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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Transforming microseismic clouds into near real-time visualization of the growing hydraulic fracture

SUMMARY Microseismic observations during unconventional reservoir stimulation are typically seen as a proxy for clusters of hydraulic fractures and the extent of the stimulated reservoir. Such straightforward interpretation is often misleading and fails to provide a physically reasonable image of the fracturing process. This paper demonstrates the application of a physics-based machine learning algorithm which enables a rapid and accurate fracture mapping from the microseismic data. Our training and validation data set relies on a history-matched geomechanical modelling workflow implemented in GEOS software for the Hydraulic Fracturing Test Site 1 (HFTS-1) project. For this study we augmented the simulated fracture growth through geostatistical modelling of induced seismicity, so that the synthetic microseismic catalogue matches the main statistical properties of the field observations. We formulated the problem of mapping the actual fracture in the clutter of events to parallel common video segmentation workflows: several past video frames (microseismic density snapshots) are passed through a deep convolutional network to classify whether a given voxel is associated with a fracture or intact rock. We found that for accurate fracture mapping, the network’s input and architecture must be augmented to incorporate the fluid injection parameters (pressure, rate, concentration of proppant, and location of the perforation within the cluster). The error rate for the network reached as little as 10 per cent of the fracture area, while a conventional microseismic interpretation approach yielded ∼300 per cent. Our approach also yields must faster predictions than conventional methods (minutes instead of weeks), and could enable engineers to make rapid decisions regarding engineering parameters (pumping rate, viscosity) in real time during stimulation.

58 GEOSCIENCES↗
DOE OSTI2023

Constraint energy minimizing generalized multiscale finite element method for multi-continuum Richards equations

In fluid flow simulation, the multi-continuum model is a useful strategy. When the heterogeneity and contrast of coefficients are high, the system becomes multiscale, and some kinds of reduced order methods are demanded. Combining these techniques with nonlinearity, we will consider in this paper a dual-continuum model which is generalized as a multi-continuum model for a coupled system of nonlinear Richards equations as unsaturated flows, in complex heterogeneous fractured porous media; and we will solve it by a novel multiscale approach utilizing the constraint energy minimizing generalized multiscale finite element method (CEM-GMsFEM). In particular, such a nonlinear system will be discretized in time and then linearized by Picard iteration (whose global convergence is proved theoretically). Subsequently, we tackle the resulting linearized equations by the CEM-GMsFEM and obtain proper offline multiscale basis functions to span the multiscale space (which contains the pressure solution). More specifically, we first introduce two new sources of samples, and the GMsFEM is used over each coarse block to build local auxiliary multiscale basis functions via solving local spectral problems, that are crucial for detecting high-contrast channels. Second, per oversampled coarse region, local multiscale basis functions are created through the CEM as constrainedly minimizing an energy functional. Various numerical tests for our approach reveal that the error converges with the coarse-grid size and that only few oversampling layers as well as basis functions are needed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Efficient Multi-Scale, Thermo-Hydro-Mechanical Numerical Model for Simulation of Long-Term Stability of Rooms for Nuclear Waste Disposal

This project demonstrated the feasibility of developing a numerical modeling tool that provides an efficient and unique approach to analyze the geomechanical performance of a deep geological repository (DGR) for high-level nuclear waste. The numerical modeling tool is physics-based and models the thermo-hydro-mechanical (THM) processes during the required time (up to one million years) for a DGR. The unique capability of the developed code is explicit representation of fracturing and a discrete fracture network (DFN) in the model that includes the entire repository layout for simulated time of one million years. Therefore, it can potentially address one of the challenges of analysis of a DGR, which is efficient numerical simulation of a multi-scale, physics-based models.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Utah FORGE 5-2615: Thermo-poromechanical Response of Fractured Rock - Workshop Presentation

This is a presentation on the Experimental Determination and Modeling-Informed Analysis of Thermo-poromechanical Response of Fractured Rock for Application to Utah FORGE project by the University of Oklahoma, presented by Dr. Ahmad Ghassemi, McCasland Chair Prof. The project objective is to improve understanding and control of coupled thermo-poromechanical (or thermo-hydro-mechanical- TPM) processes in reservoir development, and to study any role in interpretations of the fracture closure. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 8, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Predicting Flow in Fracture Networks With Quantum Algorithms

