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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

MODELING AND OPTIMIZATION OF A PCM-BASED OCEAN THERMAL ENERGY HARVESTER FOR POWERING UNMANNED UNDERWATER VEHICLES

As oceans cover over 70% of the planet’s surface, they represent a large reservoir of resources that remained vastly untapped. Uncrewed Underwater Vehicles (UUVs) are becoming key technology for ocean exploration. Ocean thermal gradient is a permanent and reliable energy source that can be used to power UUVs using phase change material (PCM)-based thermal engines. However, the main drawback of this technology is its low conversion efficiency. When using PCM-based thermal engines to power UUVs, there are different energy conversion stages, thermal-hydraulic, hydraulic-kinetic, kinetic-electrical, dependent of a wide variety of parameters. Thus, optimization of the overall energy conversion is still a challenge for powering the increasing energy demanding UUVs for long missions. The goal of this study is to propose a PCM-based ocean thermal energy harvesting system for powering the Solo II float. Using the ocean thermal energy reduces the cost for battery replacement and expands the float’s mission time. For this purpose, we developed a multiphysics model for a system consisting of thermal material, hydraulic, and electrical systems. This system is designed to provide the electrical power needed for the instruments aboard the underwater vehicle. The models of the hydraulic and the electric systems are implemented in MATLAB-Simulink/Simscape environment. The final model developed can provide 13.66 kJ of electrical energy, which is more than 1.5 times the energy requirement per cycle for the SOLO II float.

Ouro-Koura, Habilou↗
DOE OSTI2022

Coreflood Tests to Evaluate Enhanced Oil Recovery Potential of Wettability-Altering Surfactants for Oil-Wet Heterogeneous Carbonate Reservoirs

Summary Oil-wetness and heterogeneity are two main factors that result in low oil recovery (OR) by waterflood in carbonate reservoirs. The injected water is likely to flow through high-permeability regions and bypass the oil in the low-permeability matrix. In this study, systematic coreflood tests were carried out in both “homogeneous” cores and “heterogeneous” cores with a wettability-altering surfactant. The homogeneous coreflood tests were conducted to evaluate surfactant retention, as well as to compare tertiary surfactant flooding with secondary surfactant flooding. The heterogeneous coreflood test was proposed to model bypassing in low-permeability matrix during waterfloods, and dynamic imbibition of surfactant into the low-permeability matrix. Surfactant retention results suggest that retention increases as initial oil saturation decreases. The retention of selected surfactant in the target reservoir cores was measured to be within a range of 0.07–0.12 mg/g-rock, which is economically acceptable. The results of homogeneous coreflood tests showed that both secondary waterflood and secondary surfactant flood can achieve high OR (>50%) from relatively homogeneous oil-wet cores. A shut-in phase after the surfactant injection resulted in a surge in oil production, which suggests that enough time should be given for wettability alteration by surfactants. The results of heterogeneous coreflood tests showed that more oil is bypassed in the tighter matrix by waterflood if the permeability is higher in the flooded layer and this bypassed oil is the target for the wettability-altering surfactant floods. Slow wettability-altering surfactant injection leads to imbibition into bypassed regions. When the oil-wet carbonate reservoirs have large unswept regions after waterflood, wettability-altering surfactants can significantly improve OR if enough time is given for imbibition.

Engineering↗
DOE OSTI2020

Abstract for Joint Work Statement 5 (AGMT-1005) between National Energy Technology Laboratory (NETL) and ExxonMobil Research and Engineering Company (EMRE) to Umbrella CRADA (AGMT-0922)

NETL and EMRE will focus on fundamental questions aimed at understanding the controlling factors on tight oil production flow paths and how those flow paths are impacted by the hydraulic fracturing fluids and processes. Key questions for the Parties to explore include the following: Are there geochemical reactions between hydrocarbon producing tight reservoir rocks and water from the hydraulic fracturing process? To what extent does this alteration impact oil production? By further characterizing the flow paths near the fracture-matrix interface, what is the relative impact of geochemical process compared to geomechanical changes on production? This research focuses on rock types found in the Permian Basin. The research drives along two main thrusts: 1) Inorganic geochemistry studies involving representative rock types, connate fluids (hydrocarbons and water), and injected fluids (fracturing water) will be conducted in order to bound the kinetics of key mineral reactions; 2) Computed tomography (CT) for characterization of flow paths as a function of geochemical and geomechanical processes associated with hydraulic fracture creation and reservoir production. The objective of this characterization is to ultimately develop new insights into the role geochemical and geomechanical effects play on production. The work will include studying mechanical damage near the rock-fracture interface and how it impacts flow properties.

