Search Results (408)

With the continuous development of the petroleum industry, bottomhole pressure prediction technology, which exerts a significant impact on oil production and recovery, has become a key research direction in the current oil and gas field. To enhance the accuracy and robustness of bottomhole pressure prediction under transient and variable operating conditions, a method based on data augmentation strategies and hyperparameter optimization was proposed in this paper. Addressing challenges such as limited data volume and significant disturbances in actual oilfield production, a data augmentation strategy incorporating noise perturbation and sliding windows was introduced to expand training samples and improve model generalization. In terms of model architecture, a deep network integrating CNN, BiGRU, and Multi-Head Attention mechanisms was proposed in this paper, which is referred to as the CNN-BiGRU-Multi-Head Attention model. By introducing Bayesian optimization for automatic hyperparameter search, the performance of the temporal model was further enhanced, achieving efficient extraction and dynamic focusing of wellbore pressure temporal features. Prediction results demonstrated that the proposed method outperforms existing mainstream forecasting models in metrics such as Mean Absolute Error (MAE) and Coefficient of Determination (R²), with R² reaching 0.9831, which confirms its strong generalization capability and engineering applicability. Practical guidance for intelligent oilfield production management and bottomhole pressure forecasting, along with a novel prediction method, is provided by this study, which holds significant importance for extending well life and stabilizing hydrocarbon production. Full article

Background: This study examined the effects of an individualized weighted vest sprint training program on sprint performance and countermovement jump (CMJ) outcomes in post-peak height velocity (PHV) male youth soccer players while accounting for maturation status. Methods: Fifty players (mean age 17.76 ± 0.95 years) were randomly assigned to a weighted vest sprint group (WVG; n = 25) or a traditional unloaded sprint group (TS; n = 25). Sprint performance (5, 10, 20, and 30 m) and CMJ-derived variables (jump height, peak power output, reactive strength index modified (RSI-modified), and eccentric rate of force development) were assessed before and after an 11-week intervention performed twice weekly, with the WVG completing sprint drills while wearing a weighted vest (~11% body mass). Results: Weighted vest sprint training produced greater improvements in 10 m sprint performance and RSI-modified (d = 1.37 and 1.55, respectively). However, after Benjamini–Hochberg adjustment for multiple comparisons, the effects were no longer statistically significant and should therefore be interpreted with caution. Maturity offset did not meaningfully moderate training-induced adaptations. Conclusions: These findings suggest that weighted vest sprint training may provide potential benefits for mid-acceleration performance and reactive strength in post-PHV youth soccer players, although the magnitude of these effects remains uncertain. Full article

Load monitoring is essential in football to optimise training prescription and reduce injury risk, yet the internal and external demands of common possession drills such as rondos remain insufficiently described. Rondo formats are widely used across levels, but changes in player configuration may substantially alter their load profile. This study examined how three rondo configurations (5vs2, 6vs2 and 8vs2) affect internal load (RPE) and external load (GPS-derived metrics) in semi-professional football players. Twenty-one Spanish players (mean age = 28.9 years) from the same team participated in the study. All players completed three rondo formats (5vs2, 6vs2 and 8vs2) across four separate weeks. Each format consisted of three 3-min bouts with 1 min of recovery, and players were restricted to one touch. Internal load was assessed using players’ rating of perceived exertion (RPE), while external load was measured using a global positioning system (GPS). The results showed a significantly higher perceived exertion in the 5vs2 rondo compared with the other formats (p < 0.001). Regarding external load, significantly greater values (p < 0.001) were observed in the 6vs2 rondo for distance covered at 12.1–18.0 km·h⁻¹ (DZ2) and 18.1–21.0 km·h⁻¹ (DZ3) compared with the other rondo formats. In contrast, 6vs2 also elicited a significantly lower number of accelerations above 3 m·s⁻² and decelerations below −3 m·s⁻² than the other formats (p < 0.001; p < 0.006). Finally, 5vs2 produced significantly higher maximum speed than 8vs2 (p = 0.016). In conclusion, the 6vs2 rondo may be the most suitable option to target DZ2 and DZ3 compared with 5vs2 and 8vs2. Conversely, 5vs2 induced the greatest acceleration and deceleration demands, followed by 8vs2. Therefore, coaches can select the rondo format according to the desired external load requirements. Full article

