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DOE OSTI2025

Interfacial Hydrophilicity Controls Mineral Transformation Outcomes for Enstatite and Amorphous MgSiO 3

Subsurface injection of carbon dioxide (CO 2 ) into mafic-ultramafic rocks for permanent storage via mineralization is being studied to reduce emissions. Here, we investigated the carbonation products of enstatite (MgSiO 3 ) to assess its efficiency in sequestering CO 2 for safe and permanent storage as carbonate minerals. This was accomplished by conducting variable temperature carbonation reactions with samples of differing crystallinities and surface chemistries. Reaction progress was monitored utilizing in situ X-ray diffraction, and the presence of carbonate products was confirmed using additional techniques, such as thermogravimetric analysis coupled with mass spectrometry and scanning electron microscopy with energy dispersive spectrometry. Our results show that crystalline enstatite produces small amounts of the anhydrous form of MgCO 3 (magnesite), while amorphous MgSiO 3 , which was used to simulate mafic glass, more readily converts to the hydrated/hydroxylated hydromagnesite [Mg 5 (CO 3 ) 4 (OH) 2 ·4H 2 O]. These results, supplemented with dynamic vapor sorption experiments, suggest that surface properties play a significant role in the pathway and degree of carbonation. These developments concerning the reactivity of CO 2 with reactive mafic phases will help further our understanding of the reactivity of these mafic-ultramafic minerals with implications for permanent carbon storage and other subsurface engineering scenarios involving reactive reservoirs.

basalt↗

DOE OSTI2020

Experimental Investigation of Polymer Induced Fouling of Heater Tubes in the First-ever Polymer Flood Pilot on Alaska North Slope

Polymer flooding has been validated in the lab and by successful applications in other countries, such as Canada and China, to be an effective EOR technique for heavy oil reservoirs. Currently, polymer flooding is being pilot tested for the first time in the Schrader Bluff viscous oil reservoir at Milne Point field on Alaska North Slope (ANS). One of the major concerns of the operator is the impact of polymer on the oil production system after polymer breakthrough, especially the polymer induced fouling issues in the heat exchanger. This study investigates the propensity of polymer fouling on the heater tubes as a function of different variables, with the ultimate goal of determining safe and efficient operating conditions. A unique experimental set-up was indigenously designed and developed to simulate the fouling process on the heating tube. The influence of heating tube skin temperature, tube material, and polymer concentration on fouling tendency was investigated. Under each test condition, the test was run five times with the same tube, and in each run, the freshly prepared synthetic brine and polymer solution were heated from 77°F to 122°F to mimic field operating conditions. The heating time and fouling amount were recorded for each run. The morphology and composition of the deposit samples were analyzed by environmental scanning electron microscopy (ESEM) and X-ray diffraction (XRD), respectively. It has been found that, in general, the presence of polymer in produced fluids would aggravate the fouling issues on both carbon steel and stainless steel surfaces at all tested skin temperatures (165°F, 250 °F and 350°F), but only higher skin temperatures of 250°F and 350°F could cause polymer induced fouling issues on the copper tube surface and the fouling tendency increased with polymer concentration. At the lower skin temperatures of 165°F, no polymer-induced fouling was identified on the copper tube. A critical temperature that is related to the cloud point of the polymer solution was believed to exist, below which polymer induced fouling would not occur and only mineral scale deposited, but above which the polymer would obviously aggravate the fouling issue. The heating efficiency of the tube would be reduced gradually as more fouling material accumulates on its surface. The ESEM results indicate that if polymer precipitated and deposited on the surface, it would bond to the mineral crystals to form a stronger three- dimensional network structure, and that is why the polymer induced fouling was tougher and more difficult to be removed from the tube surface. The XRD analysis results confirm that the presence of polymer in the fluids can enhance the mineral scale propensity. Overall, the study results have provided practical guidance to the field operator for the ongoing polymer flooding pilot test on ANS. This study may also prove to be valuable for other chemical EOR projects around the world.

