Petroleum Research Articles

A particle swarm optimizer-based optimization approach for locating electric vehicles charging stations in smart cities

Conventional fossil fuel-powered vehicles are gradually being replaced by electric and hydrogen vehicles in the transportation sector. Even with all the recognized benefits and recent advancements in energy efficiency, decrease of noise, and environmental impact reduction, the market of electric and hydrogen mobility is still not up to par. Allocating charging stations in metropolitan areas for electric vehicles is considered as one of the most significant obstacles preventing electric and hydrogen vehicles from becoming more widely used. In this paper, an efficient approach aimed at finding optimal locations for electric vehicles (EV) charging stations in urban areas is proposed. Particle Swarm Optimization algorithm technique is utilized with the proposed approach. Various parameters were taken into consideration in this work, such as the horizontal distance that EVs travel to reach charging stations (CSs), and positive slope that EVs face to reach charging stations. The optimization problem is formulated as a Mixed-integer problem. The objective function works on minimizing the energy consumption of EVs to reach CSs in the investigated area. Difference constraints are incorporated with the proposed approach in order to increase the accuracy and efficiency of the proposed approach. The proposed approach is applied on real world datasets and is experimentally validated using through comparison with Genetic Algorithm and the greedy approach. The results demonstrate that the proposed approach saves energy about 22% and 43% compared to the genetic algorithm and greedy technique, respectively.

Insight of low flammability limit on sustainable aviation fuel blend and prediction by ANN model

Sustainable aviation fuel (SAF) blend has been confirmed to benefit for greenhouse gases reduction, and thus the property of blend fuel should be understanded the detail to support the utilization in aircraft. Low flammability limit (LFL) is a key property of jet fuel which should be sufficiently flammable to burn in combustor of aeroengine and meanwhile should be non-flammable for safety storage in fuel tank of aircraft. LFL of fuel could be influenced by integrating effects including molecule structure, intramolecular chemical bond energy and binding energy of molecule to molecule. Three types of theoretical models, based on different individual view including LFL of every pure hydrocarbon, stoichiometric concentration, and combustion enthalpy, present unsatisfactory simulation results, which can be deduced without integrating all potential influence factors together. The artificial neural network (ANN) approaches have been involved to bridge the relationship of the complex compositions in jet fuels with LFL. For providing adequate and available composition input, the boundary of fuel compositions has been extracted based on constrains of boiling point, flash point and freeze point coupling with statistic petroleum-based jet fuels. By clustering analysis, 43 critical classes of compositions, extracted as surrogate hydrocarbons based on with similar LFL within 1 % deviation, have been deployed as input matrix. ANN-LFL model, trained by only drop-in fuel with feature of Sigmoid function as an activation function, can distinguish drop-in fuel with non-drop-in fuel. ANN LFL model can predict LFL of drop-in fuel with 0.988 accuracy. The predict output value of non-drop-in fuel could present obvious deviation with traditional jet fuel. The optimization methodologies of ANN-LFL model could be improved the understanding of LFL and extend ANN in SAF utilization.

Well-to-Wheel emissions of electric vehicles in Türkiye and emission mitigation by renewable penetration

Automotive technology is currently on the verge of transitioning to electric vehicles, and both the impact of these vehicles on electricity consumption and their environmental performance are the focus of significant interest. In this paper, the emission impacts based on the use of electric vehicles are analyzed using the Well-to-Wheel methodology. In order to evaluate electric vehicle emissions, emissions based on electricity generation and consumption are first determined. Emission intensities are found in gCO2e/kWh for electricity consumption and gCO2e/km for battery electric vehicles. Well-to-wheel emissions are found 172.2 and 89.1 gCO2e/km for conventional and electric vehicles, respectively. With the renewable penetration in electricity generation, the emission intensity will be lower, which means that the emissions of electric vehicles will be further reduced. Thus, a renewable energy supported charging station is simulated and it is shown that emission intensities can be reduced by 60 %. It is concluded that Türkiye should focus primarily on renewable energy sources and then nuclear energy in order to meet the increasing electricity demand and reduce emission intensities.

