Search Results (273)

During sand cleanout operations in shale oil horizontal wells, severe wellbore leakage occurs due to incompatibility between plugging particles and the formation, resulting in a failure to establish circulation. This study determined the optimal plugging theory for the target formation characteristics through laboratory leakage sealing tests and numerical simulations such as fluid–discrete element coupling (CFD-DEM). The results show the following: Plugging experiments indicated that the Vickers criterion achieved the best performance, with an invasion depth of 9 mm, followed by the Ideal Packing Theory, at 12 mm, while the D90 rule performed the worst, with an invasion depth of 13 mm. The simulations results from the CFD-DEM coupling model demonstrated that the Vickers criterion achieves the most effective plugging performance, followed by the Ideal Packing Theory, with the D90 rule exhibiting the least effectiveness. This indirectly validates the rationality and effectiveness of the Vickers criterion in configuring particle sizes for plugging materials. Finally, sand-packed-tube displacement experiments demonstrate that the Vickers criterion yields the lowest permeability and optimal plugging performance, further validating its rationality and effectiveness in configuring particle sizes for plugging materials. This research provides crucial technical support for the safe and efficient development of shale oil horizontal wells, effectively reduces operational costs, and holds significant importance for advancing technological progress in shale oil extraction. Full article

Shale gas pressure post-production accompanies the entire production process. The depth of the tubing is crucial for the entire life cycle of production, especially influencing the production dynamics in the middle and later stages of downward-inclined Wells. The full dynamic multiphase flow simulation method is adopted, combined with wellbore structure, fluid composition (gas), gas layer temperature and pressure gradient, production dynamic data, etc., to establish the wellbore structure model of the gas well, simulate the production dynamics under different formation pressures and tubing depths, and determine a reasonable tubing depth. Considering the material balance of the constant-volume gas reservoir and the critical formation pressure of the gas well’s self-injection, the cumulative gas production of the gas well at different tubing depths was analyzed. Taking 11210-1-well as an example, it was believed that when the tubing depth reached 4000 m, the self-injection production time could be extended by 206 days, and the cumulative gas production increased by 5.1 × 10⁶ m³, compared with the tubing depth of 2983 m. The gas production is increased by approximately 12.2 × 10⁶ cubic meters when the tubing depth is 2000 m. The research conclusion can provide theoretical guidance for the optimization of tubing depth during the drainage and production process of shale gas downward-inclined horizontal Wells. Full article

Macro-scale modeling is a fundamental approach for assessing structural damage and occupant comfort in urban high-rises during earthquakes or typhoons. The key to its effectiveness is accurately reproducing dynamic responses and extracting modal characteristics. The critical issue is whether the macro-scale model can effectively capture Flexure-Shear Coupled (FSC) dynamic behavior. This paper proposes a macro-scale modeling method for high-rise structures with FSC dynamic behavior using deep learning (DL). FSC dynamic behavior is quantified by establishing Displacement Interaction Coefficients (DInC) under each mode shape. To account for the flexural resistance of horizontal members and the anti-overturning contribution of vertical members in high-rise structures, equivalent stiffness parameters representing horizontal and vertical members are introduced into the Lumped Parameter Model (LPM), enhancing the flexibility of the macro-scale model in expressing FSC dynamic behavior. The DInCs are used as input features to identify the LPM’s stiffness parameters, enabling efficient macro-scale modeling. The method was validated on a frame and a frame-core tube structure by comparing dynamic characteristics with their detailed finite element models. This method holds engineering application potential in areas requiring highly accurate and rapid structural characteristic or response calculations, such as seismic response analysis and design optimization of high-rise structures. Full article

