Search Results (137)

The stability of nitrogen gas foam hinders its applicability in petroleum applications. Fly ash nanoparticles and clay improve the N₂ foam stability, and flue gas foams provide a cost-effective solution for carbon capture, utilization, and storage (CCUS). This study examines the stability, volume, and bubble structure of foams formed using two anionic surfactants, sodium dodecyl sulfate (SDS) and sodium dodecylbenzene sulfonate (SDBS), along with the cationic surfactant cetyltrimethylammonium bromide (CTAB), selected for their comparable interfacial tension properties. Analysis of foam stability and volume and bubble structure was conducted under different CO₂/N₂ mixtures, with half-life and initial foam volume serving as the evaluation criteria. The impact of fly ash and clay on SDS-N₂ foam was also evaluated. The results showed that foams created with CTAB, SDBS, and SDS exhibit the greatest stability in pure nitrogen, attributed to low solubility in water and limited gas diffusion. SDS showed the highest foam strength attributable to its comparatively low surface tension. The addition of fly ash and clay significantly improved foam stability by migrating to the gas–liquid interface, creating a protective barrier that reduced drainage. Both nano fly ash and clay improved the half-life of nitrogen foam by 11.25 times and increased the foam volume, with optimal concentrations identified as 5.0 wt% for fly ash and 3.0 wt% for clay. This research emphasizes the importance of fly ash nanoparticles in stabilizing foams, therefore optimizing a foam system for enhanced oil recovery (EOR). Full article

Natural vaporization in LPG (liquefied petroleum gas) tanks refers to the process where liquid LPG is converted to vapor naturally due to ambient heat. This natural vaporization process relies on ambient heat from the surroundings, which is transferred through the walls of the LPG tank. The natural vaporization rate depends on several factors, such as the ambient temperature, the surface area of the tank in contact with the liquid (i.e., the filling fraction), the exact composition of LPG, and the design and positioning of the LPG tank. When natural vaporization rates cannot meet the gas demand, as in the case of colder climates and large commercial applications, an additional LPG vaporizer will be necessary. The obtained results revealed that pure propane at an operating pressure of 1.75 bar achieves specific vaporization rates per unit of tank surface area of 0.7 kg/h/m², which decreases to 0.4 and 0.25 kg/h/m² for LPG mixtures with 20% and 40% butane, respectively. For a lower operating pressure of 1.10 bar, the specific vaporization rate per unit of tank surface area is 1.0 kg/h/m² for pure propane, 0.85 kg/h/m² for 20% butane, and 0.70 kg/h/m² for 40% butane. Full article

Petroleum-based insulating liquids have traditionally been used in the electrical industry for cooling and insulation. However, their environmental drawbacks, such as non-biodegradability and ecological risks, have led to increasing regulatory restrictions. As a sustainable alternative, vegetable-based insulating liquids have gained attention due to their biodegradability, non-toxicity to aquatic and terrestrial ecosystems, and lower carbon emissions. Adopting vegetable-based insulating liquids also aligns with United Nations Sustainable Development Goals (SDGs) 7 and 13, which focus on cleaner energy sources and reducing carbon emissions. Despite these benefits, most commercially available vegetable-based insulating liquids are derived from edible seed oils, raising concerns about food security and the environmental footprint of large-scale agricultural production, which contributes to greenhouse gas emissions. In recent years, waste cooking oils (WCOs) have emerged as a promising resource for industrial applications through waste-to-value conversion processes. However, their potential as transformer insulating liquids remains largely unexplored due to limited research and available data. This review explores the feasibility of utilizing waste cooking oils as green transformer insulating liquids. It examines the conversion and purification processes required to enhance their suitability for insulation applications, evaluates their dielectric and thermal performance, and assesses their potential implementation in transformers based on existing literature. The objective is to provide a comprehensive assessment of waste cooking oil as an alternative insulating liquid, highlight key challenges associated with its adoption, and outline future research directions to optimize its properties for high-voltage transformer applications. Full article