Alaska North Slope↗

DOE OSTI2020

Structure and Stability of Iron Fluoride at High Pressure–Temperature and Implication for a New Reservoir of Fluorine in the Deep Earth

Fluorine (F) is the most abundant halogen in the bulk silicate Earth. F plays an important role in geochemical and biological systems, but its abundance and distribution in the terrestrial mantle are still unclear. Recent studies suggested that F reservoirs in the deep mantle are potentially hosted in terrestrial oxide minerals, especially in aluminous bridgmanite. However, the knowledge about the formation and stability field of fluoride in the Earth’s interior is rare. In this study, we combine in situ laser-heated diamond anvil cell, synchrotron X-ray diffraction, and first-principles structure search to show that a new tetragonal structure of FeF 3 is stable at pressures of 78–130 GPa and temperatures up to ~1900 K. Simulation predicted the tetragonal phase takes a much denser structure due to the rotation of FeF 6 octahedral units. The equations of states of tetragonal FeF3 are determined by experiment and verified by simulation. Our results indicate that FeF 3 can be a potential key phase for storing F in the Earth’s lower mantle and may explain some mantle-derived magma with high F concentration.

58 GEOSCIENCES↗

DOE OSTI2021

Geomechanical and flow implications with continued bioconversion of coal to methane: Experiments and modeling

Microbial conversion of coal to methane is a promising technology during transition of coal-based energy from conventional coal mining to natural gas recovery from coal. Significant research advances have been made towards engineering ideal microbial communities and nutrients for bio-stimulation of coal. However, actual field applications require geomechanical and flow behavior characterization of coal during the bioconversion process as well as gas production over the life of the created “biogenic gas reservoirs”. This work presents the results of an experimental investigation to estimate gas/methane production using bioconversion of coal and analyses of variations in bulk modulus, strain and permeability. Bulk modulus of coal demonstrated time-dependent behavior with continued bioconversion of solid coal. The phenomenon was modeled using mass balancing in a closed environment and the logistic equation based biogenic gas production with time. The modeled gas production and changes in modulus of coal showed excellent agreement with the corresponding experimental results. Next, numerical simulation of biogenic conversion of coal in a constant stress in-situ condition, replicating the Huff ‘n Puff method under field conditions, was carried out. The results showed that bioconversion can lead to decrease in effective stress, increase in permeability and decrease in the modulus of coal with time. Repeated recharge of coal with nutrients and recovering the produced gas, that is, sequential cycles of Huff n’ Puff, showed further increase in permeability and decrease in coal strength, potentially leading to coal failure in-situ, further increasing the permeability, thus enhancing the prospect of field application of the technology.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2025

Unraveling Hydrogen Induced Geochemical Reaction Mechanisms through Coupled Geochemical Modeling and Machine Learning

Underground hydrogen storage (UHS) provides a promising large-scale, long-term energy storage solution. A reasonable recovery of stored hydrogen is critical for a successful storage scheme. However, in subsurface reservoirs hydrogen is subject to active geochemical reactions that might result in hydrogen loss. In this study, we implemented a geochemical modeling approach coupled with an unsupervised machine learning technique called non-negative matrix factorization (NMF) to unravel the complex brine-rock-H 2 geochemical processes responsible for hydrogen losses, with particular focus on sulfate reduction reactions. NMF is applied to modeled mineral evolution and fluid component profiles to retrieve profiles that can be interpreted to more easily assess competing processes. NMF decouples simulated competing equilibrium reactions. This facilitates separation of overlapping reaction profiles from redox processes, dissolution fronts, and secondary precipitation while considering the effects of simulation parameters such as salinity, temperature, and total H 2 pressure. NMF successfully discriminates these competing effects in nonlinear ways, allowing robust interpretation. In addition, NMF reveals subtle coupled mineral associations and reaction fronts that are invisible to conventional model analysis. This integrated approach strengthens the conceptual understanding of complex nonlinear hydrogen-brine-rock interactions and advances geochemical research on UHS systems to resolve complexities in modeled geochemical systems without the need for direct experiments or prior knowledge. Furthermore, this study highlights the efficacy of combining geochemical modeling with machine learning techniques to enhance the interpretability of the intricate geochemical simulation output through deciphering the overlapping reaction path that cannot be achieved only using conventional analysis of geochemical models alone.

