Oil Stations Research Articles

A Low-Carbon Planning Strategy for Integrated Energy System and Hydrogen Refueling Stations With the Retirement of Oil Stations

A Low-Carbon Planning Strategy for Integrated Energy System and Hydrogen Refueling Stations With the Retirement of Oil Stations

A method for recognizing abnormal behaviors of personnel at petroleum stations based on GTB-ResNet

PurposeThe abnormal behaviors of staff at petroleum stations pose significant safety hazards. Addressing the challenges of high parameter counts, lengthy training periods and low recognition rates in existing 3D ResNet behavior recognition models, this paper proposes GTB-ResNet, a network designed to detect abnormal behaviors in petroleum station staff.Design/methodology/approachFirstly, to mitigate the issues of excessive parameters and computational complexity in 3D ResNet, a lightweight residual convolution module called the Ghost residual module (GhostNet) is introduced in the feature extraction network. Ghost convolution replaces standard convolution, reducing model parameters while preserving multi-scale feature extraction capabilities. Secondly, to enhance the model's focus on salient features amidst wide surveillance ranges and small target objects, the triplet attention mechanism module is integrated to facilitate spatial and channel information interaction. Lastly, to address the challenge of short time-series features leading to misjudgments in similar actions, a bidirectional gated recurrent network is added to the feature extraction backbone network. This ensures the extraction of key long time-series features, thereby improving feature extraction accuracy.FindingsThe experimental setup encompasses four behavior types: illegal phone answering, smoking, falling (abnormal) and touching the face (normal), comprising a total of 892 videos. Experimental results showcase GTB-ResNet achieving a recognition accuracy of 96.7% with a model parameter count of 4.46 M and a computational complexity of 3.898 G. This represents a 4.4% improvement over 3D ResNet, with reductions of 90.4% in parameters and 61.5% in computational complexity.Originality/valueSpecifically designed for edge devices in oil stations, the 3D ResNet network is tailored for real-time action prediction. To address the challenges posed by the large number of parameters in 3D ResNet networks and the difficulties in deployment on edge devices, a lightweight residual module based on ghost convolution is developed. Additionally, to tackle the issue of low detection accuracy of behaviors amidst the noisy environment of petroleum stations, a triple attention mechanism is introduced during feature extraction to enhance focus on salient features. Moreover, to overcome the potential for misjudgments arising from the similarity of actions, a Bi-GRU model is introduced to enhance the extraction of key long-term features.

Real time detection of fatigue cracks on steel structures by applying square wave induction

For years the Eddy currents principle together with inductive thermography have been applied to detect cracks or defects in metallic machine components. In case a component has a crack, by inducing Eddy currents within a coil, it is possible to cause a temperature increase in the edges of the crack. This temperature variation can be observed by using an infrared camera. Thus, the crack is registered and observed in the infrared images, which are later analyzed. However, currently used systems require an enormous amount of power and a long time for image processing. For this reason, applying this method to large steel structures such as bridges, cranes, wind power towers, pipe lines or offshore oil stations has been much more complex. To overcome these limitations, a light portable system that optimally recreates the Eddy currents principle has been developed and used in this research. This system generates a square wave AC voltage, it uses considerably less power and it is capable of detecting cracks in real time. This paper presents the simulations and experiments carried out on two different structural steel specimens to demonstrate the efficiency of the system and its potential in the field of nondestructive testing.

Optimal design of sizing and allocations for highway electric vehicle charging stations based on a PV system

The world’s demand for fossil fuels has recently increased significantly for both transportation and electric power generating sectors. Using these resources not only results in high costs and depletion of them but also increases greenhouse gas emissions and pollution. The electric vehicle (EV) market is growing globally, aiming to face climate change due to greenhouse gas (GHG) emissions and to reduce reliance on fossil fuels. However, the long charging time of EVs and the shortage of charging outlets limits the global adoption of EVs, especially on highways where the problem of accessibility to the electricity distribution grid appears. These issues can be faced by the good planning of charging infrastructure. However, this planning is a multidisciplinary field that includes electricity generation, transportation networks, EVs’ characteristics, and driver behavior. A methodology to provide the optimal locations and sizing of electric vehicle charging stations with their own electricity generation and storage using photovoltaic (PV) and energy storage systems on highways considering different factors is proposed in this paper. This paper takes a section of the western desert highway in Egypt connecting Assiut and Cairo cities as a case study. Four scenarios are proposed for the design of EV charging stations’ locations and sizing which are centralized charging stations, two-way charging stations, utilizing oil stations’ locations, and distributed fixed sizing charging points with a comparison between them. The work also discusses the potential effects of highway slope, wind speed, and number of passengers on the location problem. The results can be used to optimize the design of EV charging stations along highways for a completely sustainable system.

