Search Results (3,108)

To address the problems of rapid water cut increases and severe interlayer interference in offshore composite rhythmic edge-water reservoirs, this paper aims to reveal the three-dimensional spatiotemporal evolution laws of water-flooding fronts under complex heterogeneous conditions. A systematic study was carried out using a combination of three-dimensional large-scale physical simulation, mathematical derivation, and orthogonal numerical simulation. The results indicate that under composite rhythmic conditions, the dynamic interplay between the interlayer permeability differential and gravity segregation exacerbates bottom-water channeling, while a bottom low-permeability zone and a large formation dip angle effectively inhibit water underride. Crude oil viscosity and liquid production rate are the core factors affecting the recovery factor. Furthermore, the constructed water breakthrough time prediction model, which considers additional gravity potential energy, demonstrates a stable calculation error within 4.6%. The study confirms that promoting the longitudinally balanced advancement of multilayer oil–water fronts is the key to improving macroscopic sweep efficiency, and the optimized balanced sweep mode improves the ultimate recovery factor by up to 8.57% compared to the extreme channeling mode, providing scientific guidance for water control well selection and the optimization of liquid production schedules in offshore edge-water reservoirs. Full article

Carbon emission regulations and customers’ green preferences require ports and shipping companies to develop green services, but green investments entail significant costs. Vertical alliance cooperation between ports and shipping companies through sharing costs can address this issue. Most studies use non-cooperative game to analyze the competitive relationship between ports and shipping companies. Although such research can capture price competition, they struggle to address the distribution of cooperative benefits within an alliance. They also fail to simultaneously reflect the coexistence of competition and cooperation. So, we constructed a non-cooperative–cooperative biform game to analyze green investment under vertical alliance. In the non-cooperative stage, the model captures vertical price competition between ports and shipping companies, as well as horizontal competition among supply chains. In the cooperative stage, the Shapley value is used to allocate the coalition profits from green investment cooperation. The results indicate that alliance cooperation can promote the green development of shipping. Moderate green competition can promote the green development of shipping. Route substitution competition will increase service prices and green investment level and reduce the cost-sharing ratio for shipping companies. Port congestion prompts ports to increase green investment level. These findings offer references for the green collaborative development of ports and shipping companies across different countries, thereby enriching the research framework for global sustainable development in shipping. Full article

Characterizing multiscale fracture networks in shale gas reservoirs remains challenging, while the limited applicability of conventional continuum-based models and insufficient multi-objective coordination often lead to low efficiency in development optimization. To address these issues, this study proposes a production history matching and multi-objective collaborative optimization framework for shale gas horizontal wells based on an equivalent fractal fracture (EFF) model. By integrating fractal theory with intelligent optimization techniques, a multiscale equivalent fractal permeability tensor is constructed, forming a hybrid machine-learning framework that combines physics-based fractal constraints with data-driven learning for efficient representation of complex fracture networks. Microseismic event clouds were converted into continuous fracture-density and fractal-geometry descriptors through denoising, temporal alignment, and spatial interpolation, and these descriptors were mapped to the equivalent fractal fracture model to dynamically update key flow parameters for history matching and parameter inversion. On this basis, a multi-objective collaborative optimization strategy is developed to achieve simultaneous time-varying fracture characterization and dynamic regulation of development parameters. Comparative results indicate that the EFF-based approach yields a production prediction error of 6.8%, slightly higher than the 4.2% obtained using discrete fracture network (DFN) models, while requiring only one-eighteenth of the computational time. Using the net present value (NPV) as the unified objective function, constraints are imposed on bottom-hole flowing pressure, flowback rate and system switching time for optimization. With the optimized pressure drop being more uniform and the gas saturation distribution being more balanced, it is verified that “EFF + NPV” can achieve the coordinated optimization of “production capacity—decline—cost” and enhance the development efficiency. Full article

To address the challenges of complex wellbore trajectories in horizontal gas wells and the significant differences in droplet entrainment laws across various well sections, which make it difficult to accurately predict the most critical location for liquid loading, this study establishes a prediction model for the critical liquid-carrying flow rate in different well sections. The model is based on droplet force balance and Kelvin–Helmholtz wave theory, considering droplet deformation and energy losses due to wall collisions and friction. By integrating the critical liquid-carrying flow rate models for each section with a four-field coupled wellbore prediction model, a coupled temperature-pressure and liquid-carrying prediction model is developed. Sensitivity analysis was performed on factors influencing the critical liquid-carrying flow rate, and a field data analysis was conducted on 43 gas wells. The results indicate that the proposed model provides accurate predictions, with only one well being misjudged. For four wells near the liquid loading state, the predictions were within a ±15% error range, with an average deviation of only 5.9%. The research results provide a theoretical basis for the accurate prediction of liquid loading in horizontal gas wells. Full article