02 PETROLEUM↗
DOE OSTI2022

Evidence of Nonlinear Seismic Effects in the Earth from Downhole Distributed Acoustic Sensors

Seismic velocities and elastic moduli of rocks are known to vary significantly with applied stress, which indicates that these materials exhibit nonlinear elasticity. Monochromatic waves in nonlinear elastic media are known to generate higher harmonics and combinational frequencies. Such effects have the potential to be used for broadening the frequency band of seismic sources, characterization of the subsurface, and safety monitoring of civil engineering infrastructure. However, knowledge on nonlinear seismic effects is still scarce, which impedes the development of their practical applications. To explore the potential of nonlinear seismology, we performed three experiments: two in the field and one in the laboratory. The first field experiment used two vibroseis sources generating signals with two different monochromatic frequencies. The second field experiment used a surface orbital vibrator with two eccentric motors working at different frequencies. In both experiments, the generated wavefield was recorded in a borehole using a fiber-optic distributed acoustic sensing cable. Both experiments showed combinational frequencies, harmonics, and other intermodulation products of the fundamental frequencies both on the surface and at depth. Laboratory experiments replicated the setup of the field test with vibroseis sources and showed similar nonlinear combinations of fundamental frequencies. Amplitudes of the nonlinear signals observed in the laboratory showed variation with the saturating fluid. These results confirm that nonlinear components of the wavefield propagate as body waves, are likely to generate within rock formations, and can be potentially used for reservoir fluid characterization.

58 GEOSCIENCES↗
DOE OSTI2021

Elucidation of Aromatic Catabolic Pathways in White-Rot Fungi

This project aims to investigate the hypothesis that white-rot fungi can simultaneously depolymerize lignin extracellularly and catabolize depolymerization products intracellularly as carbon and energy sources. Evaluating this hypothesis will provide deeper understanding of the role of white-rot fungi in facilitating carbon sequestration in Nature. Additionally, identifying the most promising fungal strains for lignin turnover and catabolism will catalyze future efforts in genetic tool development to enable metabolic engineering in white-rot fungi for lignin bioconversion to bioproducts. Lignin is the second most abundant plant-based biopolymer on Earth and represents up to 40% of the energy density of lignocellulosic biomass. Even though lignin is a massive natural carbon and energy reservoir, only a small group of basidiomycete fungi, namely white-rot fungi (WRF), have evolved the ability to efficiently depolymerize and mineralize lignin to CO2 and H2O. Considerable research efforts have been undertaken to understand how WRF depolymerize lignin but the biochemical reactions that convert lignin into CO2 have been largely neglected. In fact, it is unclear if WRF intracellularly catabolize lignin-derived aromatic compounds to utilize them as a carbon and energy source, or rather if lignin is depolymerized and mineralized extracellularly merely to facilitate access to cellulose and hemicellulose for use as a primary carbon source. To date, we have employed 13C-isotope labeling, systems biology approaches, and in vitro enzyme assays to definitively demonstrate that two WRF, Trametes versicolor and Gelatoporia (Ceriporiopsis) subvermispora, funnel carbon from lignin-derived aromatic compounds into central carbon metabolism via intracellular catabolic pathways [1]. Specifically, 13C-isotopic labeling approaches showed that these WRF utilize poplar-derived aromatic compounds (e.g. 4-hydroxybenzoic acid (4-HBA)) as a carbon source. In silico genome analysis led us to hypothesize a complete catabolic pathway for 4-HBA and identify multiple homologous sequences for enzymes with putative oxidative decarboxylase, hydroxylase, and ring-opening dioxygenase activities, which are among the main biochemical reactions acting on aromatic compounds. Spatial and differential proteomic and metabolomic analyses supported the proposed catabolic pathways and showed alternative catabolic steps in T. versicolor that were not present in G. subvermispora. Based on the in silico, proteomics, and transcriptomics results, we down-selected enzymes for further in vitro characterization, and we have assigned a function to six fungal enzymes (including oxidative decarboxylases, hydroxylases, and ring-opening dioxygenases). Interestingly, even though we selected homologous enzyme pairs from both WRF with similar -omics trends, in a few cases only one of the studied fungi showed activity for the proposed substrate. Based on all the observations from this study [1], we hypothesized that 4-HBA preferentially undergoes oxidative decarboxylation to hydroquinone and subsequent hydroxylation to 1,2,4-benzenetriol in G. subvermispora before ring cleavage, whereas 4-HBA would preferentially undergo hydroxylation to protocatechuate and further oxidative decarboxylation to 1,2,4-benzenetriol in T. versicolor. Examining additional decarboxylases and hydroxylases as well as enzymes from other protein families that can perform the same or similar oxidative reactions, such as cytochromes P450 with aromatic hydroxylation activity, will also be key for elucidating enzyme preferences for specific substrates. Overall, this work forms the foundation of a new research area based on lignin catabolism by WRF, which could be further exploited to convert the undervalued biopolymer lignin into value-added compounds.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Novel Proppant Logging Technique for Infill Drilling of Unconventional Shale Wells