Alcohols as Biofuel for a Diesel Engine with Blend Mode—A Review

In the era of decarbonization driven by environmental concerns and stimulated by legislative measures such as Fit for 55, the industry and transportation sectors are increasingly replacing petroleum-based fuels with those derived from renewable sources. For many years, the share of these fuels in blends used to power compression ignition engines has been growing. The primary advantage of this fuel technology is the reduction of GHG emissions while maintaining comparable engine performance. However, these fuel blends also have drawbacks, including limited ability to form stable mixtures or the requirement for chemical stabilizers. The stability of these mixtures varies depending on the type of alcohol used, which limits the applicability of such fuels. This study focuses on evaluating the impact of eight types of alcohol fuels, including short-chain (methanol, ethanol, propanol) and long-chain alcohols (butanol, pentanol, hexanol, heptanol, and octanol), on the most critical operational parameters of an industrial engine and exhaust emissions. The engines being compared operated at a constant speed and under a constant load, either maximum or close to maximum. The study also evaluated the effect of alcohol content in the mixture on combustion process parameters such as peak cylinder pressure and heat release, which are the basis for parameterizing the engine’s combustion process. Determining ignition delay and combustion duration is fundamental for optimizing the engine’s thermal cycle. As the research results show, both the type of alcohol and its concentration in the mixture influence these parameters. Another parameter important from a usability perspective is engine stability, which was also considered. Engine performance evaluation also includes assessing emissions, particularly the impact of alcohol content on NOx and soot emissions. Based on the analysis, it can be concluded that adding alcohol fuel to diesel in a CI engine increases ignition delay (up to 57%), pmax (by approximately 15–20%), HRRmax (by approximately 80%), and PPRmax (by approximately 70%). Most studies indicate a reduction in combustion duration with increasing alcohol content (by up to 50%). For simple alcohols, an increase in thermal efficiency (by approximately 15%) was observed, whereas for complex alcohols, a decrease (by approximately 10%) was noted. The addition of alcohol to diesel slightly worsens the stability of the CI engine. Most studies pointed to the positive impact of adding alcohol fuel to diesel on NOx emissions from the compression ignition engine, with the most significant reductions reaching approximately 50%. Increasing the alcohol fuel content in the diesel blend significantly reduced soot emissions from the CI engine (by up to approximately 90%).

USE OF METHANOL AS MOTOR FUEL FOR MARINE INTERNAL COMBUSTION ENGINES

The international maritime organization's intention to reduce greenhouse gas emissions to the atmosphere by two times compared to 2008 by 2050 prompted manufacturers of marine engines to start actively searching for ways to solve this problem. Since significant global changes in the structure of ship power equipment are not expected during this period, the main efforts of researchers are aimed at solving the problem of reducing emissions based on piston engines, which today form the basis of ship power. The technology of the first stage of reducing greenhouse gas emissions was the conversion of marine diesels to gas fuels, and primarily to methane. These technologies, which are already widely used in water transport today, make it possible to reduce greenhouse gas emissions by 20...25%, but do not solve the problem completely. Today it is clear that a global solution to the problem is possible only when using as motor fuel compounds that are either carbon-free, i.e. do not contain carbon in their composition at all, or are carbon neutral, i.e. contain carbon extracted from the atmosphere by biological or technological means. One such compound is methyl alcohol or methanol. Today, most of the methanol in the world is produced either from coal or from natural gas, so the total emissions of greenhouse gases when burning such methanol even exceed emissions from burning petroleum fuels, however, unlike the latter, this compound can be obtained from biological raw materials, or by binding atmospheric carbon. Today, such methanol, which has received the name «green», is too expensive, and its production technologies require further development. This can happen only if there is international stimulation and regulation of this area of production. But the introduction of such regulation requires a clear understanding of the technical feasibility and economic and environmental feasibility of using methanol as a motor fuel. That is why leading manufacturers today are working on solving these issues. Their solution is considered the second stage on the way to the complete decarbonization of shipping, and at this stage there has been significant progress in recent years. This article is devoted to the analysis of the current state of the question regarding the use of methanol as motor fuel for ship engines of all types and sizes.

