The characteristics of low porosity, low permeability, and small pore radius of the shale oil reservoir in the Lucaogou Formation make it difficult to develop and result in low production. CO2 huff and n-puff can effectively improve the recovery rate of shale oil in the Lucaogou Formation. In this study, high-pressure mercury injection technology was used to characterize the pore distribution of the core samples. Combined with nuclear magnetic resonance technology, the recovery of different pores during CO2 huff and n-puff were studied, and the effects of injection pressure and soaking time on core recovery were analyzed. Parallel CO2 huff and puff experiment were conducted to investigate the influence of reservoir heterogeneity on the recovery of CO2 huff and n-puff. The results showed that the pores in the Lucaogou Formation shale oil reservoir were mainly nano-pores, and small pores with a pore radius between 2nm and 50nm accounted for more than 70% of the total pores. The content of large pores in the core samples increased with the increase of core permeability. CO2 huff and n-puff can effectively extract shale oil from the Lucaogou Formation. When the injection pressure is higher than the minimum miscibility pressure, increasing the injection pressure can increase the oil recovery efficiency of large pores in the core samples. The higher the content of large pores, the greater the oil recovery rate of the core samples. When the soaking time is increased from 5h to 10h, the dissolution and diffusion of CO2 in small pores are enhanced, and the recovery rate of small pores increases by about 10%. However, the recovery rate of small pores no longer increases when the soaking time exceeds 10h. The presence of fractures can effectively enhance the recovery of small pores around the fractures. However, the presence of fractures increases the heterogeneity of the reservoir, and the greater the difference in core permeability, the lower the recovery rate of small pores. The recovery rate of small pores in the matrix core samples is only 12.17%.
Carbonate gas reservoirs are rich in reserves, with various types of reservoirs, developed cross-scale porous media, and complex seepage mechanisms. In this paper, the natural cores of the fourth member of the Dengying Formation in the Anyue gas field were selected, CT scanning experiments were carried out, and digital cores were constructed. The plane pore characteristics, three-dimensional pore characteristics and pore and throat distribution frequency characteristics of the digital core are studied respectively.
The results of CT scanning show that: (1) the pore and throats of pore-type reservoirs are small, poor in connectivity, and the karst caves and fractures are underdeveloped, with low seepage capacity; (2) The pore and throats of cavity-type reservoirs are relatively large in size, with good connectivity, medium and small-sized karst caves and micro-fractures are widely developed, and the seepage capacity is good; (3) Fracture-cavity-type reservoirs have large pore and throats and good connectivity, and various-sized cavities and various types of fractures are widely developed in the reservoir, and the entire rock block area is full of Interconnected fracture-cavity network system with excellent seepage capacity.
The in-situ production of hydrogen from hydrocarbon reservoirs offers a novel and cost-efficient approach, leveraging gasification and cracking reactions of fossil fuel sources. This study investigates the process of hydrogen production through heavy oil cracking under various atmospheric conditions, employing a kinetic cell apparatus. Additionally, this work pioneers the definition and computation method for hydrogen production efficiency, providing a quantitative framework to assess in-situ hydrogen generation performance during the later stages of heavy oil reservoir development. The outcomes of this research highlight that hydrogen generation transpires during the phases of pyrolysis and coke dehydrogenation reactions. Particularly noteworthy is that over 60% of the produced hydrogen originates from the coke dehydrogenation reaction range, prevailing at temperatures within 500â€“650 Â°C. In regard to the hydrogen production efficiency, when heavy oil samples are subjected to an air environment, it fluctuates within a range of 9.24â€“15.66%. This range is significantly lower compared to the nitrogen atmosphere, where efficiency varies from 12.26% to 28.65%. The inclusion of clay minerals serves as a natural catalyst, augmenting hydrogen generation rate and elevating efficiency to the peak value of 28.65%. This enhancement coincides with the maximum conversion rate of heavy oil, reaching 262.46 mL/g. Furthermore, the introduction of water substantially amplifies the overall mole count of hydrogen production, indicating its pivotal role in reducing the lower limit temperature for hydrogen generation from 400 Â°C to 300 Â°C.
