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At least 19 records

A two-stage magnetic refrigerator for astronomical applications with reservoir temperatures above 4 K

We propose a novel adiabatic demagnetization refrigerator (ADR) to produce temperatures as low as 100 mK starting from a high temperature reservoir between 4 and 8 K. The high temperature reservoir for the ADR can be provided by a mechanical cooler or an unpumped liquid helium bath. This refrigerator can be used to cool bolometric infrared detectors for low background astronomy from mountain tops, balloons or satellites as well as to cool cryogenic x-ray detectors. The two-stage ADR consists of a single magnet with a paramagnetic chromic-cesium-alum (CCA) salt pill to produce the low temperature and paramagnetic gadolinium-gallium-garnet (GGG) as the first stage to intercept heat from the high temperature reservoir. Thermal contact between the paramagnets and the reservoir during magnetization is made with a mechanical heat switch. The ADR is suspended with Kevlar chords under tension for high mechanical stiffness and low parasitic heat leak. In a single cycle, the ADR maintains a temperature of 100 mK for 10 to 100 hours. This time depends strongly on the magnetic field and reservoir temperature but not on the volume of the paramagnetic material as long as the heat leak is dominated by the suspension.

Hagmann, C.↗

Reservoir Temperature Estimator

The Reservoir Temperature Estimator (RTEst) is a program that can be used to estimate deep geothermal reservoir temperature and chemical parameters such as CO2 fugacity based on the water chemistry of shallower, cooler reservoir fluids. This code uses the plugin features provided in The Geochemist's Workbench (Bethke and Yeakel, 2011) and interfaces with the model-independent parameter estimation code Pest (Doherty, 2005) to provide for optimization of the estimated parameters based on the minimization of the weighted sum of squares of a set of saturation indexes from a user-provided mineral assemblage.

Palmer, CarlD.↗

The Reservoir Temperature Estimator (RTEst): A multicomponent geothermometry tool

The Reservoir Temperature Estimator (RTEst) is a multicomponent geothermometry tool for estimating reservoir geochemical parameters including reservoir temperature, CO 2 fugacity, mass of water lost or gained, and a reaction factor. It estimates these parameters and their associated uncertainties by minimizing an objective function that is the weighted sum of squares of the saturation indices of a user-selected set of minerals believed to be equilibrated with the reservoir fluid. RTEst accomplishes these estimates by combining the geochemical modeling capabilities of The Geochemist’s Workbench® with the optimization/parameter estimation resources of PEST®. An included interface aids the user in selecting plausible mineral phases to comprise the objective function and calculates their weighting factors. The working principles of RTEst are described and its efficacy is illustrated by presenting results of its application to various geothermal fields with known conditions. These examples show RTEst can account for the alteration of ascending reservoir fluid by mineral (calcite) re-equilibration with changes in temperature, reconstruct waters with CO 2 loss, correct for the deficit of water and other volatiles (CO 2,gas , H 2 S gas ) from boiling, and determine the amount of mixing of thermal and non-thermal waters. RTEst can use data with basis species below detection limit, missing, or unreliable either by assuming equilibrium with a controlling mineral (fixed-analyte method) or by treating the analyte concentration as an optimization parameter. The inverse of variance weighting method included in RTEst provides more representative results than either the normalization or unit weighting methods. Finally, the ability of RTEst to calculate reservoir temperatures, gas fugacity, and mixing fractions demonstrates its usefulness as a tool for evaluating geothermal systems.