Uncertainty quantification plays a crucial role in the modeling of subsurface flow. For instance, uncertainties in the properties of geologic fracture networks significantly impact flow, requiring numerous simulations to accurately estimate quantities of interest. However, each simulation is computationally expensive because it requires solving a large linear system to capture features that involve both small and large fractures. An example is in percolation, where the interaction of many small fractures (which cumulatively can have a large surface area) with the rock matrix must be modeled precisely. Quantum computing is an emerging tool with the potential to address this issue. Quantum algorithms offer a significant speedup in solving linear systems, achieving efficiencies that are challenging to match with classical approaches. These classical approaches include direct solvers, such as LU decomposition, and iterative methods, notably preconditioned conjugate gradient, commonly used in subsurface modeling to solve large sparse systems. However, applying quantum algorithms to geologic fracture flow requires careful attention to algorithmic and problem-specific constraints to fully realize this quantum advantage. In this work we describe a quantum algorithm for generalized Monte Carlo applications with a quadratic speedup over the classical approaches which can be combined with the quantum speedup, currently under investigation, for solving quantum linear systems for subsurface flow. We show that for quantum algorithms the computational cost of estimating a quantity of interest for a statistical ensemble of networks is roughly the same as that of a single realization, essentially implying that one can get uncertainty quantification for free.

58 GEOSCIENCES↗
DOE OSTI2022

Assessment of Lost Circulation Material Particle-Size Distribution on Fracture Sealing: A Numerical Study

Summary Lost circulation materials (LCMs) are essential to combat fluid loss while drilling and may put the whole operation at risk if a proper LCM design is not used. The focus of this research is understanding the function of LCMs in sealing fractures to reduce fluid loss. One important consideration in the success of fracture sealing is the particle-size distribution (PSD) of LCMs. Various studies have suggested different guidelines for obtaining the best size distribution of LCMs for effective fracture sealing based on limited laboratory experiments or field observations. Hence, there is a need for sophisticated numerical methods to improve the LCM design by providing some predictive capabilities. In this study, computational fluid dynamics (CFD) and discrete element methods (DEM) numerical simulations are coupled to investigate the influence of PSD of granular LCMs on fracture sealing. Dimensionless variables were introduced to compare cases with different PSDs. We validated the CFD-DEM model in reproducing specific laboratory observations of fracture-sealing experiments within the model boundary parameters. Our simulations suggested that a bimodally distributed blend would be the most effective design in comparison to other PSDs tested here.

Engineering↗
DOE OSTI2020

Towards real-time forecasting of natural gas production by harnessing graph theory for stochastic discrete fracture networks

In this work, we compare hydrocarbon production curves obtained from a graph-based reduced-order model with the high-fidelity Discrete Fracture Network (DFN) predictions for a fracture network created using data from a real shale site. We observe that the bounds for the high fidelity DFN model lie within the bounds for the reduced order model, implying that the reduced-order model provides a conservative estimate. Moreover, we found that except for first-passage times and late arriving mass, the production curves from the reduced-order model predict transport accurately. However, it is to be noted that the results are inspite of trading a three-dimensional geometry for a reduced system in the form of a graph, one that is 500–1000 times faster in terms of computational efficiency (for this particular application). In addition, we also compare the production curves for large drawdown and small drawdown using our graph approach. The reduced-order model is successful in showing that the long term productivity is higher in case of small drawdown although the initial productivity is higher for large drawdown. Thus, this reduced-order model offers great potential in uncertainty quantification for production, as well as in providing operators with information to make real-time decisions for optimal production.