With the increasing complexity of reservoir formation mechanisms and the increasing difficulty of exploration, accurate reservoir prediction is critical for oil and gas exploration. However, traditional methods struggle to simultaneously achieve multi-source data fusion and spatial structure characterization. This study proposes a sequential stochastic fuzzy simulation (SSFS) method that integrates fuzzy recognition and sequential stochastic simulation to fuse well logging and seismic data while preserving geological spatial structure. In order to verify the effectiveness of the method, a tight sandstone reservoir in the D block of the Sulige gas field, Ordos Basin, was taken as the research target. Four gas-sensitive seismic attributes are selected, and the SSFS model is then constructed by fusing well–seismic multi-source data. Validation shows high consistency between predicted and measured gas thickness, with an R² of 0.955 and an RMSE of 0.866 m, consistent with the dynamic gas testing results of horizontal wells. Compared with conventional geostatistical and machine learning methods, the SSFS method achieves higher accuracy, stronger spatial rationality, and better generalization ability in blind-well validation. Uncertainty analysis (mean, SD, CV, P10-P50-P90) confirms low uncertainty and high reliability. Therefore, the proposed method is reliable and effective, providing new insights for reservoir prediction. Full article

This study presents a numerical investigation of the laminar forced convection of polyethylene glycol-based nanocolloids within a horizontal pipe. To bridge the gap between theoretical predictions and practical performance, simulations were conducted over a Reynolds number range of 500 to 2000, utilizing a model validated against laboratory-scale experimental data and well-defined boundary conditions. Our analysis focuses on the thermal behavior of polyethylene glycol 200 enriched with metal oxide nanoparticles and multi-walled carbon nanotubes, which were selected for their capacity to enhance thermal conductivity while maintaining manageable viscosity. The results demonstrate that PEG 200-based nanocolloids significantly improve heat transfer performance in the laminar regime. This enhancement is attributed to the superior intrinsic thermal properties of the nanoparticles and the complex synergistic interactions—such as Brownian motion and thermophoresis—between the particles and the PEG base fluid. A critical evaluation of the standard approach of incorporating thermophysical properties into the numerical approach led to significant discrepancies in flow predictions. Additionally, our study establishes that assuming constant thermophysical properties during the heating process introduces simulation errors exceeding 10%. These findings underscore the necessity of incorporating temperature-dependent, experimentally validated data into numerical models to ensure predictive accuracy. Ultimately, this work advocates for a nuanced approach to nanocolloid design that prioritizes the specific chemical and rheological compatibility between nanoparticle types and the base fluid. Full article

The evaluation of sweet spots for infill wells is critical to identifying premium reservoir zones, avoiding fracture hits, and achieving safe, efficient development with maximum production potential. Firstly, considering that geological and engineering factors—such as high fracability and good reservoir quality—are conducive to the formation of complex fracture networks and sufficient gas production after fracturing, quantitative evaluation indicators for fracability and geological properties have been established. Secondly, a classification method for different sweet spot tiers in infill wells was proposed. Lastly, taking the Changning infill pilot wells as an example, for sections not affected by fracture interference, higher sweet spot evaluation scores show a strong correlation with improved predictive performance of tracer-based gas production forecasts. Conversely, in fracture-interfered zones, a discrepancy was observed between the sweet spot evaluation results and actual gas production volumes. The horizontal wellbores were classified into a six-tier system (L1–L6), with tailored fracturing design recommendations provided accordingly. This study offers scientific guidance for the precise evaluation of sweet spots in infill wells and the design of customized staged fracturing, thereby significantly enhancing fracturing effectiveness. Full article

The accuracy of static computer-aided implant surgery (s-CAIS) is fundamental for predictable clinical outcomes. The objective of this study was to evaluate the influence of different guide-support modalities on the linear and angular accuracy of implant placement. In this retrospective clinical investigation conducted at a single specialty hospital, a total of 180 implants were analyzed, divided into three equal groups (n = 60) based on the guide support type: tooth-supported, bone-supported, and mucosa-supported. Accuracy was assessed by superimposing preoperative virtual plans with postoperative cone-beam computed tomography (CBCT) scans, measuring linear deviations at the neck and apex of the implant, as well as angular discrepancies. The type of guide support was found to be a significant factor associated with surgical accuracy (p < 0.001). Tooth-supported guides demonstrated the highest level of accuracy, with a mean angular deviation of 1.81° ± 0.45° and linear deviations at the neck and apex of 0.59 ± 0.18 mm and 0.73 ± 0.19 mm, respectively. These were followed by bone-supported guides (2.14° ± 0.48°; 1.04 ± 0.26 mm; 1.61 ± 0.31 mm), while mucosa-supported guides exhibited the greatest deviations (2.95° ± 0.60°; 1.47 ± 0.29 mm; 1.87 ± 0.37 mm). Significant intergroup differences and large effect sizes were observed, particularly regarding angular and horizontal discrepancies. These findings demonstrate a distinct gradient of accuracy based on guide support, establishing tooth-supported guides as the most accurate, followed by bone-supported and, lastly, mucosa-supported guides. While all modalities are clinically applicable, the use of mucosa-supported guides necessitates increased safety margins to account for the increased risk of linear and angular discrepancies inherent to mucosal tissue displacement. Full article

