attenuation-related biases could be effectively mitigated with relative magnitude measurements. The maximum likelihood method is applied to understand the magnitude frequency distributions and quantify the seismogenic index of the clusters. Statistical analyses with new magnitudes suggest that fractures that are more favourably oriented for shear failure have lower b-value and higher seismogenic index, suggesting higher potential for relatively larger earthquakes, rather than fractures subparallel to maximum horizontal principal stress orientation.

58 GEOSCIENCES↗
NASA NTRS1991

Interlaminar fracture characterization: A current review

Interlaminar fracture characterization has been investigated for several years. Only now is it well enough understood for standardization organizations to attempt to write standard test methods. A review of the current philosophies in characterizing interlaminar fracture is presented. First, the mode 1, double cantilever beam test (DCB) for measuring G(sub 1c) and the end notched flexure (ENF) test for measuring G(sub 2c) are discussed. These tests have undergone the most extensive research throughout the years and are furthest towards standardization. In addition, the mode 2, end loaded split (ELS) specimen is discussed. Mixed mode fracture is also discussed and the recently developed mixed mode bending (MMB) test is detailed. Then, tests for evaluating mode 3 fracture toughness, including the split cantilever beam (SCB), are reviewed. Finally, the work done on interlaminar fracture characterization in fatigue is reviewed.

Martin, Roderick H.↗
DOE OSTI2021

Hydraulic fracture characterization by integrating multidisciplinary data from the Hydraulic Fracturing Test Site 2 (HFTS-2)

Various technologies have traditionally been used to monitor and describe hydraulic fractures from different perspectives. This work demonstrates the value of data integration for hydraulic fracture characterization when multiple data resources are available. The Hydraulic Fracturing Test Site 2 (HFTS 2) is a hydraulic fracturing research project in the Delaware Basin with multiple surveillance techniques including fiber optics sensing, microseismic, pressure/temperature gauges, etc. We integrated the multidisciplinary data from the HFTS-2 to characterize hydraulic fractures. The integrated data revealed interesting fracture propagation features including layering, vertical propagation affected by pore pressure gradient, and different microseismic activities due to difference in-situ conditions. Furthermore, these findings can be insightful for understanding hydraulic fracture propagation. The comparison among multiple surveillance data also helps us to evaluate the roles of various surveillance technologies and provides us experience to make informative decisions depending on different monitoring objectives.

58 GEOSCIENCES↗
DOE OSTI2024

Heart Shape to Fracture Distance: Characterizing Hydraulic Fracture Propagation before Hits

Estimating the distance from the hydraulic fracture tip to the monitor well can be useful for fracture characterization, well spacing optimization, and preventing parent-child well interference. A heart-shaped signal is referred to as the extensional precursor of a fracture hit recorded by crosswell strain measurements and can serve as a vital tool for such estimation. This study incorporates the 3D displacement discontinuity method (DDM) to understand the impact of fracture geometry and monitor well offset on the heart-shaped signal’s characteristics. Results from numerical simulation and analytical solutions reveal a strong linear correlation between the spatial extent of the heart-shaped signal and the fracture tip distance. This relationship was further developed to predict tip distance using field data from the Hydraulic Fracture Test Site 2 (HFTS2). A reasonable approximation result from field data further validates the methodology. In addition, it is worth noting that the estimation accuracy depends on the ratio between fracture dimension and tip distance. The findings of this study offer a novel approach for real-time monitoring and characterizing hydraulic fracture propagation, which can be further used for well spacing optimization in unconventional and enhanced geothermal system reservoir development, as well as caprock integrity monitoring for carbon sequestration projects.

58 GEOSCIENCES↗
DOE OSTI2024

Fracture Characterization Via AI‐Assisted Analysis of Temperature Logs

Abstract Fractures control fluid flow, mass transport, and heat transfer in a geothermal reservoir. This makes accurate characterization of fracture networks a prerequisite for optimal design and control of a reservoir's exploitation. We develop a deep‐learning procedure to identify fracture locations via interpretation of temporally and spatially continuous downhole temperature measurements. A long short‐term memory fully convolutional network (LSTM‐FCN) is used both to capture long‐term dependencies in sequential temperature data and to distill local features around fractures. A wellbore and fractured‐reservoir thermal model is established to generate temperature data for network training. The trained LSTM‐FCN exhibits a unique ability to detect multiple fractures intersecting a borehole. We use the LSTM‐FCN algorithm to evaluate the effectiveness of different‐stage wellbore temperature measurements on fracture detection in a complex fractured system. Our experiments reveal that the use of various‐stage temperature information as an input feature set improves the robustness of fracture detection to noise interference. This study indicates the practical feasibility of obtaining accurate fracture‐network reconstructions from temperature signals, at reasonable computational cost.

