Search Results (1,753)

As information and sensor technologies advance swiftly, data-driven approaches have emerged as a dominant paradigm in scientific research. In the petroleum industry, precise forecasting of patterns of two-phase flow involving oil and water is essential for enhancing production efficiency and ensuring safety. This study investigates the application of Kolmogorov–Arnold Networks (KAN) for predicting patterns of two-phase flow involving oil and water and compares it with the conventional Multi-Layer Perceptron (MLP) neural network. To obtain real physical data, we conducted the experimental section to simulate the patterns of two-phase flow involving oil and water under various well angles, flow rates, and water cuts at the Key Laboratory of Oil and Gas Resources Exploration Technology of the Ministry of Education, Yangtze University. These data were standardized and used to train both KAN and MLP models. The findings indicate that KAN outperforms the MLP network, achieving 50% faster convergence and 22.2% higher accuracy in prediction. Moreover, the KAN model features a more streamlined structure and requires fewer neurons to attain comparable or superior performance to MLP. This research offers a highly effective and dependable method for predicting patterns of two-phase flow involving oil and water in the dynamic monitoring of production wells. It highlights the potential of KAN to boost the performance of energy systems, particularly in the context of intelligent transformation. Full article

The perforating–fracturing–testing combined technology has emerged as a crucial well completion technique to enhance production efficiency. However, the shock loads generated during perforation in the packed section of an oil and gas well significantly affect the stability of the perforating tubing string system, potentially leading to deformation or even fracture. During the perforating operation, a large amount of blast products is generated, and as these products escape the perforating gun and interact with the perforating fluid, the fluid pressure pulsates. These pressure fluctuations are the primary cause of the dynamic response of the perforating tubing string. The greatest threat to tubing string integrity occurs when pulsating pressure reaches its peak amplitude, potentially leading to tubing failure. To address this, this study employs underwater explosion theory to analyze the pressure variations during the generation and propagation of shock waves in perforation operations. Additionally, quantitative numerical simulation analysis reveals key relationships governing peak perforating fluid pressure: peak pressure remains remarkably stable at 370–371 MPa despite variations in perforating fluid viscosity (0–110 cP) or tubing Young’s modulus (100–260 GPa). However, it responds significantly to other parameters: fluid density (1–3 g/cm³) causes a linear increase from 335 MPa to 598 MPa; total charge mass drives a proportional rise from 162 MPa to 388 MPa; detonation interval (0–50 μs) elevates pressure from 268 MPa to 378 MPa; and formation pressure (0–100 MPa) increases it from 315 MPa to 372 MPa. Crucially, peak pressure decreases from 376 MPa to 243 MPa as the explosion space expands (0–5 m³). Furthermore, a nonlinear regression model is developed to predict peak perforating shock loads. The results indicate that residual perforation energy critically impacts tubing string safety. Validated against two field cases, the model achieves nearly 10% error compared to predictions from Pulsfrac (industry-standard perforating shock software), meeting field requirements while providing actionable insights for wellbore integrity and perforating tubing string stability. Full article

In this study, non-isothermal pyrolysis of a mixture of disposable surgical face masks (FMs) and nitrile gloves (NGs) was conducted, using a heating rate of 100 °C/min, N₂ flowrate of 100 mL/min, and temperatures between 500 and 800 °C. Condensable product yield peaked at 600 °C (76.9 wt.%), with gas yields rising to 31.0 wt.%, at 800 °C. GC-MS of the condensable product confirmed the presence of aliphatic compounds (>90%), while hydrogen, methane, and ethylene dominated the gas composition. At 600 °C, gasoline (C₄ to C₁₂)-, diesel (C₁₃ to C₂₀)-, motor oil (C₂₁ to C₃₅)-, and heavy hydrocarbon (C₃₅₊)-range compounds accounted for 23.7, 46.7, 12.5, and 17.1%, of the condensable product, respectively. Using model-free methods, the average activation energy and pre-exponential factor were found to be 309.7 ± 2.4 kJ/mol and 2.5 ± 3.4 × 10²⁵ s⁻¹, respectively, while a 2-dimensional diffusion mechanism was determined. Scale-up runs confirmed high yields of condensable product (60–70%), with comparable composition to that obtained from lab-scale tests. The pyrolysis oil exceeds acceptable oxygen, nitrogen, chlorine, and fluorine levels for industrial steam crackers—needing pre-treatment—while other contaminants like sulphur and metals could be managed through mild blending. In summary, this work offers a sustainable approach to address the environmental concerns surrounding disposable FMs and NGs. Full article

