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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↗
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↗
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↗
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↗
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↗
DOE OSTI2021

Thermal Experiments for Fractured Rock Characterization: Theoretical Analysis and Inverse Modeling

Abstract Field‐scale properties of fractured rocks play a crucial role in many subsurface applications, yet methodologies for identification of the statistical parameters of a discrete fracture network (DFN) are scarce. We present an inversion technique to infer two such parameters, fracture density and fractal dimension, from cross‐borehole thermal experiments data. It is based on a particle‐based heat‐transfer model, whose evaluation is accelerated with a deep neural network (DNN) surrogate that is integrated into a grid search. The DNN is trained on a small number of the heat‐transfer model runs and predicts the cumulative density function of the thermal field. The latter is used to compute fine posterior distributions of the (to be estimated) parameters. Our synthetic experiments reveal that fracture density is well constrained by data, while fractal dimension is harder to determine. Adding nonuniform prior information related to the DFN connectivity improves the inference of this parameter.

Zhou, Zitong↗
DOE OSTI2022

Use of Mini-CT Specimens for Fracture Toughness Characterization of Irradiated Highly Embrittled Weld

In the 1990’s, the Heavy Section Steel Irradiation Program at the ORNL performed investigation of the shape of the fracture toughness master curve for reactor pressure vessel steel highly embrittled because of irradiation exposure. A radiation-sensitive reactor pressure vessel (RPV) weld with intentionally enhanced copper content, designated KS-01, has been characterized in terms of static initiation (KJc) and Charpy impact toughness in the unirradiated and irradiated conditions. The objective of this original project was to investigate the ability of highly embrittled material to maintain the shape of the unirradiated transition fracture toughness curve, as well as to examine the ability of the Charpy 41-J shift to predict the fracture toughness shift at such high level of embrittlement. Irradiation of this weld was performed at the University of Michigan Ford Reactor in the new HSSI irradiation-anneal-reirradiation (IAR) facility. Broken specimens from that project have been saved in ORNL storage. To verify applicability of Mini-CT specimens for fracture toughness characterization of RPV materials as part of the DOE Light Water Reactor Sustainability Program, Mini-CT specimens were machined from broken Charpy specimens and tested according to ASTM E1921 standard. As result of this study, the fracture toughness of this weld derived by testing Mini-CT specimens in the unirradiated and irradiated conditions is compared to previously reported fracture toughness derived by large number of conventional specimens.

Sokolov, Mikhail A.↗
DOE OSTI2023

Multiscale spatial analysis of fracture nodes in two dimensions

Spatial arrangement of fractures as a function of scale is an important component of fracture quantification for inferential and predictive modeling. Available methods that analyze fracture spatial arrangement are based on one-dimensional spacing data; therefore, they are limited to semi-parallel fractures. Such methods cannot be applied to fracture networks in higher dimensions, particularly when fractures have different orientations. Here to characterize fracture arrangements in two dimensions, we propose using Ripley’s K-function, as a method of point pattern analysis, to quantify spatial arrangement of fracture nodes. Fracture nodes, such as barycenters, intersection points, and tips, are point-based representations of fracture locations and connectivity within the fracture network. We introduce formulations for isotropic as well as directional analyses of spatial arrangement. In addition, we derive formulations for edge correction in circular and rectangular study domains. Finally, we demonstrate applications of Ripley’s K-function on two natural fracture datasets. Our proposed method supports quantification and characterization of fracture spatial arrangements that allow practitioners to build representative models of fractures in the subsurface.

02 PETROLEUM↗
DOE OSTI2022

Post-Irradiation Fracture Toughness Characterization of Generation II FeCrAl Alloys