Thermal studies on the lower Carboniferous basins of Khenifra and Qasbat-Tadla, Morocco: What do they teach us about the pre-Variscan stages in NW Africa?

Within the Variscan Belt of Morocco, the Central Massif preserves Early Carboniferous rift basins. The Lower Carboniferous Khenifra and Qasbat-Tadla basins are aborted rifts, developed just before the Variscan orogenesis in Morocco that occurred during the Pennsylvanian-Cisuralian in NW Africa. Due to both weak inversion of these basins during the Variscan orogeny and limited burial afterwards, these basins offer the opportunity to study the Early Carboniferous pre-orogenic thermal regimes. In the Khenifra basin, 77 samples collected across the basin and its basement's boundaries, allowed the determination of the maximal temperature reached during the rocks burial by means of Raman spectroscopic analyses. The Ordovician basement shows mean temperatures between 230 and 300 °C whereas the upper Visean/Serpukhovian infill has a wide range, from temperatures <160 °C to 250–260 °C. This thermal variation within the basinal series has been evidenced from west to east and cannot have been acquired during the Variscan events. The acquisition of these maximal temperatures occurred between Late Devonian to Upper Visean/Serpukhovian and is thought to result from the formation of an extended rift. In the Qasbat-Tadla basin, Rock-Eval data from Ordovician to Devonian source-rocks indicate significantly lower maximal temperatures reached by pre-Carboniferous samples that are within the oil window. Our results are in favor of a heterodox model for the Variscan belt in Morocco and NW African in general, suggesting that no pre-Variscan compressional events are needed. Instead, the development of the intraplate Variscan belt in NW Africa was permitted through the development of hot and weak Lower Carboniferous basins, subsequently inverted in a far-field stress field. The striking thermal differences between the Khenifra and Qasbat-Tadla basins suggest that important tectonic segmentation must have shaped the area during the Early Carboniferous extensional phase.

Hydrocarbons, Hydrogen, and Organic Acids Generation by Ball Milling and Batch Incubation of Sedimentary Rocks

Pulverized rock samples are widely used in laboratory experiments, e.g., to assess microbial or abiotic processes in batch incubation tests. However, it is unclear if ball-milled samples accurately reflect in-situ conditions and if observed processes are affected by by-products artificially generated during the sample preparation procedure. As such, this study examined the effects of dry ball milling on the release of gases, which include C1-C4 hydrocarbons, carbon dioxide (CO2), hydrogen (H2), and low molecular weight organic acids (LMWOAs) from different sedimentary rocks. The experiments involved pulverization using a gas-tight zirconium oxide planetary ball mill followed by wet and dry batch incubation and thermal desorption up to 200 o C. During milling, all sedimentary rocks, except a low organic carbon sandstone sample, yielded methane (CH4), ethane (C2H6), propane (C3H8), butane (C4H10), H2, CO2, and unsaturated hydrocarbons, e.g., ethene (C2H4). Sandstones only yielded H2, CH4, and CO2. Stable carbon isotope signatures of these products are similar to thermogenic gases. The gases were also detected in subsequent wet incubation experiments (after gases from milling had been removed). Additionally, formate, acetate, and citrate, were detected in all samples except for sandstone. Pyruvate, malate, and succinate were also detected in some samples. Thermal desorption products of powdered limestone, shale, and pyrite concretion samples included organic acids, such as acetate and formate, which were higher in milled samples than in crushed particles (∼1 mm). The original geological thermal maturity of the studied sedimentary rock samples was low (below “oil window”) and, thus, considerably below “gas window”, suggesting that most of the detected gases were generated during ball milling. H2 generated during ball milling may be derived from the reduction of water from fluid inclusion or phyllosilicates, involving the formation of reactive mineral surfaces or radicals. Notably, the concentrations of gaseous hydrocarbons derived from milling are relatively high and comparable to “wet” gases. At the same time, these data indicate that substantial amounts of gases and LWMOAs might be artificially generated during laboratory batch experiments with milled samples. Hence, ball milled rock samples must be used with caution if assessing (bio-)geochemical processes for natural environments.