The significant interannual variability in Madden–Julian Oscillation (MJO) intensity remains incompletely understood. Empirical orthogonal function (EOF) analysis reveals that the first three leading EOF modes of the annual mean MJO intensity are significantly correlated with the Quasi-Biennial Oscillation (QBO), Eastern Pacific El Niño-Southern Oscillation (ENSO), and Central Pacific ENSO. Focusing on the distinct EOFs related to three key tropical interannual variabilities, we conduct an investigation into the potential governing processes through which the changes in background mean states impact MJO intensity based on the MJO moisture mode theory. Observations suggest that the accumulation of moist static energy (MSE) during MJO moistening phases and its dissipation during drying phases play a crucial role in regulating MJO amplitude. At the interannual timescale, regions characterized by positive EOF values display positive (negative) MSE tendency anomalies during MJO moistening (drying) phases, leading to amplified MSE accumulation (dissipation) throughout the MJO lifecycle and subsequently facilitating an increase in MJO amplitude. Conversely, regions with negative EOF values exhibit opposing trends. Further analysis reveals that these MSE tendency anomalies are mainly associated with the zonal advection term, which is influenced by interannual changes in the background mean MSE and low-level winds. The spatial pattern of the background mean MSE is strongly linked to sea surface temperature (SST) anomalies, with low-level background winds aligning well with the horizontal gradients of SST anomalies. Full article

Asymptotic solutions are derived to model the development of atmospheric internal gravity waves generated by latent heating in a two-dimensional configuration involving a vertically-sheared background flow. The mathematical model comprises nonlinear partial differential equations derived from the conservation laws of fluid dynamics under the anelastic approximation where the background density and temperature vary with altitude. The latent heating is represented by a horizontally-periodic but vertically-localized nonhomogeneous forcing term in the energy conservation equation. This generates gravity waves that are considered as perturbations to the background flow and are expressed as perturbation series, with the leading-order contributions being the solutions of linearized equations. Taking into account the nonlinear terms at the next order gives expressions for the effects of the waves on the background mean flow. Due to the vertical shear, there is a critical level where momentum and energy are transferred from the wave modes to the mean flow. The asymptotic solutions show that the wave–mean-flow interaction is nonlocal and occurs over the range of altitudes from the thermal forcing level up the critical level. This is in contrast to what occurs in the case of waves forced by an oscillatory lower boundary, where the interaction is typically localized around the critical level. It is found that the wave drag is negative above the thermal forcing level, making the mean flow velocity more negative, but it becomes positive as the waves approach the critical level, indicating wave absorption in this region. There is wave transmission through the critical level, as well as absorption, and the extent of transmission depends on the depth of the latent heating profile. The mean potential temperature is reduced above the thermal forcing level and enhanced at the critical level, a situation that could ultimately lead to the development of convective instabilities. Full article

Coal is inherently soft, characterized by well-developed cleat systems, low strength, and significant anisotropy. Existing models that treat coal as a continuous medium or consider only a single plane of weakness fail to capture the synergistic effects of multiple weaknesses on wellbore instability. This study addresses this gap by integrating the strength criteria of weakness planes with wellbore stress theory. First, in situ stresses were transformed into the coordinate system of the weakness planes to derive the acting stress components. A strength criterion incorporating multiple structural planes—accounting for the coal matrix, bedding, face cleats, and butt cleats—was then applied to establish a coupled wellbore stability criterion. A corresponding collapse pressure program was developed using Visual Basic to analyze the effects of stress state, wellbore trajectory, and weakness orientation. The results show that the presence of multiple weakness planes significantly increases the sensitivity of wellbore stability to trajectory. Drilling parallel to the direction of minimum horizontal stress minimizes shear stress and collapse pressure, whereas drilling at high angles or parallel to the maximum horizontal stress activates the weakness planes, leading to a sharp increase in collapse pressure. The presence of these weaknesses results in a highly non-uniform and direction-dependent collapse pressure distribution, with their synergistic interactions further exacerbating the risk of localized failure. Full article

