Energy & Fuels最新文献

Wax deposition in crude oil extraction and transportation endangers petroleum industry safety, raises operational costs, and is an urgent key challenge. Exploring collaborative wax prevention mechanisms is of great significance for innovative wax prevention technologies. In our study, molecular dynamics simulations were applied to clarify the combined effect of ethylene-vinyl acetate copolymer (EVA) and polyvinylpyrrolidone (PVP) or PVP derivatives in the process of wax crystal growth. The simulation results demonstrate that the vinyl acetate (VA) side units enhance the adsorption affinity of pyrrolidone-based polymers around the eutectic surface through polarity effects. On surfaces with low wax-EVA eutectic degrees, pyrrolidone-based polymers adsorbed around VA side chains exert a repulsive effect on solute wax molecules via their polar groups, thereby increasing the induction time of wax crystal growth. On high eutectic surfaces, pyrrolidone-based polymers adsorb onto eutectic surfaces via electrostatic interactions with adjacent VA side chains, forming steric hindrances. Here, hydrophobically modified PVP derivatives (PVP-C and PVP-A) compete for eutectic adsorption sites. This disrupts the orderly growth of wax crystals and either dissipates newly formed wax adsorption layers or prevents their formation entirely. Exploring the potential of collaborative wax prevention facilitates breakthroughs in traditional wax inhibitor performance bottlenecks and enables the development of efficient and eco-friendly composite wax inhibitor systems.

To address the complex production characteristics of unconventional oil reservoirs, we propose TimeSenseNet, a prediction model designed to improve both the accuracy and the robustness of shale oil production forecasting. The model innovatively integrates Time2Vec time encoding, Convolutional Neural Networks (CNN), Bidirectional Long Short-Term Memory networks (BiLSTM), and a Transformer-based attention mechanism. This architecture automatically captures complex nonlinear patterns in time-series data and simplifies traditional preprocessing procedures, while explicitly incorporating physical reservoir parameters including lithology, measured depth (MD), true vertical depth (TVD), porosity, permeability, reservoir temperature, and pressure, to guide feature extraction and temporal modeling. Monthly production data from 18 wells in the Bakken Formation were used, with 80% for training and 20% for testing, and 5 wells in the Eagle Ford Formation, including both horizontal and vertical wells, were reserved for independent validation. Results on the Eagle Ford Formation validation set show that TimeSenseNet achieves an average R² of 0.81 across all wells, with peak single-well performance reaching 0.91. It also attains the lowest average mean absolute error (MAE) (205.70), root-mean-square error (RMSE) (434.86), normalized root mean squared error (NRMSE) (0.08), and weighted absolute percentage error (WAPE) (0.21), demonstrating strong generalization to the unseen reservoirs. This study establishes a closed-loop process of data governance, model optimization, and field validation, showing that TimeSenseNet provides accurate short-term production forecasts and supports long-term rolling predictions with reduced error accumulation. The separation of static reservoir features and dynamic production data allows efficient real-time updates when new data become available. These capabilities demonstrate TimeSenseNet’s potential for data-driven decision-making and more efficient shale oil production in unconventional reservoirs.

Characterizing pore–throat structures at the micron scale is essential for evaluating productivity in deepwater tight sandstone reservoirs, yet conventional well-log analysis lacks the resolution required to capture these features. This study proposes a scalable machine-learning-based workflow that integrates digital rock physics (DRP) measurements with continuous well-log data to enable the full-wellbore characterization of pore–throat properties. A Stacking ensemble model combining XGBoost, Gradient Boosting, Random Forest, Extra Trees, and CatBoost is developed to establish a robust cross-scale mapping from sparse DRP samples to logging responses under small-sample conditions. Using 423 DRP samples from 65 wells in the eastern South China Sea, the model achieves an average R² of 0.90 in 10-fold cross-validation, substantially outperforming single-model approaches. Continuous 0.1 m resolution profiles of median pore–throat radius (R₅₀) and connected pore ratio (CPR) show strong and physically consistent correspondence with independent production test data, with high R₅₀ and CPR intervals systematically associated with higher oil rates. The results demonstrate that the proposed workflow provides a practical and engineering-relevant solution for continuous micron-scale reservoir characterization, supporting improved sweet-spot identification and development decision-making in deepwater tight sandstone reservoirs.