03 NATURAL GAS↗
DOE OSTI2022

Method to account for natural fracture induced elastic anisotropy in geomechanical characterization of shale gas reservoirs

Shale has been usually recognized as a transverse isotropic (TI) medium in conventional geomechanical log interpretation due to its laminated nature. However, when natural fractures exist in the shale rock, additional elastic anisotropy is introduced, converting laminated Shale to an orthorhombic (OB) medium. Previous studies illustrate that neglecting the natural fracture induced anisotropy in shale geomechanical log interpretation could lead to inaccurate evaluations of elastic moduli and in-situ stresses. In this paper, a new method is developed to account for the natural fracture induced anisotropy in geomechanical log interpretation based upon the TI acoustic model developed by the author and a characterization technique of elastic wave anisotropy (Sayers, 1991). The new OB model incorporates the four acoustic log data inputs and five modeling constraints in a nonlinear optimization algorithm to solve for the nine independent stiffness coefficients of an OB rock, and further to solve for the geomechanical properties and in-situ stress profiles in an OB formation. The new method was validated with a Marcellus Gas Shale field case. Both the new OB model and the conventional TI model were applied to interpret the minimum horizontal stress profile for the same formation. By comparing the results, the OB model is more robust than the TI from two aspects. First, the average stress magnitude predicted by the OB model is closer to the one measured by the Diagnostic Fracture Injection Test (DFIT). Second, the OB model predicts a more obvious stress barrier between the lower Marcellus and upper Onondaga Limestone than the TI model does. Finally, the predicted stress barrier is consistent with the observation of the microseismic events of a horizontal well drilled and completed nearby, which reveals that no hydraulic fracture propagates downward through the bottom boundary of Marcellus Shale into the underlying Onondaga Limestone.

03 NATURAL GAS↗
DOE OSTI2023

Demonstration of new fracture criteria based on micro-structure and compare to empirical model and measurements

The US nuclear industry is currently exploring extending the peak rod average burnup limits above the current regulatory limit of 62 GWd/tU. A potential concern for fuel exceeding the burnup limit is the fragmentation during a temperature transient such as a loss-of-coolant accident (LOCA). In the event of cladding failure, the fragmented fuel could relocate and disperse within the reactor. The potential impact of fuel fragmentation, relocation and dispersal (FFRD) on licensing assumptions for burnup extension has focused a great amount of efforts and research on this topic.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Simulating current flow through a well casing and an induced fracture

A system includes a receiver component that receives a model of a well system, the model comprising a representation of an electrically energized well casing and/or a fracture as a transmission line that leaks electric current as the current traverses the well casing and/or fracture. The receiver component also receives a value that indicates an amount of the current that is applied to the well casing and a location of a source of the current on the well casing. The system further includes an electromagnetic field calculator component that calculates an estimated electromagnetic field at at least one location on the surface of the earth based at least in part upon the representation of the electrically energized well casing and/or fracture, the value that indicates the amount of current that is applied to the well casing, and the location of the source of the current on the well casing.

02 PETROLEUM↗
DOE OSTI2022

High-fidelity micromechanical modeling of the effects of defects on damage and creep behavior in single tow ceramic matrix composite

Despite the superior properties of ceramic matrix composites (CMCs), their fabrication process generates inevitable defects with high density that significantly influence material integrity and residual useful life. Recent efforts have focused on CMC property prediction and investigation of their different inelastic mechanisms, but very limited work exists on understanding the influence of defects on inelastic responses of CMCs. Here, we introduce a three-dimensional micromechanics computational framework that includes experimentally informed material microstructure and architectural variabilities to investigate CMC response in the presence of manufacturing-induced defects. A developed microstructure generation algorithm is used to generate the representative volume elements in the micromechanics models from complex material morphology information obtained from extensive characterization studies of C/SiNC and SiC/SiNC CMCs. A fracture mechanics-informed matrix damage model is reformulated, in which the model considers the growth of porosity and microcracks in the as-received material. A progressive fiber damage model as well as Orthotropic viscoplasticity creep formulation are also utilized for the study. This methodology is implemented within the micromechanics framework to investigate the complex temperature- and time-dependent load transfer and damage mechanisms of CMCs under operation loading conditions. The developed framework explores the influence of as-received defects on the damage and creep behavior in service conditions. It also provides new insights into the effect of size, shape, distribution, and location of these defects on material response. The framework is then calibrated with unidirectional CMC minicomposite results available in the literature.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Predicting fracture behavior in single crystal nickel using a coupled crystal plasticity phase field damage approach