Produced water, a byproduct of oil and gas extraction, poses significant environmental challenges due to its complex composition and high salinity. Conventional treatment technologies often struggle to achieve efficient contaminant removal while maintaining long-term operational stability. Membrane-based separation processes, particularly forward osmosis (FO), offer a promising alternative due to their low hydraulic pressure requirements, high selectivity, and ability to mitigate fouling and scaling effects. This study fabricated and evaluated a novel dual-layer zwitterion-modified electrospun nanofibrous membrane for enhanced produced water (PW) treatment. The dual-layer design consists of a highly porous electrospun nanofibrous support layer for improved permeability and mechanical strength, coupled with a zwitterionic-modified selective layer to enhance antifouling properties and selective contaminant rejection. The zwitterionic surface modification imparts superior hydration capacity, reducing organic and biological fouling while improving water transport efficiency. The membranes are characterized using scanning electron microscopy (SEM), thermogravimetric analysis (TGA), Fourier Transform Infrared (FTIR) spectroscopy, X-ray diffraction (XRD), contact angle and tensile strength measurements, and nuclear magnetic resonance (NMR) spectroscopy to assess their morphological, structural, and chemical properties. The performance evaluations demonstrated significantly higher water flux (up to 16.05 L m⁻² h⁻¹ for SPW (synthetic produced water) and 6.00 L m⁻² h⁻¹ for PW using NaBr) and excellent solid rejection (up to 96.02% for SPW and 88.90% for PW), reduced concentration polarization, and superior antifouling performance compared to conventional FO membranes. Experimental results from bench-scale trials demonstrate that this advanced membrane technology offers enhanced water recovery and contaminant removal efficiency, making it a viable solution for industrial-scale PW treatment and reuse. The findings underscore the potential of next-generation dual-layer FO membranes in promoting sustainable water resource management within the oil and gas sector while minimizing environmental impact. Full article

The pronounced heterogeneity and geological complexity of low-permeability reservoirs pose significant challenges to parameter optimization and performance prediction during the development of CO₂ water-alternating-gas (CO₂-WAG) injection processes. This study introduces a predictive model based on the Extreme Gradient Boosting (XGBoost) algorithm, trained on 1225 multivariable numerical simulation cases of CO₂-WAG injection. To enhance the model’s performance, four advanced metaheuristic algorithms—Collective Parallel Optimization (CPO), Grey Wolf Optimization (GWO), Artificial Hummingbird Algorithm (AHA), and Black Kite Algorithm (BKA)—were applied for hyperparameter tuning. Among these, the CPO algorithm demonstrated superior performance due to its ability to balance global exploration with local exploitation in high-dimensional, complex optimization problems. Additionally, the integration of Chebyshev chaotic mapping and Elite Opposition-Based Learning (EOBL) strategies further improved the algorithm’s efficiency and adaptability, leading to the development of the ICPO (Improved Crowned Porcupine Optimization)-XGBoost model. Rigorous evaluation of the model, including comparative analyses, cross-validation, and real-case simulations, demonstrated its exceptional predictive capacity, with a coefficient of determination of 0.9894, a root mean square error of 2.894, and errors consistently within ±2%. These results highlight the model’s robustness, reliability, and strong generalization capabilities, surpassing traditional machine learning methods and other state-of-the-art boosting-based ensemble algorithms. In conclusion, the ICPO-XGBoost model represents an efficient and reliable tool for optimizing the CO₂-WAG process in low-permeability reservoirs. Its exceptional predictive accuracy, robustness, and generalization capability make it a highly valuable asset for practical reservoir management and strategic decision-making in the oil and gas industry. Full article

