Search Results (673)

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

One of the most important challenges the tire industry faces is becoming carbon-neutral and using 100% sustainable materials by 2050. Utilizing materials from renewable sources and recycled substances is a key aspect of achieving this goal. Petroleum-based oils, such as Treated Distillate Aromatic Extract (TDAE), are frequently used in rubber compounds, and a promising strategy to enhance sustainability is to use bio-based plasticizer alternatives. However, research has shown that the replacement of TDAE oil with bio-based oils or resins can significantly alter the glass transition temperature (T_g) of the final compound, influencing the tire properties. In this study, the theory was proposed that using a plasticizer blend, comprising oil and resin, in a rubber compound would result in similar T_g values as the reference compound containing TDAE. To test this, the cycloaliphatic di-ester oil Hexamoll DINCH, which can be made out of bio-based feedstock by the BioMass Balance approach, was selected and blended with the cycloaliphatic hydrocarbon resin Escorez 5300. Various oil-to-resin ratios were investigated, and a linear increase in the T_g of the vulcanizate was obtained when increasing the resin content and decreasing the oil content. Additionally, a 50/50 blend, consisting of 18.75 phr Hexamoll DINCH and 18.75 phr Escorez 5300, resulted in the same T_g of −19 °C as a compound containing 37.5 phr TDAE. Furthermore, this blend resulted in similar curing characteristics and cured Payne effect as the reference with TDAE. Moreover, a similar rolling resistance indicator (tan δ at 60 °C = 0.115), a slight deterioration in wear resistance (ARI = 83%), but an improvement in the stress–strain behavior (M300 = 9.18 ± 0.20 MPa and Ts = 16.3 ± 0.6 MPa) and wet grip indicator (tan δ at 0 °C = 0.427) were observed. The results in this work show the potential of finding a balance between optimal performance and sustainability by using plasticizer blends. Full article

This paper presents a comprehensive study of torsional stick–slip vibrations in rotary drilling systems through a comparison between two lumped parameter models with differing complexity: a simple two-degree-of-freedom (2-DOF) model and a complex high-degree-of-freedom (high-DOF) model. The two models are developed under identical boundary conditions and consider an identical nonlinear friction torque dynamic involving the Stribeck effect and dry friction phenomena. The high-DOF model is calculated with the Finite Element Method (FEM) to enable accurate simulation of the dynamic behavior of the drill string and accurate representation of wave propagation, energy build-up, and torque response. Field data obtained from an Algerian oil well with Measurement While Drilling (MWD) equipment are used to guide modeling and determine simulations. According to the findings, the FEM-based high-DOF model demonstrates better performance in simulating basic stick–slip dynamics, such as drill bit velocity oscillation, nonlinear friction torque formation, and transient bit-to-surface contacts. On the other hand, the 2-DOF model is not able to represent these effects accurately and can lead to inappropriate control actions and mitigation of vibration severity. This study highlights the importance of robust model fidelity in building reliable real-time rotary drilling control systems. From the performance difference measurement between low-resolution and high-resolution models, the findings offer valuable insights to optimize drilling efficiency further, minimize non-productive time (NPT), and improve the rate of penetration (ROP). This contribution points to the need for using high-fidelity models, such as FEM-based models, in facilitating smart and adaptive well control strategies in modern petroleum drilling engineering. Full article

The increasing levels of ozone pollution have become a significant environmental issue in urban areas worldwide. Previous studies have confirmed that the urban ozone pollution in China is mainly controlled by volatile organic compounds (VOCs) rather than nitrogen oxides. Therefore, a study on the emission characteristics and source analysis of VOCs is important for controlling urban ozone pollution. In this study, hourly concentrations of 57 VOC species in four groups were obtained in April 2022, a period of high ozone pollution in Kunming, China. The ozone formation potential analysis showed that the accumulated reactive VOCs significantly contributed to the subsequent ozone formation, particularly aromatics (44.16%) and alkanes (32.46%). In addition, the ozone production rate in Kunming is mainly controlled by VOCs based on the results of the empirical kinetic modeling approach (K_NOx/K_VOCs = 0.25). The hybrid single-particle Lagrangian integrated trajectory model and polar coordinate diagram showed high VOC and ozone concentrations from the southwest outside the province (50.28%) and the south in local areas (12.78%). Six factors were obtained from the positive matrix factorization model: vehicle exhaust (31.80%), liquefied petroleum gas usage (24.16%), the petrochemical industry (17.81%), fuel evaporation (11.79%), coal burning (7.47%), and solvent usage (6.97%). These findings underscore that reducing anthropogenic VOC emissions and strengthening controls on the related sources could provide a scientifically robust strategy for mitigating ozone pollution in Kunming. Full article