Summary During the development of an unconventional play, wells are drilled and completed in batches, and depending on the development plans, current and expected energy market trends, as well as other developmental considerations, new wells are drilled and hydraulically fractured later near existing producing laterals. This creates challenges in terms of optimizing resource recovery and reducing interwell communication. A novel approach is proposed that utilizes systematic composite sampling and analysis of drilling mud returns to look for and quantitatively identify sand particles. The workflow involves cleaning, drying, and segregation of samples into sizes of interest to us (size distribution of pumped proppant in offset parent wells). These samples are imaged at a very high resolution and analyzed for grains using characteristic optical imaging properties to classify proppant sand particles using computer vision algorithms. Further analysis, such as elemental compositional analysis, is used to validate the results from the imaging workflow. We present a case study from the Permian Basin, where a new child well was used as a test case to prove this technology at the Hydraulic Fracturing Test Site (HFTS-2) in Delaware Basin. We introduce new proppant parameters that help identify sustained proppant zones vs. localized propped fractures. We have used additional diagnostics and data collected at the test site to validate observations from the proppant log and have successfully interpreted significantly propped vs. unpropped zones. A key finding from this test has been the significant proppant transport distances observed away from parent wells. Observable proppant was found at a lateral distance of approximately 425 m for one set of parent wells and more than 915 m for another set of parent wells. While a major limitation of this technique is the sampling rate, given adequate sampling, the proposed technology represents a systematic and one-of-a-kind interpretation of spatial proppant distribution while drilling infill wells. It provides us with unique opportunities to better understand the current state of the reservoir being targeted, including zones that are likely highly drained relative to others, and how the planned hydraulic fracturing of child wells can be improved.

Energy & Fuels↗
DOE OSTI2023

Rapid Simulation of Unconventional Reservoirs by Multidomain Multiresolution Modeling Based on the Diffusive Time of Flight

Summary The fast marching method (FMM)-based rapid flow simulation has been shown to accelerate simulation efficiency by orders of magnitude by transforming 3D simulation to equivalent 1D simulation using the concept of the “diffusive time of flight” (DTOF). However, the 1D transformation does not directly apply to multiwell problems. In this paper, we propose a novel DTOF-based multidomain multiresolution discretization scheme to accelerate multiwell simulation of unconventional reservoirs. Our method formulates multiwell simulation problems based on the DTOF which displays the pressure front propagation in unconventional reservoirs. The DTOF contours are used to partition the reservoir into local and shared domains. A local domain is where the flow is dominated by a single well, and the shared domain is where the fluid flow is influenced by multiple wells. The DTOF contours expand independently in local domains and interfere in the shared domain. After the partitioning, each domain is discretized using a multiresolution scheme whereby the original 3D fine mesh is preserved near the wells to account for detailed physics including gravity, and the rest of the domain is discretized into 1D mesh based on the DTOF contours to alleviate the simulation workload. The power and efficacy of our approach are demonstrated using synthetic and field-scale simulation models with different degrees of geologic and well-completion complexity. The simulation results, number of active cells, and computation time for the proposed discretization scheme are compared with the original high-fidelity 3D model for each case. The results show that the proposed method is suitable for multiwell simulation problems in unconventional reservoirs and can accelerate flow simulations by orders of magnitude with minimal loss of accuracy. The novelty of this work is the creation of DTOF-derived multiresolution discretization with local and shared domains to simplify and accelerate the calculation of subsurface flow problems, especially in unconventional reservoirs. Our workflow can be easily interfaced with commercial simulators, making it suitable for large-scale field applications.