15 GEOTHERMAL ENERGY↗

Machine-learning-assisted high-temperature reservoir thermal energy storage optimization

High-temperature reservoir thermal energy storage (HT-RTES) has the potential to become an indispensable component in achieving the goal of the net-zero carbon economy, given its capability to balance the intermittent nature of renewable energy generation. In this study, a machine-learning-assisted computational framework is presented to co-optimize the performance metrics of HT-RTES by combining physics-based simulation with stochastic hydrogeologic formation and thermal energy storage operation parameters, artificial neural network regression of the simulation data, and genetic algorithm-enabled multi-objective optimization. A doublet well configuration with a layered (aquitard-aquifer-aquitard) generic reservoir is simulated for cases of continuous operation and seasonal-cycle operation scenarios. Further, neural network-based surrogate models are developed for the two scenarios and applied to generate the Pareto fronts of the HT-RTES performance for four potential HT-RTES sites. The developed Pareto optimal solutions indicate the performance of HT-RTES is operation-scenario (i.e., fluid cycle) and reservoir-site dependent, and the performance metrics have competing effects for a given site and a given fluid cycle. The developed neural network models can be applied to identify suitable sites for HT-RTES, and the proposed framework sheds light on the design of resilient HT-RTES systems.

15 GEOTHERMAL ENERGY↗

Geothermal Reservoir Temperatures in Southeastern Idaho using Multicomponent Geothermometry

Southeastern Idaho exhibits numerous warm springs, warm water from shallow wells, and hot water within oil and gas test wells that indicate a potential for geothermal development in the area. Although the area exhibits several thermal expressions, the measured geothermal gradients vary substantially (19 – 61 ºC/km) within this area, potentially suggesting a redistribution of heat in the overlying ground water from deeper geothermal reservoirs. We have estimated reservoir temperatures from measured water compositions using an inverse modeling technique (Reservoir Temperature Estimator, RTEst) that calculates the temperature at which multiple minerals are simultaneously at equilibrium while explicitly accounting for the possible loss of volatile constituents (e.g., CO2), boiling and/or water mixing. Compositions of a selected group of thermal waters representing southeastern Idaho hot/warm springs and wells were used for the development of temperature estimates. The temperature estimates in the the region varied from moderately warm (59 ºC) to over 175 ºC. Specifically, hot springs near Preston, Idaho resulted in the highest temperature estimates in the region.

15 GEOTHERMAL ENERGY↗

Hybrid Uses of High-Temperature Reservoir Thermal Energy Storage: Lessons Learned from Previous Projects

One of the critical challenges of the green energy transition is resolving the mismatch between energy generation provided by intermittent renewable energy sources such as solar and wind and the demand for energy. There is a need for large amounts of energy storage over a range of time scales (diurnal to seasonal) to better balance energy supply and demand. Subsurface geologic reservoirs provide the potential for storage of hot water that can be retrieved when needed and used for power generation or direct-use applications, such as district heating. It is important to identify potential issues associated with high-temperature reservoir thermal energy storage (HT-RTES) systems so that they can be mitigated, thus reducing the risks of these systems. This paper reviews past experiences from moderate and high-temperature reservoir thermal energy storage (RTES) projects, along with hot water and steam flood enhanced oil recovery (EOR) operations, to identify technical challenges encountered and evaluate possible ways to address them. Some of the identified technical problems that have impacted system performance include: 1) insufficient site characterization that failed to identify reservoir heterogeneity; 2) scaling resulting from precipitation of minerals having retrograde solubility that form with heating of formation brines; 3) corrosion from low pH or high salinity brines; 4) thermal breakthrough between hot and cold wells due to insufficient spacing. Proper design, characterization, construction, and operational practices can help reduce the risk of technical problems that could lead to reduced performance of these thermal energy storage systems.