08 HYDROGEN↗

DOE OSTI2022

Evaluating power grid model hydropower feasibility with a river operations model

Production cost models (PCMs) simulate dispatch of generators across a large power grid and are used widely by planners to study the reliability of electricity supply. As energy systems transition away from the thermoelectric technologies that have traditionally balanced electricity supply and demand, hydropower and its representation in PCMs is of increasing importance. A limitation of PCMs applied to continental power grids with diverse generation portfolios is that hydropower generation is simulated without full consideration of complex river dynamics, leading to possible misrepresentation of grid flexibility and performance. In addition, data used in PCMs may reflect outdated operating policies. In this paper we propose a hydropower generation feasibility test for PCMs. The approach uses a detailed hydropower model to determine whether the hourly hydropower schedule from a PCM with simplified monthly parameterization can be attained after accounting for realistic river dynamics and operating policies, such as spill requirements and general water movement and balance through a cascade reservoir system. We perform this hydropower generation test for the ‘Big 10’ hydropower system on the Columbia River (part of the Western Interconnect of the United States), revealing 9% overestimation of available hydropower generation in a PCM solution in an average hydrologic year. Our evaluation provides insight on the cost and opportunities for better representing hydropower in PCMs.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Continuous operation of a coherent 3,000-qubit system

Neutral atoms are a promising platform for quantum science, enabling advances in areas ranging from quantum simulations and computation to metrology, atomic clocks and quantum networking. Although atom losses typically limit these systems to a pulsed mode, continuous operation could substantially enhance cycle rates, remove bottlenecks in metrology and enable deep-circuit quantum evolution through quantum error correction. Here we demonstrate an experimental architecture for high-rate reloading and continuous operation of a large-scale atom-array system while realizing coherent storage and manipulation of quantum information. Our approach utilizes a series of two optical lattice conveyor belts to transport atom reservoirs into the science region, where atoms are repeatedly extracted into optical tweezers without affecting the coherence of qubits stored nearby. Using a reloading rate of 300,000 atoms in tweezers per second, we create over 30,000 initialized qubits per second, which we leverage to assemble and maintain an array of over 3,000 atoms for more than 2 hours. Furthermore, we demonstrate persistent refilling of the array with atomic qubits in either a spin-polarized or a coherent superposition state while preserving the quantum state of stored qubits. Our results pave the way for the realization of large-scale continuously operated atomic clocks, sensors and fault-tolerant quantum computers.

atomic and molecular physics↗

DOE OSTI2025

COMPUTATION FLUID DYNAMICS ANALYSIS FOR GENERIC SMALL MODULAR REACTOR CONTAINMENT SEPARATE EFFECTS TEST

It is desirable for fourth-generation Small Modular Reactors to be passively cooled in standard and accident operations. Passive Containment Cooling Systems can reject heat from the containment structure, without using pumps or blowers. The targeted design containment structure is a large, domed, stainless steel, cylindrical vessel. In a postulated Design Basis Accident, steam will flash inside containment. Steam condensation occurs on the inner containment wall and transfers heat through the steel containment into a large body of water known as the annular reservoir (AR) surrounding the vessel serving as the ultimate heat sink. Natural circulation drives the flow in the AR and heat will be released to the environment by evaporation of water. Unique containment geometry requires a separate effects test (SET) facility for the verification and validation of the computer code and evaluation model development and assessment for reactor licensing efforts. In this study, STAR-CCM+, a computational fluid dynamics (CFD) code was used to inform the decision-making process on the design of the SET. The CFD simulation modeled, a two-phase turbulent flow with fluid film development and heat transfer for different containment geometries. The Reactor Excursion and Leak Analysis Program will also be used in a code-to-code verification against the CFD results.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