Engineering↗
DOE OSTI2023

Kirigami Photopiezo Catalysts for Self-Sustainable Environment Remediation

Photo(electro)-piezo catalysis has emerged as one of the most effective strategies for sustainable environmental remediation. While various (nano)materials have been investigated for enhancing the intrinsic properties related to the interfacial band structure, increasing the efficiency by integration of materials with rational design for stress–strain applications has not yet been considered. Herein, we introduce kirigami strain engineering to photopiezo catalysts for enhancing efficiency by increasing the magnitude of applied strain and density of bends. Macroscale stretching motion is converted into localized bending by a pliable kirigami structure using similar or even lower input energy, which can be easily modulated by natural waves. The kirigami structure leads to a significant enhancement (~250%) in the degradation of dyes, and we discovered the significant contribution of the oxygen reduction pathway in the charge-transfer mechanism, which corresponds to the observed enhancement. In conclusion, the photopiezo catalytic effects of kirigami were further highlighted by the small water reservoir test, showing its feasibility in nature for self-sustainable environmental remediation that can be modulated using motions of winds, waves, and life vibrations.

14 SOLAR ENERGY↗
DOE OSTI2025

Fundamental Understanding of “Fresh” Lithium Nucleation and Growth in Sulfide-Based Anode-Free Solid-State Batteries: Effects of Substrate, Current Density, and Li + Supply

Understanding the electrochemical extraction and deposition of lithium (Li) from cathode is crucial for advancing anode-free solid-state batteries (AFSSBs). Herein, cryo-transmission electron microscopy (cryo-TEM) and electrochemical studies are employed to investigate how current collector surface properties, current densities, and cathode loadings influence the morphology of fresh electrochemically deposited Li and the electrochemical performance in sulfide-based AFSSBs. Cryo-TEM reveals that Cu current collectors induce irregular, dendritic Li deposits due to their lithiophobic nature and reactivity with Li 5.4 PS 4.4 Cl 1.6 (LPSC), while Ni and Au facilitate more uniform, planar-like Li growth. The morphology of the deposited Li also depends on current density: higher rates produce smaller, porous particles versus larger, denser deposits at lower rates. Importantly, for the first time, we discovered that low cathode loadings lead to poor cycling stability due to insufficient Li + supply for complete anode coverage, contrary to conventional solid-state batteries with preloaded Li metal anodes. This finding establishes a design principle where adequate cathode Li + reservoirs are essential for anode interface stability in AFSSBs. Overall, this work elucidates the interplayed effect of current collectors, current densities, and cathode loadings on Li morphology and cycle stability, offering fundamental insights into cathode-derived Li behavior and practical guidelines for optimizing AFSSBs performance through nucleation control and interface engineering.

25 ENERGY STORAGE↗
DOE OSTI2025

Exploring Water System Vulnerabilities in California's Central Valley Under the Late Renaissance Megadrought and Climate Change

Abstract California faces cycles of drought and flooding that are projected to intensify, but these extremes may impact water users across the state differently due to the region's natural hydroclimate variability and complex institutional framework governing water deliveries. To assess these risks, this study introduces a novel exploratory modeling framework informed by paleo and climate‐change based scenarios to better understand how impacts propagate through the Central Valley's complex water system. A stochastic weather generator, conditioned on tree‐ring data, produces a large ensemble of daily weather sequences conditioned on drought and flood conditions under the Late Renaissance Megadrought period (1550–1580 CE). Regional climate changes are applied to this weather data and drive hydrologic projections for the Sacramento, San Joaquin, and Tulare Basins. The resulting streamflow ensembles are used in an exploratory stress test using the California Food‐Energy‐Water System model, a highly resolved, daily model of water storage and conveyance throughout California's Central Valley. Results show that megadrought conditions lead to unprecedented reductions in inflows and storage at major California reservoirs. Both junior and senior water rights holders experience multi‐year periods of curtailed water deliveries and complete drawdowns of groundwater assets. When megadrought dynamics are combined with climate change, risks for unprecedented depletion of reservoir storage and sustained curtailment of water deliveries across multiple years increase. Asymmetries in risk emerge depending on water source, rights, and access to groundwater banks.