Sizing requirements of the photovoltaic charging station for small electrical vehicles

Electric vehicles (EVs) are being introduced in Rwanda and becoming attractive for different reasons. For instance, these types of vehicles can help decrease air pollution and noise emissions. In addition, it presents an alternative to combustion engines, given the increased price of fuel resources in Rwanda and around the world. This paper presents a tool tailored to optimize the design of an electrical charging station serving small-sized electric vehicles, utilizing the algorithm to assist in sizing stand-alone mopped charging stations. The developed tool is based on the toolbox EventSim from MathWorks, which permits the combination of the simulation of discrete events (such as the arrival of customers at the station) with continuous states (such as the simulation of the charging process). The required PV power was estimated by utilizing solar resources, for the location, from renewables. Ninja. The number of customers arriving at the existing oil station is normalized to estimate the energy requirements of the mopped fleet. A Poisson distribution was proposed to model the battery discharge upon arrival, and different related parameters were evaluated through a sensitivity analysis to identify their effects on the performance of photovoltaic charging station. For the testing values, the station parameters were changed by ±25% to determine the impact of key design parameters on station performance, as well as other satisfaction measures such as average waiting time and average queue length. With a 25% increase in photovoltaic panels, the blackout period decreases by 2.12%, while a 25% decrease in photovoltaic panels causes an increase of 2.18% in the blackout period. Utilizing the energy management system (EMS), the waiting time was reduced by 8%.

Investigations for Soil Contamination with Hydrocarbon Compounds near Oil Stations

Field companies are subject to many standards to preserve the environment. Oil companies are considered among the companies that cause the most environmental pollution for two reasons: the first is the extraction of large quantities of crude oil, and the second is their violation of the controls imposed on them. In this research the investigations on the nearby and around a Rumaila oil station area were abducted scientifically through a real tested sample. In this research, investigations in an area near and around the Rumaila Oil Station were conducted scientifically through real laboratory samples. An analysis was made to determine the total petroleum hydrocarbons (TPH), where 22 samples were collected, as well as 5 laboratory samples of soil from an unpolluted area, and crude oil was added to it in known proportions to determine the spectral signature. The ASD Field spec 3 device was used to record the spectral signatures of each sample. Areas sensitive to hydrocarbons 17050 and 1350 appeared. The results show a variation in the concentrations of hydrocarbon in the samples from (2 ppm) at the minimum and reach (197 ppm) at other locations around the station.

Research on Intelligent Construction of Shale Oil Station in Daqing Oilfield

Research on Intelligent Construction of Shale Oil Station in Daqing Oilfield

Wpływ technologii fotowoltaicznej na redukcję gazów cieplarnianych: studium przypadku w Jordanii

The global warming phenomenon, primarily caused by the emissions from conventional energy sources, has become a pressing concern worldwide. Greenhouse gases (GHGs), particularly carbon dioxide (CO2), emitted into the atmosphere contribute significantly to this issue. They have diverse impacts on climate, ecosystems, public health, and socio-economic systems, highlighting the need for comprehensive mitigation and adaptation strategies. To address this problem and minimize GHG emissions, renewable energy sources have emerged as the most promising alternative for power generation. These sources offer a sustainable and clean alternative to fossil fuels, mitigating climate change, reducing air pollution, and fostering energy independence. In the context of this study, a 100 kW solar photovoltaic (PV) station was proposed in Ma’an, Jordan, as a sustainable solution. The effectiveness of this PV station in mitigating GHG emissions was evaluated by comparing it to a base case involving an oil station. To perform this analysis, RETScreen software, a widely recognized tool for assessing renewable energy projects, was used to examine the environmental impact of switching from a conventional energy system to a renewable energy system. The results obtained from the analysis revealed a remarkable reduction in annual gross GHG emissions in the proposed case compared to the base case. Specifically, the emissions would be reduced by 89%, translating to an annual reduction of 49.9 tonnes of CO2. These findings underscore the significant potential of the proposed solar PV station in curbing the emissions responsible for global warming. By significantly reducing GHG emissions, the solar PV station contributes to creating a more sustainable future, aligned with the principles of environmental preservation and climate change mitigation.