energy storage↗

Sudden change of geometric quantum discord in finite temperature reservoirs

We investigate sudden change (SC) behaviors of the distance-based measures of geometric quantum discords (GQDs) for two non-interacting qubits subject to the two-sided and the one-sided thermal reservoirs. We found that the GQDs defined by different distances exhibit different SCs, and thus the SCs are the combined result of the chosen discord measure and the property of a state. We also found that the thermal reservoir may generate states having different orderings related to different GQDs. These inherent differences of the GQDs reveal that they are incompatible in characterizing quantum correlations both quantitatively and qualitatively. - Highlights: • Comparable study of different distance-based geometric quantum discords. • Evolution of the geometric quantum discords in finite temperature reservoirs. • Different geometric quantum discords exhibit distinct sudden changes. • Nonunique states ordering imposed by different geometric quantum discords.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification. In this study, a machine-learning-assisted computational framework is presented to identify High-Temperature Reservoir Thermal Energy Storage (HT-RTES) site with optimal performance metrics by combining physics-based simulation with stochastic hydrogeologic formation and thermal energy storage operation parameters, artificial neural network regression of the simulation data, and genetic algorithm-enabled multi-objective optimization. A doublet well configuration with a layered (aquitard-aquifer-aquitard) generic reservoir is simulated for cases of continuous operation and seasonal-cycle operation scenarios. Neural network-based surrogate models are developed for the two scenarios and applied to generate the Pareto fronts of the HT-RTES performance for four potential HT-RTES sites. The developed Pareto optimal solutions indicate the performance of HT-RTES is operation-scenario (i.e., fluid cycle) and reservoir-site dependent, and the performance metrics have competing effects for a given site and a given fluid cycle. The developed neural network models can be applied to identify suitable sites for HT-RTES, and the proposed framework sheds light on the design of resilient HT-RTES systems. All the simulations and the neural network model were done by Idaho National Laboratory. A detailed description of the work was reported in publication linked below.

15 GEOTHERMAL ENERGY↗

Effects of Charged Solute-Solvent Interaction on Reservoir Temperature during Subsurface CO2 Injection

A short-term side-effect of CO2 injection is a developing low-pH front that forms ahead of the bulk water injectant, due to differences in solute diffusivity. Observations of downhole well temperature show a reduction in aqueous-phase temperature with the arrival of a low-pH front, followed by a gradual rise in temperature upon the arrival of a high concentration of bicarbonate ion. In this work, we model aqueous-phase transient heat advection and diffusion, with the volumetric energy generation rate computed from solute-solvent interaction using the Helgeson–Kirkham–Flowers (HKF) model, which is based on the Born Solvation model, for computing specific molar heat capacity and the enthalpy of charged electrolytes. A computed injectant water temperature profile is shown to agree with the actual bottom hole sampled temperature acquired from sensors. The modeling of aqueous-phase temperature during subsurface injection simulation is important for the accurate modeling of mineral dissolution and precipitation because forward dissolution rates are governed by a temperature-dependent Arrhenius model.

58 GEOSCIENCES↗

Testing and Modeling of Subscale Ice-on-Coil Module as Low Temperature Reservoir for sCO2 based Pumped Thermal Energy Storage Systems

Echogen tested approximately 10 kWthsubscale IOC system in their lab in Akron, OH for studying the feasibility, endurance and performance impact of the technology on PTES system. This paper discusses the test loop setup, testing and results from this sub-scale IOC testing. Along with testing, the project team also developed sub-scale IOC transient model. The paper discusses this transient model development and its validation against the test data.

Avadhanula, Vamshi Krishna [Echogen Power Systems ↗

Geothermometric Temperature Comparison of Hot Springs and Wells in Southern Idaho

Conventional geothermal resource prospecting often begins with geochemical analysis of geothermal fluids sampled from surface expressions (hot springs and fumaroles). Similarly, water samples from hot wells located near the surface expressions are also routinely collected and analyzed as a part of regional exploration efforts. The chemical compositions of these water samples can be used to assess the likely reservoir temperatures of the geothermal sites as well as to understand other reservoir characteristics. In this paper, we present comparative results of geothermometric reservoir temperatures based on water compositions measured from pairs of hot springs and nearby wells of 10 potential geothermal sites in southern Idaho using both traditional and multicomponent equilibrium geothermometric approaches. Our results show that the reservoir temperatures estimated using water compositions measured surface thermal features and wells produce similar results. However, for two of the 10 sites, Durfee Hot Spring and Fairchild Hot Spring, the estimated reservoir temperatures based on water compositions measured from hot springs were significantly higher than the estimated reservoir temperatures using the well water sample. In the case of the Durfee system, the well water may have chemically re-equilibrated within the aquifer resulting in a lower estimated temperature than that calculated using the hot spring. Similarly, in the case of the Fairchild system, the hot spring and well water chemistry are chemically distinct and had the greatest distance between the hot spring and well pairs of the examined geothermal sites. The difference in fluid chemistry suggests that the Fairchild Hot Spring reservoir is compartmentalized and the two expressions are issuing waters migrated from two separate portions of the reservoir. Although the majority of the hot spring/well pairs in southern Idaho provided concordant reservoir temperatures, it is imperative to consider the consistency of the water types and distance between the sources when estimating reservoir temperatures.

