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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Development of planar P-type point contact germanium detectors for low-mass dark matter searches

The detection of low-energy deposition in the range of sub-eV through ionization using germanium (Ge) with a bandgap of ~ 0.7 eV requires internal amplification of the charge signal. This can be achieved through high electric field that accelerates charge carriers, which can then generate more charge carriers. The minimum electric field required to generate internal charge amplification is derived for different temperatures. We report the development of a planar point contact Ge detector in terms of its fabrication and the measurements of its leakage current and capacitance as a function of applied bias voltage. With the determination of the measured depletion voltage, the field distribution is calculated using GeFiCa, which predicts that the required electric field for internal charge amplification can be achieved in proximity to the point contact. The energy response to an Am-241 source is characterized and discussed. We conclude that such a detector with internal charge amplification can be used to search for low-mass dark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Characterizing Shielded Special Nuclear Material by Neutron Capture Gamma-Ray Multiplicity Counting

We present a new neutron multiplicity counting analysis and measurement method for neutron-shielded fissile material using neutron-capture gamma rays. Neutrons absorbed in shielding produce characteristic gamma rays that preserve the otherwise lost neutron multiplicity signature. Neutron multiplicity counting provides estimates of fission parameters, such as neutron leakage multiplication, spontaneous fissioner (e.g. Pu-240) mass, and (α,n) ratio. Standard neutron multiplicity counting can incorporate the new neutron-capture gamma-ray multiplicity counting technique to characterize previously degenerate or intractable source configurations by maximizing the multiplicity signature. The new method decouples neutron source-detector interferences, such as reflection and thermalization time in the detector, that could improve measurements of the mean neutron lifetime. We also develop a detector prototype for the multiplicity counting of neutron-capture gamma rays and present detector design considerations, such as detection material and shielding, to optimize the detection of the 2.2 MeV hydrogen capture gamma ray. We simulate the prototype neutron- capture gamma-ray multiplicity counter against the BeRP ball in polyethylene shells to inform future measurements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Machine Protection Studies of Fast Instability-Driven Beam Losses in the EIC Electron Storage Ring

Fast transverse beam instabilities represent one of the most challenging protection scenarios for the Electron-Ion Collider (EIC) electron storage ring (ESR). Coherent betatron oscillations driven by collective effects can grow rapidly and lead to substantial beam losses within only a few tens of turns, posing a threat to collimators, superconducting (SC) magnets, cryogenic systems, and detector components. A dedicated simulation framework based on distributed transverse excitations was developed to evaluate instability-driven beam losses in the ESR. A conservative instability rise time on the order of 10 turns was used to define a bounding protection scenario. Simulations show that the original two-collimator configuration is insufficient to localize losses under all operating conditions, whereas an optimized four-collimator configuration reduces loss leakage into protected regions by more than two orders of magnitude. Nevertheless, the most severe instability scenarios produce catastrophic beam impacts, with nearly half of the stored beam being intercepted by the collimators within a single turn, exceeding the preliminary estimated survivability limits of the baseline collimator design. The results demonstrate that collimation alone is insufficient to guarantee safe ESR operation and must be complemented by a fast machine-protection system. Dedicated turn-by-turn beam-position monitors and fast beam-loss monitors provide sufficient advance warning to detect instability growth and initiate a beam abort before equipment-damaging loss levels are reached. These findings establish quantitative requirements for the ESR machine-protection architecture and support the implementation of a multilayer protection strategy for both accelerator and detector systems.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Thermal Stability of Schottky Contacts and Rearrangement of Defects in β ‐Ga 2 O 3 Crystals