Large-scale post-marketing drug safety data from spontaneous reporting systems offer new opportunities to explore adverse drug events (ADEs). However, these datasets often contain high rates of missing and incomplete data, undermining the reliability and interpretability of pharmacovigilance analyses. Effective management of these data quality issues requires interactive tools to explore patterns of missingness across multiple dimensions. We present IRVINE (Interactive Visualization for Spontaneous Reporting Systems Databases Missing Values), an interactive visualization system designed to explore and compare missing data in spontaneous reporting systems. IRVINE integrates multiple coordinated components—including a global overview, detailed attribute-level breakdowns, a temporal analysis interface, and a cross-database comparison environment—allowing users to fluidly transition between global summaries and fine-grained diagnostic views. The system supports dynamic filtering, drill-down exploration, and interactive temporal analysis to examine changes in data completeness over time and across categories. Through three usage scenarios and a user study, we demonstrate how IRVINE supports effective exploration of reporting completeness. Results indicate that users perceived the system as easy to use and effective for identifying missingness patterns, with particular strengths in comparative and detail-level analysis. This work lays a foundation for improved transparency, interpretability, and data quality assessment in large-scale pharmacovigilance systems. Full article

The annual soccer training cycle consists of preparatory, competitive, and transition periods. The transition phase is usually characterized by a decrease in training volume, which may lead to detraining and declines in physical fitness. The aim of this study was to examine the effects of a structured transitional training program on anthropometric characteristics, aerobic capacity, and jumping performance in young soccer players. Twenty-three under-17 players participated in the study and, following a two-week period of training cessation, completed a three-week program that included aerobic training three times per week (continuous and interval running sessions) and strength progressive resistance training twice per week. Pre- and post-intervention measurements were analyzed using paired-samples t-tests, with statistical significance set at p < 0.05. The results revealed significant reductions in body fat percentage (p = 0.016, d = 0.547), body fat mass (p = 0.018, d = 0.535), and resting systolic blood pressure (p = 0.024, d = 0.507). Additionally, time to reach the anaerobic threshold (p = 0.022, d = −0.515) and movement speed at the anaerobic threshold (p = 0.029, d = −0.487) significantly increased. No significant changes were observed in the remaining variables. These findings indicate that a three-week transition-period training program combining structured aerobic running drills with progressive resistance training can induce favorable adaptations in selected anthropometric and physiological parameters in youth soccer players. However, the lack of a control group should be considered when interpreting the magnitude of the program’s effects. Full article

Due to reservoir heterogeneity and drilling/completion damage, the gas production distribution along the wellbore in low-permeability gas reservoirs generally exhibits significant unevenness, restricting the full utilization of single-well productivity. To address this issue, this paper constructs a novel multi-segment horizontal-well flow model considering the permeability differences along the wellbore. Our methodology developed the skin factor calculation method to quantitatively predict production after acid stimulation. Studies have shown that the heterogeneity of permeability along the wellbore significantly controls the gas production contribution and early production response of each well section, and the traditional homogeneity assumption is prone to leading to biases in production capacity evaluation. Compared with general acidizing, targeted acidizing combined with flow constraints can effectively reconstruct the gas production distribution, significantly enhance the contribution of low-yield sections, and improve overall production performance. Taking the P002-H3 well in the Sichuan Basin as an example, based on gas production profile identification and skin coefficient decomposition, drilling fluid invasion was identified as the dominant damage mechanism, and the acidizing scheme was optimized accordingly, verifying the engineering applicability of the proposed method in horizontal-well production capacity evaluation and stimulation optimization. Full article

The triplex reciprocating drilling pump is a critical piece of equipment in drilling platforms, and the operational condition of its core component—the valve body—directly affects the pump’s performance and the stability of the entire system. Therefore, accurate prediction of the valve body’s Remaining Useful Life (RUL) is of great significance for ensuring the safe operation of drilling pumps and enabling predictive maintenance. However, achieving this goal involves two major challenges: (1) The complex degradation process of the valve body, which involves strong impact loads, nonlinear wear, and coupling effects between fluid and mechanical systems, makes it difficult to establish a stable degradation model and achieve accurate RUL prediction. (2) There is a lack of publicly available real-world datasets for research purposes. To address these challenges, we propose CEEMDAN-BWO-optimized Bidirectional LSTM for Remaining Useful Life prediction (CB²-RUL). The method first applies Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) to the raw vibration signals for decomposition and denoising, thereby improving signal stationarity and enhancing feature representation. Next, the Black Widow Optimization (BWO) algorithm is employed to automatically tune key hyperparameters of a Bidirectional Long Short-Term Memory (BiLSTM) network. Finally, the optimized BiLSTM captures the temporal evolution patterns of valve-body degradation and produces high-accuracy RUL estimates. Finally, to verify the effectiveness of the proposed approach, we constructed a real-world dataset named VB-Lifecycle, which comprises ten valve bodies from different positions within the equipment and spans the complete lifecycle from pristine condition to failure. Extensive experiments conducted on the VB-Lifecycle dataset demonstrate that the proposed method provides accurate RUL prediction for valve bodies. Full article

