Oil Refinery Industry Research Articles

Advancing green technology: demulsifier preparation and evaluation for crude oil emulsion treatment using corn oil

Globally, oil production has steadily increased which causes a rise in the coproduction of oil and water emulsions. These emulsions pose significant challenges in transportation and the oil refinery industry, causing high-pressure drops and corrosion problems due to chlorides in the water. Despite advancements in renewable energy, crude oil remains a primary energy source. The crude oil industry faces numerous challenges, including cost emulsion issues. This study developed a corn oil bio-demulsifier (MFK). A unique demulsifier was tested using FTIR, GC-MS, and TGA. Using the bottle test method, the produced demulsifier MFK was tested with Basrah oil and East Baghdad S1 oil. The emulsion-breaking processes have been studied under several factors, such as settling time, dosage, temperature, pH, water content, and mixing time after demulsifier addition. At 2000 ppm Basrah oil, water separation efficiency reached 75%. For East Baghdad S1 oil, the highest separation result was 43.3% at 4000ppm, after 5 h of settling time at 70°C, with a 30/70 water-to-oil ratio. When studying the pH, the best water separation rate was 86.5% at a pH of 10. The best water content was 92% when the water-to-oil ratio was 50/50, and the best demulsifier mixing time with the emulsion was 2 min with a separation rate of 74.5%. When mixing was increased, undesirable results occurred. This study demonstrated that biodemulsifiers may replace conventional biodemulsifiers in early units while reducing environmental and economic impacts with further study and development.

Sustainable locating of petroleum refinery projects

The Petroleum Refinery Industry (PRI) is notorious for its significant contribution to environmental degradation. Operations of refineries in local neighborhoods often lead to adverse impacts on the surrounding community and environment. However, PRI projects also yield positive effects on local, national, and international economies. Mitigating the negative consequences of refinery operations necessitates a scientific and quantitative approach to selecting refinery locations. This process should consider a multitude of parameters and alternatives, encompassing social and environmental resiliency, transportation factors, and product markets throughout the refinery life cycle, in an integrated manner. Quantifying the impact of these parameters on the triple bottom line is essential for informed decision-making.In this study, we employ a previously developed integrated sustainability assessment framework in conjunction with a Multiple Attribute Decision Making (MADM) based scenario model to evaluate the impact of various location alternatives on the three pillars of sustainability. Despite the complexities inherent in refinery location decisions and the unpredictability of long-term and short-term parameters, this study's life-cycle approach offers a valuable tool for locating petroleum refineries.

Response surface methodology optimization of the effect of pH, contact time, and microbial concentration on chemical oxygen removal potential of vegetable oil industrial effluents.

The vegetable oil refinery industry generates highly polluted effluents during oil production, necessitating proper treatment before discharge to prevent environmental hazards. Treating such wastewater has become a major environmental concern in developing countries. Chemical oxygen demand (COD) is a key parameter in assessing the wastewater's organic pollutant load. High COD levels can lead to reduced dissolved oxygen in water bodies, negatively affecting aquatic life. Various technologies have been employed to treat oily wastewater, but microbial degradation has gained attention due to its potential to remove organic pollutants efficiently. This study aims to optimize the biodegradation treatment process for vegetable oil industrial effluent using response surface methodology (RSM). The wastewater's physicochemical properties were characterized to achieve this, and COD removal was analyzed. Furthermore, RSM was used to investigate the combined effects of pH, contact duration, and microbial concentration on COD removal efficiency. The result showed that the microbial strain used recorded a maximum COD removal of 92%. Furthermore, a quadratic model was developed to predict COD removal based on the experimental variables. From the analysis of variance (ANOVA) analysis, the model was found to be significant at p < 0.0004 and accurately predicted COD removal rates within the experimental region, with an R2 value of 90.99% and adjusted R2 value of 82.89%. Contour plots and statistical analysis revealed the importance of contact duration and microbial concentration on COD removal. PRACTITIONER POINTS: Response surface methodology (RSM) optimization achieved a significant chemical oxygen demand (COD) removal efficiency of 92% in vegetable oil industrial effluents. The study's success in optimizing COD removal using RSM highlights the potential for efficient and environmentally friendly wastewater treatment. Practitioners can benefit from the identified factors (pH, contact time, and microbial concentration) to enhance the operation of treatment systems. The developed predictive model offers a practical tool for plant operators and engineers to tailor wastewater treatment processes. This research underscores the importance of sustainable practices in wastewater treatment, emphasizing the role of microbial degradation in addressing organic pollutant loads.

