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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

In-Process Melt Separation of Depolymerized PET in PET/PE Blends for Upcycling via Twin-Screw Extrusion

Our previous work focused on depolymerizing polyethylene terephthalate (PET) in twin-screw extrusion, as part of a broader project to continuously separate PET from polyolefins in the melt. This study focused on linear low-density polyethylene (LLDPE) and PET films and the use of ethylene glycol (EG), diethylene glycol (DEG), triethylene glycol (TEG), and bis(2-hydroxyethyl) terephthalate (BHET) to depolymerize the PET in the extruder to levels above 90% Mw. In this work, the focus will shift to achieving separation of the two polymers in the twin-screw extruder, which is made possible due to a 90% reduction in the Mw of the PET, which caused a decrease of its viscosity by several orders of magnitude. Owing to the viscosity difference and pressure buildup in the die, the low-viscosity PET preferentially exited a degassing vent instead of going through the die. This is because the flow of the PET would travel through a non-pressure vent rather than through a high-pressure die. However, owing to the higher viscosity of the LLDPE, the pressure was too high to pass through such a small diameter vent hole. Supercritical CO 2 (SCCO 2 ) was used to assist in this extraction, but SCCO 2 negatively impacted the overall degree of separation. Through analysis of the separated materials, it was concluded that a high separation of the two materials was achieved. TGA and FTIR confirmed that the material separated from the vent was 100% PET. The material removed from the die was composed of 95% LLDPE and 5% PET.

36 MATERIALS SCIENCE↗
DOE OSTI2026

In‐Process Melt Separation of PE/PET Blends for Upcycling via Twin‐Screw Extrusion. Impact of Catalyst Reagents on PET Depolymerization

Part 1 of this work focused on depolymerizing polyethylene terephthalate (PET) in twin-screw extrusion, as part of a broader project to continuously separate PET from polyolefins in the melt. This study focused on linear low-density polyethylene (LLDPE) and PET films and the use of ethylene glycol (EG), diethylene glycol (DEG), triethylene glycol (TEG), and bis(2-hydroxyethyl) terephthalate (BHET) to depolymerize the PET in the extruder to levels above 90% Mw. In part 2, the focus will shift to achieving separation of the two polymers in the twin-screw extruder, which is made possible due to a 90% reduction in the Mw of the PET, which caused a decrease of its viscosity by several orders of magnitude. Owing to the viscosity difference and pressure buildup in the die, the low-viscosity PET preferentially exited a degassing vent instead of going through the die. This is because the flow of the PET would travel through a non-pressure vent rather than through a high-pressure die. However, owing to the higher viscosity of the LLDPE, the pressure was too high to pass through such a small diameter vent hole. Supercritical CO₂ (SCCO₂) was used to assist in this extraction, but SCCO₂ negatively impacted the overall degree of separation. Through analysis of the separated materials, it was concluded that a very high separation of the two materials was achieved. TGA and FTIR confirmed that the material separated from the vent was 100% PET. The material removed from the die was composed of 90% LLDPE and 10% PET.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Implementation and evaluation of multi-dual mode counter-current chromatography in the CUP Modeler software