Kazakhstan, a fossil-fuel-dependent economy, faces growing pressure to reduce greenhouse gas emissions while maintaining industrial competitiveness. Carbon Capture, Utilization, and Storage (CCS/CCUS) technologies offer a viable pathway for decarbonizing hard-to-abate sectors, particularly in power generation, metallurgy, and oil and gas processing. This paper provides a comprehensive review of the state of CCS/CCUS technologies globally and examines their applicability within Kazakhstan. The study also explores long-term CO₂ storage mechanisms and monitoring frameworks, with attention to carbon leakage risks and the importance of addressing methane emissions. A critical part of the analysis is dedicated to Kazakhstan’s Emissions Trading System, identifying its current limitations such as low carbon prices, and limited sectoral coverage, and outlining practical reforms to enhance its role in supporting CCS/CCUS and broader decarbonization efforts. The integration of CCS/CCUS with a strengthened ETS, combined with access to international climate finance instruments and voluntary carbon markets, is proposed as a key strategy for Kazakhstan’s transition to a low-carbon economy. By linking engineering innovation with targeted policy interventions, this study offers a dual-perspective contribution. It not only provides technical insights into CCS/CCUS technologies but also presents policy recommendations that are specifically tailored to Kazakhstan’s context. The findings reinforce the role of CCS/CCUS as a crucial component of national climate strategy and industrial transformation. Full article

Recently, essential rose oils and rose products have gained increasing importance in both the cosmetic and food industries, as well as in the composition of medicinal products. We investigated the in vitro antiviral activity of essential oil and floral water from Rosa damascena Mill against herpes simplex virus type 1 (HSV-1) infection in rabbit retinal cells (RRCs). The composition of the main chemical components in the rose essential oil was determined by means of gas chromatographic analysis. The effect on the viral replication cycle was determined using the cytopathic effect (CPE) inhibition assay. The virucidal activity, the effect on the adsorption stage of the virus to the host cell, and the protective effect on healthy cells were evaluated using the endpoint dilution method. The effects were determined as deviation in the viral titer, Δlg, for the treated cells from the one for the untreated viral control. The identified main active components of rose oil are geraniol (28.73%), citronellol (21.50%), nonadecane (13.13%), nerol (5.51%), heneicosane (4.87%), nonadecene (3.93), heptadecane (2.29), farnesol (2.11%), tricosane (1.29%), eicosane (1.01%), and eugenol (0.85%). The results demonstrated that both rose products do not have a significant effect on the virus replication but directly affect the viral particles and reduce the viral titer by Δlg = 3.25 for floral water and by Δlg = 3.0 for essential oil. Significant inhibition of the viral adsorption stage was also observed, leading to a decrease in the viral titers by Δlg = 2.25 for floral water and by Δlg = 2.0 for essential oil. When pretreating healthy cells with rose products, both samples significantly protected them from subsequent infection with HSV-1. This protective effect was more pronounced for the oil (Δlg = 2.5) compared to the one for the floral water (Δlg = 2.0). We used the in silico molecular docking method to gain insight into the mechanism of hindrance of viral adsorption by the main rose oil compounds (geraniol, citronellol, nerol). These components targeted the HSV-1 gD interaction surface with nectin-1 and HVEM (Herpesvirus Entry Mediator) host cell receptors, at N-, C-ends, and N-end, respectively. These findings could provide a structural framework for further development of anti-HSV-1 therapeutics. Full article

Oil palm kernel shell is an abundant agricultural waste generated by the palm oil industry. To achieve sustainable use of this waste, oil palm kernel shells were converted into valuable resources as active biocarbons. A two-stage preparation method involving N₂ pyrolysis, followed by CO₂ activation, was used to produce the active biocarbon. The optimum pyrolysis conditions that produced the largest BET surface area of 519.1 m²/g were a temperature of 600 °C, a hold time of 2 h, a nitrogen flow rate of 150 cm³/min, and a heating rate of 10 °C/min. The optimum activation conditions to prepare the active biocarbon with the largest micropore surface area or the best micropore/BET surface area combination were a temperature of 950 °C, a CO₂ flow rate of 300 cm³/min, a heating rate of 10 °C/min, and a hold time of 3 h, yielding BET and micropore surface areas of 1232.3 and 941.0 m²/g, respectively, and consisting of 76.36% of micropores for the experimental optimisation technique adopted here. This study underscores the importance of optimising both the pyrolysis and activation conditions to produce an active biocarbon with a maximum micropore surface area for gaseous adsorption applications, especially to capture CO₂ greenhouse gas, to mitigate global warming and climate change. Such a comprehensive and detailed study on the conversion of oil palm kernel shell into active biocarbon is lacking in the open literature. The research results provide a practical blueprint on the process parameters and technical know-how for the industrial production of highly microporous active biocarbons prepared from oil palm kernel shells. Full article