The western region of the Tarim Basin is a typical deep and ultra-deep oil and gas reservoir with complex geological conditions in China. This area includes a thick salt–gypsum layer, high-pressure brine layers, and other formations with high pressures and a complex pressure system. These geological features present challenges such as a high risk of drilling fluid contamination by formation fluids, the deep burial of subsalt reservoirs, high temperatures, and difficulty in designing drilling fluids. In this paper, by systematically screening and optimizing key additives, a diesel oil-based drilling and completion fluid system resistant to 220 °C ultra-high temperatures with a density of 2.60 g/cm³ was developed. The overall performance was evaluated. Utilizing an independently developed high-temperature emulsifier (BZ-PSE), an organically modified lithium silicate viscosity modifier (BZ-CHT), and compounded fluid loss reducers (BZ-OLG/BZ-OSL), the system maintained excellent rheological stability (yield point > 4.3 Pa) and filtration control capacity (HTHP fluid loss < 4.8 mL) even after aging at 220 °C. The system demonstrated a resistance to contamination by 30–50% composite brines, 15% salt–gypsum cuttings, and 10% cement, proving its capability to effectively handle extremely thick mud shale, salt–gypsum layers, and high-pressure brine. Field tests were conducted in wells GL 3C, DB X, Boz 13X, and Boz 3X. The results indicated that the high-temperature, high-density diesel oil-based drilling fluids and completion fluids can effectively address the technical challenges posed by wellbore instability in thick salt–gypsum layers, high-pressure brine invasion, and performance degradation under ultra-high temperature conditions, providing reliable technical support for the safe and efficient drilling of similar complex formations. Full article

Injection mold design is a repetitive and time-consuming process with common individual tasks related to each other. This study presents the development of an automatic computer-aided design (CAD) tool for basic injection molds with complete modeling and no other interaction by the user after inserting the part, built on the SolidWorks Application Programming Interface 2022 (API) and Visual Basic for Applications 7.1 2012(VBA). The tool combines user input forms and supplier catalog data as inputs in an algorithm to automatically generate mold structures, cavity blocks, runner system, ejection system and straight drilled cooling channels without further manual modeling. Three case studies with one-, two-, and four-cavity molds demonstrate the approach. The results show that complete mold assemblies can be produced in less than 10 min rather than hours while maintaining standard component dimensions. Although the present version applies to rule-based geometric placement rather than thermal or injection process optimization, it provides a framework for future integration of more complex mold structures and functions such as slides, hot runner system, unscrewing geometries, conformal cooling, heat-transfer-based design, family molds and machine selection. This work demonstrates how API-driven automation can reduce design time, standardize layouts, and lay the groundwork for next-generation injection mold development. Full article

Reservoir boundary distance measurement is a key technology in geosteering drilling. In this field, it is difficult to balance detection precision and depth. This paper proposes a method to measure reservoir boundary distance using a drill-attached impulse sound source equipped with a reflector. The COMSOL Multiphysics (COMSOL) is used to construct a while-drilling reservoir model with a reflector and verify the model’s effectiveness through the real-axis integration method. Under this model, the dimensions of the reflector are analyzed, the relative ranging error under different distances is calculated, and source distance combinations and reservoir interface dip angles are considered. Moreover, the effectiveness of this method is verified through the results of ranging for two sets of actual geological parameters. These results show that the rotating parabolic reflector (depth 45 mm, opening radius 12.2 mm) has a good energy bunching effect. When the dominant excitation frequency of the sound source is 8 kHz, and the source distance combination is 2 m and 4 m, the minimum relative ranging error for the reservoir boundary at 7 m is 2.1%. The relative error becomes smaller when the reservoir boundary dip angle and source distance are smaller. When the source distance is 2 m or 7 m, and the dip angle is between [−20, 20] degrees, the relative error is below 15%. Simulations with actual formation parameters indicate that the proposed method attains good ranging precision. Full article