Counter-current chromatography (CCC) is a separation technique that utilizes immiscible solvent pairs as stationary and mobile phases, which imparts numerous benefits compared to solid-liquid chromatography including the ability to treat either the more-dense or less-dense solvent layer as the mobile phase. Multi-dual mode (MDM) is a CCC elution mode capable of improving the separation of closely eluting compounds by alternating upper- and lower-layer solvent flows in opposing directions within the same separation. While some effort has been made to model MDM, implementation of these models in experimental design has yet to be widely adopted. Accordingly, we further developed our previously published cell utilized partitioning (CUP) model to include MDM predictions with CCC and packaged the full suite of CUP modeling capabilities into a user-friendly, open-source tool called the CUP Modeler. The mathematical model for MDM CCC was derived and validated with experimental separation of ethyl guaiacol (EG) and ethyl phenol (EP), two compounds that co-elute in our previously demonstrated reductive catalytic fractionation (RCF) lignin monomer isolation method. The developed MDM model provided insights into the effect of multiple operating parameters - including stationary phase retention, flow rate, column efficiency, feed concentration ratio, selectivity factor, and solute distribution ratios - on the separation yields, productivity, and purities. Our model agreed with prevailing understanding of MDM but also revealed new insights including that the ideal distribution ratios for co-eluting solutes to be separated by MDM is between 1.1 and 1.5, with the lower value ideally close to 1.25. Overall, this work provides fundamental insights for MDM process design and enables broader adoption of general liquid-liquid chromatography with a new, open-source user-friendly interface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Experimental investigation of flow distribution in enhanced geothermal systems with deep eutectic solvent

Geothermal energy has been recognized as a valuable alternative to fossil fuels and nuclear power, as it is renewable and reliable. Enhanced Geothermal Systems (EGSs) have the potential to expand geothermal energy production by enabling access to previously untapped geothermal resources. Geothermal short-circuiting poses a significant challenge to EGS development, leading to reduced heat extraction. Deep Eutectic Solvent (DES) exhibits favorable thermal and rheological properties, making it a candidate for geothermal applications. Here, this paper examines Choline Chloride-Based Deep Eutectic Solvent (DES) as a working fluid in geothermal applications and its potential to mitigate geothermal short-circuiting. Hydraulic experiments using a dual fracture flow loop were conducted at high temperatures. The results showed that DES exhibited higher differential pressure behavior compared to water. Flow distribution results revealed that DES enhances flow allocation within the small fracture, particularly when a temperature difference exists between fractures. Specifically, DES increased flow distribution by an average of 11% when the temperature difference was 85°C, and by 13% when the difference was 45°C, relative to water. These findings suggest that DES responds to thermal fracture differences, making it a potential remedy to address geothermal short-circuiting.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

High-pressure Cr 3+ luminescence and Raman spectroscopy of a natural MgAl 2 O 4 spinel to ∼60 GPa

Cr 3+ luminescence and Raman spectroscopy of a natural spinel were collected up to ∼60 GPa at ambient temperature using a Ne or a 4:1 methanol-ethanol mixture as the pressure transmitting media. Here, in the Ne experiments above ∼40 GPa, and in the 4:1 methanol–ethanol experiments above ∼20 GPa, all luminescence emission lines shift non-linearly, and by 59 GPa the spectra are broadened and are significantly changed. The Raman modes shift smoothly to higher frequencies with pressure, with a slight change in slope above 40 GPa, with no kinks or discontinuities. By ∼60 GPa, only the most intense Eg mode remains resolvable, appearing broadened and reduced in intensity. The change in slope in the Raman modes and luminescence bands may be due to a change in the compression mechanism of spinel. When spinel was decompressed from 40 GPa all changes were fully reversible; however, when the samples were decompressed from 54 to 60 GPa in Ne and 59 GPa in 4:1 methanol-ethanol the spectra were irreversibly changed. The change in the luminescence spectra and the Raman spectra are likely due to a pressure induced disorder of the anions or partial amorphization between 40 and 60 GPa.

Cr3+↗
DOE OSTI2024

Producing multiple chemicals through biological upcycling of waste poly(ethylene terephthalate)