The development of biomass-derived fuels presents a promising solution for mitigating the severe carbon emissions associated with fossil fuels. A key strategy involves the direct refining of aqueous-phase bioethanol into higher alcohols, which serves as key precursors for diesel blendstocks and biojet fuel. Herein, to enable the direct upgrading of aqueous ethanol, we developed carbon-encapsulated Ni nanocatalysts (Ni@C) with water resistance by pyrolyzing organic precursors under acid–base regulation. The catalytic coupling yields 46.5 C-mol % of higher alcohols, of which C₄–C₇ and C₈–C₁₆ alcohols constitutes 56.9% and 35.2% in product selectivity, respectively. Excellent miscibility with diesel is exhibited by C₄–C₇ alcohols across a wide range of blending ratios. Furthermore, hydrodeoxygenation of C₈–C₁₆ alcohols provides a direct route to biojet fuel. Results from experiment and characterization demonstrate that acid–base regulation effectively tunes the local electronic structure and carbon defects on the Ni@C nanocatalyst surface. The proposed approach allows for precise modulation of the dehydrogenation, aldol condensation, and hydrogenation steps in the Guerbet reaction pathway, which suppress carbon chain scission and enhance the yield of higher alcohols. Overall, this research offers a novel and feasible strategy to the sustainable synthesis of higher alcohols from bioethanol, producing products directly applicable as blending components and biojet fuel precursors.

Sustainable aviation fuels (SAFs) are receiving increasingly high attention by science, industry, and politics as they are considered an effective tool to reduce the impact of aviation on the climate system and air quality. While numerous experimental studies on the effects of SAFs were performed, these are often limited to specific test scenarios or engine measurements. This work combines predictions based on the DLR SimFuel platform with field data from the first campaign to investigate a 34% hydrotreated esters and fatty acids (HEFA) SAF blend under real-world operating conditions during regular passenger flights. For this purpose, an Airbus A320-251N flying between Copenhagen and Arlanda was fueled with conventional Jet A-1 for 30 flights during 1 week and with a 34% HEFA SAF blend for 85 flights in 2 weeks. The corresponding exhaust gas plumes during taxiing were analyzed by the DLR mobile lab. Equipped with state-of-the-art instruments, this analysis contains total and non-volatile particle number concentrations and size distribution, gas analytics (CO₂ and NO_x), and weather parameters. The results confirm the beneficial effects of SAF usage toward the air quality by reducing total particle emissions by about 10% and non-volatile particle emissions by about 40%. Also, this data set obtained under real-world conditions provides a valuable basis for model development and validation.

Unconventional shale gas is vital for clean energy and energy security. However, its ultralow permeability leads to low primary recovery. This study investigates CO₂-enhanced shale gas recovery (ESGR) in the Yanchang shale reservoir by using a CMG-GEM compositional simulator with a dual porosity/permeability model, evaluating well placements and both continuous and huff-and-puff injection methods. Findings show that continuous CO₂ injection increases CH₄ recovery by 7.59% over no injection. For huff-and-puff, a shorter 1 year injection period yielded the highest CH₄ recovery; extending injection to 2 and 3 years caused declines of 1.93 and 3.89%, respectively. Conversely, using five injection cycles resulted in the highest cumulative CH₄ recovery. Starting CO₂ injection later in the production lifecycle also optimized recovery, with a 1.15% increase observed after 10 years of initial CH₄ production, as it utilizes more favorable reservoir pressure conditions. Moreover, for CO₂ storage, the reservoir exhibited 99.565% efficiency during continuous injection. In huff-and-puff, longer injection durations improved storage, with a 3 year period achieving 98.35% efficiency. Similarly, five injection cycles yielded the highest storage efficiency, at 99.12%. Delaying the injection start time also significantly enhanced CO₂ storage, with efficiency improving from 96.38% after 1 year to 98.35% after 10 years, leveraging improved pressure dynamics over time. In addition, a sensitivity analysis confirmed that key reservoir parameters, such as matrix porosity, permeability, and pressure, significantly influence both gas recovery and storage capacity. Critical hydraulic fracture parameters, including half-length, spacing, conductivity, and bottom-hole pressure, are essential for optimizing gas flow and CO₂ injection efficiency. This study applies to tight shale gas formations worldwide, offering insights into optimizing hydraulic design and injection strategies to enhance shale gas production and CO₂ sequestration, supporting global carbon management and climate change mitigation.

The construction of a high-quality artificial solid electrolyte interphase (SEI) on lithium metal anodes is of great importance to regulate preferred crystal orientation, thereby realizing interfacial stability and dendrite suppression. Herein, we develop a novel low-temperature gas–liquid composite source (SF₆ + silane coupling agent) plasma method for synthesis of dense inorganic–organic hybrid SEI on lithium metal anodes. The designed hybrid SEI layer consists of inorganic LiF and Li₃N and organic lithium compounds (e.g., Li–O–Si). In-situ and ex-situ XRD results demonstrate that the modified hybrid SEI can induce preferential growth of the Li(110) crystal plane, thereby promoting lateral and dendrite-free morphology, in contrast to the (200)-oriented vertical dendrites of bare lithium. The preferential growth of the Li(110) plane is due to the synergistic effect of inorganic components (LiF and Li₃N) and lithium compounds in SEI, which can enhance interfacial structural stability and inhibit dendrite propagation. Consequently, symmetric cells with modified Li metal anodes (P-SEI@Li) exhibit exceptional stability over 900 h at 1 mA cm^–2/1 mAh cm^–2 with a low overpotential of ∼11 mV. Full cells with LiNi_0.9Co_0.05Mn_0.05O₂ cathodes show improved capacity retention. This work demonstrates the effectiveness of plasma-engineered SEI in regulating crystal plane deposition and provides new insights for developing high-performance lithium metal batteries.