Sudan: Oil Station Seized

Sudan: Oil Station Seized

Contactless Interfacial Thin‐Film Breaking Caused Splash‐Like Demulsification of Floating Micron Emulsions via Ionic Wind

AbstractEmulsified oil leakage onto the bulk water surface causes severe issues on global ecology and health. Developing efficient, rapid, and universal separation methods of emulsions has been a significant topic in scientific studies. However, a contactless and additive‐free strategy to achieve continuous floating emulsion separation and oil collection remains to be discovered. Herein, a universal contactless demulsification, transportation, and collection method to dispose floating emulsions by ionic wind, which contains active charged particles generated by corona discharge is reported. The splash‐like demulsification process of floating emulsions is attributed to the rupture of water film enveloped on oil droplet surface, simultaneously and respectively. The evidence of this process recorded by a high‐speed camera with 20 000 fps has a referential significance for other works. This study may clean up universal floating emulsions discharged on water in real situations such as oil stations, chemical plants, and restaurants, and furthermore increase the potential of remote control in liquid dynamics by corona discharge.

Risk Assessment and Reliability Analysis of Oil Pump Unit Based on D-S Evidence Theory

Oil pumps are crucial equipment in pipeline transportation, and their safe and reliable operation is essential for the smooth and efficient operation of the oil station and associated pipelines. The failure of oil pumps can result in significant consequences, making it crucial to evaluate their safety for effective maintenance and reliable system prediction. Failure mode, effects, and criticality analysis (FMECA) is a quantitative fault analysis technique that assigns priority to fault modes using the risk priority number (RPN). However, the RPN may not accurately express uncertainty judgments of risk factors given by multiple experts. To address this limitation, this paper proposes a novel FMECA method based on the D-S evidence theory. The method involves using interval form to obtain risk factor evaluations from experts and data combination to obtain a multi-value representation of the RPN for each fault mode. The prioritization of fault modes is optimized using confidence and fidelity distribution to eliminate multiple modes of the same level. Finally, the normalization method is used to determine the risk degree ranking of oil pump units. Overall, the proposed method is an effective and practical approach for the risk evaluation and reliability analysis of oil pump units.

Integrating queue theory and multi-criteria decision-making tools for selecting roll-over car washing machine

The study aims to develop a decision-making framework by integrating queuing theory and multi-criteria decision-making (MCDM) tools, namely TOPSIS, EDAS, CoCoSo, and TODIM to select a roll-over car washing machine for an oil station. The queue, technical and financial characteristics of the alternatives are added to the decision-making process. The decision matrix includes five criteria and five alternatives. One million weight sets are created randomly, and MCDM techniques are applied to interpret the results statistically. Results indicate that Alternative 3 is statistically superior to the others. The proposed procedure can help decision makers to make decisions when expert knowledge isn’t available, and it can be applied for other purposes by making small changes.

Using novative UAVs to support maritime emergency operations

In the past years, the airship industry became an emerging business with the possibility of developing new transport methods for both tools and people by respecting the environmental constraints given by the United Nations Framework Convention on Climate Change. With this paper, we want to describe a possible scenario of applying this technology. The issue of lost or broken equipment on marine infrastructures is not a rare event. The scenario proposed regarding the delivery of equipment and spare parts to an oil station at sea broke pipe during a storm. We think that the suggested application of this technology may, in the future, help many people. By showing the calculations of the final chapter, we think that using the airships will be a convenient technology in the near future to solve these problems without involving human personnel.

Modernization and Ways to Improve Reliability of Oil Supply to Steam Turbine Units for DPM-2

Russia has announced a DPM-2 programme to modernize old power plant equipment. One of the main areas of modernization is the replacement of some of the equipment while maintaining the foundations, building structures, most of the equipment and piping of the turbine unit. It is common practice to introduce additional equipment, such as control and protection units for electro-hydraulic control systems, as well as new pipework, which leads to problems in the layout of the steam turbine unit.The oil system is an integral part of the turbine unit. It accounts for a significant proportion of the cell volume of the steam turbine unit layout. This property of the system can be used to solve problems associated with the layout of a steam turbine unit in modernizations. A solution is proposed for redesigned layout of the oil system in the cell by introducing an oil supply module (station) into the structure of the steam turbine unit. As of now, there are no commercially available offers of an oil station with the required oil tank capacity. The oil station module is arranged at places free from equipment of the cell, for example, at the 0.000 elevation or under the upper operating mark near the generator and below the level of turbine unit bearings to enable oil drainage by gravity. The main differences are outlined between the proposed oil station and the existing oil system.The oil system determines the reliable and trouble-free operation of the steam turbine unit. In order to be able to introduce an oil supply module into operation it is necessary to design the system based on the requirement of maximum reliability. Reliability analysis of oil supply unit has been carried out. The regularities between the designer's decisions and the reliability of the resulting system are revealed. The influence is considered of the oil station components on individual reliability constituents: survivability, durability, fail-safety, maintainability, fire safety.