Carbon Capture and Storage (CCS) is a key technology for reducing anthropogenic greenhouse gas emissions, in which pipelines play a vital role in transporting CO₂ captured from industrial emitters to geological storage sites. To aid the efficient and safe operation of the CO₂ transport infrastructure, robust, accurate, and reliable solutions for monitoring pipelines transporting industrial CO₂ streams are urgently needed. This literature review study summarizes the monitoring objectives and identifies the problems and relevant mathematical algorithms developed for optimization of monitoring systems for pipeline transportation of water, oil, and natural gas, which can be relevant to the future CO₂ pipelines and pipeline networks for CCS. The impacts of the physical properties of CO₂ and complex designs and operation scenarios of CO₂ transport on the pipeline monitoring systems design are discussed. It is shown that the most relevant to liquid- and dense-phase CO₂ transport are the sensor placement optimization methods developed in the context of detecting leaks and flow anomalies for water distribution systems and pipelines transporting oil and petroleum liquids. The monitoring solutions relevant to flow assurance and monitoring impurities in CO₂ pipelines are also identified. Optimizing the CO₂ pipeline monitoring systems against several objectives, including the accuracy of measurements, the number and type of sensors, and the safety and environmental risks, is discussed. Full article

Petroleum is an indispensable energy source in modern industrial society, and maintaining the safe and stable operation of its injection and production system is of great significance. To analyze the mechanism of pipeline damage caused by corrosion and scaling in the injection production system, taking a water injection pipeline in an oil field as an example, the causes of corrosion and scaling damage were studied by detecting pipeline samples and analyzing corrosion products and various service conditions of the pipeline. The results showed that there was more scaling on the inner wall of the pipeline, and there was local corrosion in the pipeline sections that had experienced water injection, shutdown, and gas injection conditions, while there was no significant corrosion thinning in the pipeline sections that had only experienced water injection and shutdown conditions. The scale layer formed under water injection conditions is mainly composed of barium strontium sulfate (Ba_0.75Sr_0.25SO₄), barium sulfate (BaSO₄) and a small amount of silica (SiO₂). The main reason for scale formation is the high content of barium ions (Ba²⁺) in the injected water. The corrosion products formed under gas injection conditions, including strontium ions (Sr²⁺) and sulfate ions (SO₄²⁻), are mainly composed of ferrous carbonate (FeCO₃) and ferric oxide (Fe₂O₃). The pipeline corrosion product FeCO₃ is mainly caused by carbon dioxide (CO₂) in the medium. In addition, the high liquid content, cecal position, high Cl⁻ (chloride ion) content, and slightly acidic environment in the pipeline also accelerate the occurrence of corrosion damage. The Fe₂O₃ in the corrosion products is formed when the pipeline is exposed to air after sampling, and is not the main cause of pipeline corrosion. Full article

With the global emphasis on sustainable growth and development, the depletion of natural energy reserves due to reliance on fossil fuels and non-renewable sources remains a critical concern. Despite strides in transitioning to electrical mobility, rural and agricultural communities depend heavily on liquefied petroleum gas and firewood for cooking, lacking viable, sustainable alternatives. This study focuses on community-led efforts to advance biogas adoption, providing an eco-friendly and reliable energy alternative for rural and farming households. By designing and developing balloon-type anaerobic biodigesters, this initiative provides a robust, cost-effective, and scalable method to convert farm waste into biogas for household cooking. This approach reduces reliance on traditional fuels, mitigating deforestation and improving air quality, and generates organic biofertilizer as a byproduct, enhancing agricultural productivity through organic farming. The study focuses on optimizing critical parameters, including the input feed rate, gas production patterns, holding time, biodigester health, gas quality, and liquid manure yield. Statistical tools, such as descriptive analysis, regression analysis, and ANOVA, were employed to validate and predict biogas output data based on experimental and industrial-scale data. Artificial neural networks (ANNs) were also utilized to model and predict outputs, inspired by the information processing mechanisms of biological neural systems. A comprehensive database was developed from experimental and literary data to enhance model accuracy. The results demonstrate significant improvements in cooking practices, health outcomes, economic stability, and solid waste management among beneficiaries. The integration of statistical analysis and ANN modeling validated the biodigester system’s effectiveness and scalability. This research highlights the potential to harness renewable energy to address socio-economic challenges in rural areas, paving the way for a sustainable, equitable future by fostering environmentally conscious practices, clean energy access, and enhanced agricultural productivity. Full article

