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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 307 records · Page 17

​Understanding a Stratigraphic Hydrothermal Resource – Geophysical Imaging at Steptoe Valley, Nevada

Sandia National Laboratories partnered with a multi-disciplinary group of subject matter experts to evaluate a stratigraphic geothermal resource in Steptoe Valley, Nevada using both established and novel geophysical imaging techniques. The stratigraphic reservoir in northern Steptoe Valley was previously discovered during oil and gas exploration. Subsequent studies, such as the Nevada Play Fairway Analysis, included data which further highlighted potential resource targets in the basin. Geophysical surveys, complemented with refined geologic mapping and geochemical sampling, were deployed to further characterize the resource. The resulting 3D geologic interpretation, conceptual model refinements, and reservoir simulations suggest that a >100MWe power-capable reservoir is likely economically accessible using conventional well placement and stimulation techniques in the Paleozoic carbonates of the deep/central basin of northern Steptoe Valley. Additional geophysical characterization and exploration drilling efforts are recommended to calibrate interpretation and determine where/how to potentially develop the northern Steptoe resource. The geophysical tools, interpretations, lessons learned, and public data generated by this study establish an exploration methodology to inform decisions for characterization and development of northern Steptoe Valley and other stratigraphic geothermal reservoirs in the western U.S.

15 GEOTHERMAL ENERGY↗

Synthesis and characterization of zeolite sorbents from coal fly ash by a microwave-assisted hydrothermal method for removal of boron leachate from coal impoundments

This study developed promoted zeolite-based sorbents derived from coal fly ash to remove leachates (like boron) from ash impoundment or landfill to protect the environment and reuse legacy coal ash. The sorbents were synthesized using machine learning model results as guide to accelerate the sorbent development.

Wang, Ping↗

Hydrothermally carbonized biomass formed via reactive twin-screw extrusion

A biomass-derived thermosetting polymer material being a product of processing a biomass feed material via a twin screw extruder having a length extending between an inlet and an outlet. Hot water from a water heater is injected into at least one inlet along the length of the twin screw extruder, the at least one inlet generally corresponding with a pressure boundary within the twin screw extruder. A pressure-sustaining valve is connected between the length of the twin screw extruder and the outlet, with the valve being adjusted to produce the biomass-derived thermosetting polymer material.

09 BIOMASS FUELS↗

Laser-driven hydrothermal processing

Systems for processing a material by submerging the material in a fluid and directing laser pulses at the fluid and the material for processing the material. An embodiment removes the surface of concrete, brick, or rock or minerals in a relatively gentle, energy-efficient, and controlled manner that also confines the material that is removed.

36 MATERIALS SCIENCE↗

Reactor for hydrothermal growth of structured materials

Design, fabrication, and usage of a reactor are presented for synthesis of structured materials from a liquid-phase precursor by heating. The structured materials are particles, membranes or films of micro-porous molecular sieve crystals such as zeolite and meso-porous materials. The precursor solution and structured materials in the reactor are uniformly heated by a planar heater with characteristic heat transfer dimension in the range of 3 mm to 10 cm. A planar heater having width and length at least three times of the characteristic heat transfer dimension provides at least one surface of uniform temperature distribution for heating purposes. Heating is conducted over a temperature range of 20 to 300° C. The planar heater can be heated by electrical power of by thermal fluid.

36 MATERIALS SCIENCE↗

Laser-driven hydrothermal processing

Systems for processing a material by submerging the material in a fluid and directing laser pulses at the fluid and the material for processing the material. An embodiment removes the surface of concrete, brick, or rock or minerals in a relatively gentle, energy-efficient, and controlled manner that also confines the material that is removed.

Mariella, Jr., Raymond P.↗

Laser-driven hydrothermal processing

Systems for processing a material by submerging the material in a fluid and directing laser pulses at the fluid and the material for processing the material. An embodiment removes the surface of concrete, brick, or rock or minerals in a relatively gentle, energy-efficient, and controlled manner that also confines the material that is removed.