The Digital Services Act (DSA) represents a landmark regulatory context aiming to secure a safer, trusted and more transparent digital environment. While the DSA establishes a harmonised regulatory framework for intermediary services across the EU, its enforcement system relies significantly on national regulatory authorities, leaving member states a degree of institutional autonomy in designing the supervisory structures. This article examines the implementation of the DSA in Cyprus and discusses the national legal framework adopted through primary and secondary legislation. It analyses the powers, legally mandated tasks, rights, and obligations of the digital services coordinator in Cyprus including its supervisory, investigatory, and enforcement competences as well as the sanctioning mechanisms. This article provides a comprehensive legal analysis of the coordinator’s operation and contributes to the academic debate on the national implementation of the DSA as a horizontal legal tool of intermediary services and digital platforms accessed by European citizens. Full article

Fibropapillomatosis, a disease associated with Scutavirus chelonidalpha5, commonly known as Chelonid alphaherpesvirus 5 (ChHV5), manifests as benign tumors that impair the motor, visual, and physiological functions of affected sea turtles. In this study, blood and tissue samples were collected from turtles exhibiting fibropapilloma-like lesions as well as from clinically healthy individuals. A nested PCR approach was employed to amplify the viral UL30 and UL28 genes for the detection and characterization of the virus variants. The mitochondrial control region was used to assess the relationship between the turtle population and the viral variant. Among the 19 turtles analyzed, six tested positive for ChHV5, including both symptomatic and asymptomatic turtles. Phylogenetic analysis revealed that three positive samples belonged to the Western Atlantic/Caribbean clade, whereas the other three grouped within the Atlantic clade. New oligonucleotides and probes were designed for ChHV5 qPCR detection, accounting for the globally accumulated genetic variability. The qPCR test parameters demonstrated an optimized assay with an efficiency of 101.4% and a detection limit of 2.4 genome copy equivalents (GCE)/μL. This study confirms the presence of two ChHV5 viral variants in rescued turtles from the Caribbean region of Colombia, including both clinically affected and asymptomatic individuals. Therefore, these results support the association between ChHV5 and fibropapillomatosis. Furthermore, analysis of the mitochondrial control region supports the hypothesis of horizontal transmission of the virus. A novel qPCR protocol with a synthetic control is proposed to improve early diagnosis and strengthen conservation and prevention strategies. Full article

Amid the global transition to carbon neutrality, tidal current energy has become a strategic sustainable energy resource due to its high predictability, power density, and environmental compatibility. Horizontal-axis turbines show great potential for marine energy harvesting, yet the large-scale commercialization of tidal turbines is severely hindered by complex wake dynamics and the lack of reliable, efficient prediction tools for out-of-distribution (OOD) operating conditions. Traditional high-fidelity CFD methods are computationally prohibitive for engineering optimization, while conventional data-driven surrogate models suffer from poor extrapolation performance, extrapolation collapse near training parameter boundaries, and the absence of uncertainty quantification. To address these bottlenecks, this study focuses on the OOD extrapolation of wake flow prediction across tip speed ratio (TSR) distributions for a single horizontal-axis tidal turbine. A CFD-generated spatiotemporal benchmark dataset is constructed for comparative OOD evaluation across various TSR conditions with 9504 total samples. A novel physics-constrained Fourier neural operator framework named TSR-FNO is proposed to improve OOD generalization. The model integrates TSR–Lipschitz regularization to suppress extrapolation collapse and Monte Carlo Dropout to provide reliable uncertainty estimation. Extensive experiments demonstrate that the proposed method effectively reduces prediction error in unseen TSR regimes, mitigates performance degradation in far-field extrapolation, and produces well-calibrated uncertainty estimates consistent with actual prediction confidence. This work provides a data-driven surrogate modeling strategy for fast and reliable wake prediction on a common CFD-generated benchmark, supporting the efficient design, array layout optimization, and engineering deployment of tidal current energy systems. Full article

Coal is the primary energy source in China and has long dominated energy consumption, serving as both the cornerstone for safeguarding national energy security and the backbone of stable energy supply. Despite the gradual improvement in the level of fully mechanized and intelligent mining in recent years, as well as the remarkable progress achieved in safe and efficient mining technologies, significant challenges are still encountered in the horizontal slicing mining of steeply inclined coal seams. This study was conducted against the engineering backdrop of the steeply inclined extra-thick coal seam in the Yimen Coal Mine, Sichuan Province. A combination of theoretical analysis, FLAC3D numerical simulation, and on-site monitoring was employed to investigate the support technology for mining roadways. Considering the geological occurrence conditions, roadway dimensions, and service life, the bolt (cable) + steel strip + metal mesh system was selected as the basic support method, with shed supports supplemented for reinforcement in areas with special geological structures or fractured surrounding rock. A non-uniform roadway support technology for horizontal slicing mining of steeply inclined extra-thick coal seams was proposed. The optimal support parameters of the roadways were determined through numerical simulation, and favorable support effects were verified by field measurements. Full article