Sensitivity Analysis of Edible Oil Refinery Industry using Machine Learning

This research paper discusses the use of machine learning for sensitivity analysis in the edible oil refinery industry. The edible oil refinery consists of four units, and subsystem A (Cleaning) contains parallel subcomponents that enable it to function in reduced capacity when some of its components fail. As a result, the system operates in reduced capacity and fails entirely when unit A fails. There is single repairman who is available for 24x7. The failure and repair time distributions are distinct and constant for each unit. Subunits B (Shelling), D (Crushing/Ribbing), and E (Expeller Pressing) are connected in series, so, if any of them malfunctions, the entire system fail. System parameters' behavior for various repair and failure rates is discussed graphically and in tabular form. Comparison of the Performance of system parameters is carried out using linear Classifier and Logistic Regression and graphs are drawn. From the comparative analysis of models, it is concluded that the linear classifier is better than logistic regression for MTSF, Busy Period of server and Availability.

Metal levels in sediments and caged mussels in one of the industrial zones of the Eastern Aegean Sea.

Caged mussels make biomonitoring studies possible with their ability to take up pollutants in the industrial zones. The goal of this study was applied to assess metal levels in the biomonitoring organism Mytillus galloprovincialis Lamark, 1819 for transplantation from three locations for two periods (2016-2018) in the industrial zone of the Eastern Aegean Sea. Metals were also determined in sediments; high concentrations of Hg, As and Zn in surficial sediments of Nemrut Bay can cause hazardous impacts on the aquatic environment with respect to sediment quality guidelines. The highest contamination factor (Cf) was calculated for Hg (Cf = 10), suggesting serious anthropogenic pollution in the study area. According to Pearson product-moment correlation analysis, As is not correlated with other metals due to As mainly originating from natural sources. Hg, Cd, Pb and Cu concentrations increased in the transplanted mussels during a field transplant experiment because of chronic pollution from industrial activities. Cumulative effects of both the oil refinery and shipbreaking industry cause higher uptake of Hg, Cd, Pb and Cu in sampling station 3 as a result of higher exposure levels in transplanted mussels. Mussel consumption was compared with provisional maximum tolerable intake from literature; the estimated provisional intake (EDI) for Cd, Hg and Pb does not exceed maximum levels; however, Cu and Zn exceed reference EDI values. Since Nemrut Bay is heavily influenced by industrialisation, it is not a suitable region for seafood production.

Towards improvement of hydroprocessing catalysts - understanding the role of advanced mineral materials in hydroprocessing catalysts

Mineral materials play a pivotal in heterogeneous catalysts as active, support, or promoter components, with the oil refinery industry being one of the biggest beneficiaries. While conventional hydroprocessing catalysts have historically met the industry’s needs, the growing need to accommodate unique feedstocks, meet the increasing demand for environmentally acceptable products, obtain better product specifications, enhance selectivity for reactions to increase ratios for certain product cuts, and use more cost-effective and abundant mineral materials, has recently motivated for fresh considerations in the development of hydroprocessing catalysts. Based on periodic trends, noble metals possess the most desirable qualities, but their relative abundance in the Earth’s crust is too low to meet industry needs. They are costly and highly sensitive to sulfur poisoning. Mo and W lie in the sweet spot, but it is anticipated that they cannot meet the increasing demand. Investigations of electronic interactions of more economical and abundant metals, such as Nb, V, and Fe, with other elements and support materials have yielded a better understanding of synergistic effects that help to access noble metal-like qualities. This work contrasts conventional hydroprocessing catalysts and recently improved catalysts, detailing the chemistry considerations behind the selection of mineral materials used in the catalysts. It also explores how further manipulation of these mineral materials and synthesis approaches is driving toward more desirable properties. The work brings to the attention of the readers the challenges and opportunities for the further improvement of hydroprocessing catalysts to ensure environmental sustainability while meeting the industry’s growing needs.