Poly(ethylene terephthalate) (PET) waste is of low degradability in nature, and its mismanagement threatens numerous ecosystems. To combat the accumulation of waste PET in the biosphere, PET bio-upcycling, which integrates chemical pretreatment to produce PET-derived monomers with their microbial conversion into value-added products, has shown promise. The recently discovered Rhodococcus jostii strain PET (RPET) can metabolically degrade terephthalic acid (TPA) and ethylene glycol (EG) as sole carbon sources, and it has been developed into a microbial chassis for PET upcycling. However, the scarcity of synthetic biology tools, specifically designed for the non-model microbe RPET, limits the development of a microbial cell factory for expanding the repertoire of bioproducts from post-consumer PET. Herein, we describe the development of potent genetic tools for RPET, including (1) two inducible and titratable expression systems for tunable gene expression and (2) Serine Integrase-based Recombinational Tools (SIRT) for genome editing. Using these tools, we systematically engineer the RPET strain to ultimately establish microbial supply chains for producing multiple chemicals, including lycopene, lipids, and succinate, from post-consumer PET waste bottles, achieving the highest titer of lycopene ever reported thus far in RPET (i.e., 22.6 mg/L of lycopene, approximately 10,000-fold higher than that of the wild-type strain). Furthermore, this work highlights the great potential of plastic upcycling as a generalizable means of sustainable production of diverse chemicals.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Ionic Liquid-Enhanced Interfaces to Boost Reactive C O2 Capture

The addition of ionic liquids (ILs) to a mixture containing a molecular solvent and other ionic species can induce the heterogeneous redistribution of cations and anions at the gas–liquid interface. This nonuniform redistribution of cations and anions driven by the differences in the solvophilicity of ions can improve the thermophysical and interfacial properties of such mixtures, creating a local chemical environment that is conducive to some reactions. In this work, ILs are added to a mixture of potassium hydroxide (KOH) and ethylene glycol (EG), used as a reactive absorbent and electrolyte in the migration-assisted moisture-gradient (MAMG) process for CO 2 capture. Molecular dynamics (MD) simulations are employed to probe into the effects of complex ion–ion and ion–solvent interactions and to examine the chemical composition at the gas–liquid interface. A total of 12 systems are investigated using molecular simulations to identify trends in the performance of IL additives based on the choice of cation, anion, and IL concentration. The cation effects are studied using IL additives based on 1-ethyl-3-methylimidazolium ([EMIM] + ) and 1-butyl-3-methylimidazolium ([BMIM] + ), while the impact of anions is examined using additives based on dicyanamide [DCA] − , triflate [TfO] − , bistriflimide [NTf 2 ] − , and hexafluorophosphate [PF 6 ] − anions, respectively. The influence of the IL concentration is also evaluated at molar concentrations between 1% and 4%. The simulation results indicate that the use of IL additives can affect the physical CO 2 solubility, surface tension, and the localization of CO 2 around the [OH] − ions at the gas–liquid interface. It is also evident that the choice of cations, anions, and IL concentration determines the extent to which the IL additives impact the local physicochemical properties. Physical dissolution, diffusive transport, and interaction with [OH] − are critical intermediate steps toward reactive CO 2 capture using a liquid absorbent. Hence, the improvement in one or more of these properties, aided by IL additives, is expected to improve the overall CO 2 capture performance. Experiments reaffirmed the impact of IL additives on CO 2 capture performance and the sensitivity to the choice of the cation, anion, and concentration of the IL additive.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Orthorhombic Structures as Inorganic Halide Perovskite Models for High-Throughput DFT Investigations

Although high-symmetry Pm-3m space group cubic models are computationally efficient for high-throughput density functional theory (DFT) calculations of inorganic ternary (ABX 3 ) halide perovskites (HPs), they frequently predict band gaps (E g ) that disagree with experiment. Conversely, while low-symmetry cubic polymorphous networks (PN) comprised of 160 to 320 atoms incur significantly greater computational cost, they predict E g ’s that are more closely aligned with experiment. Here, in this study, we compare the DFT total energies and E g ’s predicted by four high-symmetry structure models (Pnma orthorhombic, R3m trigonal, P4/mbm tetragonal, and Pm-3m cubic) to cubic PNs for 5 experimentally characterized ternary HPs and find that the orthorhombic model computes Eg’s with the smallest MAD of 0.23 eV relative to the PNs. Pair distribution functions and DFT-computed total energies show that octahedral tilting, which is present in the 20-atom orthorhombic and 160-atom cubic PN models but not in the 5-atom cubic models, stabilizes all 5 compositions in our benchmarking set. We also find that imposing PN constraints when generating and optimizing these orthorhombic structures by fixing the unit cell lattice vectors and displacing the atoms prior to ionic relaxation with DFT, which we call the orthorhombic surrogate model (OSM), lowers the MAD of E g predictions to 0.09 eV. Our OSM predicts the PN band gaps of an additional 95 theoretical inorganic ternary HPs with MAD of 0.08 eV, supporting its usage in high-throughput DFT investigations to closely estimate PN band gaps with much less computational expense.