The strong heterogeneity in and complex engineering conditions of deep shale gas reservoirs make productivity prediction challenging, especially in nascent blocks where data is scarce. This scarcity constitutes a critical research gap for the application of data-driven methods. To bridge this gap, we develop an interpretable framework by combining grey relational analysis (GRA) with three machine learning algorithms: Random Forest (RF), Support Vector Machine (SVR), and eXtreme Gradient Boosting (XGBoost). Utilizing small-sample data from 87 shale gas wells in the study area, eight key controlling factors were identified, namely, total fracturing fluid volume, proppant intensity, average tubing head pressure, pipeline transfer pressure, casing head pressure, ceramic proppant fraction, fluid placement intensity, and flowback recovery ratio. These factors were used to train, optimize, and validate a productivity prediction model tailored for deep shale gas horizontal wells. The results demonstrate that XGBoost delivers the highest predictive accuracy and generalization capability, achieving an R² of 0.907 for productivity prediction—surpassing RF and SVR by 12.11% and 131.38%, respectively. Integrating SHapley Additive exPlanations (SHAP) interpretability analysis further enabled immediate post-fracturing productivity assessment and engineering parameter optimization. This research provides a reliable, data-driven strategy for predicting productivity and optimizing operations within the studied block, offering a valuable template for development in geologically similar areas. Full article

To address the decision-making requirements for drainage gas recovery in horizontal gas wells within low-permeability tight reservoirs, this study proposes an intelligent classification approach that integrates supervised and unsupervised learning techniques. Initially, the static and dynamic performance characteristics of gas wells are characterized across multiple dimensions, including static performance, liquid production intensity, liquid drainage capacity, and liquid carrying efficiency. These features are then quantitatively categorized using Linear Discriminant Analysis (LDA). Subsequently, a hybrid classification framework is developed by integrating LDA with the K-means clustering algorithm. The effectiveness of this supervised–unsupervised fusion method is validated through comparative analysis against direct K-means clustering, demonstrating enhanced classification accuracy and interpretability. Key findings are summarized as follows: (1) Classification based on individual dynamic or static parameters exhibits low consistency, indicating that single-parameter approaches are insufficient to fully capture the complexity of actual production conditions. (2) By incorporating both dynamic and static parameters and applying a strategy combining LDA-based dimensionality reduction with K-means clustering, gas wells are precisely classified into five distinct categories. (3) Tailored optimization strategies are proposed for each well type, including production allocation optimization, continuous production (without the need for drainage gas production measures), mandatory drainage measures, foam-assisted drainage, and optimal tubing or plunger lift systems. The methodologies and findings of this study offer theoretical insights and technical guidance applicable to the classification and management of horizontal gas wells in other unconventional reservoirs, such as shale gas formations. Full article

The goal of this paper is to assess the evolution of the autogenous strains as well as the thermal strains (thanks to the assessment of the coefficient of thermal expansion) of alkali-activated slag-based materials at early age. The effect of the sand and the coarse aggregates on the paste and mortar scale to upscale to mortar and concrete, respectively, has been investigated as a function of the age of the material. The restraint imposed by the sand on the paste seemed more significant than that of the coarse aggregate on the mortar. In addition, the long-term autogenous strains have been monitored on the mortar scale. These results revealed a separation into groups based on the solution concentration. Different testing methods were also compared. Thermal and autogenous strains were monitored with a customized testing device where the thermal variations are controlled. These devices were the horizontal corrugated tubes method (for tests on paste and mortar scales) and the vertical corrugated tubes method (for tests on mortar and concrete scales). Depending on the compositions (lower concentration), good correlations can be obtained between the two testing methods. Moreover, the autogenous strain of two different specimen sizes was also assessed manually (initially for the long-term), but early-age comparison showed good correlation for lower solution-to-binder ratios. On the concrete scale, a correlation based on the modified equations from the standards was established between the compressive strength and the tensile strength, obtained from the splitting tensile test. Full article