Gupta, Rohini S. [School of Civil and Environmenta↗
DOE OSTI2023

An organic electrochemical transistor for multi-modal sensing, memory and processing

By integrating sensing, memory and processing functionalities, biological nervous systems are energy and area efficient. Emulating such capabilities in artificial systems is, however, challenging and is limited by the device heterogeneity of sensing and processing cores. Here we report an organic electrochemical transistor capable of sensing, memory and processing. The device has a vertical traverse architecture and a crystalline–amorphous channel that can be selectively doped by ions to enable two reconfigurable modes: a volatile receptor and a non-volatile synapse. As a volatile receptor, the device is capable of multi-modal sensing and is responsive to stimuli such as ions and light. As a non-volatile synapse, it is capable of 10-bit analogue states, low switching stochasticity and good state retention. We also show that the homogeneous integration of the devices could provide functions such as conditioned reflexes and could be used for real-time cardiac disease diagnoses via reservoir computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Water-enhanced bifunctional metal-acid catalyst for C=C bond hydrogenation

Water-assisted proton shuttling can promote hydrogenation of polar functional groups, and it is generally believed that such an effect can be hardly applied to hydrogenation of C═C bonds due to the latter's weak interaction with water. Here, we report density functional theory calculations and metadynamics simulations, through which we show a dynamic bifunctional metal–acid site that can be transformed, when interacting with water, into an active configuration for unexpected water-enhanced proton shuttling to C═C bonds. In particular, we investigated B(OH)3 anchored to a Ni catalyst for hydrogenation of cyclohexene in an organic solvent, which showed in experiments an increased rate by 100 times when adding a small amount of water. Metadynamics simulations suggest that a B(OH)3–H2O cluster can form on Ni(111), which promotes the proton transfer in the first hydrogenation step, while the second hydrogenation is still driven by metal-mediated direct H-transfer. The recovery process of B(OH)3–H2O also involves a proton shuttling step. We find that the boric species on the surface serves as an electron reservoir and carries the negative charge to balance the positive charge in the proton transfer steps. This work thus provides fundamental insights into this dynamic transformation process of the metal–acid interface, which can in principle be applied to many other bifunctional systems for hydrogenating non-polar unsaturated groups by engineering the interfacial charge separation.