14 SOLAR ENERGY↗
DOE OSTI2025

Kinetics Measurements in Resistive Electrolytes Using Ring-Disk Electrode: Ring as Current “Shield” Enables Uniform Disk Current Distribution

Rotating disk electrodes are commonly used for electrochemical kinetics measurements. A major disadvantage of these types of electrodes is their nonuniform secondary current distribution, especially when performing electroanalytical measurements in resistive electrolytes. Such nonuniform current distribution can render the values of kinetics constants extracted from the disk electrode to be highly inaccurate. Furthermore, one emerging class of electrolytes that suffer from low ionic conductivities is deep eutectic solvents (DES). DES are a promising class of electrolytes for various emerging applications; however, due to their resistive nature, the secondary current distribution when using them is typically highly nonuniform. For example, the Wagner number when measuring Cu²⁺/Cu⁺ kinetics in choline chloride–ethylene glycol DES (1:4 molar ratio of ChCl:EG) is very low (<0.1), indicating highly nonuniform current distribution over the disk electrode. We show here that the Cu²⁺/Cu⁺ exchange current density measured using disk electrodes is very inaccurate due to the aforementioned nonuniform current distribution. To obtain uniform disk current distribution, we employ here a coplanar concentric rotating ring-disk electrode (RRDE), where the ring serves the function of a current “shield.” Specifically, we show using modeling that the ring minimizes the current distribution nonuniformity at the disk by effectively shielding the disk against current spikes near the disk edge. This enables improved precision in electrode kinetics measurements for the Cu²⁺/Cu⁺ couple in resistive DES. To enable broad applicability of this technique, an analytical expression based on the Wagner number is integrated into an iterative algorithm to help users identify ring conditions to achieve uniform current distribution and thus improved electroanalytics at the disk.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Use of Renewable Alcohols in Autocatalytic Production of Aspen Organosolv Lignins

This study aimed to investigate the intrinsic efficiency of renewable alcohols, applied under autocatalytic conditions, for removing lignin from aspen and hot-water-extracted aspen while substantially preserving the lignin structure so as to facilitate various valorization strategies. Ethylene glycol (EG), propylene glycol (PG), 1,4-butanediol (BDO), ethanol (EtOH), and tetrahydrofurfuryl alcohol (THFA) were evaluated based on their lignin solubilization ability, expressed as the relative energy difference (RED) following the principles of the Hansen solubility theory. The findings indicate that alcohols with a higher lignin solubilization potential lead to increased delignification, almost 90%, and produce a lignin with a higher content of β-O-4 bonds, up to 68% of those found in aspen milled wood lignin, thereby indicating their potential for valorization through depolymerization. However, these alcohols also produce lignin with a higher content of β-β and β-5 bonds, resulting in a higher molecular weight and polydispersity, due to readily occurring homolytic reactions. Hot-water extraction (HWE) conducted prior to alcohol treatment reduced the delignification efficiency and resulted in a lignin with a lower β-O-4 bond content. The lignins produced in these experiments exhibited a superior UV-A absorption capacity compared with synthetic benzophenone, as well as a greater radical quenching ability than synthetic butylated hydroxytoluene, indicating their potential for use in the protection of polymers against degradation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Selecting Appropriate Model Complexity: An Example of Tracer Inversion for Thermal Prediction in Enhanced Geothermal Systems