DOE OSTI2025

Wellbore Stability and Mud Loss Management in Geothermal Drilling: Optimizing Mud Weight to Mitigate Tensile Wellbore Fracturing at The Geysers, California

As part of a U.S. Department of Energy (DOE) Geothermal Technologies Office-funded initiative, Geysers Power Company, LLC, a subsidiary of Calpine Corporation, has been working to enhance drilling performance at the world’s largest geothermal field, The Geysers, in northern California. In a recent drilling operation of the GDC-36 well, excessive mud losses were encountered, initially addressed through repeated but largely ineffective cement plugging. Ultimately, the most effective strategy was to drill blind through the loss zones, made feasible by the high rate of penetration (ROP) achieved with PDC bits, allowing significant progress before the mud tanks were depleted and water-sensitive argillic formation layers could collapse. In response to these challenges, the project team explored alternative methods to minimize downtime and risks associated with cement plugging and continuous mud loss and to contemplate the driving mechanisms for the losses. Wellbore imaging using Formation MicroImager (FMI) and Ultrasonic Borehole Imager (UBI) tools revealed longitudinal tensile fractures, which were attributed to mud weights exceeding the minimum circumferential stress resulting from the native stress field and formation pressure. This study examines the mud losses encountered and leverages wellbore imaging data to understand the mechanisms behind mud induced tensile fracturing in specific rock facies. Understanding fracture behavior across different lithologies is crucial, as fractures within the reservoir can enhance steam migration throughout the system. The reservoir at The Geysers lies within the Mesozoic Franciscan Assemblage, a tectonic mélange formed by subduction. It consists of metamorphosed turbidite sandstone (greywacke) and mudstone (argillite), oceanic upper crust (including greenstone and chert), and serpentinized ultramafic rocks - each exhibiting distinct geomechanical fracturing properties. The structural fabric of the Franciscan Assemblage was shaped by low-angle Mesozoic thrust faulting and later overprinted by sub-vertical strike-slip structures related to the Pacific-North American plate boundary. A wellbore stability model was developed using core measurements and logs to simulate fracturing scenarios during drilling under varying stress conditions. These simulations guided the development of an optimized mud weight management strategy that should enable adaptive adjustments during drilling, reducing the likelihood of tensile fracturing and mud losses, ultimately improving operational efficiency.

15 GEOTHERMAL ENERGY↗

DOE OSTI2020

Using Concentrating Solar Power to Create a Geological Thermal Energy Reservoir for Seasonal Storage and Flexible Power Plant Operation

Abstract We propose a hybrid renewable energy system—a geothermal energy storage system (GeoTES) with solar—to provide low-cost dispatchable power at various timescales from daily, to weekly, to seasonally. GeoTES with solar uses a concentrating solar power collector field to produce hot water that is injected into a sedimentary basin to create a synthetic geothermal resource. The stored geothermal heat can then be dispatched when required by the electrical grid. GeoTES is particularly valuable for a grid with a high penetration of non-flexible renewable technologies such as photovoltaic and wind power. In this work, a sophisticated hybrid model is developed to assess the technical and economic potential of GeoTES by combining IPSEpro, which is a power-cycle simulation tool, and SAM, an economic analysis tool by National Renewable Energy Laboratory (NREL). The analysis shows with proper initial charging period that the heat loss in storage is almost negligible and is a suitable technology for long-term energy storage. Various power-cycle options are evaluated, and the most suitable power cycle is selected for further study. Annual calculations of the GeoTES system indicate that a levelized cost of storage (LCOS) of 12.4 ¢/kWh e can be achieved for seasonal storage of 4000 h; this value is much lower than the existing long-term storage. The LCOS of GeoTES is insensitive to the storage duration above 8 h, unlike battery and molten-salt thermal storage systems. This result demonstrates that GeoTES can be a competitive seasonal storage technology in the future electricity market. The levelized cost of electricity of the GeoTES system is also carefully analyzed and can vary between 10.0 and 16.4 ¢/kWh e , depending on solar-collector prices.