15 GEOTHERMAL ENERGY↗

Testing of a Loop Heat Pipe with Two Evaporators and Two Condensers

Most existing Loop Heat Pipes (LHPs) consist of one single evaporator and one single condenser. LHPs with multiple evaporators will be very desirable for cooling multiple heat sources or a heat source with large thermal footprints. Extending the LHP technology to include multiple evaporators and multiple condensers faces some challenges, including the interaction between individual compensation chambers, operating temperature stability, and adaptability to rapid power and sink temperature transients. This paper describe extensive testing of an LHP with two evaporators and two condensers. Tests performed include start-up, power cycle, sink temperature cycle, reservoir temperature cycle, and capillary limit. Test results showed that the loop could operate successfully under various heat load and sink conditions. The loop operating temperature is a function of the total heat load, the heat load distribution between the two evaporators, and temperatures of the two condenser sinks. Under most conditions, only one reservoir contained two-phase fluid and the other reservoir was completely liquid filled. Moreover, control of the loop operating temperature could shift from one reservoir to the other as the test condition changed.

Ku, Jentung↗

Mixing effects on geothermometric calculations of the Newdale geothermal area in the Eastern Snake River Plain, Idaho

The Newdale geothermal area in Madison and Fremont Counties in Idaho is a known geothermal resource area whose thermal anomaly is expressed by high thermal gradients and numerous wells producing warm water (up to 51 °C). Geologically, the Newdale geothermal area is located within the Eastern Snake River Plain (ESRP) that has a time-transgressive history of sustained volcanic activities associated with the passage of Yellowstone Hotspot from the southwestern part of Idaho to its current position underneath Yellowstone National Park in Wyoming. Locally, the Newdale geothermal area is located within an area that was subjected to several overlapping and nested caldera complexes. The Tertiary caldera forming volcanic activities and associated rocks have been buried underneath Quaternary flood basalts and felsic volcanic rocks. Two southeast dipping young faults (Teton dam fault and an unnamed fault) in the area provide the structural control for this localized thermal anomaly zone. Geochemically, water samples from numerous wells in the area can be divided into two broad groups – Na-HCO3 and Ca-(Mg)-HCO3 type waters and are considered to be the product of water-rhyolite and water-basalt interactions, respectively. Each type of water can further be subdivided into two groups depending on their degree of mixing with other water types or interaction with other rocks. For example, some bivariate plots indicate that some Ca-(Mg)-HCO3 water samples have interacted only with basalts whereas some samples of this water type also show limited interaction with rhyolite or mixing with Na-HCO3 type water. Traditional geothermometers [e.g., silica variants, Na-K-Ca (Mg-corrected)] indicate lower temperatures for this area; however, a traditional silica-enthalpy mixing model results in higher reservoir temperatures. We applied a new multicomponent equilibrium geothermometry tool (e.g., Reservoir Temperature Estimator, RTEst) that is based on inverse geochemical modeling which explicitly accounts for boiling, mixing, and CO2 degassing. RTEst modeling results indicate that the well water samples are mixed with up to 75% of the near surface groundwater. Relatively, Ca-(Mg)-HCO3 type water samples are more diluted than the Na-HCO3 type water samples. However, both water types result in similar reservoir temperatures, up to 150 °C. Samples in the vicinity of faults produced higher reservoir temperatures than samples away from the faults. Although both the silica-enthalpy mixing and RTEst models indicated promising geothermal reservoir temperatures, evaluation of the subsurface permeability and extent of the thermal anomaly is needed to define the hydrothermal potential of the Newdale geothermal resource.