Abstract A major challenge in the inversion of subsurface parameters is the ill‐posedness issue caused by the inherent subsurface complexities and the generally spatially sparse data. Appropriate simplifications of inversion models are thus necessary to make the inversion process tractable and meanwhile preserve the predictive ability of the inversion results. In this study, we investigate the effect of model complexity on fracture aperture inversion and thermal performance prediction in a field‐scale EGS model. Principal component analysis was used to map the aperture field to a low‐dimensional latent space. The complexity of the inversion model was quantitatively represented by the percentage of total variance in the original aperture fields preserved by the latent space. Tracer, pressure and flow rate data were used to invert for fracture aperture through an ensemble‐based inversion method, and the inferred aperture field was used to predict thermal performance. With an over‐simplified aperture model, ensemble collapse occurred. The inverted aperture models failed to resolve necessary flow and transport features, leading to a biased thermal performance prediction. A complex aperture model involved excessive features and was prone to overinterpreting the inversion data. Both the tracer/pressure/flow rate data reproduction and thermal prediction showed significant uncertainties, making it difficult to properly estimate long‐term thermal performance. Fortunately, our results indicate that there exists an appropriate model complexity which can simultaneously match inversion data and predict thermal performance with an acceptable uncertainty. The quality of the fit of tracer data appears to be a useful indicator of such an appropriate model complexity.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Deep learning forecasts the spatiotemporal evolution of fluid-induced microearthquakes

Microearthquakes generated by subsurface fluid injection record the evolving stress state and permeability of reservoirs. Forecasting their spatiotemporal evolution is therefore critical for applications such as enhanced geothermal systems, carbon dioxide sequestration and other geoengineering applications. Here we propose a transformer neural network model that ingests hydraulic stimulation history and prior microearthquake observations to forecast four key quantities: cumulative microearthquake count, cumulative logarithmic seismic moment, and the 50th- and 95th-percentile extents of the microearthquake cloud. Applied to the EGS Collab Experiment 1 dataset, the model achieves R2 > 0.98 for the 1-s forecast horizon and R2 > 0.88 for the 15-s forecast horizon across all targets, and supplies uncertainty estimates through a learned standard deviation term. These accurate, uncertainty-quantified forecasts enable real-time inference of fracture propagation and permeability evolution, demonstrating the strong potential of deep-learning approaches to improve seismic-risk assessment and guide mitigation strategies in future fluid-injection operations.

Chung, Jaehong↗
DOE OSTI2024

Day-to-day reliability of basal heart rate and short-term and ultra short-term heart rate variability assessment by the Equivital eq02+ LifeMonitor in US Army soldiers

Introduction The present study determined the (1) day-to-day reliability of basal heart rate (HR) and HR variability (HRV) measured by the Equivital eq02+ LifeMonitor and (2) agreement of ultra short-term HRV compared with short-term HRV. Methods Twenty-three active-duty US Army Soldiers (5 females, 18 males) completed two experimental visits separated by >48 hours with restrictions consistent with basal monitoring (eg, exercise, dietary), with measurements after supine rest at minutes 20–21 (ultra short-term) and minutes 20–25 (short-term). HRV was assessed as the SD of R–R intervals (SDNN) and the square root of the mean squared differences between consecutive R–R intervals (RMSSD). Results The day-to-day reliability (intraclass correlation coefficient (ICC)) using linear-mixed model approach was good for HR (0.849, 95% CI: 0.689 to 0.933) and RMSSD (ICC: 0.823, 95% CI: 0.623 to 0.920). SDNN had moderate day-to-day reliability with greater variation (ICC: 0.689, 95% CI: 0.428 to 0.858). The reliability of RMSSD was slightly improved when considering the effect of respiration (ICC: 0.821, 95% CI: 0.672 to 0.944). There was no bias for HR measured for 1 min versus 5 min (p=0.511). For 1 min measurements versus 5 min, there was a very modest mean bias of −4 ms for SDNN and −1 ms for RMSSD (p≤0.023). Conclusion When preceded by a 20 min stabilisation period using restrictions consistent with basal monitoring and measuring respiration, military personnel can rely on the eq02+ for basal HR and RMSSD monitoring but should be more cautious using SDNN. These data also support using ultra short-term measurements when following these procedures.