Lithology identification is one of the most important research areas in petroleum engineering, including reservoir characterization, formation evaluation, and reservoir modeling. Due to the complex structural environment, diverse lithofacies types, and differences in logging data and core data recording standards, there is significant overlap in the logging responses between different lithologies in the second member of the Lucaogou Formation in the Santanghu Basin. Machine learning methods have demonstrated powerful nonlinear capabilities that have a strong advantage in addressing complex nonlinear relationships between data. In this paper, based on felsic content, the lithologies in the study area are classified into four categories from high to low: tuff, dolomitic tuff, tuffaceous dolomite, and dolomite. We also study select logging attributes that are sensitive to lithology, such as natural gamma, acoustic travel time, neutron, and compensated density. Using machine learning methods, XGBoost, random forest, and support vector regression were selected to conduct lithology identification and favorable reservoir prediction in the study. The prediction results show that when trained with 80% of the predictors, the prediction performance of all three models has improved to varying degrees. Among them, Random Forest performed best in predicting felsic content, with an MAE of 0.11, an MSE of 0.020, an RMSE of 0.14, and a R² of 0.43. XGBoost ranked second, with an MAE of 0.12, an MSE of 0.022, an RMSE of 0.15, and an R² of 0.42. SVR performed the poorest. By comparing the actual core data with the predicted data, it was found that the results are relatively close to the XRD results, indicating that the prediction accuracy is high. Full article

This study aims to provide a comprehensive overview of the application of artificial intelligence (AI) methods to solve real-world problems in the oil and gas sector. The methodology involved a two-step process for analyzing AI applications. In the first step, an initial exploration of scientific articles in the Scopus database was conducted using keywords related to AI and computational intelligence, resulting in a total of 11,296 articles. The bibliometric analysis conducted using VOS Viewer version 1.6.15 software revealed an average annual growth of approximately 15% in the number of publications related to AI in the sector between 2015 and 2024, indicating the growing importance of this technology. In the second step, the research focused on the OnePetro database, widely used by the oil industry, selecting articles with terms associated with production and drilling, such as “production system”, “hydrate formation”, “machine learning”, “real-time”, and “neural network”. The results highlight the transformative impact of AI on production operations, with key applications including optimizing operations through real-time data analysis, predictive maintenance to anticipate failures, advanced reservoir management through improved modeling, image and video analysis for continuous equipment monitoring, and enhanced safety through immediate risk detection. The bibliometric analysis identified a significant concentration of publications at Society of Petroleum Engineers (SPE) events, which accounted for approximately 40% of the selected articles. Overall, the integration of AI into production operations has driven significant improvements in efficiency and safety, and its continued evolution is expected to advance industry practices further and address emerging challenges. Full article

The study examined the relations and Granger causality among environmental pollution, air quality, life expectancy, religious tourism, petroleum consumption and economic growth in three countries, Italy, Saudi Arabia and Türkiye, three countries with a prominent role of religious tourism, given the high shares of religious tourism revenues in their economies and due to pilgrimage-type religious tourism activities in total tourism activities. The study employed a yearly sample of 1975–2019 and novel Fourier-augmented vector autoregressive and Fourier Granger causality tests, under the structural breaks in the data. The findings indicate negative effects on environmental pollution and air quality from tourism in addition to such effects on life expectancy in all countries analyzed, and in this relation, fossil fuel consumption in these nations and its acceleration with tourism play crucial roles. These effects are amplified by economic growth coupled with tourism revenues that go in hand with high fossil fuel consumption, which further worsen the impacts on the environment. In the causality testing stage, the results determined unidirectional causality from tourism, fossil fuel energy consumption, and economic growth to both carbon dioxide emissions and to particulate matter 2.5. These effects are also reinforced by feedback effects between air pollution and life expectancy, which enhance the effects on both environment and air quality. These findings are used to suggest important policy recommendations, among which, the reduction in high dependency on fossil fuel in the energy mix is most central. Equally, policies are suggested to encourage sustainable tourism to reverse the adverse effects on health, environmental degradation and worsened air quality in these nations. Full article