This paper introduces “SmartTURVENT,” a hybrid windcatcher and turbine roof ventilator system with triple benefits: enhancing indoor environmental quality (IEQ), harnessing renewable energy, and reducing carbon emissions. Utilising a transient state pressure-based solver with CFD airflow modeling, the SmartTURVENT system optimises heat exchange, achieving about 6-40% and 11-55% faster attainment of acceptable humidity levels compared to individual windcatcher and turbine roof ventilator operations, respectively. In energy harvesting, SmartTURVENT generates 0.37 W, 11.27 W, and 69.10 W at wind speeds of 2 m/s, 5 m/s, and 10 m/s, respectively. Over an 8-hour operation, SmartTURVENT reduces carbon emissions by an average of 13.0% compared to conventional systems.
The continuous industrial chemical processes are typically designed through steady-state conditions. Nevertheless, there is evidence that processes can be intensified by applying optimized forced periodic operation. Possible improvements in reactor performances caused by the implementation of forced periodic operation (FPO) can be successfully evaluated by applying a nonlinear frequency response (NFR) analysis, before experimental investigation. In this study, we will present the results of two case studies based on heterogeneously catalyzed methanol synthesis in a continuous stirred tank reactor (CSTR). The first is an isothermal case, and the second is a more complicated and more realistic, non-isothermal case.
Negative externalities of fossil fuels together with adjuvant features of solar energy is driving the global espousal of solar energy technologies. This article presents a forecasting model for photovoltaic (PV) power generation using real-time data analysis of two solar plants through machine learning time series model (MLTSM). The work focuses on critical factors such as predictive accuracy, residual distribution, RMSE values, data quality, and model suitability for forecasting. The findings demonstrate that the predictive model achieves an accuracy of 98% for Plant 1 and 91% for Plant 2. Overall, the MLTSM exhibits its effectiveness in enhancing PV power generation forecasting, thereby contributing to the attainment of energy security.
With the development of oil field water flooding, many oil fields have entered the high water cut stage one after another, and some parts of the actual reservoir have been washed by water drive for many years, so the understanding of traditional oil drive efficiency needs to be improved, and the oil drive efficiency under high multiple displacement needs to be clarified. There are many factors affecting oil displacement efficiency. This paper mainly considers the influence of water displacement PV number, crude oil viscosity, permeability and water displacement velocity (capillary number). In order to reveal the changes of high-power water flooding from macroscopic and microscopic points of view, 21 sets of unsteady water flooding core experiments with water flooding PV number of 1000PV were carried out. Among them, 11 sets were high-power water flooding and measured parameters to calculate high-power phase permeability curves. The other 10 groups were subjected to NMR scanning during high-power water flooding to determine the effects of different permeability, viscosity and water flooding speed on the residual oil utilization of different pore sizes. The right shift ratio of residual oil and the expansion ratio of water phase permeability were selected to characterize the change law of high phase permeability.