General & Internal Medicine↗
DOE OSTI2025

GEOS-DEV/FORGE

This dataset is a repository that provides the input deck for numerical models associated with two Utah FORGE research projects: "Closing the Loop Between In situ Stress Complexity and EGS Fracture Compexity" (Project Number: 2-2446) and "Coupled Investigation of Fracture Permeability Impact on Reservoir Stress and Seismic Slip Behavior" (Project Number: 5-2428). Three kinds of simulation decks are included: (i) hydraulic fracturing simulation (HydroFrac folder), (ii) phase-field simulation (PhaseField folder), and (iii) thermo-hydro-mechanical simulation (ThermoHydroMech folder).

Cusini, Matteo [Lawrence Livermore National Labora↗
DOE OSTI2024

Utah FORGE 2-2439v2: Characterizing In-Situ Stress with Laboratory Modelling and Field Measurements - 2024 Annual Workshop Presentation

This is a presentation on A Multi-Component Approach to Characterizing In-Situ Stress at the Utah FORGE Site: Laboratory Modelling and Field Measurements project by The University of Pittsburgh, presented by Andrew Bunger. The project characterizes the stress in the Utah FORGE EGS reservoir using three methods: Method 1: Demonstrate complimentary laboratory rock-core stress estimation combined with Machine Learning approach for measuring in-situ stress from field sonic log data; Method 2: Complete field based in-situ measurement (mini-frac); and Method 3: Develop a mechanics-based method for connection near wellbore stress measurements to stresses away from the well-bore. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 14, 2024.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

M3SF-24LL010302062-NEA-TDB Management and International Collaborations in Sorption and Thermodynamic Modeling

This progress report (Level 3 Milestone Number M3SF-24LL010302062) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Crystalline International Collaborations Work Package Number SF-24LL01030206. The activity is focused on our long-term commitment to engaging our partners in international nuclear waste repository research. This includes participation in the Nuclear Energy Agency Thermochemical Database (NEA-TDB) Project and development of methodologies for integrating US and international thermodynamic databases for use in SFWST Generic Disposal System Assessment (GDSA) efforts. A continuing focus for FY24 efforts is to support the US participation in the NEA-TDB effort. The focus of FY24 activities was the development of an agreement for a Phase 7 activity that will start in Q1 of 2025. Mavrik Zavarin is now the US representative on both the Management Board and the Executive group to the NEA-TDB. He is also the POC for the Cements State of the Art Report that is undergoing peer review in FY24. In FY24, we used our position on the NEA-TDB MB and EG to facilitate the integration of NEA-TDB thermochemical data with LLNL’s SUPCRTNE thermodynamic database that supports the SFWST GDSA activities. This effort is coordinated with the Argillite work package SUPCRTNE database development efforts (Wolery, 2024). The goal is to provide a downloadable database that will be hosted on LLNL’s thermodynamics website which incorporates NEA-TDB data into the LLNL database where appropriate. We also began engagement with the EURAD2 program that was initiated in FY24 by our European collaborators at the Karlsruhe Institute of Technology (KIT), Germany. The primary focus of the engagement is with WP20: DITUSC Thermodynamic database evaluation program. A kickoff meeting for this activity is planned for early FY25. Finally, we have been selected to co-host (with Clemson University) the International Conference on Chemistry and Migration Behaviour of Actinides and Fission Products in the Geosphere in 2025 (Migration2025). The meeting will be held September 21-26, 2025, in New Orleans, Louisiana, and will focus on international efforts to understand the risks of radionuclide releases into the environment. This central focus of this conference is on international efforts to develop safe disposal options for nuclear wastes. As such, we are developing a theme focused on US underground nuclear waste repository science.