In response to the complex drilling conditions in the carbonate reservoirs of the Tahe Oilfield, a brine-based solids-free drilling fluid system using oilfield-produced water was developed. Most existing solids-free drilling fluid systems are formulated with fresh water or low-mineralization water, which cannot maintain stability in the high-salinity, high-mineralization conditions of oilfield water. This study addresses this gap by systematically optimizing viscosifiers, fluid-loss control agents, and lubricants, enabling the use of highly mineralized produced water. The developed system maintains good rheological properties and fluid loss control even under challenging conditions. Laboratory tests show that the system, with POLY-V as the viscosifier, DEG-FLO and STAR-AM as fluid-loss agents, and ATV-SLIP as the lubricant, exhibits stable performance under the high-temperature, high-salinity conditions typical of the Tahe Oilfield, with limited performance degradation. Full article

Enhanced Geothermal Systems (EGS) extend geothermal energy beyond conventional hydrothermal resources but face challenges in creating sustainable heat exchangers in low-permeability formations. This review synthesizes achievements from the Utah Frontier Observatory for Research in Geothermal Energy (FORGE), a field laboratory advancing EGS readiness in 175–230 °C granitic basement. From 2017 to 2025, drilling, multi-stage hydraulic stimulation, and monitoring established feasibility and operating parameters for engineered reservoirs. Hydraulic connectivity was created between highly deviated wells with ~300 ft vertical separation via hydraulic and natural fracture networks, validated by sustained circulation tests achieving 10 bpm injection at 2–3 km depth. Advanced monitoring (DAS, DTS, and microseismic arrays) delivered fracture propagation diagnostics with ~1 m spatial resolution and temporal sampling up to 10 kHz. A data infrastructure of 300+ datasets (>133 TB) supports reproducible ML. Geomechanical analyses showed minimum horizontal stress gradients of 0.74–0.78 psi/ft and N–S to NNE–SSW fractures aligned with maximum horizontal stress. Near-wellbore tortuosity, driving treating pressures to 10,000 psi, underscores completion design optimization, improved proppant transport in high-temperature conditions, and coupled thermos-hydro-mechanical models for long-term prediction, supported by AI platforms including an offline Small Language Model trained on Utah FORGE datasets. Full article

Modern telemedicine requires advanced analytical solutions for efficient management of chronic diseases. This study presents the development of a comprehensive business intelligence (BI) framework using Microsoft Power BI, applied to the optimization of diabetes mellitus management. The methodology integrates Power Query transformations, 35 DAX measures organized into five functional categories, and Python 3.14.2. capabilities for advanced statistical analysis. The framework was implemented and demonstrated using a public clinical dataset of 100,000 patient records, generating five interactive dashboards covering epidemiological, demographic, clinical, geographical, and equity perspectives. A global prevalence of 8.5%, exponential growth with age, gender differences (9.75% males against 7.62% females), and substantial connections between metabolic indicators (BMI, HbA1c, and blood glucose) are all confirmed by the results. Heart disease rates are 6.2 times higher in diabetic people, according to comorbidity research. Complete methodological openness through thorough documentation, Python integration for sophisticated visualizations, and interactive multidimensional drill-down features are some of the major additions. The predictive elements are included as interpretable, exploratory components embedded in the BI environment rather than as clinically validated prediction models. This approach provides an affordable and user-friendly approach that makes advanced analytical capabilities accessible to a broader range of healthcare organizations managing chronic diseases. Full article

Severe reservoir heterogeneity in offshore oilfields often leads to dominant flow channels, high water cut, and low sweep efficiency during long-term water flooding. In this study, an in situ self-assembled composite foam system combining soft polymer particles with a low-interfacial-tension foaming agent was developed for profile control and enhanced oil recovery (EOR) in offshore heterogeneous reservoirs. The self-assembly characteristics and physicochemical properties of different particle systems were evaluated to optimize the composite foam structure. Static and dynamic experiments were conducted to assess foam stability, plugging performance, injectivity behavior, and oil displacement efficiency. Results show that the optimized composite foam undergoes in situ self-assembly under reservoir conditions, forming a stable particle–foam structure that enhances selective plugging and mobility control. Core flooding experiments demonstrate that the system increases oil recovery by up to 27.2% across a wide permeability range. Field application further confirms its effectiveness in regulating interlayer water absorption, stabilizing injection pressure, and reducing water cut. These results indicate that the proposed in situ self-assembled composite foam is a promising technique for integrated profile control and enhanced oil recovery in offshore heterogeneous reservoirs. Full article