Wire-to-two-drop plasma thruster: Experimental and numerical investigation of electroaerodynamic jet flow for micro aerial vehicle propulsion

Conventional micro aerial vehicles (MAVs) have primarily relied on complex, flapping-wing mechanisms for propulsion, often exhibiting limitations in terms of reliability and efficiency. To overcome these challenges, this study explores the potential of electroaerodynamic (EAD) thrusters as a novel propulsion system. By accelerating air molecules through ion collisions, EAD jet flow generates thrust, offering advantages such as noiseless operation and zero emissions due to its moving-part-free design. This research presents a comprehensive experimental and numerical investigation of a wire-to-two-drop thruster configuration to elucidate its electromechanical performance, plasma flow dynamics, and EAD jet characteristics. Experimental measurements of key parameters, including current, thrust, power, and effectiveness, were correlated with numerical simulations, demonstrating excellent agreement with a maximum error below 5%. These findings align strongly with established theoretical frameworks, revealing an inverse square root relationship between effectiveness and thrust. To optimize thruster performance, optimal operating voltages were identified at approximately 8.2, 9.4, and 11.6 kV for inter-electrode gap distances of 10, 15, and 20 mm, respectively, achieving a balanced trade-off between thrust and effectiveness. Detailed numerical visualizations of the plasma flow field, including velocity distribution, jet morphology, potential distribution, and electric field lines, provided valuable insights into the thruster's operation. Building upon these insights, a proof-of-concept EAD flier was constructed and tested, incorporating a serrated emitter electrode and lightweight materials. This flier achieved a mass of 0.5 g and generated a thrust of 0.77 g at 15 kV, resulting in a thrust-to-weight ratio of 1.54 and successful liftoff. This demonstration highlights the potential of EAD propulsion for practical MAV applications.

Statistical analysis of fuel combustion and emissions considering the adverse effects of investment economic environment: Exploring alternatives amid oil prices Swings, digital economy, and local market inflation

The depletion of natural gas reserves, combined with rising oil prices, local market inflation, and concerns about pollution, has accelerated the search for alternative energy sources. As a result, research on turbines and internal combustion engines for electricity generation is increasingly focusing on using vaporized ethanol as a fuel substitute. However, the high cost of analyzing the chemical composition of these fuels often leads to an oversight of their impact on combustion characteristics, such as flame behavior, emission profiles, and temperature distribution.This study employs a statistical approach to assess the combustion and emission characteristics of biofuels, aiming to find suitable alternatives to petroleum-based fuels. By integrating considerations of oil price fluctuations and the digital economy's impact, the research proposes a cost-effective method for evaluating the chemical makeup of vaporized fuels and their effects on post-combustion pollution.Experimental data reveal that alternative fuels can offer stable ignition performance and lower pollution levels, contingent on their specific properties. Fuels with high aromatic content and viscosity tend to produce significant CO emissions, while reducing these characteristics may increase CO2 production. The study also highlights the challenge of simultaneously reducing both CO and NOx emissions. Additionally, the findings show that petroleum gasoline, due to its lower volatility, has favorable fire safety properties and generates fewer pollutants.In the context of economic pressures from rising oil prices and inflation, this research underscores the importance of exploring biofuels as viable, sustainable alternatives for the future energy landscape.