Background: Exposure to household air pollution (HAP) is one of the primary risk factors for acute lower respiratory infection (ARI) morbidity and mortality among children in low-income settings. This study aimed to examine the relative contribution of residing in deprived neighbourhoods and exposure to HAP on the occurrence of ARI among children using data from the 2014–2015 Chad Demographic and Health Survey (DHS). Methods: We applied multilevel modelling techniques to survey data of 2882 children from 372 communities to compute the odds ratio (OR) for the occurrence of ARI between children of respondents exposed to clean fuels (e.g., electricity, liquid petroleum gas, natural gas, and biogas) and respondents exposed to polluting fuel (e.g., kerosene, coal/lignite, charcoal, wood, straw/shrubs/grass, and animal dung). Results: The results showed that children exposed to household polluting fuels in Chad were 215% more likely to develop ARI than those not exposed to household air pollution (OR = 3.15; 95% CI 2.41 to 4.13). Further analysis revealed that the odds of ARI were 185% higher (OR = 2.85; 95% CI 1.73 to 4.75) among children living in rural residents and those born to teenage mothers (OR = 2.75; 95% CI 1.48 to 5.15) who were exposed to household polluting fuels compared to their counterparts who were not exposed. In summary, the results of the study show that the risk of ARI is more common among children who live in homes where household air-polluting cooking fuel is widely used, those living in rural areas, those living in socioeconomically deprived neighbourhoods and from the least wealthy households, and those born to teenage mothers in Chad. Conclusions: In this study, an independent relative contribution of variables, such as HAP from cooking fuel, neighbourhood deprivation, living in rural areas, being from a low-income household, having a mother who is a manual labourer worker, and being given birth to by a teenage mother, to the risk of ARI among children is established. Full article

The chemical composition and molecular structure of the pitch-like products obtained by liquid-phase reaction of bituminous coal with heavy hydrocarbon fractions of coal and petroleum origin as solvents at a moderate temperature were comprehensively characterized in terms of a new aromatic feedstock for needle coke and other valuable high-tech carbon materials. The molecular parameters of the products were characterized by using FTIR, ¹H NMR, ¹³C NMR and XPS. Liquid-phase chromatography was used to analyze benzo(a)pyrene (BaP) as a carcinogenicity marker. The chemical composition and the characteristics of the molecular structure of the products were shown to depend greatly on the solvent used. The product obtained using coal tar as a solvent was highly aromatic, its polyaromatic nuclei consisted predominantly of protonated and pericondensed cycles sparsely substituted by CH₃ and occasionally CH₂ groups. The product obtained using petroleum-derived heavy gas oil as solvent was much less aromatic and prone to autogenous surface oxidation. Its aromatic nuclei contained mainly protonated and highly alkylated catacondensed chains. The intermediate structural parameters were characteristic of the product obtained using binary solvent. A remarkable feature of the pitch-like products obtained was a reduced BaP concentration (up to 40 times compared to typical coal-tar pitch). In terms of the molecular structure, the pitch-like products obtained by low-temperature dissolution of coal can serve as a new polyaromatic feedstock with a reduced carcinogenicity for the production of valuable high-tech carbon materials, needle coke, in particular. Full article

Electric Submersible Pumps (ESPs) play a pivotal role in the petroleum industry, but their performance is significantly affected by factors such as oil viscosity, gas–liquid ratios, and solid content. Traditional performance prediction methods, including polynomial fitting and mechanistic modeling, often lack adaptability and efficiency, requiring extensive empirical testing. This study leverages experimental data from the viscous and gas–liquid flow tests reported in the literature to benchmark various prediction methods. This research provides a comparative analysis of traditional curve-fitting methods, mechanistic modeling, and seven machine learning approaches. A key innovation of this study is an in-depth sensitivity analysis of different machine learning methods, especially focused on neural network parameters, such as activation functions and training configurations, to assess their impact on prediction accuracy and identify optimal network designs. Furthermore, a pump testing methodology is introduced to significantly reduce testing costs while maintaining a high prediction accuracy. The findings demonstrate the advantages of machine learning over traditional methods, including an enhanced prediction accuracy, practical guidelines for efficient parameter tuning, and the ability to address incomplete pump curve data. These contributions not only highlight the value of integrating machine learning into ESP modeling and operational workflows but also pave the way for future advancements in universal modeling frameworks for diverse ESP applications. Full article