25 ENERGY STORAGE↗

DOE OSTI2021

Viral Fate and Transport for COVID-19 - NVBL

The NVBL Viral Fate and Transport Team includes researchers from eleven DOE national laboratories and is utilizing unique experimental facilities combined with physics-based and data-driven modeling and simulation to study the transmission, transport, and fate of SARSCoV-2. The team was focused on understanding and ultimately predicting SARS-CoV-2 viability in varied environments with the goal of rapidly informing strategies that guide the nation’s resumption of normal activities. The primary goals of this project include prioritizing administrative and engineering controls that reduce the risk of SARS-CoV-2 transmission within an enclosed environment; identifying the chemical and physical properties that influence binding of SARS-CoV-2 to common surfaces; and understanding the contribution of environmental reservoirs and conditions on transmission and resurgence of SARS-CoV-2.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Viral Fate and Transport for COVID-19

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Open-Loop Control of Adjustable Tuned Mass Dampers for Floating Wind Turbine Platforms

In this study, we demonstrate the ability of adjustable tuned mass dampers (TMDs) to reduce the platform motion of floating offshore wind turbines (FOWTs). The TMDs are located in the hull and provide control authority by varying the amount of water ballast and compressed air in a reservoir over time. The optimal TMD settings depend on the wind and wave conditions of the FOWT. We present an open-loop control scheme that changes the TMD natural frequency based on sea state and a simple method for estimating the peak wave period and significant wave height. The performance of this open-loop control is compared to ideal control of the TMDs (set knowing the exact sea state), a TMD with a constant natural frequency targeting the design load case with the greatest platform motion, and a baseline set of simulations of the platform without TMDs. The constant natural frequency case performs nearly as effectively as the actively controlled case, suggesting that the TMDs can be simply designed for extreme load conditions and provide consistent control over a range of environments; however, the methods used to find the optimal TMD parameters and estimate sea state statistics could be used in other aspects of FOWT control and design.

artificial intelligence↗

DOE OSTI2025

Hydroboost

HydroBoost is the most realistic revenue optimization tool for the hybridization of hydropower and battery energy storage systems to date. The innovative representation of how operators actually schedule hydropower in practice results in more realistic predictions of revenue and operations. Unlike other optimization tools, HydroBoost generates forecast energy prices with uncertainty to use in the optimization. This allows HydroBoost to give users a range of potential revenue with an upper bound using the perfect foresight pricing and a lower bound using a naive persistence forecast model. Additional forecast can be generated and used in the optimization, such as additive models, random forest, and neural networks to give further insight into potential revenue. HydroBoost has been designed to be applicable for both run-of-river and reservoir storage sites. The primary focus is on the day-ahead market and requires year-long data with an hour time-step. All time-series input and constraints are contained in an Excel worksheet for convince. The user will run the forecasting generation first with a Python script to give the optimization model the necessary requirements. Next the optimization is ran using Julia and results are generated and stored into a directory as csv files. HydroBoost includes an additional module to generate figures based on the results of the optimization simulation. The results help analyze the results and users to draw insights into how the hydro and battery systems are operated and the revenue each is producing. Additionally, the difference between the perfect foresight model and models that include forecast can easily be inspected.

Phillips, TylerB. [Idaho National Laboratory (INL)↗

DOE OSTI2026

Optimal CO 2 storage management considering safety constraints in multi-stakeholder multi-site GCS projects: A Markov game perspective