Eastern Snake River Plain, Newdale, RTEst, geother↗

Fabrication and test of a variable conductance heat pipe

A variable conductance heat pipe (VCHP) with feedback control was fabricated with a reservoir-condenser volume ratio of 10 and an axially grooved action section. Tests of the heat transport capability were greater than or equal to the analytical predictions for the no gas case. When gas was added, the pipe performance degraded by 18% at zero tilt as was expected. The placement of the reservoir heater and the test fixture cooling fins are believed to have caused a superheated vapor condition in the reservoir. Erroneously high reservoir temperature indications resulted from this condition. The observed temperature gradients in the reservoir lend support to this theory. The net result was higher than predicted reservoir temperatures. Also, significant increases in minimum heat load resulted for controller set point temperatures higher than 0 C. At 30 C, control within the tolerance band was maintained, but high reservoir heater power was required. Analyses showed that control is not possible for reasonably low reservoir heater power. This is supported by the observation of a significant reservoir heat leak through the condenser.

Lehtinen, A. M.↗

Classical and integrated multicomponent geothermometry at the Tengchong geothermal field, Southwestern China

To reconstruct deep fluid chemical composition and increase the confidence in estimated reservoir temperatures, a more integral geothermometry method was compared to other classical geothermometers. Here in this paper, we apply the integrated multicomponent geothermometry (IMG) method using the GeoT code to estimate reservoir temperatures at the Tengchong geothermal field in Southwestern China. Results show reservoir temperatures calculated using the quartz geothermometer are closest to those estimated with the IMG method. The concentrations of Al and Mg, as well as selected minerals for geothermometry computations, are key factors for successfully using the IMG. Using the IMG method together with classical geothermometers can significantly increase confidence in reservoir temperature estimations. The methods presented and simulation program used here may be useful for analysis of other geothermal fields under similar conditions.

15 GEOTHERMAL ENERGY↗

The Preston Geothermal Resources; Renewed Interest in a Known Geothermal Resource Area

The Preston Geothermal prospect is located in northern Cache Valley approximately 8 kilometers north of the city of Preston, in southeast Idaho. The Cache Valley is a structural graben of the northern portion of the Basin and Range Province, just south of the border with the Eastern Snake River Plain (ESRP). This is a known geothermal resource area (KGRA) that was evaluated in the 1970's by the State of Idaho Department of Water Resources (IDWR) and by exploratory wells drilled by Sunedco Energy Development. The resource is poorly defined but current interpretations suggest that it is associated with the Cache Valley structural graben. Thermal waters moving upward along steeply dipping northwest trending basin and range faults emanate in numerous hot springs in the area. Springs reach temperatures as hot as 84° C. Traditional geothermometry models estimated reservoir temperatures of approximately 125° C in the 1970’s study. In January of 2014, interest was renewed in the areas when a water well drilled to 79 m (260 ft) yielded a bottom hole temperature of 104° C (217° F). The well was sampled in June of 2014 to investigate the chemical composition of the water for modeling geothermometry reservoir temperature. Traditional magnesium corrected Na-K-Ca geothermometry estimates this new well to be tapping water from a thermal reservoir of 227° C (440° F). Even without the application of improved predictive methods, the results indicate much higher temperatures present at much shallower depths than previously thought. This new data provides strong support for further investigation and sampling of wells and springs in the Northern Cache Valley, proposed for the summer of 2015. The results of the water will be analyzed utilizing a new multicomponent equilibrium geothermometry (MEG) tool called Reservoir Temperature Estimate (RTEst) to obtain an improved estimate of the reservoir temperature. The new data suggest that other KGRAs and overlooked areas may need to be investigated using improved geothermal exploration methods.

15 GEOTHERMAL ENERGY↗