It has been proven that the performance of fluid catalytic cracking (FCC), as the most important oil refining process for converting low-value heavy oils into high-value transportation fuels, light olefins, and feedstocks for petrochemicals, depends strongly on the quality of the feedstock. For this reason, characterization of feedstocks and their relationships to FCC performance are issues deserving special attention. This study systematically reviews various publications dealing with the influence of feedstock characteristics on FCC performance, with the aim of identifying the best characteristic descriptors allowing prediction of FCC feedstock cracking capability. These characteristics were obtained by mass spectrometry, SARA analysis, elemental analysis, and various empirical methods. This study also reviews published research dedicated to the catalytic cracking of biomass and waste oils, as well as blends of petroleum-derived feedstocks with sustainable oils, with the aim of searching for quantitative relationships allowing prediction of FCC performance during co-processing. Correlation analysis of the various FCC feed characteristics was carried out, and regression techniques were used to develop correlations predicting the conversion at maximum gasoline yield and that obtained under constant operating conditions. Artificial neural network (ANN) analysis and nonlinear regression techniques were applied to predict FCC conversion from feed characteristics at maximum gasoline yield, with the aim of distinguishing which technique provided the more accurate model. It was found that the correlation developed in this work based on the empirically determined aromatic carbon content according to the n-d-M method and the hydrogen content calculated via the Dhulesia correlation demonstrated highly accurate calculation of conversion at maximum gasoline yield (standard error of 1.3%) compared with that based on the gasoline precursor content determined by mass spectrometry (standard error of 1.5%). Using other data from 88 FCC feedstocks characterized by hydrogen content, saturates, aromatics, and polars contents to develop the ANN model and the nonlinear regression model, it was found that the ANN model demonstrated more accurate prediction of conversion at maximum gasoline yield, with a standard error of 1.4% versus 2.3% for the nonlinear regression model. During the co-processing of petroleum-derived feedstocks with sustainable oils, it was observed that FCC conversion and yields may obey the linear mixing rule or synergism, leading to higher yields of desirable products than those calculated according to the linear mixing rule. The exact reason for this observation has not yet been thoroughly investigated. Full article

Groundwater sustains ecosystems, agriculture, and human consumption; therefore, its interaction with hydrocarbons is an important area of research under the umbrella of environmental science and resource exploration. Naturally occurring or anthropogenically introduced hydrocarbons can significantly impact groundwater through complex geochemical processes such as dissolution, adsorption, biodegradation, and redox reactions and can also affect groundwater chemistry in terms of pH, redox potential, dissolved organic carbon, and trace element concentrations. Accurate determination and identification of hydrocarbon contaminants requires advanced analytical methods like gas chromatography, GC–MS, and fluorescence spectroscopy, complemented with isotopic analysis and microbial tracers, which provide insights into sources of contamination and biodegradation pathways. The presence of hydrocarbons in groundwater is a matter of environmental concern but can also valuable data for petroleum exploration, tracing subsurface reservoirs and seepage pathways. This paper refers to the basic need for geochemical investigations combined with advanced detection techniques for successful regulation of thermal–mineral groundwater quality. This contributes towards successful sustainable hydrocarbon resource exploration and water resource conservation, with emphasis on the relationship between groundwater quality and hydrocarbon exploration. The study points out the significance of continuous observation of thermal mineral waters to identify their connection with the specific hydrocarbons of each study area. Full article

This research work seeks to introduce eco-friendly, low-carbon, and high-octane biofuel gasoline production using a synergistic approach. Four types of high-octane gasoline, including SynergyFuel-92, SynergyFuel-95, SynergyFuel-98, and SynergyFuel-100, were generated, emphasizing the deliberate combination of petroleum-derived gasoline fractions using reformate, isomerate, and delayed coking (DC) naphtha with octane-boosting compounds—bio-methanol and bio-ethanol. A set of tests have been performed to examine the effects of antiknock properties, density, oxidation stability, distillation range characteristics, hydrocarbon composition, vapor pressure, and the volatility index on gasoline blends. The experimental results indicated that the gasoline blends made from biofuel (SynergyFuel-92, -95, -98, and 100) showed adherence to important fuel quality criteria in the USA, Europe, and China. These blends had good characteristics, such as low quantities of benzene and sulfur, regulated levels of olefins and aromatics, and good distillation qualities. By fulfilling these strict regulations, Synergy Fuel is positioned as a competitive and eco-friendly substitute for traditional gasoline. The results reported that SynergyFuel-100 demonstrated the strongest hot-fuel-handling qualities and resistance to vapor lock among all the mentioned Synergy Fuels. Finally, the emergence of eco-friendly, low-carbon, and high-octane biofuel gasoline production with synergistic benefits is a big step in the direction of sustainable transportation. Full article

Bio-polyurethane foam was synthesized in this study using bio-polyol derived from liquefied waste wood as a sustainable alternative to petroleum-based polyols. It has been widely reported that polyurethane foams incorporating liquefied wood exhibit biodegradability when buried in soil, with assessments typically relying on CO₂ emission measurements in a close system. However, this method cannot obtain any chemical bonding breakage information of the bio-polyurethane foam. On the other hand, our study investigated the biodegradation process by employing an elemental composition analysis using a CHN coder and functional group analysis through Fourier transform infrared (FT-IR) spectroscopy to capture chemical structure changing. The results demonstrated that biodegradation occurs in three different stages over time, even in the absence of significant early-stage weight loss. The gradual breakdown of urethane bonds was confirmed through changes in the elemental composition and functional group ratios, providing a more detailed understanding of the degradation mechanism. These findings suggest highlighting the importance of complementary chemical analytical techniques for a more accurate evaluation. On the other hand, TG data showed that bio-polyurethane foams remained thermally stable even after biodegradation occurred. Full article