Maintaining well integrity is essential in the oil and gas industry to prevent environmental hazards, operational risks, and economic losses. Cement bond log (CBL) tools are essential in evaluating cement bonding and ensuring wellbore stability. This study presents a patent landscape review of CBL technologies, based on 3473 patent documents from the Lens.org database. After eliminating duplicates and irrelevant entries, 167 granted patents were selected for in-depth analysis. These were categorized by technology type (wave, electrical, radiation, neutron, and other tools) and by material focus (formation, casing, cement, and borehole fluid). The findings reveal a dominant focus on formation evaluation (59.9%) and a growing reliance on wave-based (22.2%) and other advanced tools (25.1%), indicating a shift toward high-precision diagnostics. Geographically, 75% of granted patents were filed through the U.S. Patent and Trademark Office, and 97.6% were held by companies, underscoring the dominance of corporate innovation and the minimal presence of academia and individuals. The review also identifies notable patents that reflect significant technical innovations and discusses their role in advancing diagnostic capabilities. These insights emphasize the need for broader collaboration and targeted research to advance well integrity technologies in line with industry goals for operational performance and safety. Full article

Rotating compressors are foundational in various industrial processes, particularly in the oil-and-gas sector, where reliable fault detection is crucial for maintaining operational continuity. While Graph Attention Network (GAT) frameworks are widely available, this study advances the state of the art by introducing a Bayesian GAT method specifically tailored for vibration-based compressor fault diagnosis. The approach integrates domain-specific digital-twin simulations built with Rotordynamic software (1.3.0), and constructs dual adjacency matrices to encode both physically informed and data-driven sensor relationships. Additionally, a hybrid forecasting-and-reconstruction objective enables the model to capture short-term deviations as well as long-term waveform fidelity. Monte Carlo dropout further decomposes prediction uncertainty into aleatoric and epistemic components, providing a more robust and interpretable model. Comparative evaluations against conventional Long Short-Term Memory (LSTM)-based autoencoder and forecasting methods demonstrate that the proposed framework achieves superior fault-detection performance across multiple fault types, including misalignment, bearing failure, and unbalance. Moreover, uncertainty analyses confirm that fault severity correlates with increasing levels of both aleatoric and epistemic uncertainty, reflecting heightened noise and reduced model confidence under more severe conditions. By enhancing GAT fundamentals with a domain-tailored dual-graph strategy, specialized Bayesian inference, and digital-twin data generation, this research delivers a comprehensive and interpretable solution for compressor fault diagnosis, paving the way for more reliable and risk-aware predictive maintenance in complex rotating machinery. Full article

With the emergence of Survey 4.0, the oil and gas (O & G) industry is now considering spatial digital twins during their field design to enhance visualization, efficiency, and safety. O & G companies have already initiated investments in the research and development of spatial digital twins to build digital mining models. Existing studies commonly adopt surveys and case studies as their evaluation approach to validate the feasibility of spatial digital twins and related technologies. However, this approach requires high costs and resources. To address this gap, this study explores the feasibility of the informed argument method within the design science framework. A land survey data model (LSDM)-based digital twin prototype for O & G field design, along with 3D spatial datasets located in Lot 2 on RP108045 at petroleum lease 229 under the Department of Resources, Queensland Government, Australia, was selected as a case for this study. The ISO/IEC 25010 model was adopted as a methodology for this study to evaluate the prototype and Digital Twin Victoria (DTV). It encompasses eight metrics, such as functional suitability, performance efficiency, compatibility, usability, security, reliability, maintainability, and portability. The results generated from this study indicate that the prototype encompasses a standard level of all parameters in the ISO/IEC 25010 model. The key significance of the study is its methodological contribution to evaluating the spatial digital twin models through cost-effective means, particularly under circumstances with strict regulatory requirements and low information accessibility. Full article