Environmental impact of waste plastic oil and hydrogen-enriched diesel engines: A comprehensive review on performance, combustion, and emissions

This review focuses on the sustainable use of waste plastic by converting it into waste plastic oil (WPO) through catalytic pyrolysis. The primary objective is to explore the potential of WPO, derived from used polyethylene terephthalate bottles, as an alternative fuel for diesel engines. This review also evaluates WPO's physical and chemical properties, revealing that it possesses fuel attributes similar to those of petroleum-based fuels. Catalytic pyrolysis is employed on a laboratory scale, using catalysts such as silica, Zeolite Socony Mobil-5 (ZSM-5), alumina, and kaolin to extract WPO from mixed waste plastics. However, direct use of WPO in diesel engines has shown drawbacks, including significant combustion delays and increased emissions. To address these issues, this review suggests blending WPO with diesel fuel rather than using it as a standalone fuel. Furthermore, the review explores hydrogen enrichment in WPO blends to improve combustion efficiency. Hydrogen enrichment enhances thermal efficiency and reduces environmental emissions, showing potential for improved performance and lower brake-specific fuel consumption. This review presents a comparative analysis of various WPO blends with hydrogen enrichment, highlighting the benefits of incorporating hydrogen to boost combustion and performance. Although promising, further research is needed to ensure the sustainability and effectiveness of WPO blends as a long-term energy source.

Comparison of machine learning algorithms on a low heat rejection diesel engine running on ternary blends

Depletion of fossil fuels and increasing the energy demand are the critical concerns for the sustainable growth of every country. These challenges highlight the need for a cleaner fuel globally. In particular, substituting the petroleum fuels with biofuels could significantly support sustainability. Hence, this study explores the impact of acetylene induction in a low heat rejection (LHR) diesel engine with ternary blend (TB) as a pilot fuel. TB includes 10%methanol + 20%WCOB + 70%diesel. During the dual fuel operation, the acetylene induction was varied (12, 18, and 24 lpm) with different pilot fuel combinations in a LHR engine. From the experimental results, it was revealed that brake thermal efficiency (BTE) is improved by 10.3% for TB with acetylene at 24 lpm and increased the exhaust gas temperature (EGT) by 10.3% at full load conditions. This study further evaluates the implementation of machine learning algorithms, namely, Random Forest regression (RFR) and Polynomial regression (PR) in predicting the performance parameters [BTE, brake-specific fuel consumption (BSFC), and EGT]. The results indicate that RFR outperforms PR in accurately predicting engine performance characteristics with a coefficient of determination R2 = 0.97, R2 = 0.98 for BTE, whereas for BSFC the R2 = 0.96, R2 = 0.95, and for EGT, the R2 = 0.95, R2 = 0.97 for the test fuels diesel and TBA3, respectively. These findings suggest that the combination of LHR technology, TB fuel, and acetylene can enhance engine efficiency and performance characteristics, and machine learning models can effectively predict these outcomes.

Study of energy consumption improvement for electric vehicles in platoon driving

Abstract It is known that platoon driving has a large impact on fuel economy for conventional vehicles and using current available technologies, could be implemented especially on highway driving. Since the transition to electric vehicles is in progress, it is important to evaluate its applicability to this type of vehicles which have different characteristics than conventional ones equipped with an internal combustion engine. This paper aims to investigate the energy consumption improvement for a platoon of up to 7 electric passenger vehicles using a validated detailed model created in LMS Imagine. Lab AMESim, an industrial modelling and simulation environment. The energy consumption of individual vehicles and also the platoon’s will be calculated for several stabilized speeds and also on a standardized high-speed cycle (HWFET). The analysis will show how the special characteristics of an electric vehicle (lower drag coefficient, increased mass, regenerative braking, etc.) have an influence on the vehicle’s energy consumption when driving in a platoon. This will allow us to also evaluate the platoon driving efficacity in increasing the vehicle’s driving range.