Yang, Xiaoyu↗
DOE OSTI2026

Detecting and Characterizing Fracture Zones Using a Convolutional Neural Network

This project directly supports the Geothermal Technologies Office (GTO) objectives outlined in the Multi-Year Program Plan (MYPP) by advancing two key research areas: “Exploration and Characterization” and “Data, Modeling, and Analysis.” This project has successfully demonstrated a pre-drilling ability to image and characterize the distribution and connectivity of subsurface faults and fractures, key parameters for identifying permeable pathways that enable geothermal fluids to circulate and produce energy. Specifically, we developed and implemented innovative machine learning methodologies to enhance geothermal exploration. Large-scale faults were detected using a Convolutional Neural Network (CNN), while small-scale fractures were characterized using a novel Double-Beam Neural Network (DBNN). These tools have proven both technically effective and cost-efficient by reducing reliance on expensive exploratory drilling. Through collaboration with our geothermal industry partner, this research has significantly advanced techniques for identifying hidden geothermal systems and extending the productive lifespan of existing geothermal fields. We applied our methods to two geothermal fields—Soda Lake (Nevada) and Lightning Dock (New Mexico)—to identify shallow steam-charged fracture zones and characterize deep faults at depths of 1.5-2 km. The steam zone identified at the Soda Lake geothermal field showed excellent agreement with prior drilling data, validating the effectiveness of our approaches. In addition, the analysis revealed three new prospective drilling targets for further development and verification. The outcomes of this project improve our scientific understanding of geothermal reservoir behavior, enhance exploration efficiency, extend the economic life of existing geothermal plants. Ultimately, these advancements contribute to GTO’s goal of achieving more sustainable, affordable, and data-driven geothermal energy development across the United States.

15 GEOTHERMAL ENERGY↗
NASA NTRS1992

Determination of cleavage planes and fracture characterization of Ni-based single crystal superalloys

The room temperature fracture behavior of the Ge Rene N-4, CMSX-2, and CMSX-4C single crystal Ni-based superalloys was studied. All crystals were grown along the (001) direction and tensile tested in both helium and hydrogen atmospheres. A stereoscopic technique developed for use with a scanning electron microscope was applied to determine cleavage planes. Planar gamma(') morphologies also were examined to help determine cleavage planes. Helium charged specimens failed on a number of planes including the (111), (110), and (320). In most cases planes of the (111)-type initiated at the notch region and became smaller and smaller as they moved in radially. Tensile strengths in helium averaged 1000 MPa higher than that of the hydrogen charged specimens. Specimens tested in hydrogen generally failed on (100)-type planes originating from the notch region. This (100) region comprised 60 to 80 percent of the total fracture surface on most samples and appeared as large flat planes perpendicular to the growth direction of the crystal. The interior regions contained (100)-type planes as well as (321), (320), (210), and (111)-types. Hydrogen charged specimens also showed a high percentage of large cracks oriented at 90 deg to one another, indicative of the (100)-type fracture. The Ge Rene N4 and the CMSX-4C samples contained 3-5 percent gamma/gamma(') eutectic, while the CMSX-2 samples had little or no gamma/gamma(') eutectic. The relationship between gamma/gamma(') eutectic and the fracture surface has not been fully determined, but it is thought that the gamma/gamma(') eutectic may serve as a possible trapping site for hydrogen.