Lightning represents a critical danger to facilities such as oil tank farms, with the potential to cause major explosive incidents. To address this risk, Indonesia’s oil and gas industry has adopted the NFPA 780 Standard for lightning protection systems. However, tank explosions and refinery disruptions caused by lightning strikes continue to occur annually, highlighting the need to reassess the standard’s self-protection criteria, particularly in Indonesia’s tropical climate. The NFPA 780 standard was primarily developed based on lightning characteristics in subtropical regions. This study evaluates its effectiveness in tropical environments, where lightning parameters such as peak currents, frequencies, and ground flash densities differ significantly. By analyzing specific incidents of tank explosions in Indonesia, the research reveals that compliance with the NFPA 780 standard alone may not be adequate to protect critical infrastructure. To address these challenges, this study proposes a novel approach to lightning protection by designing solutions tailored to the unique characteristics of tropical climates. By incorporating local lightning parameters, the proposed measures aim to enhance safety and resilience in oil and gas facilities. This research provides a framework for adapting international standards to regional needs, improving the effectiveness of lightning protection in tropical environments. Full article

Wax deposition, driven by the crystallization of long-chain n-alkanes, poses severe challenges across industries such as petroleum, oil and natural gas, food processing, and chemical manufacturing. This phenomenon compromises flow efficiency, increases energy demands, and necessitates costly maintenance interventions. Wax inhibitors, designed to mitigate these issues, operate by altering wax crystallization, aggregation, and adhesion over the pipelines. Classic wax inhibitors, comprising synthetic polymers and natural compounds, have been widely utilized due to their established efficiency and scalability. However, synthetic inhibitors face environmental concerns, while natural inhibitors exhibit reduced performance under extreme conditions. The advent of nano-based wax inhibitors has revolutionized wax management strategies. These advanced materials, including nanoparticles, nanoemulsions, and nanocomposites, leverage their high surface area and tunable interfacial properties to enhance efficiency, particularly in harsh environments. While offering superior performance, nano-based inhibitors are constrained by high production costs, scalability challenges, and potential environmental risks. In parallel, the development of “green” wax inhibitors derived from renewable resources such as vegetable oils addresses sustainability demands. These eco-friendly formulations introduce functionalities that reinforce inhibitory interactions with wax crystals, enabling effective deposition control while reducing reliance on synthetic components. This review provides a comprehensive analysis of the mechanisms, applications, and comparative performance of classic and nano-based wax inhibitors. It highlights the growing integration of sustainable and hybrid approaches that combine the reliability of classic inhibitors with the advanced capabilities of nano-based systems. Future directions emphasize the need for cost-effective, eco-friendly solutions through innovations in material science, computational modeling, and biotechnology. Full article

This study evaluates the risk assessment and hazard identification of hydrothermal liquefaction (HTL)-derived bio-oil from the MARINES project, which converts military organic waste into fuel. The high oxygen content (35–50 wt%), acidic pH (2–4), and viscosity (10–1000 cP) of bio-oils pose unique challenges, including oxidative polymerization, corrosion, and micro-explosions during combustion. Key hazards include storage instability, particulate emissions (20–30% higher than diesel), and aquatic toxicity (LC50 < 10 mg/L for phenolics). Mitigation strategies such as inert gas blanketing, preheating, and spill containment are proposed. While offering renewable fuel potential, HTL bio-oil demands rigorous safety protocols for military/industrial deployment, warranting further experimental validation. Full article

Barite, a mineral composed of barium sulphate, holds global significance due to its wide range of industrial applications. It plays a crucial role as a weighting agent in drilling fluids for the oil and gas industry, in radiation shielding, and as a filler in paints and plastics. Although there are significant deposits of the mineral in commercial quantities in Nigeria, the use of barite of Nigerian origin has been low in the industry due to challenges that require further research and development. This research employed nanoindentation experiments using a model Ti950 Tribo indenter instrument equipped with a diamond Berkovich tip. Using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX), we gained information about the structure and elements in the samples. The load–displacement curves were examined to determine the hardness and reduced elastic modulus of the barite samples. The SEM images showed that barite grains have a typical grainy shape, with clear splitting lines and sizes. XRD and EDX analysis confirmed that the main components are chlorite, albite, barium, and oxygen, along with small impurities like silicon and calcium from quartz and calcite. The average hardness of the IB3 and IB4 samples was 1.88 GPa and 1.18 GPa, respectively, meaning that the IB3 sample will need more energy to crush because its hardness is within the usual barite hardness range of 1.7 GPa to 2.0 GPa. The findings suggest further beneficiation processes to enhance the material’s suitability for drilling and other applications. Full article