Abstract

Hot dry rock (HDR) is a deep geothermal resource with great potential and is clean and environmentally friendly. During HDR exploitation, it is necessary to form a penetrating heat transfer channel. Therefore, heat transfer in thermal reservoir has an important influence on the heat extraction of HDR. The rough single fracture is obtained by means of Brazilian splitting test, and the point-cloud data on the rough fracture is acquired by 3D laser scanner. The 2D rough single fracture convective heat transfer model is established by numerical simulation to analyze the convective heat transfer characteristics and carry out the Morris global sensitivity analysis. The results show that the outlet temperature and average heat transfer coefficient increase with the roughness increasing, and the local heat transfer coefficient is strongly correlated with the undulating and fluctuating degree. The increase of the average and local heat transfer coefficient is more obvious when the fracture aperture is larger (>40μm) or initial flow rate is higher (>50mm/s). This study can provide scientific basis for engineering design of enhanced geothermal systems.

Abstract

Newly proven tight reservoirs show increasingly poor physical properties, insufficient natural energy, and small pore throats. As a result, waterflooding often faces the problem of “difficult injection and poor production”, making the switch of displacement media urgent for oilfield sites. This study couples the Navier-Stokes (N-S) equations and level-set equations to build a mathematical model of microscale two-phase flow. Using this model, it simulates the entire process of water, N₂ and CO₂ flooding and reveals the mechanism behind differences in pore-throat utilization characteristics of different injected media. Results indicate: Water has low injectivity and cannot enter small-medium pore throats with high seepage resistance, with its displacement front advancing slowest and microscale oil displacement efficiency lowest. N₂ flooding has higher injectivity but suffers severe gas channeling, leading to low efficiency. CO₂ flooding eases gas channeling, and crude oil in small-medium pores can be displaced via dissolution, diffusion, viscosity reduction, and interfacial tension lowering, achieving the highest efficiency. Based on the microscale pore-throat simulation via the level set method, this study provides theoretical guidance for developing tight oil reservoirs by switching displacement media.

Abstract

This study focuses on the significance of energy communities and their policy development, aiming to explore the formation process of European energy community policies and their application in the Netherlands. As a key mechanism for advancing energy transition and promoting public participation, the design of energy community policies is not only tied to the localized development of renewable energy but also spans multiple dimensions, including equity, governance efficiency, and social resilience. Employing a combined approach of case analysis and text mining, this research systematically examines drivers and impacts of EU policy formation, thereby providing practical insights for policy adaptation and contextual design in other countries.

Abstract

High penetration of variable renewable energy (VRE) often leads to curtailment in wind-dominant grids with limited storage or transmission flexibility, lowering effective capacity factors, reducing low-carbon generation and weakening project economics. We develop a Stage-1 MATLAB/Simulink proof-of-concept that couples a 0.2 MW wind-turbine equivalent with dispatchable ASIC Bitcoin miners sized to utilise 10-90% of otherwise curtailed power through export-cap limits. Turbine drivetrain/electrical losses are modelled at 9% (η_WECS = 0.91); downstream rectifier/PSU/cabling efficiency is η_chain = 0.91 (η_overall ≈ 0.82). A synthetic baseline capacity factor (CF) of 0.20 is used with results reported as ΔCF above baseline or capacity factor uplift from a representative 10% curtailment case observed in multiple markets (e.g. ERCOT, CAISO, UK 0and Ireland). Counterfactual scenarios indicate ΔCF ≈ +0.01 (base case 10% scenario) to ΔCF ≈ +0.09 (extreme 90%). Using a transparent monetisation rate derived from £4/day per 100 TH/s miner (≈£55/MWh absorbed), the 0.2 MW case yields up to £70,000 annually under high utilisation conditions. Our Stage-1 findings demonstrate that programmable digital demand can convert curtailed wind into cashflow and CF gains, motivating fuller Stage-2/3 validation.

Abstract

Utilizing logging dynamic monitoring data for identifying drilling operation conditions is crucial for precise analysis of drilling efficiency and operational enhancement. However, the time series distribution of samples across various drilling conditions exhibits notable non-uniformity, leading to a substantial imbalance in the category labels of drilling conditions. This imbalance issue significantly reduces the accuracy of recognition models due to a bias towards the majority class.In this study, drilling history data from 98 wells were examined to create 14 distinct sets of drilling condition samples. To address the sample imbalance problem, the weights of the samples were determined using the K-means clustering algorithm based on cluster proportions and sample distribution specificity within each cluster. These weight factors were integrated into the loss function to develop a drilling condition recognition model known as K-means Long Short-Term Memory (LSTM), enabling precise recognition of the 14 drilling conditions.Experimental findings demonstrate that the K-means-LSTM model outperforms the LSTM model, with an increase in recognition accuracy of 3.561%, recall by 4.554%, and F1-score by 3.667%. Particularly noteworthy is the substantial improvement in recognition accuracy for break out a single joint and make up a single joint sparse conditions, with increases of 39% and 42%, respectively. Compared to conventional deep learning approaches, the proposed method exhibits remarkable accuracy enhancements and suitability for recognizing sparse drilling conditions, thereby offering robust technical support for fine-tuning drilling operations and supervision.