Piston engines used for powering automobiles as well as machinery and equipment have traditionally relied on petroleum-derived fuels. Subsequently, renewable fuels began to be used in an effort to reduce the combustion of hydrocarbon-based fuels and the associated greenhouse effect. Researchers are currently developing technologies aimed at eliminating fuels containing carbon in their molecular structure, which would effectively minimize the emission of carbon oxides into the atmosphere. Ammonia is considered a highly promising carbon-free fuel with broad applicability in energy systems. It serves as an excellent hydrogen carrier (NH₃), free from many of the storage and transportation limitations associated with pure hydrogen. Safety concerns regarding the storage and transport of hydrogen make ammonia an increasingly important fuel also due to its larger hydrogen storage capacity. This manuscript investigates the use of ammonia for powering a dual-fuel engine. The results indicate that the addition of ammonia improves engine performance; however, it may also lead to an increase in NO_x emissions. Due to the limitations of ammonia as a fuel, approximately 40% of the energy input must still be provided by diesel fuel to achieve optimal engine performance and acceptable NO_x emission levels. The presented research findings highlight the significant potential of NH₃ as an alternative fuel for compression-ignition engines. Proper control of the injection strategy or the adoption of alternative combustion systems may offer a promising approach to reducing greenhouse gas emissions while maintaining satisfactory engine performance parameters. Full article

This paper constructs a modified hypothesis extraction method (MHEM)–structural decomposition analysis (SDA)–structural path decomposition (SPD) analytical framework and employs the 2018–2022 Chinese input–output tables to discuss sectoral consumption correlations, driving forces of consumption, and the transmission paths of carbon energy (CE), oil and gas energy (OGE) and electric energy (EE). The results of the study indicate that energy-exporting sectors are primarily energy production or conversion industries, while energy-importing sectors are mainly in the construction sector. China’s energy consumption has shown consistent year-on-year growth, with the primary driving force being the intensity of energy consumption and the secondary factor being per capita demand. The consumption of all three types of energy is primarily directed toward domestic consumption and capital formation. Regarding energy consumption transmission paths, the first-order path with the largest overall impact on CE is “electricity, gas, and water supply sector → domestic consumption”, while higher-order paths are primarily subpaths of “electricity, gas, and water supply sector → capital formation”. For OGE, the main supply and transfer path is “coke, refined petroleum, and nuclear fuel sector → domestic consumption”, along with its subpaths. In contrast, EE transmission is more balanced, with a high demand for electricity across all sectors. Full article

This article analyses the necessity of employing an interdisciplinary approach in the geotechnical practice of designing, constructing, and operating industrial hydraulic structures—tailings dams of processing plants. Tailings dam failures often lead to irreversible consequences for the ecological state of the environment. The interdisciplinary approach involves treating the foundation soils of structures and anthropogenic tailings deposits as a multicomponent system. In this system, soil acts as a medium hosting groundwater of varying compositions and contamination levels, containing biotic components and their metabolic products, including the gaseous phase. It has been demonstrated that the justified application of this approach increases the operational safety of existing structures and the long-term stability of starter and tailings dikes built on weak clay foundation soils. Particular emphasis is placed on the biotic component and the dual role of subsurface microorganisms. These bacteria negatively impact the strength and load-bearing capacity of water- and water–gas-saturated clay soils in the foundation of the structures under consideration. The diverse biocenosis in groundwater simultaneously facilitates self-purification from petroleum hydrocarbons to undetectable levels. This aspect holds fundamental importance, as groundwater discharges into river systems. Full article

Volatile C2–C5 olefins are important bulk chemicals in the polymer industry. Traditionally, C2–C5 olefins are produced from cracked petroleum resources using an energy-consuming and hazardous distillation method. Currently, volatile olefins can be produced from renewable biomass. To obtain polymer-grade volatile olefins from diversified resources, more sustainable and feasible separation techniques need to be developed. This review focuses on two updated separation techniques for C2–C5 olefins: (a) adsorption separation, which separates olefins through porous affinity, the pi complexation effect, and size-exclusion and gate-opening sieving, and (b) liquid absorption separation, which utilizes either organic solvents or ionic liquids for olefin separation. In this review, different separation techniques are compared in terms of their mechanisms and operation conditions in the separation of different types of C2–C5 olefins from variable resources, such as cracked ethylene/propylene/butylene/isoprene and bio-isoprene. Full article