Vehicle routing problem for omnichannel retailing including multiple types of time windows and products

This paper addresses the capacitated vehicle routing problem for omnichannel retailing with multiple types of time windows (hard time windows and soft time windows) and multiple types of products simultaneously. The problem aims to transfer multiple products from a central warehouse to stores and satellites, where split delivery is allowed since the demands of stores or satellites are large and the different product types have different volumes. Based on different characteristics of purchasing channels, the time window of a store is a hard constraint while the time window of a satellite is a soft one. This type of vehicle routing problem exists extensively in omnichannel retail distribution systems in the logistics industry of China, which considers multiple purchasing channels for customers. Since this type of vehicle routing problem is an NP-hard problem and more complicated than the conventional vehicle routing problem with time windows, we design an adaptive large neighborhood search (ALNS) method to solve it. Finally, numerical experiments are conducted to evaluate the effectiveness of the proposed algorithm and reveal some managerial insights. The numerical experiments show that the proposed algorithm can obtain a high-quality solution under a shorter computation time compared with the state-of-the-art MIP solver (Gurobi).

Exploring alternative fuel solutions: lemon grass oil biodiesel blend with dibutyl ether additive for VCR diesel engines - an experimental analysis

There has been an intense surge in interest in the search for alternative sources of petroleum fuels in the modern world as a result of the inflation of fuel prices and the historic supply gap. When compared to petroleum fuels, biodiesel is becoming an increasingly valuable option due to the fact that it produces less emissions and provides the almost same amount of energy. In point of fact, the prime aim of this work is to explore the possibility of utilizing biodiesel derived from lemongrass oil and including dibutyl ether as an additive for the test diesel engine operating on varied compression ratios. The findings showed that the best operating settings are a 17.5 compression ratio with a blend of 30% biodiesel and 70% diesel fuel. At greater loads, brake thermal efficiency is lower than that of diesel engines. Lower loads result in lower specific fuel usage. Mechanical efficiency at higher loads is highest in the B30 blend, but emission metrics such as CO, CO2, HC, and NOx were reduced with the inclusion of an additive, though HC rose with higher loads of lemongrass oil biodiesel blends. When compared to the B30 biodiesel blend with various composition additives, the B30 + 4% additive has the highest efficiency at the fourth load in terms of both brake power and mechanical efficiency.

In-situ stabilized lipase in calcium carbonate microparticles for activation in solvent-free transesterification for biodiesel production

Biodiesel serves as a crucial biofuel alternative to petroleum-based diesel fuels, achieved through enzymatic transesterification of oil substrates. This study aims to investigate stabilized lipase (LP) within calcium carbonate (CaCO3) microparticles as a catalyst for solvent-free transesterification in biodiesel synthesis. The specific hydrolysis activity of the in-situ immobilized LP was 66% of that of free LP. However, the specific transesterification activity of immobilized LP in the solvent-free phase for biodiesel production was 2.29 times higher than that of free LP. These results suggest that the interfacial activation of LP molecules is facilitated by the inorganic CaCO3 environment. The immobilized LP demonstrated higher biodiesel production levels with superior stability compared to free LP, particularly regarding methanol molar ratio and temperature. To the best of our knowledge, there are no previous reports on the in-situ immobilization of LP in a CaCO3 carrier without any crosslinker as an interfacial-activated biocatalyst for biodiesel production.

Analyzing Riders’ Behavioral Adaptation to Driving Patterns of Advanced Autonomous Vehicles: A Virtual Reality Simulation Study