Abstract The thermal stability of different Schottky contacts (Au, Pt, and Ni) on (100) β ‐Ga 2 O 3 single crystals grown by the Czochralski method is investigated. Besides the examination of the Schottky barrier parameters, contact‐dependent defect levels are investigated by deep‐level transient spectroscopy (DLTS) in a 100–650 K (ramp‐up) and 650–100 K (ramp‐down) temperature cycle. Several defect levels are detected below the conduction band minimum at 0.41, 0.60, 0.77, 0.96, and 1.17 eV. In the temperature ramp‐down DLTS, the 1.17 eV level disappears, and the 0.60 eV level appears for all Schottky contacts. DFT calculations suggest that rearrangement and dissociation of a single hydrogen from a doubly‐hydrogenated Ga─O divacancy complex occurs during the temperature sweep under bias. The trap level at 0.96 eV only appears after the thermal load for the Ni contact, in contrast to Au and Pt, where it is present without a thermal budget. Temperature‐dependent leakage current (at −4 V) measurements indicate oxidation of Ni, and further thermodynamic analysis suggests alloying of Au‐Ga atoms at the Au/ β ‐Ga 2 O 3 interface. These studies provide insight into the behavior induced by these common Schottky contacts and the alteration associated with temperature cycling.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Unveiling the influence of selective-area-regrowth interfaces on local electronic properties of GaN p-n junctions for efficient power devices

Here, we report correlated nanoscale mapping of the structure, composition, and properties of regrown GaN p-n junctions to identify how etching and non-planar regrowth processes limit diode performance via the introduction of unintentional dopants and defect states. p-GaN was selectively regrown in n-GaN trenches with SiO 2 masks of variable mask-to-trench-width ratio. Dilute Al layers were periodically introduced during regrowth as markers of the growth interface. Correlated nanoscale mapping of doping, conductivity, and dopant complexes was achieved with atom probe tomography (APT), scanning spreading resistance microscopy (SSRM), and cathodoluminescence (CL) spectroscopy, respectively. The Al marker layers, detected by APT, enabled reconstruction of the faceted growth interface and correlation of the dopant concentration with position and time. The p-GaN growth rate is proportional to the mask-to-trench width ratio while the dopant incorporation rate is invariant. At trench edges, magnesium incorporation is suppressed, and oxygen incorporation enhanced, due to preferential incorporation on the semi-polar growth surface, leading to compensation and less abrupt p-n junctions; the SiO 2 mask is a source of oxygen. Residual etch damage below the regrowth interface induces n-type and p-type conductivity, creating leakage pathways. The non-uniform Mg incorporation is driven by crystal anisotropy and is thus inherent to non-planar regrowth, but can be mitigated by engineering the regrowth interface and process parameters. The unprecedented integration of spatially resolved mapping of dopants, impurities, conductivity, and carrier type is a powerful approach to discriminating distinct factors that limit the performance of regrown diodes, enabling the rational optimization of process and device design.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Time-Resolved Neutron Imaging for Hydrogen Uptake in Subsurface Lithologies

Geologic hydrogen production and underground storage are increasingly important for meeting rising energy demands while providing clean-combustion advantages. However, hydrogen’s high diffusivity and propensity for leakage through porous media necessitate direct evaluation of its transport behavior in subsurface materials. Whereas X-ray microcomputed tomography (μCT) studies often employ contrast agents or surrogate gases, this study leverages neutron transmission radiography/CT to observe hydrogen migration in situ. This work represents the first demonstration of real-time neutron radiography of hydrogen migration in reservoir and caprock lithologies. Cylindrical cores of Indiana limestone, Amherst Gray sandstone, and Tumey shale were subjected to constant-pressure hydrogen charging and scanned in real time using high-resolution neutron radiography. Results indicate immediate hydrogen infiltration in sandstone and limestone, with homogeneous distribution detected throughout their pore structure. In contrast, hydrogen remained largely absent from fine-grained shale under the same pressure, except in an apparently localized fracture zone, where neutron signatures confirmed the presence of hydrogen. Subsequent neutron CT of the sandstone sample, using image subtraction against an uncharged reference, corroborated hydrogen distribution patterns. Even under lowpressure, single-phase conditions, distinct neutron imaging signatures of hydrogen were achieved. These preliminary findings underscore the potential of neutron imaging for advancing subsurface hydrogen migration research.