Abstract

Solid polymer water electrolysis is a promising hydrogen production technology for renewable energy utilization with the essential prerequisite of durability. Durability is inherently a system-level attribute, affected by the intrinsic properties of components as well as operational factors. Yet literatures on these are highly fragmented and often confined to single-parameter studies. We propose a structured taxonomy of operational factors comprising three classes: External environmental, Side-reaction, and Mechanical factors. Representative secondary factors including impurities, redox cycles, non-uniformities, etc. are reviewed. Furthermore, key couplings factors including Fe contamination synergizing with peroxide to trigger Fenton action, and alkaline conditions combined with local thermal hotspots accelerating Hofmann elimination are illustrated. Additional coupling factors among local pH, components volume change and Halogen corrosion are also delineated. We propose that systematically suppressing the influence of these operational factors can unlock operation at elevated temperature and current density, achieving a dual objective of enhanced performance and extended durability. Herein, we provide guidance for the operation and maintenance of PEM/AEM systems and for the development of electrolyzer components for renewable-powered hydrogen production.

Abstract

Geothermal energy, as an abundant renewable resource, holds significant potential to serve as a reliable baseload power source in the future through advanced power generation technologies. The Organic Rankine Cycle (ORC) and ORC-based integrated systems, being relatively mature, have been widely adopted in geothermal power generation applications. In this study, a novel cycle (IPEPC) integrating combined heat and power generation is proposed, featuring an increasing-pressure endothermic process (IPEP) within the downhole heat exchanger (DHE) and utilizing refrigerant as the working fluid. The net power output and heat supply rate of the IPEPC system were evaluated by varying key operational parameters-namely injection pressure and mass flow rate-to identify optimal operating conditions. Compared with the conventional ORC, the IPEPC design achieves a more favorable thermal match between the working fluid and the geofluid temperature profile in the DHE. Thermodynamic performance of the IPEPC was systematically compared with that of the ORC across a geofluid temperature range of 100°C to 180°C. Results indicate that the IPEPC yields higher net power output than the ORC at lower heat source temperatures, particularly below 160°C.

Abstract

Ni-Co/Al2O3 bimetallic catalysts efficiently treat sewage sludge and produce valuable hydrogen-rich syngas through the pyrolysis-catalytic steam reforming. This study investigates a novel redox preparation method to enhance interactions at the nickel-cobalt active site. For the experimental work, sewage sludge pyrolysis volatiles were steam-reformed at 650 °C over bare alumina and catalysts prepared by redox, precipitation, and impregnation methods. The preparation conditions for all catalysts were identical. The resulting gas and liquid products were then analyzed using GC and GC×GC-TOFMS. The catalyst prepared using the redox method performed best. After reforming with this catalyst, the experimental results show that 9.09 mmol/g of gas and 4.24 mmol/g of H2 were produced. The main liquid product of this catalyst is chain hydrocarbons, which is more than 62.6%.

Abstract

Gas wells in long-term production commonly encounter liquid accumulation, among which insufficient liquid-carrying capacity is one of the key factors restricting productivity enhancement and stable operation. As a novel drainage tool with a simple structure and convenient operation, the spiral flow device can significantly enhance liquid removal performance and effectively mitigate liquid buildup when a stable spiral flow regime is sustained within the wellbore. However, most conventional liquid-carrying models for gas wells are established on the assumptions of droplet entrainment or annular liquid film flow. These models fail to adequately capture the force characteristics and boundary transition mechanisms of liquid films under spiral flow conditions, leading to considerable deviations in predicting the liquid-carrying boundary and making it difficult to accurately determine the applicability and failure limits of spiral flow tools. To address this issue, this study develops a spiral flow liquid film carrying-boundary model by analyzing the dynamic behavior of liquid films and incorporating the mechanisms of shear instability and film fallback. Laboratory visualization experiments were conducted to compare the predictive performance of the proposed model with conventional critical liquid-carrying models, including those of Turner, Li Min, and Wang. The results demonstrate that the proposed model achieves an average prediction error of only 7.9%, which is markedly superior to conventional models. Further sensitivity analysis reveals that smaller pipe diameters, lower spiral angles, narrower liquid film thicknesses, and higher pressure conditions are more favorable for maintaining stable spiral flow. This study not only deepens the theoretical understanding of liquid-carrying mechanisms in gas wells but also provides theoretical and technical guidance for the design optimization and field application of spiral flow tools.

Abstract

The production adjustment of ESP layered production wells in offshore oilfields relies on manual measurement and adjustment. The intricate interplay of layered completion systems, lifting equipment, and formation energy results in nonlinear production allocation. This complexity impedes multi-layer collaborative control, extends operation time, and presents challenges in maintaining optimal ESP efficiency.Therefore, this study takes maximizing ESP operating efficiency and minimizing production allocation errors as the cooperative decision objectives. It utilizes position PID to explore the target distribution space, and based on the Bayesian probabilistic information inference algorithm(PID-BO), introduces an uncertainty filtering strategy to establish a multi-parameter cooperative adjusting method for ICV openings and ESP operating frequency. Taking offshore layered production well A-01 as the experimental object, PID-BO can quickly narrow the search space based on limited historical production data, identifying the optimal joint adjustment strategy of ESP frequency and ICV openings within only 20 exploration rounds. The maximum production allocation error of the three production layers does not exceed 5.31%, with the pump efficiency of ESP reaching 63.15%. The comprehensive index of the strategy is significantly higher than that of traditional methods. Verification results demonstrate that this method ensures fine production and high-efficiency operation of ESP layered production wells, effectively improves the level of fine oilfield development, reduces energy consumption losses in oil and gas exploitation, and holds important practical significance for the efficient and energy-saving development in the field of energy exploitation.