The wettability of falling film flow outside multi-row horizontal tubes is a core factor determining the heat and mass transfer performance of falling film heat exchangers, which is critical for their optimized design and stable operation. A visualization experimental platform for falling film flow over ten rows of horizontal tubes was constructed, with water as the working fluid. High-definition imaging technology and image processing methods were employed to systematically investigate the liquid film distribution and wettability under three tube diameters (d = 0.016, 0.019, 0.025 m), four tube spacings (s = 0.75d, 1d, 1.25d, 1.5d), and four inter-tube flow patterns (droplet, columnar, column-sheet, and sheet flow). Two parameters, namely the “total wetting length” and the “total wetting area”, were proposed and defined. The distribution characteristics of the wetting ratio for each row of tubes were analyzed, along with the variation laws of the total wetting area of the ten rows of tubes with respect to tube diameter, tube spacing, and liquid film Reynolds number (Re_l). The following results were indicated: (1) Increasing the fluid flow rate and the tube spacing both promote the growth of the wetting length. When Re_l ≤ 505, with the increase of tube diameter, the percentage of the wetting length of the tenth tube row relative to that of the first tube row decreases under the same fluid flow rate; when Re_l > 505, this percentage first decreases and then increases. (2) The total wetting area exhibits a trend of “first increasing then decreasing” or “continuous increasing” with the tube spacing, and the optimal tube spacing varies by flow pattern: s/d = 1 for droplet flow (d ≤ 0.016 m), s/d = 1.25 for columnar flow, and s/d = 1.25 (0.016 m), 1 (0.019 m), 1.5 (0.025 m) for sheet flow. (3) The effect of tube diameter on the total wetting area is a balance between the inhibitory effect (reduced inter-tube fluid dynamic potential energy) and promotional effect (thinner liquid film spreading). The optimal tube diameter is 0.016 m for droplet flow and 0.025 m for columnar/sheet flow (at s/d = 1.25). (4) The wetting performance follows the order 0.016 m > 0.025 m > 0.019 m when Re_l > 505, and 0.025 m > 0.019 m > 0.016 m when Re_l ≤ 505. Finally, an experimental correlation formula for the wetting ratio considering the Re_l, the tube diameter, and tube spacing was fitted. Comparisons with the present experimental data, the literature simulation results, and the literature experimental data showed average errors of ≤10%, ≤8%, and ≤14%, respectively, indicating high prediction accuracy. This study provides quantitative data and theoretical support for the structural optimization and operation control of multi-row horizontal tube falling film heat exchangers. Full article

This study presents a comprehensive experimental investigation into the frictional pressure drop of two-phase flows—boiling and condensation—in horizontal minichannels, emphasizing its impact on the energy efficiency of vapor compression systems. A total of 3553 data points were obtained using six low-GWP refrigerants (R32, R134a, R290, R410A, R513A, and R1234yf) across a wide range of operating conditions in multiport aluminum tubes with hydraulic diameters of 0.715 mm and 1.16 mm. The dataset covers mass fluxes from 200 to 1230 $\mathrm{kg}{\mathrm{m}}^{-2}{\mathrm{s}}^{-1}$, saturation temperatures between 5 °C and 55 °C, and vapor qualities from 0.05 to 0.95. Results showed a strong dependence of frictional pressure gradient on vapor quality, mass flux, and channel size. Boiling flows generated higher frictional losses than condensation, and high-density refrigerants such as R32 exhibited the largest pressure penalties, which can directly translate into increased compressor power demand. Conversely, higher saturation temperatures were associated with lower frictional losses, highlighting the role of thermophysical properties in improving energy performance. Additionally, an inverse correlation between saturation temperature and frictional pressure gradient was observed, attributed to variations in thermophysical properties such as viscosity and surface tension. Existing correlations from the literature were assessed against the experimental dataset, with notable deviations observed in several cases, particularly for R134a under high-quality conditions. Consequently, a new empirical correlation was developed for predicting the frictional pressure drop in two-phase flow through minichannels. The proposed model, formulated using a power-law regression approach and incorporating dimensionless parameters, achieved better agreement with the experimental data, reducing prediction error to within ±20%, improving the accuracy for the majority of cases. This work provides a robust and validated dataset for the development and benchmarking of predictive models in compact heat exchanger design. By enabling the more precise estimation of two-phase pressure drops in compact heat exchangers, the findings support the design of refrigeration, air-conditioning, and heat pump systems with minimized flow resistance and reduced auxiliary energy consumption. This contributes to lowering compressor workload, improving coefficient of performance (COP), and it ultimately advances the development of next-generation cooling technologies with enhanced energy efficiency. Full article