58 GEOSCIENCES↗
DOE OSTI2025

Connecting In Situ Stress and Wellbore Deviation to Near-Well Fracture Complexity Using Phase-Field Simulations

The interactions among in situ stress, rock fabric, wellbore geometry, natural fractures, and other natural or man-made defects create highly complex fracture trajectories in the near-wellbore region, far more intricate than those in the far-field. These near-wellbore complexities are critical for the Utah FORGE project and Enhanced Geothermal Systems (EGS) in general. Frictional pressure loss in the near-wellbore region during stimulation can significantly influence the growth of far-field fractures, while pressure losses during circulation serve as a major source of energy dissipation. Near-wellbore fracture complexities are often observable through image logs, offering valuable insights into in situ stress characteristics. However, leveraging this information requires a high-fidelity model capable of capturing the interplay among the diverse factors influencing fracture behavior.

58 GEOSCIENCES↗
DOE OSTI2025

Wellbore Fracture Imaging Using Inflow Detection Measurements

One of the most striking measurements taken during DOE’s EGS Collab project at the 4850-foot depth location was the so-called ‘sewer cam’, which enabled direct visualization of the flow of water into the production well through fractures during the stimulation. The ability to see directly which fractures were flowing and (roughly) how much was a breakthrough in understanding the topology of the created fracture network. Achieving this kind of fracture flow imaging at FORGE would be more challenging because of the 225°C temperature, but equally or even more valuable if it could be achieved. In 2017, a joint project between Sandia and Stanford developed a downhole tool concept to measure the enthalpy of multiphase fluid entering a geothermal well from individual fractures (Gao et al., 2017). For the FORGE project, measuring enthalpy is of less interest because the fluid is expected to be single-phase liquid water. However, the foundation of the device was the measurement of chloride ion concentration, which could form the basis for a direct measurement of inflow from fractures. During the 2017 project, this novel chloride sensing system was implemented into a laboratory test instrument, and we confirmed the capability of the system to measure the ion concentration of fluid entering a model wellbore through a small entry port. The wellbore was a 6-inch diameter model well, and the port was approximately 0.08 inch (2mm) in diameter. The device could measure the chloride concentration accurately even when the well was flowing in a bubbly flow. Given its accuracy, the tool should be able to identify locations of water entering the wellbore even if the ion concentration differs only slightly from that of the water in the well. It is likely that different fractures may flow slightly different chloride concentrations, which would make it feasible to detect individual fractures as well as to estimate the volume of their flow. Ultimately, we could also recognize different fractures flowing back significantly different ion concentrations after fracturing in the FORGE wells. This could be realized by adding different ions in the fracturing fluids in different fractures created at different stages of stimulation (and modifying the tool to include different ion specificity). Sandia’s tool was shown during the study to have the capability to withstand the 225°C temperature, and the electrochemical sensing elements were tested in the laboratory to 225°C at 1500 psia for 24 hours. An early implementation of the fully integrated downhole electrochemical tool, including high-temperature electronics, robust housing, and wireline truck interface, had previously been constructed and tested successfully at Sandia; thus, hardware development tasks focused on advancing the technology readiness level (TRL) of this promising technology for FORGE deployment, rather than on developing a new scientific basis for its operation. The data collection electronics in this tool allowed for several other sensors (pressure, temperature, flow spinner) to be implemented in parallel as well. The research was a new collaboration between Stanford and Sandia to modify and refine the tool for FORGE deployment, to make the downhole measurements, and to characterize the evolving fractures.

15 GEOTHERMAL ENERGY↗