08 HYDROGEN↗
DOE OSTI2024

Machine Learning‐Assisted Microearthquake Location Workflow for Monitoring the Newberry Enhanced Geothermal System

Abstract Enhanced geothermal systems (EGS) offer a sustainable energy source but face challenges in accurately locating microearthquakes induced during reservoir stimulation. Locating these microearthquakes provides reliable feedback on the stimulation progress. Current deep learning methods for locating earthquakes require extensive data sets for training, which is problematic as detected microearthquakes are often limited. To address the scarcity of training data, we propose a practical workflow using probabilistic multilayer perceptron (PMLP) which predicts microearthquake locations from cross‐correlation time lags in waveforms. Utilizing a 3D velocity model of Newberry site derived from ambient noise interferometry, we generate numerous synthetic microearthquakes and 3D acoustic waveforms for PMLP training. Accurate synthetic tests prompt us to apply the trained network to the 2012 and 2014 stimulation field waveforms. To enhance the accuracy of source localization, we carefully handpick the P‐arrival times. Predictions on the 2012 stimulation data set show major microseismic activity at depths of 0.5–1.2 km, correlating with a known casing leakage scenario. In the 2014 data set, the majority of predictions concentrate at 2.0–2.9 km depths, consistent with results obtained from conventional physics‐based inversion, and align with the presence of natural fractures from 2.0 to 2.7 km. We validate our findings by comparing the synthetic and field picks, demonstrating a satisfactory match for the first arrivals. By combining the benefits of quick inference speeds and accurate location predictions, we demonstrate the feasibility of using realistic synthetic data set to locate microseismicity for EGS monitoring.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Artificial Intelligence Thermostat to Detect Faults

Residential air conditioners and heat pumps often experience faults due to inadequate maintenance, which can severely reduce efficiency or even cause system failure. Common issues include dirty or clogged air filters and refrigerant leaks. These problems degrade performance and increase energy use and operating costs. This study presents a smart thermostat with embedded artificial intelligence to detect such faults and alert homeowners when maintenance is needed. The thermostat uses low-cost measurements—including return-air temperature, relative humidity, supply-air temperature, outdoor-air temperature, and condenser subcooling—to identify abnormal operations. Because different faults produce distinct response patterns, tailored algorithms are developed to recognize characteristic fault signatures. The investigation is built on a detailed co-simulation platform that couples EnergyPlus with the DOE/ORNL Heat Pump Design Model (HPDM). EnergyPlus represents the building’s dynamic environment, while HPDM is a high-fidelity, hardware-based model that can simulate fault-free performance as well as a wide range of faults, including gradual degradation such as minor refrigerant leakage. This platform provides a virtual training and testing environment that helps distinguish fault-induced behavior from normal operation and supports development of robust diagnostic algorithms. Using this framework, a Dynamic Bayesian Network was developed to identify two common faults—gradual refrigerant charge loss and indoor airflow blockage—and the AI-embedded thermostat was verified through annual building simulations.

Shen, Bo [ORNL] (ORCID:0000000336600393)↗
DOE OSTI2021

Defect characterization and charge transport measurements in high-resolution Ni/n-4H-SiC Schottky barrier radiation detectors fabricated on 250 μ m epitaxial layers