FeCrAl alloys are promising candidate materials for the accident tolerant fuel (ATF) cladding application due to their exceptional resistance to oxidation in elevated temperature steam environments. Currently, limited fracture toughness data are available for the FeCrAl alloys, including the FeCrAl alloys newly developed at Oak Ridge National Laboratory (ORNL) under the U.S. Department of Energy’s Advanced Fuels Campaign (AFC) program. In this study, two Generation II candidate FeCrAl alloys, i.e., C06M (81.8Fe-10Cr-6Al-0.03Y-2Mo-0.2Si) and C36M (78.8Fe-13Cr-6Al-0.03Y-2Mo-0.2Si), were irradiated in the High Flux Isotope Reactor (HFIR) at ORNL to assess the fracture characteristics of these alloys after neutron irradiation. A total of six rabbit capsules were irradiated in HFIR at target temperatures of 200°C, 330°C, and 500°C up to target damage doses of 8 displacements per atom (dpa) and 16 dpa. Post-irradiation fracture toughness testing was performed following the Master Curve method in the ASTM E1921 standard. The main findings of this study are:1) Both the C06M and C36M alloys exhibited a similar response to irradiation concerning irradiation hardening and embrittlement.2) The irradiation temperature played different roles in terms of irradiation hardening and embrittlement for both C06M and C36M: after irradiation between 166°C and 204°C, both materials exhibited significant irradiation hardening and embrittlement; after irradiation between 315°C and 343°C, both materials showed small irradiation hardening without irradiation embrittlement. After irradiation between 501°C and 507°C, however, the irradiation softening without irradiation embrittlement was observed in both materials.3) Comparing the microhardness and Master Curve reference temperature T0q before and after neutron irradiation, we did not observe a linear correlation between the two parameters for both C06M and C36M steels. This should be mainly due to a flat response of the Master Curve reference temperature T0q to the irradiations at 166–204°C and 315–343°C ranges4) C06M showed a lower T0q, meaning better toughness, than C36M at the unirradiated condition, and such trend was kept even after neutron irradiation except for the 166–204°C irradiation after which both materials had similar T0q.5) In terms of hardening and embrittlement, the irradiation effect on both C06M and C36M appeared to saturate after an irradiation dose of 7 dpa.

Chen, Xiang↗
DOE OSTI2021

Fracture Toughness Characterization of Generation II FeCrAl Alloys after ~18 dpa Irradiation

FeCrAl alloys are promising candidate materials for the accident tolerant fuel (ATF) cladding applications due to their excellent corrosion resistance to the elevated temperature steam environment. Currently, the handbook on FeCrAl material properties contains only limited data regarding the fracture toughness properties of any FeCrAl alloy. This includes alloys currently under investigation within the Advanced Fuels Campaign (AFC) at Oak Ridge National Laboratory (ORNL). In this project, a series of irradiation capsules have been irradiated in the High Flux Isotope Reactor (HFIR) at ORNL with two Generation II FeCrAl candidate alloys, i.e., C06M and C36M, to assess the fracture response of these alloys after neutron irradiation. These alloys represent the “book-end” compositions for C26M, the alloy currently being developed as the leading candidate for LWR cladding. A total of six irradiation capsules were irradiated in HFIR at target temperatures of 200°C, 330°C, and 500°C up to target damage doses of 8 displacements per atom (dpa) and 16 dpa. These damage doses represent the expected middle and end of life damage levels for typical LWR cladding while the irradiation temperature regimes will provide insight into the role of varying microstructural features on the fracture toughness properties of neutron irradiated FeCrAl alloys. To date, irradiation of all capsules has been completed in HFIR. This report summarizes the latest results of microhardness and fracture toughness PIE for the 16 dpa capsules (FCAB2, FCAB4, and FCAB6), for which the measured irradiation conditions were: 204°C/17.6dpa, 343°C/18.3dpa, and 507°C/18.6dpa. The main conclusions of this study can be summarized as follows: 1) After the 204°C/17.6dpa irradiation, both C06M and C36M exhibited significant irradiation hardening and embrittlement 2) After the 343°C/18.3dpa irradiation, both C06M and C36M exhibited small irradiation hardening without irradiation embrittlement 3) After the 507°C/18.6dpa irradiation, both C06M and C36M exhibited irradiation softening without irradiation embrittlement 4) Comparing the microhardness and Master Curve reference temperature T 0q before and after neutron irradiation, we did not observe a linear correlation between the two parameters for both C06M and C36M. This should be mainly due to a flat response of the Master Curve reference temperature T 0q to the irradiations at 166-204°C and 315-343°C ranges 5) C06M showed a lower T 0q , meaning better toughness, than C36M at the unirradiated condition and such trend was kept even after neutron irradiation except for the 166-204°C irradiation where both materials had similar T 0q . 6) In terms of hardening and embrittlement, the irradiation effect on both C06M and C36M appeared to saturate after an irradiation dose of 7 dpa.

36 MATERIALS SCIENCE↗