The necessity of human supervision and intervention during autonomous driving has long been a topic of controversial discussion. From a developer’s perspective, it is expected that users will readily adapt to well-calibrated autonomous driving systems (ADS) due to their superior performance in dynamic driving tasks (DDT) compared to conventional human-driven vehicles. However, when passengers experience an autonomous vehicle (AV), there may be an adjustment period during which they modify their behavior to accommodate the driving patterns of the ADS. Additionally, some passengers might not adapt to autonomous driving at all, highlighting potential limitations in the current ADS development strategy. This work studies the dynamics of human-automation interaction and introduces an “objective method”, which employs a Virtual Reality (VR)-enabled simulation approach for in-depth behavioral analysis concerning riders’ behavioral adaptation to autonomous driving. Specifically, we examined how participants interacted with and intervened in Level 4 ADS operating under conservative, moderate, and aggressive driving patterns in a fully autonomous environment. A realistic urban road network was recreated in VR, integrated with traffic microsimulation to generate various driving scenarios. Twenty-seven participants completed driving tasks across different AV modes, with their intervention behaviors analyzed in relation to traffic conditions and AV aggressiveness. Key findings include: (1) Participants showed higher intention to intervene but lower actual intervention rates under aggressive AV modes compared to moderate and conservative modes, suggesting quicker adaptation to more challenging driving scenarios. (2) Interventions generally proved unnecessary and sometimes detrimental to overall traffic performance in a full-AV environment. (3) Aggressive AV modes significantly improved traffic efficiency, with a 40% increase in average travel speed and a 53% reduction in waiting time. However, human interventions posed the greatest challenge to achieving optimal traffic conditions. This research provides insights into the complex dynamics of human-AV interaction and adaptation, offering valuable implications for AV interface design, implementation strategies, and public acceptance of autonomous driving technologies.

Chemical composition and antimicrobial activity of essential oils and various extracts of endemic Onosma malatyana (Boraginaceae) from Anatolia

ABSTRACT The chemical contents of the endemic Onosma malatyana roots collected from Malatya/Türkiye were determined using the hydrodistillation and the soxhlet methods and antimicrobial activity analysis of the extracts was also performed. The hydrodistillation method applied to the roots of O.malatyana resulted in identifying 31 compounds according to their retention times in GC-MS analysis. Additionally, crude ethyl acetate and crude oil etheric extracts of O.malatyana roots contained 14 compounds each. This research identified that the main component of the essential oil obtained by the hydrodistillation method was palmitic acid comprising 56.48% of the total composition. Additionally, in the crude petroleum etheric extract, oleic acid methyl ester (31.22%); and palmitic acid (24.69%) were identified as the main components in the crude ethyl acetate extract. The results of the antimicrobial activities indicated that O.malatyana root extracts were particularly effective against Gram-positive bacteria, specifically S. aureus and B. subtilis.

Petroleum source-rock characterization and the depositional environment of Kimmeridgian–Tithonian sequences, Jaisalmer Basin, western Rajasthan, India

In hydrocarbon exploration, total organic carbon (TOC) content and Rock-Eval pyrolysis are commonly employed geochemical techniques that offer concise insights into kerogen type, effective source-rock identification and thermal maturity. In the current study, the data obtained from Rock-Eval pyrolysis has been used to define the source-rock quality, generative potential, kerogen type, maturity of the source sediments and kerogen kinetics of the Baisakhi–Bhadesar Formation of Kimmeridgian–Tithonian (154.7–145.6 Ma) age. Basinal level hydrogen index (HI), TOC content, source-rock maturity, transformation ratio and heat-flow maps have been generated by integrating the data from pyrolysis with previously available data from wells drilled in the basin. The TOC content of the Kimmeridgian–Tithonian sequence ranges from 0.03 to 12.71% in the studied samples, with an average TOC content of 1.28%, indicating good source-rock quality. The HI, in collaboration with T max and vitrinite reflectance (VR o ) data, demonstrates that the Baisakhi–Bhadesar Formation is characterized by type II, a mixture of type II/III and type III kerogen facies and exhibits good source-rock quality and poor to good generative potential in the basin. The studied samples are marginally mature to mature in nature ( T max , 430–450°C; VR o , 0.52–0.72%). A maturity analysis of the basin suggests that during the Late Jurassic most areas were under the oil window zone, except for the Bhakhari Tibba and Miajlar areas. The transformation ratio overlay for the Kimmeridgian–Tithonian source sequences shows better transformations of the source rock in the area of the Shagarh Sub-basin. Kerogen kinetics of the studied Baisakhi–Bhadesar Formation demonstrate that the activation energy ranges between 46 and 74 kcal mol −1 with the significant distribution of activation energy being 54 kcal mol −1 (42.07%), representing a strong heterogeneous type of organic matter in the sediments. Based on lithological, palaeontological and electrolog studies, a shallow-marine to nearshore environment of deposition with a sediment-input direction from the SE has been inferred for the Kimmeridgian–Tithonian sequences. The results of this study quantitatively establish the role of the Kimmeridgian–Tithonian sequence as a source rock, ultimately contributing to the generation of hydrocarbons in the basin along with spatial changes in the quality of source sediments in different parts of the basin.