Advances in the growth processes of 4H-SiC epitaxial layers have led to the continued expansion of epilayer thickness, allowing for the detection of more penetrative radioactive particles. In this work, we report the fabrication and characterization of high-resolution Schottky barrier radiation detectors on 250 μm thick n-type 4H-SiC epitaxial layers, the highest reported thickness to date. Several 8 × 8 mm 2 detectors were fabricated from a diced 100 mm diameter 4H-SiC epitaxial wafer grown on a conductive 4H-SiC substrate with a mean micropipe density of 0.11 cm -2 From the Mott–Schottky plots, the effective doping concentration was found to be in the range (0.95–1.85) × 10 14 cm -3 , implying that full depletion could be achieved at ~5.7 kV (0.5 MV/cm at the interface). The current-voltage characteristics demonstrated consistently low leakage current densities of 1–3 nA/cm 2 at a reverse bias of -800 V. This resulted in the pulse-height spectra generated using a 241Am alpha source (5486 keV) manifesting an energy resolution of less than 0.5% full width at half maximum (FWHM) for all the detectors at -200 V. The charge collection efficiencies (CCEs) were measured to be 98–99% with no discernable correlation to the energy resolution. A drift-diffusion model fit to the variation of CCE as a function of bias voltage, revealed a minority carrier diffusion length of ~10 μm. Deep level transient spectroscopy measurements on the best resolution detector revealed that the excellent performance was the result of having ultralow concentrations of the order of 1011 cm-3 lifetime limiting defects—Z 1/2 and EH 6/7 .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Fracture Network Quantification during CO2 Injection

This is the presentation prepared for the ARMA 2025 (59th US Rock Mechanics/Geomechanics Symposium) Conference held in Santa Fe, New Mexico, June 8-11, 2025. Accurate mapping and quantification of these networks are essential to ensure the integrity of CO2 storage reservoirs, understand and reduce potential leakage, and maintain long-term environmental safety. This study presents a novel machine learning-driven approach, integrated with geomechanical analysis, to quantify fracture networks and assess their spatial distribution during CO2 injection. This paper combines microseismic monitoring data with principles of hydraulic diffusivity and geomechanical analysis to characterize reservoir scale fracture network. The novelty of our approach lies in its capacity to assimilate time-dependent pressure data and microseismicity into a cohesive framework, which not only identifies microseismic triggering fronts but also tracks fracture distribution during active injection. Besides, leveraging image log data and analysis our approach also provides another angle of the insights to solidate the fracture networks understanding and geomechanical impacts. Key results from our study include the detection of over 100 distinct fracture clusters across the injection site, with fracture orientations strongly correlated with the prevailing in-situ stress field.

CO2 storage and sequestration↗
DOE OSTI2025

Fracture Network Quantification during CO2 Injection

This is the conference paper accompanying an oral presentation at the ARMA 2025 (59th US Rock Mechanics/Geomechanics Symposium) Conference held in Santa Fe, New Mexico, June 8-11, 2025. Accurate mapping and quantification of these networks are essential to ensure the integrity of CO2 storage reservoirs, understand and reduce potential leakage, and maintain long-term environmental safety. This study presents a novel machine learning-driven approach, integrated with geomechanical analysis, to quantify fracture networks and assess their spatial distribution during CO2 injection. This paper combines microseismic monitoring data with principles of hydraulic diffusivity and geomechanical analysis to characterize reservoir scale fracture network. The novelty of our approach lies in its capacity to assimilate time-dependent pressure data and microseismicity into a cohesive framework, which not only identifies microseismic triggering fronts but also tracks fracture distribution during active injection. Besides, leveraging image log data and analysis our approach also provides another angle of the insights to solidate the fracture networks understanding and geomechanical impacts. Key results from our study include the detection of over 100 distinct fracture clusters across the injection site, with fracture orientations strongly correlated with the prevailing in-situ stress field.

CO2 storage and sequestration↗
DOE OSTI2020

Planck 2018 results: III. High frequency instrument data processing and frequency maps