Sun, Shoutian↗
DOE OSTI2022

Findings on Subtask 3.1 - Bakken Rich Gas Enhanced Oil Recovery Project

Total in-place oil for the Bakken petroleum system (BPS) (which includes the Bakken and Three Forks Formations) has been estimated to be 600 billion barrels (bbl). However, BPS wells have decline rates as high as 85% over the first 3 years of their lives, and primary recovery factors typically range from 3% to 10% of original oil in place. Given the low initial recovery rates, even small incremental productivity improvements could dramatically increase technically recoverable oil in the BPS. One potential solution is enhanced oil recovery (EOR) using gas injection, such as carbon dioxide (CO2) or hydrocarbon (HC) gases. While commonly used in conventional reservoirs, CO2 EOR in unconventional tight oil reservoirs has been limited to pilot tests. EOR using rich gas (mixture of methane, ethane, and propane) has also been employed in numerous pilots in several unconventional plays and has recently been successfully applied in the Eagle Ford play. If successful, large-scale gas-based EOR in the BPS could dramatically increase oil productivity and recovery factors and extend the life of the play for decades. While CO2 may be a technically suitable working fluid for EOR in the BPS, supplies are limited and costs for using CO2 in EOR pilots are prohibitively high. Meanwhile, produced gas flaring has presented challenges for BPS operators in North Dakota. Analysis conducted by the North Dakota Pipeline Authority indicates that the current gas-gathering infrastructure in North Dakota is insufficient to accommodate all of the associated gas that is produced from the BPS. The geographically isolated location of North Dakota relative to large natural gas markets, combined with suppressed natural gas prices, has made it economically challenging for industry to invest capital in expanding gas-gathering infrastructure in the state. These circumstances led to a research program conducted by the Energy & Environmental Research Center (EERC) in partnership with Liberty Resources Management Company LLC (LR) to examine the potential to use rich gas injection for EOR and mitigate flaring. A rich gas EOR pilot test was designed and executed by LR at its Stomping Horse development area in Williams County, North Dakota. From July 2018 through May 2019, a total of 160 million standard cubic feet (MMscf) of rich produced gas was injected into the BPS using five different wells in a sequential injection strategy. LR’s Leon–Gohrick drill spacing unit (DSU) was used as the test site. Regulatory oversight was provided by the North Dakota Industrial Commission (NDIC). Technical support was provided by the EERC through a series of laboratory, modeling, and field-based activities, and additional post-pilot research activities incorporated learnings from the test, developed new laboratory data, improved fracture modeling methods, and developed machine learning and big data analytics. The results from the Stomping Horse rich gas EOR pilot activities indicate that developing an effective, economical EOR approach for the BPS will require more field tests. Another key lesson learned from the Stomping Horse tests is that detailed pre- and posttest data on reservoir conditions and fluids production are essential. Robust reservoir characterization provides information that is crucial to creating realistic geomodels and conducting valid dynamic simulations of potential EOR scenarios. A detailed understanding of the completions and production history of offset wells is also necessary for valid test result interpretations. This knowledge is essential to designing the operational parameters of injectivity tests and interpreting the results. A conformance control strategy is also essential to success. Laboratory-based examinations of rich gas interactions with reservoir fluids and rocks were conducted, with an emphasis on determining the ability to mobilize oil in the tight reservoir rocks and shales of the BPS. Injection fluid composition was shown to have a positive impact on reducing reservoir oil minimum miscibility pressure (MMP), reducing interfacial tension (IFT), and altering wettability. IFT and contact angle measurements demonstrated that wettability can be altered in the presence of rich gas, suggesting the potential to improve oil recovery. Iterative modeling of surface infrastructure and reservoir performance using data generated by the various project activities was conducted. A geologic model of the Stomping Horse area was built; history-matched oil, gas, and water production was used in simulations of various EOR scenarios. Early programmatic modeling results were used to support LR’s design and operation of the EOR pilot and to provide insight regarding optimization of future commercial-scale BPS EOR design and operations. Post-pilot modeling focused on alternative methods of understanding complex fracture networks and accelerating simulation time. These led to improved simulation run times and provide excellent history-matching results. Several of these iterative models were used as the bases for developing algorithms into machine learning and big data analytics. History matching in reservoir simulation is time-consuming and computer processing-intensive. Machine learning algorithms were created, and an automated history-matching tool was developed. A large set of synthetic reservoir simulations were created to generate well responses (oil, gas, and water production, well bottomhole pressure [BHP], and tracer or propane breakthrough) for a set of EOR operating parameters that included offset well status (open or closed), injectate (rich gas or propane), injection rate, and injection well BHP. A user interface was developed to provide real-time visualization. Machine learning-based models were developed to provide rapid forecasting of well performance given a set of user-defined EOR operating parameters. These predictive models allow the user to modify the offset well status, injection rate, and injection well BHP and rapidly forecast future production performance. The combination of real-time visualization tools with real-time forecasting tools provides a framework for real-time control—operational changes that the EOR site operator can enact (e.g., changing gas injection rates) to affect the observed performance and potentially improve the EOR outcome. There is great reason to be optimistic about the future of EOR in the Bakken. The results of the laboratory studies suggest significant potential for high rates of oil mobilization using produced field gas injection under the right conditions. The results of the lab studies, combined with rigorous statistical analysis of well production data and associated modeling efforts, confirm the notion that fluid mobility within the reservoir is controlled by fractures. As more knowledge is gained about the nature and distribution of fracture networks in the Bakken, the industry will be in a better position to predict and, ultimately, influence fluid mobility. New field tests are necessary to develop a more complete understanding of those conditions. Thoughtful and creatively engineered field tests within a well-characterized geologic setting will yield the fundamental knowledge needed to take Bakken oil production to the next level. This subtask was cofunded through the EERC–U.S. Department of Energy Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FE0024233. Nonfederal funding was provided by the North Dakota Industrial Commission’s Oil and Gas Research Program and Computer Modelling Group.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2023

Optofluidic memory and self-induced nonlinear optical phase change for reservoir computing in silicon photonics

Nanophotonics allows to employ light-matter interaction to induce nonlinear optical effects and realize non-conventional memory and computation capabilities, however to date, light-liquid interaction was not considered as a potential mechanism to achieve computation on a nanoscale. Here, we experimentally demonstrate self-induced phase change effect which relies on the coupling between geometric changes of thin liquid film to optical properties of photonic waveguide modes, and then employ it for neuromorphic computing. In our optofluidic silicon photonics system we utilize thermocapillary-based deformation of thin liquid film capable to induce nonlinear effect which is more than one order of magnitude higher compared to the more traditional heat-based thermo-optical effect, and allowing operation as a nonlinear actuator and memory element, both residing at the same compact spatial region. The resulting dynamics allows to implement Reservoir Computing at spatial region which is approximately five orders of magnitude smaller compared to state-of-the-art experimental liquid-based systems.