Understanding the fracture behavior of single crystal metals is critical for predicting material performance under mechanical loading. Here, in this study, we investigate the fracture characteristics of single crystal nickel tensile bars using a crystal plasticity coupled phase field damage (CP-PFD) model. Experimental tensile tests were conducted on 15 specimens spanning five crystallographic orientations and three thickness variants per orientation. The results revealed two distinct fracture modes: brittle fractures with 45-degree angled surfaces and ductile fractures characterized by significant necking. The CP-PFD model successfully replicated these fracture behaviors, demonstrating strong agreement with experimental observations. The model effectively predicted the strain at which necking and fracture occurred, as well as the orientation-dependent fracture mechanisms. By comparing experimental and simulated fracture surfaces, we establish the CP-PFD model as a robust tool for predicting single crystal behavior and damage evolution. This work provides insight into the microstructural dependence of fracture behavior and establishes a predictive framework for modeling orientation-dependent damage evolution in single-crystal nickel.

Crystal plasticity↗
DOE OSTI2020

Wellbore injectivity response to step-rate CO 2 injection: Coupled thermo-poro-elastic analysis in a vertically heterogeneous formation

Safe and permanent carbon geological storages require an elaborate analysis of geomechanical stability. Subsurface injection of CO 2 changes the local temperature and pore pressure and, further, alters the stress due to thermo-poro-elastic responses. A permanent CO 2 storage testing was conducted in the water leg of Cranfield reservoir in Mississippi, USA, where hosted CO 2 enhanced-oil recovery activities. During CO 2 injection, the injection rate was ramped up twice but the bottom-hole pressure did not increase with the imposed injection rates as expected. This unexpected field observation suggests the possibility of an open-mode fracture development at the injector. However, the injector response and potential fracture development have not been rigorously interpreted with detailed near-wellbore temperature and pore pressure change upon the CO 2 injection. In this study, we performed history matching of CO 2 injection using coupled thermo-poro-elastic reservoir simulation to examine the possibility of fracturing. We built a reservoir model including vertical heterogeneity in both petrophysical and geomechanical properties estimated from well-logging analysis and laboratory experiments. The simulation results show that CO 2 injection changes stresses and support the hypothesis of development of an open-mode fracture at the injector during the Cranfield test. The near-injector region exhibits a large temperature reduction up to 55 °C with ensuing effective horizontal stress reduction up to 9.1 MPa. However, a caprock integrity issue is unlikely because of the horizontal stress contrast within layers and low hydraulic communication with the injection zone. This work indicates that the injectant temperature should be considered in the design of high-rate CO 2 injector.

58 GEOSCIENCES↗
DOE OSTI2023

Simulation of Chilled-water Injection at EGS Collab Testbed 2 using the GEOS simulation framework

This work seeks to model the chilled-water injection that occurred at EGS Collab Testbed 2 as part of experiment 3, using the open-source GEOS simulation framework. Modeling of this process, previously conducted using STOMP-GT, confirmed that thermal breakthrough was expected to occur during the chill water injection and may have been masked by strong Joule-Thompsons effects induced by large pressure drops between the fractures and the production wells. Building a GEOS numerical model of this process will allow to include additional physics. In fact, GEOS can model fully coupled thermo-poromechanical processes in fractured porous media and can be employed to model the process of artificially enhancing rock permeability by hydraulically fracturing the rocks. For example, the GEOS model could help understanding the dynamic nature of the EGS collab experiment 3 flow system. Since the limited time and resources do not allow for an extensive study, the focus is on building a baseline model of this process. As such, the main outcomes of this modelling efforts are listed below.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Earth Sciences Applications for Energy and Global Security: A Few Vignettes [Slides]

Understanding the physics of flow and transport in the subsurface environment is crucial to several National Security applications. In the Energy Security realm, some examples include characterizing radioactive waste disposal, exploring natural gas extraction and sequestering CO2. An example in the Global Security arena is to be able to distinguish between anthropogenic and naturally occurring seismic disturbances, the former being of particular concern as underground nuclear testing activity has seen an increase in recent years. A common theme across these applications is the ability to accurately model fluid flow in porous and/or fractured subsurface media. For decades, researchers have grappled with how to include the effects of uncertainties in these models, including but not limited to heterogeneity, unknown initial and boundary conditions and issues with scalability. More recently advances in computing and machine learning methodologies have allowed a broader exploration of the uncertainty space as we strive for real time decision making. I will present an overview of the field and discuss a few examples of how my own research in these topics has evolved over nearly two decades.

58 GEOSCIENCES↗