This paper presents the High Frequency Instrument (HFI) data processing procedures for the Planck 2018 release. Major improvements in mapmaking have been achieved since the previous Planck 2015 release, many of which were used and described already in an intermediate paper dedicated to the Planck polarized data at low multipoles. These improvements enabled the first significant measurement of the reionization optical depth parameter using Planck-HFI data. This paper presents an extensive analysis of systematic effects, including the use of end-to-end simulations to facilitate their removal and characterize the residuals. The polarized data, which presented a number of known problems in the 2015 Planck release, are very significantly improved, especially the leakage from intensity to polarization. Calibration, based on the cosmic microwave background (CMB) dipole, is now extremely accurate and in the frequency range 100-353 GHz reduces intensity-to-polarization leakage caused by calibration mismatch. The Solar dipole direction has been determined in the three lowest HFI frequency channels to within one arc minute, and its amplitude has an absolute uncertainty smaller than 0.35 μK, an accuracy of order 10 -4 . This is a major legacy from the Planck HFI for future CMB experiments. The removal of bandpass leakage has been improved for the main high-frequency foregrounds by extracting the bandpass-mismatch coefficients for each detector as part of the mapmaking process; these values in turn improve the intensity maps. This is a major change in the philosophy of "frequency maps", which are now computed from single detector data, all adjusted to the same average bandpass response for the main foregrounds. End-to-end simulations have been shown to reproduce very well the relative gain calibration of detectors, as well as drifts within a frequency induced by the residuals of the main systematic effect (analogue-to-digital convertor non-linearity residuals). Using these simulations, we have been able to measure and correct the small frequency calibration bias induced by this systematic effect at the 10 -4 level. There is no detectable sign of a residual calibration bias between the first and second acoustic peaks in the CMB channels, at the 10 -3 level.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A Universal Refrigerant Charge Fault Detection and Diagnostics Method Based on Pump Down Operation

The performance of the heat pump system varies greatly depending on the refrigerant charge amount. Improving the refrigerant charge fault detection and diagnostics (FDD) method of vapor compression systems have the potential for increasing energy efficiency and reducing service cost. Previous studies to predict refrigerant charge amount are mostly empirical methods which require significant amount of experimental data for high accuracy. The primary goal of this research is to develop a universal charge fault detection method which requires only a few experimental data with high prediction accuracy.Currently, pump down operations are typical practices by HVAC technicians when they need to open the refrigerant circuit to make a repairment. In addition, compressors have a built-in low-pressure cut-off protection function, and the compressor performance maps are commonly available from manufacturers. The proposed method innovatively utilizes the typical pump down operation, the compressor low-pressure cut-off protection, and the compressor performance map. It does not require any geometry information of heat exchangers, refrigerant lines, or charge buffers.The new charge prediction method is firstly formulated through theoretical analysis, then verified and calibrated by a quasi-steady-state simulation of the pump down process for a residential heat pump system. The quasi steady-state simulation uses an HVAC system simulation framework driven by DOE/ORNL Heat Pump Design Model (HPDM). Preliminary experiment validations with heat pump refrigerant leakage tests demonstrate the deviation of the proposed charge prediction method compared with measurement is within 8%. This technology makes refrigerant charge amount available at the technician’s fingertips and leads to shorter maintenance time and fewer site visits.

Li, Zhenning↗
DOE OSTI2022

Sustainable Aviation Fuel via Hydroprocessing of Catalytic Fast Pyrolysis Oil

Cycloalkanes have been identified as a promising alternative for sustainable aviation fuel (SAF) in a recent US Department of Energy Review of Technical Pathways to SAF. Cycloalkanes can provide desirable SAF properties, including energy density, and, in addition, they may be able to provide necessary seal swelling and leakage protection and replace undesirable aromatics in aviation fuel. Catalytic fast pyrolysis (CFP) followed by hydroprocessing constitutes a platform well suited for converting biomass to cycloalkanes. CFP oils are rich in phenolic compounds and, depending on CFP catalyst, in aromatic hydrocarbons, which can both be hydrogenated to form cycloalkanes. In this work, we report results from hydroprocessing of two types of CFP oil to produce fractions boiling in the sustainable aviation fuel range and meeting tested aviation fuel specifications. CFP oils prepared over a zeolite catalyst (ZSM-5) and a hydrodeoxygenation catalyst (Pt/TiO2) were hydroprocessed over a sulfided NiMo/Al2O3 catalyst in a two-stage process (1st stage ~250 degrees C and 2nd stage 385 degrees C) in a continuous trickle-bed hydrotreater. The hydrotreated product contained 39-40% material boiling in the SAF range by distillation with a carbon efficiency of 36-37% from CFP oil to SAF fraction. The SAF fractions consisted of 82-87% of cycloalkanes, had non-detectable oxygen contents and lower heating values (LHV) above the jet fuel minimum limit of 42.8 MJ/kg. The SAF-range product also had acceptable volatility and freeze and flash points per aviation fuel specifications. The results suggest a promising pathway for SAF production via the catalytic fast pyrolysis pathway. Methods to enhance the yield of SAF will be discussed.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗
DOE OSTI2025