Merrill, John M.↗
DOE OSTI2022

Integrated simulation, machine learning, and experimental approach to characterizing fracture instability in indentation pillar-splitting of materials

Measuring fracture toughness of materials at small scales remains challenging due to limited experimental testing configurations. A recently developed indentation pillar-splitting method has shown promise of improved flexibility in fracture toughness measurements at the microscale, partly due to the occurrence of an unusual fracture instability, i.e., a transition from stable to unstable crack propagation. In spite of growing interest in this method, the underlying mechanism of this phenomenon is yet to be elucidated. Furthermore, we provide a comprehensive description of fracture instability in indentation pillar-splitting by combining in situ experiments with high-fidelity simulations based on cohesive zone and J-integral methods. In addition, a machine-learning-based solution for predicting the critical indentation load of fracture instability is established through Gaussian processes regression for broad use of this method by the community.

36 MATERIALS SCIENCE↗
NASA NTRS1997

Remote Sensing Applications for Antrim Shale Fracture Characterization, Michigan Basin

Advanced Research International (ARI) sent seven staff members to the 1997 International Coalbed Methane Symposium, held in Tuscaloosa, Alabama from May 12-17. ARI gave a short course on risk reduction strategies, including remote fracture detection, for coalbed methane exploration and development that was attended by about 25 coalbed methane industry professionals; and presented a paper entitled 'Optimizing coalbed methane cavity completion operations with the application of a new discrete element model.' We met with many potential clients and discussed our fracture detection services. China has vast coalbed methane resources, but is still highly dependent on coal-and wood-burning. This workshop, sponsored by the United Nations, was intended to help China develop its less-polluting energy reserves. ARI is successfully finding new applications for its fracture detection services. Coalbed methane exploration became an important market in this quarter, with the inception of a joint industry/government collaboration between ARI, Texaco and DOE to use remote fracture detection to identify areas with good potential for coalbed methane production in the Ferron Coal Trend of central Utah. Geothermal energy exploration is another emerging market for ARI, where fracture detection is applied to identify pathways for groundwater recharge, movement, and the locations of potential geothermal reservoirs. Ari continued work on two industry/government collaborations to demonstrate fracture detection to potential clients. Also completed the technical content layout for multimedia CD-ROM that describes our remote fracture detection services.

Kuuskraa, Vello↗
DOE OSTI2025

Elasto-viscoplastic fast Fourier transform modeling framework for assessing microstructural effects on stress intensity factors characterizing fracture toughness

A large-strain elasto-viscoplastic fast Fourier transform (LS-EVPFFT) model with non-periodic (NP) velocity-based boundary conditions is adapted to simulate the sensitivity of stress intensity factors on microstructure for 304L stainless steel. The material was characterized via electron backscattered diffraction (EBSD) serial-sectioning to obtain a measured 3-D microstructural cell to perform simulations. The NP-LS-EVPFFT model, including the simulation setup and boundary conditions, was verified using a crystal plasticity finite element (CPFE) model. To this end, the generation of meshes of notched specimens was developed, which involved creating Python scripts for mesh “cutting” in Abaqus, and Sculpt scripts in Cubit for meshing of the measured microstructural cell processed with DREAM.3D. The complexity of the mesh preparation highlighted the advantages of the FFT-based model, which circumvents the mesh generation process. Given the efficiency of the FFT-based model, statistical distribution of stress intensity factors in function of crystal orientation at the crack tip, grain structure, and crystallographic texture surrounding the crack tip were predicted. Further, the distributions reveal about 10% variation of stress intensity factors with microstructure with the most significant sensitivity found to be the crystal orientation at the crack tip. The methodology developed in this work is discussed as a practical simulation tool for predicting the sensitivity of stress intensity factors on microstructural variability in metallic materials.

36 MATERIALS SCIENCE↗
NASA NTRS2017

Characterizing Fractures Across the Astronaut Corps: Preliminary Findings from Population-Level Analysis