Comprehensive evaluation of the Paleogene lacustrine source rocks within the Bodong Sag, Bohai Bay Basin using kinetics-based petroleum system modeling

The hydrocarbon potential of the Bodong Sag remains unclear. Investigation and comprehensive evaluation of Paleogene lacustrine source rocks is essential to determine the exploration potential and direction. This study examined the Paleogene source rocks using organic geochemical methods, including total organic carbon (TOC), Rock-Eval pyrolysis, maceral composition, vitrinite reflectance (Ro), and kinetic analysis. For the first time in this study area, a three-dimensional (3D) kinetics-based petroleum system modeling approach was employed to reconstruct the burial history, thermal maturity, and hydrocarbon generation history of the source rocks. The resource mass was evaluated based on the calculated generation mass. Results indicate that the third member (E2s3) and first member (E3s1) of the Shahejie Formation are mainly Type II1 organic matter, exhibiting high generation potential. The third member of the Dongying Formation (E3d3) contains mixed Type II1 and II2 organic matter, with moderate potential. The E2s3 and E3s1 source rocks matured early, entering the oil window in the Early Oligocene (∼30.3 Ma) and Middle Oligocene (∼28 Ma), respectively, and are currently in the wet gas to dry gas stage. The E3d3 source rocks matured later, entering the oil window at the end of the Oligocene (∼24.6 Ma) and are currently in the late oil to the wet gas stage. Subsidence and burial have resulted in higher maturity in the southern subsag compared to the northern subsag, with the margins remaining in low maturity to immature stages. Resource estimates for the Bodong Sag source rocks are quantified at 8.33 × 108 t of oil and 1.68 × 1011 m3 of gas. E2s3, E3s1, and E3d3 contribute 41.62%, 33.95%, and 24.43% respectively, with E2s3 source rocks being the major contributor. The southern subsag, accounting for 76.92%, is the primary hydrocarbon generation kitchen. The significant increase in natural gas resources highlights the prospects for natural gas exploration in the Bodong area.

Evolutionary Game-Based New Energy Vehicle Supply Chain Strategies That Consider Carbon Reduction and Consumers’ Low-Carbon Preferences

The rapid development of the new energy industry has intensified the competition among companies. Finding solutions to achieve technological innovation, carbon reduction, and to earn consumers’ confidence has become a pressing challenge. In this research, we aim to develop a four-party evolutionary game model involving government, manufacturers, dealers, and consumers to examine the strategic decisions made by these parties in order to accomplish carbon emission reduction goals. We will perform numerical simulations to analyze the strategic choices of each party and the relevant influencing factors. The results suggest the following: (1) The tax hike on traditional car production is less than the innovation expenses for new energy vehicles, leading manufacturers to lean towards manufacturing traditional vehicles. (2) The rise in taxes resulting from the manufacture of conventional vehicles will influence manufacturers’ strategic decisions, whereas the expenses related to technological advancements will have a more significant effect on manufacturers’ strategic choices. (3) Compared to dealers, manufacturers’ strategic choices are more significantly influenced by consumers’ awareness of low-carbon preferences. (4) In the early stages of technological innovation, the government typically offers incentive subsidies to manufacturers to boost technological innovation activities. Whereas, in the later stages of technological innovation, the government usually provides direct subsidies to consumers to encourage the market acceptance and widespread use of innovative products.