Using Fuzzy Inference System in Gas Turbine to Overcome a High Exhaust Temperature Problem

The turbine units are at the forefront of equipment in the process of pumping crude oil and exporting it to the oil ports, where there are many types of turbines used in different sites of Iraqi stations whether pumping oil stations or electrical power production stations. One of the most important types of turbines is the gas turbine, which is frequently used in oil depots. One of the remarkable depots in Iraq is Zubair-1 / Basra that exports around 850,000 barrels per day (B/D). Therefore, Zubair-1 should continue pumping the crude oil 24/7, which has five gas turbines (three Rolls-Royce AVON MK 1533 and two Siemens SGT 400). However, the three Rolls-Royce gas turbines in Zubair-1 have not worked in the summer season since 2016, when the ambient temperature goes high around 11:00 am to 3:30 pm. This paper proposes solution to solve a high exhaust temperature (EGT) shutdown signal (a preventing running turbine signal) without effect on the sequence of turbine running stages. The proposal is adding a fuzzy inference system (FIS) that controls the gas turbine in the first two running stages that demonstrates and controls of speed the turbine from 800 RPM to 3000 RPM. The inputs of FIS are the average temperature of eight combustion chambers (exhaust temperatures) and the speed of the gas turbine, while the output of FIS is the control signal to the flow control valve (FCV) with an amplifier to gain the signal.
 The FIS proposal has been applied in all three Rolls-Royce jet pumping turbines since April 7, 2021, and they work regularly at all times of the day. The FIS minimizes the maximum average of combustion chambers temperature at midafternoon in June 9, 2021 (48 ˚C ambience temperature) from 689 ˚C to 610 ˚C that means the improvement is around 45%.

Control measure prioritization in Fine - Kinney-based risk assessment: a Bayesian BWM-Fuzzy VIKOR combined approach in an oil station.

The Fine − Kinney is a risk assessment method widely used in many industries due to its ease of use and quantitative risk evaluation. As in other methods, it is a method that recommends taking a series of control measures for operational safety. However, it is not always possible to implement control measures based on the determined priorities of the risks. It is considered that determining the priorities of these measures depends on many criteria such as applicability, functionality, performance, and integrity. Therefore, this study has studied the prioritization of control measures in Fine − Kinney-based risk assessment. The criteria affecting the prioritization of control measures are hierarchically structured, and the importance weights of the criteria are determined by the Bayesian Best–Worst Method (BBWM). The priorities of control measures were determined with the fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (FVIKOR) method. The proposed model has been applied to the risk assessment process in a petrol station’s liquid fuel tank area. According to the results obtained with BBWM, the most important criterion affecting the prioritization of control measures is the applicability criterion. It has an importance weight of about 42%. It is followed by performance with 31%, functionality with 18%, and integrity with 10%, respectively. FVIKOR results show that the “Periodic control of the ventilation device” measure is the top priority for Fine − Kinney risk assessment. “The absence of any ducts or sewer pits that may cause gas accumulation in the tank area and near the dispenser; Yellow line marking of entry and exit and vehicle roads; Placing of speed limit warning signs” has been determined as a secondary priority. On conclusion, this proposed model is expected to bring a new perspective to the work of occupational health and safety analysts, since the priority suggested by Fine − Kinney risk analysis methods is not always in the same order as the one in the stage of taking action, and the source, budget, and cost/benefit ratio of the measure affect this situation in practice.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11356-022-19454-x.

Smart textiles for occupational safety health at oil stations and offshore platforms in the Black Sea

The article shows that in order to develop smart textiles, elements of knowledge about the application part in the field are needed to create a model, to describe and propose how to obtain the information necessary to perform statistical analysis of data. The acquired results will serve in making feasible decisions of techno-medical-sanitation and sustainability through safety equipment. The experimental, scientific and practical contribution refers to the design of a model of “optimal sustainable techno-medical-sanitary equipment” by using smart textiles. With the help of this model, it is possible to resort to parametric iteration/reiteration, aiming at the achievement, the value and qualitative fulfilment imposed to a general objective function of sustainable techno-medical-sanitary when smart textiles are used. The developed model goes through further processing in “soft” information programming mode, and then, there will be the possibility and probability of its use as a calculation tool