Mariella, Jr., Raymond P.↗

Co-Processing Fast Pyrolysis Bio-Oils and Hydrothermal Liquefaction Biocrudes in Fluid Catalytic Cracking and Hydroprocessing in Refineries

Co-processing of biogenic feedstocks within the existing petroleum infrastructure represents an opportunity to incorporate large volumes of bio-carbon into transportation fuels. However, upgrading intermediate liquids from biomass and waste to final products efficiently and economically, while minimizing impacts to existing refinery infrastructure, remains a notable barrier to commercialization. The co-processing project, Bio-oil Co-processing with Refinery Streams, aimed to generate foundational knowledge for processing renewable intermediates in petroleum refineries and offer co-processing strategies, as well as develop new methods for biogenic carbon tracking and measurement.

bio-oil↗

Super-hydrophobic, thermally insulating, thermal-shocks resistant well cement composites for completion of geothermal wells at hydrothermal temperatures of up to 300° C

A well cement composite and a method for making a well cement composite includes a mixture of calcium aluminate cement (CAC) and fly ash cenospheres (CS) in a weight ratio of from 30:70 to 80:20 CAC to CS; sodium metasilicate (SMS) in an amount of from 1 to 10% of the total weight of the mixture of CAC and CS; polymethylhydrosiloxane (PMHS) in an amount of from 0.5 to 6.0% of the total weight of the mixture of CAC and CS; and water in a weight ratio of from 0.5:1.0 to 1.2:1.0 of water to CAC and CS.

Pyatina, Tatiana↗

Discovering Hidden Geothermal Signatures using Unsupervised Machine Learning

Discovering hidden geothermal resources is a very challenging task. It requires the mining of large datasets, including various diverse data attributes representing subsurface hydrogeological and geothermal conditions. The commonly used Play Fairway Analysis (PFA) typically relies on subject-matter expertise to analyze site or regional data to estimate geothermal conditions and prospectivity. Here, we demonstrate an alternative approach based on machine learning (ML) to process a geothermal dataset of Southwest New Mexico (SWNM). The study region includes low- and medium-temperature hydrothermal systems. However, most of these systems are poorly characterized because of insufficient existing data and limited past explorative studies. This study aims to discover hidden patterns and relationships in the SWNM geothermal dataset to better understand regional hydrothermal conditions. This is achieved by applying an unsupervised machine learning algorithm based on non-negative matrix factorization coupled with customized k-means clustering (NMFk). NMFk can automatically identify (1) hidden (latent) signatures characterizing datasets, (2) the optimal number of these signatures, (3) dominant data attributes associated with each signature, and (4) spatial distribution of the extracted signatures. Here, NMFk is applied to analyze 18 geological, geophysical, hydrogeological, geothermal attributes at 44 locations in SWNM. NMFk successfully finds data patterns and identifies the spatial associations of hydrothermal signatures with the four physiographic provinces in SWNM (Colorado Plateau, Volcanic Field, Basin and Range, and the Rio Grande rift). The algorithm identified up to 5 hydrothermal signatures in the SWNM datasets that differentiate between low- and medium-temperature hydrothermal systems in different provinces. Also, the algorithm identifies two medium-temperature hydrothermal systems in SWNM that require further exploration for geothermal resource development. Based on our analyses, 12 of the attributes are important to identify medium-temperature hydrothermal systems, and the remaining six attributes are critical to characterize low-temperature hydrothermal systems. Based on the obtained results, we identify potential physiographic provinces for further exploration to characterize them as geothermal resources. The resulting NMFk model can be applied to predict geothermal conditions and their uncertainties at new SWNM locations based on limited data from unexplored areas.

58 GEOSCIENCES↗

Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fuid-fow pathways are relatively rare in the subsurface, but are critical components of hydrothermal systems like Brady and many other types of fuid-fow systems in fractured rock. Here, we analyze geologic data with ML methods to unravel the local geologic controls on these pathways. The ML method, non-negative matrix factorization with k-means clustering (NMFk), is applied to a library of 14 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate that macro-scale faults and a local step-over in the fault system preferentially occur along production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate: (1) the specific geologic controls on the Brady hydrothermal system and (2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes. This submission includes the published journal article detailing this work, the published 3D geologic map of the Brady Geothermal Area used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity, 3D well data, along which geologic data were sampled for PCA analyses, and associated metadata file. This work was done using the GeoThermalCloud framework, which is part of SmartTensors (both are linked below).

15 GEOTHERMAL ENERGY↗