This study develops a Green Vehicle Routing Problem (GVRP) model to address key logistics challenges, including time windows, simultaneous pickup and delivery, heterogeneous vehicle fleets, and multiple trip allocations. The model incorporates emissions-related costs, such as carbon taxes, to encourage sustainable supply chain operations. Emissions are calculated based on the total shipment weight and the travel distance of each vehicle. The objective is to minimize operational costs while balancing economic efficiency and environmental sustainability. A Genetic Algorithm (GA) is applied to optimize vehicle routing and allocation, enhancing efficiency and reducing costs. A Liquid Petroleum Gas (LPG) distribution case study in Yogyakarta, Indonesia, validates the model’s effectiveness. The results show significant cost savings compared to current route planning methods, alongside a slight increase in carbon. A sensitivity analysis was conducted by testing the model with varying numbers of stations, revealing its robustness and the impact of the station density on the solution quality. By integrating carbon taxes and detailed emission calculations into its objective function, the GVRP model offers a practical solution for real-world logistics challenges. This study provides valuable insights for achieving cost-effective operations while advancing green supply chain practices. Full article

A comprehensive understanding of the compositions and physicochemical properties of coal-based liquids is conducive to the rapid development of multipurpose, high-performance, and high-value functional chemicals. However, because of their complex compositions, coal-based liquids generate two-dimensional gas chromatography (GC × GC) chromatograms that are very complex and very time consuming to analyze. Therefore, the development of a method for accurately and rapidly analyzing chromatograms is crucial for understanding the chemical compositions and structures of coal-based liquids, such as direct coal liquefaction (DCL) oils and coal tar. In this study, DCL oils were distilled and qualitatively analyzed using GC × GC chromatograms. A deep-learning (DL) model was used to identify spectral features in GC × GC chromatograms and predominantly categorize the corresponding DCL oils as aliphatic alkanes, cycloalkanes, mono-, bi-, tri-, and tetracyclic aromatics. Regional labels associated with areas in the GC × GC chromatograms were fed into the mask-region-based convolutional neural network’s (Mask R-CNN’s) algorithm. The Mask R-CNN accurately and rapidly segmented the GC × GC chromatograms into regions representing different compounds, thereby automatically qualitatively classifying the compounds according to their spots in the chromatograms. Results show that the Mask R-CNN model’s accuracy, precision, recall, F1 value, and Intersection over Union (IoU) value were 93.71%, 96.99%, 96.27%, 0.95, and 0.93, respectively. DL is effective for visually comparing GC × GC chromatograms to analyze the compositions of chemical mixtures, accelerating GC × GC chromatogram interpretation and compound characterization and facilitating comparisons of the chemical compositions of multiple coal-based liquids produced in the coal and petroleum industry. Applying DL to analyze chromatograms improves analysis efficiency and provides a new method for analyzing GC × GC chromatograms, which is important for fast and accurate analysis. Full article

The deposition of asphaltenes in the petroleum industry has been found to be a significant factor affecting the profitability of petroleum production and refining. For this reason, many efforts have been made to clarify the mechanism of deposition formation and to find measures to reduce its harmful impact on the efficiency of oil production and refining. Recent reports on the mechanism of deposit formation by asphaltenes suggest that it is a phase transition phenomenon. Many studies have shown that this process can be slowed by using chemical inhibitors. Different classes of chemical substances (non-polymeric, organic compounds, polymers, ionic liquids and nanomaterials) have been found to be capable of inhibiting asphaltene precipitation. This paper presents a comprehensive review of asphaltene deposition research and makes an attempt to decipher the convoluted asphaltene deposition phenomena and relate the chemistry of asphaltene inhibitors to the nature of treated petroleum oils. The choice of appropriate additives to mitigate asphaltene deposition in commercial oil and gas facilities requires comprehensive knowledge of chemistry of oils, asphaltenes, and the chemical substances, along with the appropriate laboratory techniques that best mimic the commercial operation conditions. Full article