Presence of Hydrocarbon Degrading Bacteria in Contaminated Soil Collected From Various Fuel Station in Bhilai, Chhattisgarh

Abstract: In this study, we isolated seven strains (termed BY1–7) from polluted soil at an oil station and evaluated their abilities to degrade total petroleum hydrocarbons (TPHs). Among 45 bacterial colonies one bacterial strain was identified based on the cultural, morphological and biochemical characteristics. The isolated bacterium was then subjected to a preliminary assessment of their crude oil after 48 hours of incubation on nutrient agar plates overlaid with 100 ML of petroleum crude oil, the zone of clearance was observed. The isolated bacteria showed 35% petrol degradation, whereas a relatively high oil degradation rate, almost 40% was observed when the bacterium was acclimatized. The selected bacterial strains crude oil resistance was analysed based on the growth ability on the crude oil containing mediums. This strain was identified as Brevibacterium brevis. After inoculation, growth ability was measured and the highest percentage of petrol degradation occurred at temperature 37 °C with the value 30.8%. Bacteria displaying such capabilities are often exploited for the bio-remediation of petroleum oil contaminated environments. Recently, microbial remediation technology has developed rapidly and achieved major gains. However, this technology is not omnipotent. It is affected by many environmental factors that hinder its practical application, limiting the large-scale application of the technology. Keywords: Petroleum hydrocarbon-degrading Bacteria, Petroleum oil, Bio-remediation, Bacterial consortia, Environmental factors, Enzymes.

PENILAIAN RISIKO KESEHATAN KERJA PADA FASILITAS PROSES DI PT X SUMATERA SE

PT X is oil and gas production operations. Production operations are carried out in process facilities, which include oil stations and power plants. The increasing development of oil and gas companies as well as the increasing involvement of the number of workers in this sector have caused the worker very potential to be exposed to hazards in a workplace. HRA is a semi-quantitative risk assessment that determine the magnitude of risk and take control priorities. The purpose of this study was to determine the description of work activities, identify potential hazards, exposure level, and to determine the health risks that may arise, and to determine the control priority based on the Risk Manageability Matrix. This study used descriptive survey, observational approach that uses Walk Through Survey, where results are walking through the checklist, and then analyzed in Matrix Hazard Rating, Matrix Exposure Rating, Risk Matrix, and developed into Risk Manageable Matrix. The results of this study found that the potential hazards included in the moderate risk category are noise, benzene, ergonomics and psychosocial. While the low-risk category is water supply. Potential hazards with moderate risk with low level of control are noise and benzene. Due to the control and prevention efforts against the risk of exposure are not optimal, based on these results, expected of PT X can be done by applying noise control with Hearing Conservation Program, such as evaluating noise exposure. As for benzene exposure, expected that there will be biomonitoring measurements for workers and provide a warning sign to use a respirator with an organic vapor cartridge in process facility.

Thermal Analysis of Parabolic Trough Solar Collector and Assessment of Steam Power Generation at Two Locations in Cameroon

The supply of electrical energy to households remains a major concern in Cameroon. Over the past two decades, the state has devoted enormous financial resources to the construction of thermal power plant working on Heavy Fuel Oil. Despite this effort, it has been noted that the production of electricity from fossil sources has not been up to the expectations of the population because the production cost that remains quite high limits the supply to major urban centers. In this context, it becomes a necessity to explore other sources of production and in particular renewable sources. This paper is concerned with the study of the steam production potential in the stations of Maroua and Yaounde in Cameroon using Parabolic Trough Collectors. Two production modes are considered in this study which are: The direct mode using water and the indirect mode with TherminolVP1 as heat transfer fluid. The modeling of the system is based on the study of the energy balance of heat exchange between the receiver and the calorific fluids in order to assess the impact of incident solar irradiation on the fluid outlet temperature for each generation mode. Using PVGIS solar data, the outlet temperature profile of water as well as the thermal power generated and the system efficiency for different series associations using a variable number of collectors were analyzed. It was shown that the temperature of the steam increases with the increase in the number of collectors. For an association of 8 collectors, the average daily production time of pressurized steam at 40bars is 8 hours with a maximum temperature of 600 °C in direct mode and 490 ° C in indirect mode for the month of February in Maroua. The maximum efficiency for the same month is 72.7% in direct generation and 60.7% in indirect generation. These results confirm the possibility of energy generation combining solar sources with existing heavy fuel oil stations for better efficiency. However, further investigations about the energy demand and the supply are necessary for appropriate sizing of the solar generator.