To date, two-phase flow boiling has been extensively investigated for various working fluids and geometries, mainly under operating pressures and mass fluxes in the range of medium to high. However, very limited studies have been conducted, focusing on low-pressure low-flow (LPLF) conditions. Given insufficient experimental data available in the literature, most of the existing empirical correlations fail to properly predict boiling heat transfer coefficients (BHTCs) in LPLF conditions, highlighting the need for further experimental investigations. The present study experimentally investigates the heat transfer performance of single-phase and two-phase flow boiling of distilled water in a horizontal conventional tube at constant wall heat flux under LPLF conditions where the operating pressure is set to be subatmospheric and the mass flux ranges below 20 kg/m²-s. For the saturated flow boiling, the effects of mass flux and local vapor quality on the local BHTCs and Nusselt were evaluated, revealing that local BHTCs reach a peak at a certain range of vapor qualities between 55% and 75%, while increasing with the mass flux. It was also found that the impact of mass flux is stronger than that of vapor quality on the local BHTCs. The experimental results in the present study were then compared with several well-known empirical BHTC correlations in the literature to identify those with least deviations under the LPLF conditions. In contrast to single-phase flow, heat loss estimation and vapor quality measurement are known as one of the main error sources in characterizing heat transfer coefficients for two-phase flow boiling. Accordingly, the present study employs two approaches, in parallel, to reliably estimate heat losses, calibrate heat supplies, and measure local vapor qualities under the operating conditions investigated. Full article

Horizontal well multi-stage fracturing is the primary technology for deep shale gas development, but dense multi-cluster fractures are prone to non-uniform initiation and propagation, requiring real-time monitoring and interpretation techniques to adjust fracturing parameters. Although high-frequency water hammer pressure-monitoring technology shows diagnostic potential, the correlation mechanism between pressure response characteristics and multi-cluster fracture morphology remains unclear. This study utilized outcrop rock samples from the Longmaxi Formation shale to construct a long-injection-tube pipeline system and a 1 kHz high-frequency pressure acquisition system. Through a true triaxial fracturing simulation test system, it systematically investigated the effects of flow rate (50–180 mL/min) and fracturing fluid viscosity (3–15 mPa·s) on water hammer signal characteristics and fracture morphology. The results reveal that when the flow rate rose from 50 mL/min to 180 mL/min, the initiation efficiency of transverse fractures significantly improved, artificial fractures more easily broke through bedding plane limitations, and fracture height propagation became more complete. When the fracturing fluid viscosity increased from 3–5 mPa·s to 12–15 mPa·s, fracture height propagation and initiation efficiency significantly improved, but fewer bedding plane fractures were activated. The geometric complexity of fractures positively correlated with the water hammer decay rate. This research demonstrates a link between water hammer signal features and downhole fracture morphology, giving a theoretical basis for field fracturing diagnostics. Full article

Greywater can be a valuable energy source in buildings. Its advantages over other renewable energy resources include its daily availability, regardless of weather conditions. Consequently, wastewater heat exchangers are increasingly used in domestic hot water preparation systems. This article presents the results of tests on three DHW installation variants, including two integrated with various drain water heat recovery exchangers. A horizontal DWHR exchanger (a prototype of a new exchanger design) reduced the energy demand for hot water preparation by up to 29.6%, while a commercially available vertical DWHR unit (“tube-in-tube”) reduced this demand by up to 64.7%. This reduction was primarily influenced by the flow rate from the shower head and the mixed water temperature. Furthermore, a Life Cycle Cost analysis showed that, despite the additional costs associated with implementing DWHR exchangers, the traditional water heating method was the least cost-effective solution in all calculation cases. Furthermore, the tested wastewater heat exchangers significantly reduced CO₂ emissions compared to traditional water heating. This indicates the great potential of wastewater heat recovery systems in decarbonizing the building sector. Full article