Collective neutrino oscillations in three flavors on qubit and qutrit processors

Collective neutrino flavor oscillations are of primary importance in understanding the dynamic evolution of core-collapse supernovae and subsequent terrestrial detection, but also among the most challenging aspects of numerical simulations. This situation is complicated by the quantum many-body nature of the problem due to neutrino-neutrino interactions, which demands a quantum treatment. An additional complication is the presence of three flavors, which often is approximated by the electron flavor and a heavy lepton flavor. In this work, we provide both qubit and qutrit encodings for all three flavors, and develop optimized quantum circuits for the time evolution and analyze the Trotter error. We conclude our study with a hardware experiment of a system of two neutrinos with superconducting hardware: the IBM Torino device for qubits and Advanced Quantum Testbed device at the Lawrence Berkeley National Laboratory for qutrits. We find that error mitigation greatly helps in obtaining a signal consistent with simulations. Finally, while hardware results are comparable at this stage, we expect the qutrit setup to be more convenient for large-scale simulations since it does not suffer from probability leakage into nonphysical qubit space, unlike the qubit setup.

Neutrino oscillations↗
DOE OSTI2025

An approach for spent nuclear fuel containment integrity verification using gas tagging

Verification of containment integrity is required for spent nuclear fuel (SNF) managed by the commercial nuclear industry and U.S. Department of Energy (DOE), especially after extended storage. Certain SNF storage systems, such as the DOE road-ready dry storage system, hold several packaged containments within a welded over-canister. These packaged containments are called Department of Energy Standard Canisters (DOESCs). DOESC leakage identification is challenging because their containment boundary cannot be accessed for testing and their contents (i.e., SNF and fill gas) are often similar. There are concerns that this could result in costly characterization and repackaging operations of DOE road-ready dry storage systems if compromised DOESCs are suspected. Here, to address these concerns, this paper presents an approach for applying a gas tagging process using xenon to uniquely identify compromised inaccessible containments following extended storage. The containments considered for this application are seven DOESCs, each packaged within a single over-canister. Two different SNF loading configurations from the Advanced Test Reactor and Fort Saint Vrain nuclear power plant are considered. These configurations are used to represent research reactor aluminum-clad spent nuclear fuel (ASNF) and TRi-structural ISOtropic (TRISO) SNF types. Results for this application show that for ASNF and TRISO type fuels for which the selected fuels are representative, the volume of taggant required at loading is determined primarily by the lower detection limit and leak rate of taggant from a compromised DOESC, rather than the amount of fission-generated xenon in the loaded fuel. While the application presented is suited for larger leaks, smaller leaks could be detected by modifying certain design parameters. This gas tagging approach can also be applied to other DOE containments and advanced reactor SNF storage systems.

07 - ISOTOPES AND RADIATION SOURCES↗
DOE OSTI2024

Investigating Material Properties of Subsurface Rock Formations Modified by Engineering Mineral Precipitation (Final Scientific and Technical Report)