The results show that the oil displacement efficiency increases with the increase of water displacement multiple, and the increase of oil displacement efficiency decreases with the increase of water displacement multiple. The oil phases in different pore radius are used, and the displacement efficiency of large holes is higher than that of small holes. With the increase of oil viscosity, the right shift ratio of residual oil in high-power water drive increases, which is 1.11 at low viscosity and 1.29 at high viscosity. With the increase of oil viscosity, the expansion ratio of water phase in high multiple water flooding increases, which is 1.07 at low viscosity and 2.28 at high viscosity. The higher the oil viscosity, the higher the oil potential is in high multiple water flooding. The increment of oil displacement efficiency in the low-viscosity group mainly comes from the large pores with pore radius greater than 20um, and the increment of oil displacement efficiency in the medium-high viscosity group mainly comes from the small pores with pore radius less than 10um. With the increase of core permeability, the right shift ratio of residual oil and the expansion ratio of water phase infiltration decrease, and the lower the permeability, the higher the oil increase potential of high multiple water flooding. The oil displacement efficiency of each pore radius in the low permeability group increased, and the increment of oil displacement efficiency in the high permeability group mainly came from the small hole about 8.62um. After high multiple water flooding, the right shift ratio of residual oil increases with the increase of capillary number, and the oil displacement efficiency is greatly improved at high speed, and the expansion ratio of water phase infiltration increases with the increase of capillary number after high multiple water flooding. High-speed water flooding can improve the water phase flow capacity, and the oil increase potential is lower at low speed. At low speed, the displacement efficiency of each aperture increases, and the increment of small aperture is more for 8.62um. The increment of displacement efficiency under high speed condition mainly comes from the large and medium aperture of 27.75um.
Phase change heat exchanger (PCHE) is an essential component of the integrated energy system (cooling, heating and power) modeling and optimization, where the heat transfer performance directly affects the overall performance and the equipment investment accounts for a significant proportion. This work proposes a new collaborative optimization method for coupling micro-phase change heat exchanger (MPCHE) sizing and organic Rankine cycle (ORC) systems performance to recover different grades low-temperature waste heat considering the heat transfer characteristics with fuzzy heat transfer zones, complex flow patterns and chaotic motion law. Firstly, considering the dynamic changes of thermophysical property of fluids, a new design method of the infinitesimal phase-change heat exchanger based on phase transition rate infinitesimal (PCHE-PTI) is proposed, and a thermo-hydraulic model close to the real heat transfer law is established. Then, the traditional-three-stage phase change heat exchanger design method (PCHE-TTS) and the micro-segmentation phase change heat exchanger design based on the number of baffle and tube pass (PCHE-MBT) are coupled to ORC system respectively. Finally, the reinforcement learning neural network algorithm (RLNNA) is used to solve the three mixed integer nonlinear programming models to achieve the optimal thermal-economic. The results show that the new method proposed can accurately describe the actual phase change heat transfer behavior and can also obtain an electricity production cost that is 5% lower than the traditional method and 8% lower than the original design. Furthermore, the coupling optimization process of MPCHE-ORC-Fluid is successfully realized by considering Fluid selection, and the most cost-effective optimization configuration is obtained, thereby improving the accuracy and reliability of design optimization.
Passive design measures were regarded as a method to address the energy performance gap (EPG) in buildings. However, there is a lack of quantification of the impact of passive design measures on the EPG. This study aims to quantify the impact of passive design measures on the EPG using a case study of high-rise residential buildings in Hong Kong. First, key passive design variables were identified through a literature review, including window-to-wall ratio and window type. Second, an as-designed energy model and an as-occupied energy model were built using DesignBuilder and EnergyPlus. Third, sensitivity analysis was conducted using passive design variables as inputs in both the as-designed and as-occupied energy models. Results show that the EPG of the case building was about 16%. The window type has a greater impact on the EPG than window-to-wall ratio. This study demonstrates the potential of passive design measures for closing the EPG.
In the design of district energy systems, the optimization of energy station layout plays a pivotal role in catering to decentralized load demands and cost reduction. This research accounts for distinct temporal load distribution characteristics and streamlines the complex spatiotemporal distribution issue of large-scale load systems through scenario partitioning and optimization decomposition. The utilization of DBSCAN clustering method is employed to ascertain the configuration of energy stations and load assignments within each scenario. The overarching objective is to minimize the annual equivalent cost of the system, integrating the shortest path algorithm to refine energy station placements and pipeline layouts. Practical engineering cases validate the effectiveness of this approach. The study amalgamates temporal analysis to dynamically optimize energy station quantity, locations, and pipeline layouts, culminating in heightened economic viability and adaptability in the planning process, ultimately resulting in a comprehensive quantitative analysis of energy station design.