Geological carbon storage (GCS) projects could involve a diverse array of stakeholders or players from public, private, and regulatory sectors, each with different objectives and responsibilities. Given the complexity, scale, and long-term nature of GCS operations, determining whether individual stakeholders can independently optimize their interests — or whether collaborative coalition agreements are needed — remains a central question for effective GCS project planning and management. To access large, high-quality storage resources, future GCS deployment may increasingly occur in geologically connected sites, where shared geological features such as pressure space and reservoir pore capacity can lead to competitive behavior among stakeholders. In this work, we propose a paradigm based on Markov games to quantitatively investigate how different coalition structures affect the goals of stakeholders. We frame this multi-stakeholder multi-site problem as a multi-agent reinforcement learning problem with safety constraints. Our approach enables agents to learn optimal strategies while complying with safety regulations. We present an example where multiple operators are injecting CO 2 into their respective project areas in a geologically connected basin. To address the high computational cost of repeated simulations of high fidelity models, a previously developed surrogate model based on the Embed-to-Control (E2C) framework is employed. Our results demonstrate the effectiveness of the proposed framework in addressing optimal management of CO 2 storage when multiple stakeholders with different objectives and goals are involved.

58 GEOSCIENCES↗

DOE OSTI2021

Isotopic fractionation as in-situ sensor of subsurface reactive flow and precursor for rock failure

Greater utilization of subsurface reservoirs perturbs in-situ chemical-mechanical conditions with wide ranging consequences from decreased performance to project failure. Understanding the chemical precursors to rock deformation is critical to reducing the risks of these activities. To address this need, we investigated the coupled flow-dissolution- precipitation-adsorption reactions involving calcite and environmentally-relevant solid phases. Experimentally, we quantified (1) stable isotope fractionation processes for strontium during calcite nucleation and growth, and during reactive fluid flow; (2) consolidation behavior of calcite assemblages in the common brines. Numerically, we quantified water weakening of calcite using molecular dynamics simulations; and quantified the impact of calcite dissolution rate on macroscopic fracturing using finite element models. With microfluidic experiments and modeling, we show the effect of local flow fields on the dissolution kinetics of calcite. Taken together across a wide range of scales and methods, our studies allow us to separate the effects of reaction, flow, and transport, on calcite fracturing and the evolution of strontium isotopic signatures in the reactive fluids.

42 ENGINEERING↗

DOE OSTI2023

Using Data-Driven Prediction of Downstream 1D River Flow to Overcome the Challenges of Hydrologic River Modeling

Methods for downstream river flow prediction can be categorized into physics-based and empirical approaches. Although based on well-studied physical relationships, physics-based models rely on numerous hydrologic variables characteristic of the specific river system that can be costly to acquire. Moreover, simulation is often computationally intensive. Conversely, empirical models require less information about the system being modeled and can capture a system’s interactions based on a smaller set of observed data. This article introduces two empirical methods to predict downstream hydraulic variables based on observed stream data: a linear programming (LP) model, and a convolutional neural network (CNN). We apply both empirical models within the Colorado River system to a site located on the Green River, downstream of the Yampa River confluence and Flaming Gorge Dam, and compare it to the physics-based model Streamflow Synthesis and Reservoir Regulation (SSARR) currently used by federal agencies. Results show that both proposed models significantly outperform the SSARR model. Moreover, the CNN model outperforms the LP model for hourly predictions whereas both perform similarly for daily predictions. Although less accurate than the CNN model at finer temporal resolution, the LP model is ideal for linear water scheduling tools.

13 HYDRO ENERGY↗

DOE OSTI2020

Theoretical power-law relationship between permeability and formation factor

Permeability k and formation factor F are important petrophysical properties that have broad applications to reservoir engineering. Although well-log analysis has advanced reservoir characterizations, direct measurement of k is still not available. Accordingly, resistivity logs and more particularly formation factor have been frequently used to estimate k. In this study, we present a theoretical framework to relate k to F. We use power-law scaling from continuum percolation theory to develop a theoretic relationship between k and F, which is similar in form to a published power-law equation with empirical coefficients. Our result gives a physical interpretation to this empirical relationship. We also compare power-law scaling laws from percolation theory with data derived from experimental measurements and numerical simulations in the literature. Finally, using the Curve Fitting toolbox of MATLAB, the parameters of the power-law equations are determined, and the significance of the non-universal power laws are discussed.

42 ENGINEERING↗