42 ENGINEERING↗
DOE OSTI2022

Impact of Polymer Rheology on Gel Treatment Performance of Horizontal Wells with Severe Channeling

Summary Gel treatment has been a cost-effective method to control the conformance of a reservoir with severe heterogeneity problems. The water channels in such reservoirs can be classified as open fractures or high permeability porous media with pore-throat network. Many simulation studies have been conducted to discuss gel treatment performance for conformance control. However, nobody considered the polymer rheology difference in open fractures and porous media in simulation. Previous simulation studies also ignored the residual resistance factor as a function of rock permeability rather than a constant parameter. In this study, a conceptual simulation model was established to simulate the linear flow system for the reservoir with horizontal wells considering the two factors mentioned above. The results demonstrate that the gel treatment always provides the better placement results in the open fracture type channel than pore-throat network type channel. Moreover, it is very necessary to consider residual resistance factor as a function of permeability, which is based on the experimental results and can provide much greater plugging efficiency in the higher permeable channels than constant residual resistance factor. Sensitivity analysis studies and multifactor analysis indicate that increasing oil viscosity and permeability ratio has a strong positive influence on conformance control results, which indicate in-situ gel treatment can be better applied in heavy or viscous oil reservoirs with fracture-like channels. Besides, the results also indicate that in reservoirs with severe channeling problem where channel velocity was high, the differences of gelant placement and profile improvement in models with two different types of channels could be enlarged greatly.

Engineering↗
DOE OSTI2025

Predicting Dynamic-to-Static Correction Factor from Petrophysical Data and Chemostratigraphy using Unsupervised Machine Learning

Estimating static mechanical properties of stratigraphic layers is critical for optimizing subsurface engineering applications. To estimate dynamic-to-static correction factor F ds (static-to-dynamic Young’s modulus ratio) across the Caney shale interval in Oklahoma, USA, we integrated triaxial test measurements and petrophysical data, including well logs and X-ray fluorescence (XRF) using unsupervised machine learning (ML). We used a novel workflow that includes principal component analysis (PCA) to reduce data set dimensionality of well logs and XRF data sets—both separately and combined—creating three scenarios, and later applied inverse distance weighting (IDW) to derive F ds profiles for these scenarios. Furthermore, we applied K-means clustering on each scenario to predict depositional facies, and built a stiffness zonation profile through chemostratigraphic analysis of the terrigenous elements to validate the predicted F ds . The predicted F ds profile from each scenario using the PCA-IDW method was compared with the constant F ds approach from our previous study by calculating the root mean square error (RMSE). The combined data sets scenario yielded the lowest RMSE value of 0.113, while the RMSE values for the well logs and XRF scenarios were 0.131 and 0.129, respectively. In addition, the predicted F ds from the XRF scenario well-matched the stiffness zonation from the chemostratigraphic analysis that was built using the optimized K-means clustering of nine clusters for that scenario. These methods and findings offer a valuable tool for refining lithological classification and improving the F ds profile, potentially enhancing drilling and stimulation strategies for subsurface energy engineering applications.

clastic rock↗
DOE OSTI2023

Subsurface Hydrogen Assessment, Storage, and Technology Acceleration (SHASTA) - Hydrogen Estimator for Logistical Planning (HELP) User’s Manual

This user’s manual describes version 1.0 of the SHASTA-HELP (Subsurface Hydrogen Assessment, Storage, and Technology Acceleration (SHASTA) - Hydrogen Estimator for Logistical Planning (HELP)) tool and provides instructions for use. The purpose of the SHASTA-HELP tool is to integrate the suite of tools developed by the SHASTA research team in a web-based framework for ease of access and more advanced, integrated analysis. This tool contains functionality for estimating the storage potential of pure and blended natural gas-hydrogen mixtures in various subsurface formations and is intended to be used for pre-characterization or site screening purposes. Detailed storage analysis should be conducted by full reservoir simulation models.

08 HYDROGEN↗