Gas hydrate formation in pipelines transporting multiphase fluids from petroleum reservoirs can lead to the formation of blockages, representing a significant flow assurance challenge. Key issues caused by hydrates include substantial increases in the viscosity of mixed liquid phases and the deposition of hydrates on the pipeline wall. This study compares two existing transient multiphase flow simulators, OLGA and LedaFlow, in terms of their estimation of hydrate formation effects on multiphase flow. Here, we compared in detail the hydrate kinetic models, parameters used, and initial condition setup approaches that influence hydrate formation and affect multiphase flow properties. Based on the comparison between the simulation results, it was found that using both simulators with default setups may not lead to comparable results under certain conditions. Adjusting input parameters, such as the stoichiometric coefficient and hydrate formation enthalpy, is necessary in order to obtain equivalent results. Hydrate modules in both simulators have also been applied to a field case. With appropriate setup, OLGA and LedaFlow produce comparable results during steady-state simulations, which align with field observations. This work provides guidelines for setting up OLGA and LedaFlow simulation models to obtain equivalent results. Full article

Electrostatic is generated through friction or contact between certain materials—a process that frequently occurs in industries such as manufacturing, logistics, electronics, chemicals, petroleum, and gas. In particular, in industries dealing with flammable materials—such as petrochemicals, refining, energy, semiconductors, and electronics—electrostatic can pose a fire or explosion risk, highlighting the critical importance of implementing electrostatic control and preventive measures. To manage electrostatic at a safe level, it is crucial to prevent charge accumulation that would lead to high charging voltages. This study developed a streaming electrification generator that considers the flow conditions of non-conductive flammable liquids, allowing observation, comparison, and analysis of electrostatic charging characteristics. Specifically, to determine conditions that create fire and explosion hazard atmospheres, measurements of charging voltage, discharging current, and charging electric charge were obtained and analyzed under various experimental conditions. A comparative analysis of various electrostatic charging characteristics revealed that, in certain cases, increasing the temperature of a flowing liquid may actually decrease the charging voltage depending on the properties of the pipeline material. By considering not only the decrease in liquid conductivity with temperature changes but also the variation in the work function of solid materials, the underlying causes of the observed results can be understood. The experimental results derived from this study provide concrete and reliable data essential for controlling and managing electrostatic at a safe level and are expected to serve as a foundational resource to more clearly identify electrostatic risks in industrial safety management. Full article

Light non-aqueous phase liquids (LNAPLs), which include various petroleum products, are a significant source of groundwater contamination globally. Once introduced into the subsurface, these contaminants tend to accumulate in the vadose zone, causing chronic soil and water pollution. The vadose zone often contains lens-shaped bodies with diverse properties that can significantly influence the migration and distribution of LNAPLs. Understanding the interaction between LNAPLs and these lens-shaped bodies is crucial for developing effective environmental management and remediation strategies. Prior research has primarily focused on LNAPL behavior in homogeneous media, with less emphasis on the impact of heterogeneous conditions introduced by lens-shaped bodies. To investigate the impact of lens-shaped structures on the migration of LNAPLs and to assess the specific effects of different types of lens-shaped structures on the distribution characteristics of LNAPL migration, this study simulates the LNAPL leakage process using an indoor two-dimensional sandbox. Three distinct test groups were conducted: one with no lens-shaped aquifer, one with a low-permeability lens, and one with a high-permeability lens. This study employs a combination of oil front curve mapping and high-density resistivity imaging techniques to systematically evaluate how the presence of lens-shaped structures affects the migration behavior, distribution patterns, and corresponding resistivity anomalies of LNAPLs. The results indicate that the migration rate and distribution characteristics of LNAPLs are influenced by the presence of a lens in the gas band of the envelope. The maximum vertical migration distances of the LNAPL are as follows: high-permeability lens (45 cm), no lens-shaped aquifer (40 cm), and low-permeability lens (35 cm). Horizontally, the maximum migration distances of the LNAPL to the upper part of the lens body decreases in the order of low-permeability lens, high-permeability lens, and no lens-shaped aquifer. The low-permeability lens impedes the vertical migration of the LNAPL, significantly affecting its migration path. It creates a flow around effect, hindering the downward migration of the LNAPL. In contrast, the high-permeability lens has a weaker retention effect and creates preferential flow paths, promoting the downward migration of the LNAPL. Under conditions with no lens-shaped aquifer and a high-permeability lens, the region of positive resistivity change rate is symmetrical around the axis where the injection point is located. Future research should explore the impact of various LNAPL types, lens geometries, and water table fluctuations on migration patterns. Incorporating numerical simulations could provide deeper insights into the mechanisms controlling LNAPL migration in heterogeneous subsurface environments. Full article