Understanding the influence of coal composition on pore structure during thermal evolution is fundamental for elucidating the patterns of pore development and is essential for evaluating deep coalbed methane resources as well as identifying favorable target zones. This study analyzed deep coal samples of varying thermal maturity from the main strata of the Ordos Basin using basic property analysis, mercury intrusion porosimetry (MIP), low-temperature N₂ adsorption (LT-N₂A), and low-pressure CO₂ adsorption (LP-CO₂A) to comprehensively quantify the multiscale pore structures. Additionally, the fractal characteristics of the pore structure were investigated. The results indicate that, as thermal maturity increases, vitrinite content decreases while inertinite becomes enriched, fixed carbon initially declines then rises, volatile matter steadily decreases, and ash content relatively increases. Pore structure analysis reveals a negative correlation between the content of active components (vitrinite, volatile matter) and total pore volume, while inert components (inertinite, fixed carbon) correlate positively. Based on this component-pore relationship, a Pore Development Index (α) and a total pore volume fitting model were developed as quantitative indicators for reservoir evaluation. Fractal analysis reveals distinct fractal characteristics across all pore scales. Pore parameters significantly correlate with fractal dimension: the positive correlation between pore volume/specific surface area and fractal dimension in micropores and mesopores; the negative correlation for macropore pore volume. Specifically, the macropore fractal dimension decreases after the maximum vitrinite reflectance (R_o, max) of 1.9%, whereas the fractal dimensions of micropores and mesopores continuously increase. Furthermore, the content of macerals and volatile matter exerts a controlling influence on the fractal dimensions of micropores and mesopores. This study elucidates the multiscale evolution and compositional control of deep coal pore systems, providing an index and model to support reservoir quality assessment and sweet-spot prediction in deep coalbed methane exploration.

Waxy crude oil plays a vital role in global energy supply. However, wax deposition in pipelines remains a key challenge that restricts its safe and efficient development, including production and transportation. This paper provides a comprehensive review of research progress on pipeline wax deposition in waxy crude oil. First, the mechanisms of wax deposition are analyzed, with particular attention to the formation mechanisms of the wax-gel layer. Second, the major factors influencing wax deposition, including crude oil properties and operating conditions, are summarized and their effects are discussed. Third, commonly used wax prevention and removal technologies in oilfields are reviewed, their advantages and limitations are compared, and special emphasis is placed on several green and sustainable techniques. Finally, based on these analyses, the limitations of current studies are identified and future research directions are proposed: (1) investigating the emerging and potential mechanisms of wax deposition, the synergistic effects among multiple wax formation processes and multicomponent coupled deposition behaviors; (2) exploring the interactive effects among various influencing factors; (3) developing hybrid wax control strategies that integrate multiple inhibition techniques and advancing natural, eco-friendly, and highly efficient inhibition methods; (4) assessing the potential industrial utilization and recycling pathways of wax deposits; and (5) incorporating artificial intelligence and digital technologies to explore their potential in wax deposition analysis and prediction. This review provides theoretical insights and technical references for the safe and efficient development of waxy crude oil.

This study fabricated flexible phase change composites (PCCs) by integrating paraffin wax (PW) as the phase change material, ethylene-propylene-diene monomer (EPDM) as the matrix, and expanded graphite (EG) as the adsorption filler. The dual encapsulation networks-comprising EG porous adsorption and EPDM cross-linking structure were engineered to optimize thermal and mechanical performance. The resulting EPDM/PW@EG-60%, featuring a C–S_x–C cross-linking network, exhibits excellent low-temperature flexibility, good impact resistance, high latent heat of 140.1 J/g, and satisfactory cycling stability with only 2.4% enthalpy attenuation after 100 thermal cycles. Additionally, it shows a low leakage rate of 1.2% even under 500 g load at 60 °C for 10 h. In contrast, EPDM/PW@EG-60%-DCP with a C–C cross-linking network showed correspondingly lower performance: a lower latent heat of 130.8 J/g and reduced cycling stability, with an enthalpy loss of 5.3% after 100 thermal cycles. To our knowledge, this work represents the first report on the influence of EPDM cross-linking network structure on the mechanical strength, latent heat capacity, and thermal cycling stability of PCCs, elaborating the underlying mechanisms. This work provides critical theoretical insights and scientific guidelines for designing flexible PCCs with high latent heat and low leakage rate.