This study investigates the effects of magnetic field orientation and axial extent on convective heat transfer in a laminar flow of water-based ferrofluid through a heated horizontal tube. Experiments were conducted at Reynolds numbers of 109, 150, and 164 using two field configurations: lateral fields, with magnets positioned on opposite sides of the tube with varying polarities, and axial fields, with one to three magnets arranged sequentially underneath the tube to vary the magnetic interaction length. In lateral configurations, the impact on the local Nusselt number was negligible or slightly negative depending on magnet orientation. In contrast, axial configurations demonstrated a clear relationship between the magnetic field interaction length and heat transfer enhancement. The local Nusselt number increased progressively with the number of magnets, reaching a maximum of 28.0% for the triple-magnet configuration at Re = 109. The average improvements in the magnetically influenced region were 6.8%, 10.3%, and 14.7% for the single, double, and triple magnet configurations, respectively. These values resulted from the combined effect of magnetic field geometry and Reynolds number, emphasizing the importance of both interaction length and flow conditions in shaping convective heat transfer in ferronanofluid systems. Full article

Super high-rise buildings of 400 m and above are currently rare globally, making their design and construction data invaluable. Due to their enormous size, the structural safety, architectural effect, and construction cost are key concerns of all parties. This study employs parametric analysis to research the lateral force-resisting system and key local structural issues of a 400 m under-construction super-high-rise structure. The overall analysis results show that the 8-mega-column scheme can relatively well balance architectural effect and structural performance; the 5-belt truss design minimizes the steel consumption. The local research results indicate that the inward inclination of bottom columns leads to increased axial forces in floor beams significantly, necessitating reinforcement; horizontal braces directly connected to the core tube enhance folded belt truss integrity under rare earthquakes; failure of bottom gravity columns in the folded secondary frame increases beam bending moments and axial forces substantially. Steel consumption sensitivity analysis shows that when the structural first-order period is reduced by 0.1 s, adjusting the section sizes of the members in the belt truss minimizes the increase in steel consumption, while adjusting steel beams maximizes it. These findings provide essential design insights for similar super-high-rise projects. Full article

With the rapid advancement of information technology, as critical information carriers, images are confronted with significant security risks. To ensure the image security, this paper proposes an image encryption algorithm based on a dynamic rhombus transformation and digital tube model. Firstly, a two-dimensional hyper-chaotic system is constructed by combining the Sine map, Cubic map and May map. The analysis results demonstrate that the constructed hybrid chaotic map exhibits superior chaotic characteristics in terms of bifurcation diagrams, Lyapunov exponents, sample entropy, etc. Secondly, a dynamic rhombus transformation is proposed to scramble pixel positions, and chaotic sequences are used to dynamically select transformation centers and traversal orders. Finally, a digital tube model is designed to diffuse pixel values, which utilizes chaotic sequences to dynamically control the bit reversal and circular shift operations, and the exclusive OR operation to diffuse pixel values. The performance analyses show that the information entropy of the cipher image is 7.9993, and the correlation coefficients in horizontal, vertical, and diagonal directions are 0.0008, 0.0001, and 0.0005, respectively. Moreover, the proposed algorithm has strong resistance against noise attacks, cropping attacks, and exhaustive attacks, effectively ensuring the security of images during storage and transmission. Full article

In the final phases of casing production, shale gas horizontal wells with a downward slope frequently find it difficult to sustain self-flow production. The ideal tubing insertion depth for self-flow production in gas wells has not been thoroughly studied, even though the timely adoption of tubing production can successfully prolong the self-flow production period. Using a fully dynamic multiphase flow simulation program, the ideal tubing depth for gas well self-flow production was ascertained. A wellbore structural model was built using a particular well as an example. By altering the tubing depth, the formation pressure limit values necessary to sustain gas well self-flow production at various tubing depths were simulated. The appropriate tubing depth for gas well self-flow production was examined, along with the well’s cumulative gas output at various tubing depths. Using the example as a case study, it was discovered that the critical formation pressure for gas well self-flowing production dropped to 7.8 MPa when the tubing was lowered to 2600 m. This effectively increased cumulative production by 56.19 × 10⁶ m³ and extended the self-flow production time by roughly 135 days. The study’s findings offer strong evidence in favor of maximizing shale gas wells’ self-flow production performance in later phases of production. Full article