Montana State University’s (MSU) Energy Research Institute (ERI), in collaboration with the Center for Biofilm Engineering (CBE) and the Department of Civil Engineering (CE), has conducted a long‐term research program aimed at developing a novel cementing agent to address wellbore integrity and reduce the unwanted upward migration of fluids and greenhouse gases from the subsurface. The primary technology developed through this research program is known as ureolysis‐induced calcite precipitation (UICP), which harnesses bio‐chemical processes to precipitate calcium carbonate (CaCO 3 ). The same general process can also be called microbially-induced calcium carbonate precipitation (MICP) when microbes provide the process-catalyzing urease enzyme. Both terms are used in this report. Results have conclusively demonstrated that, if properly controlled, UICP can successfully seal fractures, high permeability zones, and compromised cement in the vicinity of wellbores and in nearby caprock. This technology has been successfully deployed to mitigate annular leakage in two test wells and over sixty commercial wells with a 100% success rate. This success in downhole deployment generates consideration of other subsurface applications where UICP could provide benefit to the energy sector, such as shale property modification for unconventional oil and gas recovery. The focus of this research project was to investigate fundamental material and mechanical properties of select shale cores and analyze how these properties change due to engineered mineral precipitation with the intent to control these properties to achieve a range of engineering objectives. Ultimately, the project aim was to identify valuable new areas where application of UICP might contribute to national energy security and environmental protection. The research workplan coupled UICP treatment of core samples, nuclear magnetic resonance (NMR) characterization, and mechanical strength testing at MSU with advanced X‐Ray micro-computed tomography (μCT) imaging and numerical modeling performed by collaborators at two national laboratories, the National Energy Technology Laboratory (NETL) and Lawrence Berkeley National Laboratory (LBNL). Experimental results are useful to inform geo-mechanical models which could be applied to predict mineralized rock formation behavior at field scale. Our findings suggest that NMR and μCT methods to detect and quantify biomineral formation in shale fractures are complementary and consistent with each other. Either could be used to estimate the volume of new mineral formed by UICP in shale fractures. The use of surfactants and guar gum to enhance biomineral precipitation in shale fractures merits further research. UICP can, under some conditions, increase the tensile strength of sealed shale fractures beyond that of the intact shale. These findings demonstrate that continued research in this area may be valuable to understanding and improving shale resource recovery techniques.

58 GEOSCIENCES↗
DOE OSTI2022

Heat pulse testing at monitoring wells to estimate subsurface fluid velocities in geological CO 2 storage

Monitoring the injected CO 2 during geological CO 2 storage (GCS) is essential to assure containment and identify CO 2 leakage. Here in this work, a new approach is introduced to estimate the evolution of the downhole fluid velocity at a monitoring well and identify CO 2 arrival time using in-well heat pulse/tracer test. The proposed technique involves using a downhole heater to generate a series of heat pulses and measuring their corresponding temperature response. The surface temperature of the downhole heater is controlled by the supplied electrical power and the heat loss by convection to the surroundings. Convective heat transfer is well described using Newton's law of cooling in which the temperature difference between the heater and the surrounding fluids drives the heat transfer, for which the convection heat transfer coefficient (h) controls the magnitude of heat loss. Among various factors that control h, it depends on the type of the flowing fluid and its velocity. Through analyzing the measured temperature at different heat pulses, the changes in h - due to mobilization of the in-situ brine or CO 2 arrival - can be estimated. Consequently, the velocity of the flowing fluid across the heater can be obtained. Since heat transfer by convection is sensitive to the type of the surrounding fluid, intrusion of CO 2 can be detected from the relatively higher surface temperature obtained at CO 2 arrival. Churchill and Bernstein (1977)'s correlation is adopted to estimate the change of fluid velocity in terms of the change in h. To demonstrate the validity of the proposed technique, the results are applied and validated against those of COMSOL Multiphysics simulation tool for single-phase brine (before CO 2 arrival) and single-phase CO 2 (after CO 2 arrival). The observed temperature heating is sensitive to the flowing fluid velocity and fluid type. The temperature signal observed at CO 2 arrival is large and easily detectable using temperature monitoring tool which provides reliable indication for tracking CO 2 arrival at monitoring wells compared with passive temperature monitoring. The results obtained using the proposed technique agree very well with the numerical results obtained from the simulation tool with a maximum estimation error of 7 percent.

02 PETROLEUM↗