Despite evidence of bone loss during spaceflight and operational countermeasures to mitigate this loss, the subsequent risk of fracture among astronauts is not known. The physiologic process of diminished bone density and bone recovery during or following spaceflight is multifactorial. Such factors as age, sex, fracture history, and others may combine to increase fracture risk among astronauts. As part of the 2016 Bone Research and Clinical Advisory Panel (RCAP), the authors analyzed data collected on 338 NASA astronauts to describe the demographics, bone-relevant characteristics, and fracture history of the astronaut population. The majority of the population are male (n=286, 84.6%), have flown at least one mission (n=306, 90.5%), and were between the ages of 30 and 49 at first mission (n=296, 96.7% of those with at least one mission). Of the 338 astronauts, 241 (71.3%) experienced a fracture over the course of their lifetime. One hundred and five (43.5%) of these 241 astronauts only experienced a fracture prior to being selected into the Astronaut Corps, whereas 53 (22.0%) only experienced a fracture after selection as an astronaut. An additional 80 astronauts (33.2%) had both pre- and post-selection fractures. The remaining 3 astronauts had a fracture of unknown date, which could not be categorized as pre- or post-selection. Among the 133 astronauts with at least one post-selection fracture, males comprised 90.2% (n=120) compared to 84.5% of the entire Corps, and females accounted for 9.8% (n=13) compared to 15.4% of the Corps. Ninety-seven of the 133 astronauts with post-selection fractures (72.9%) had one fracture event, 22 (16.5%) had two fractures, and 14 (10.5%) had three or more fractures. Some astronauts with multiple fractures suffered these in a single event, such as an automobile accident. The 133 astronauts with a post-selection fracture accounted for a total of 188 fracture events. One hundred and four (78.2%) of astronauts with post-selection fractures experienced those fractures following their first mission (mean 12.7 +/- 11.1 years following first mission; range 14.0 days - 50.6 years). Additional analyses are ongoing and include examination of fracture history, skeletal site, mechanism, and type of fracture, age at time of fracture, time from spaceflight to fracture, as well as multivariable analysis comparing fracture events to non-events. The results of such analyses may reveal trends in risk factors for fracture among the astronaut corps that have yet to be systematically described through a corps-wide approach.

Rossi, Meredith M.↗
NASA NTRS2017

Characterizing Fractures Across the Astronaut Corps: Preliminary Findings from Population-Level Analysis

Despite evidence of bone loss during spaceflight and the implementation of countermeasures to mitigate this loss, the subsequent risk of fracture among astronauts is not known. Multiple factors such as age, sex, fracture history, and others may combine to increase fracture risk. The purpose of this study was to describe fractures among the astronaut population and generate questions for future occupational surveillance studies.

Rossi, Meredith M.↗
DOE OSTI2024

Characterizing Hydraulic Fracture Propagation Before Fracture Hits

Estimating the distance from hydraulic fracture tip to monitor well can be very useful for fracture characterization, well spacing optimization, and preventing parent-child well interference. Heart-shape signal is referred to as the extensional precursor of fracture hit recorded by cross-well strain measurements and can be served as a vital tool to make such estimation. This study incorporates the 3D Displacement Discontinuity Method to understand the impact of fracture geometry and monitor well offset on the heart-shape signal’s characteristics. Results from numerical simulation and analytical solutions reveal a strong linear correlation between the spatial extent of heart shape signal and fracture tip distance. This relationship was further developed to predict tip distance using field data from the Hydraulic Fracture Test Site 2. A reasonable approximation result from field data further validates the methodology. In addition, it is worth noting that the estimation accuracy depends on the ratio between fracture dimension and tip distance. The findings of this study offer a novel approach for real-time monitoring and characterizing hydraulic fracture propagation, which can be further used for well spacing optimization in unconventional and Enhanced Geothermal System reservoir development, as well as cap rock integrity monitoring for carbon sequestration projects.

Jin, Ge↗
DOE OSTI2021

Scale–Bridging in Three–Dimensional Fracture Networks: Characterizing the Effects of Variable Fracture Apertures on Network–Scale Flow Channelization

Here, we incorporate observations of real fracture aperture variability observed in laboratory experiments into an ensemble of three-dimensional discrete fracture network (DFN) simulations to characterize how variations of this micro-scale feature can influence flow and transport behavior at the network scale. A shear fracture is created within a Marcellus shale sample, and the fracture aperture is measured using a triaxial direct-shear device coupled with real-time X-ray imaging at in-situ stress conditions. We construct an ensemble of fracture networks based on natural fractures in Marcellus shale and project regions of the experimental aperture field onto each fracture in the networks. Our calculations demonstrate that the degree of flow channelization, a network-scale flow field structure, is dramatically increased by local changes in the aperture field that in turn affects flow and transport properties.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