MgO/fluid catalytic cracking (FCC) ash blends for 3D printing on vertical surfaces

Fluid catalytic cracking (FCC) ash is a common industrial waste in the crude oil refinery process. In this study, raw FCC ash was incorporated to develop sustainable MgO/FCC ash blends for 3D printing on vertical surfaces. Rheological and tack behaviors of MgO/FCC ash blends were systematically studied, followed by the assessment of mechanical property and hydration products. On this basis, the suitable mixture for 3D printing on the vertical surfaces was determined, and its feasibility was verified with lab-scale 3D printing. Finally, the environmental impact of the developed mixture was estimated through batch leaching and composition tests. This study provides an alternative method to upcycle FCC ash as an ingredient for 3D concrete printing, which brings benefits to both the construction and oil refinery industries. Besides, the rheological, tack, and hydration investigations of the MgO/FCC ash blends guide the future design of similar mixtures with upcycled wastes.

Pembuatan Gum Xanthan dengan Proses Fermentasi dari Hidrolisat Selulosa Eceng Gondok dan Penerapannya dalam Enhanced Oil Recovery

Water hyacinth is a freshwater plant that has a negative impact on waters, but has a high cellulose content (77.6%) and is still underutilized. One alternative in controlling the amount of water hyacinth is to utilize its potential cellulose content as an ingredient in xanthan gum. Fermentation was carried out with the help of Xanthomonas campestris and xanthan gum was obtained, which can be used as a polymer injection material to increase crude oil production in the oil refinery industry. The stages to obtain xanthan gum are delignification, hydrolysis, and anaerobic fermentation (28 °C) with a time variation of 24 hours to 120 hours with an interval of 24 hours. The cellulose hydrolysate variable is 0.5%, 1.0%, 1.5%, 2.0%, and 2.5%. The yield of xanthan gum in this research was 18%, with a moisture content was 13% – 15% and an ash content was 3% –3.9%. The resulting xanthan gum was analyzed for its functional groups using Fourier Transform Infra Red (FTIR) and was in agreement with commercial xathan gum.

Vertex-edge based resolvability parameters of vanadium carbide network with an application

A big amount of vanadium is used in the industry. It is used as a vanadium carbide stabiliser in steel production. Only 0.5 % vanadium in an iron alloy will double the tensile strength. Vanadium salts are used in leather, ink, dye manufacturing and yellow ceramic glaze. On the other hand, vanadium pentoxide is used as a catalyst, in the chemical industry, for the production of sulphuric acid and in the petroleum refinery industry. Resolvability parameter is the most discussed topic in graph theory. This helps to reorganise a network in a unique way, sometimes in terms of atoms (metric dimension) and sometimes bound (edge metric dimension). We studied resolvability parameters of vanadium carbide network in this article i.e. metric, edge metric and partition dimension. Among these metrics resolvability defined by parameters taking a subset from the set of vertices, if it has a unique representation with all the vertices, then it is called a resolving set. The number of elements in the smallest resolving set is called the metric dimension. While the number of elements of the minimal subset of vertices taking from vertex set is called the edge metric dimension, if the representations are unique of all edges and the set is called the edge resolving set. This study can have an effect in many ways in the research, particularly, with the help of some key points such as network structure analysis, material science via material properties, graph theory applications, predictive modelling, material testing and characterisation, as well as in industrial applications.

Petroleum coke derived reduced graphene oxide as an electrocatalyst for water splitting

One of the by-products produced in the petroleum refinery industry is Petroleum coke or pet coke (PC). To make its use in the development of high-cost value-added carbon products apart from electrodes in steel and aluminium extraction is one of the areas of research interest among the scientific community. The present investigation optimized processing parameters to synthesize graphene oxide (GO) using the well-known Hummers method from different heat treated (450 °C, 1400 °C, and 2200 °C) PC. The derived GO was thermally reduced into the reduced GO (rGO). Both GO and rGO were characterized by various spectroscopic techniques to ascertain ultimate GO and rGO synthesis. The FE-SEM images demonstrated that the surface morphology of the GO and rGO is highly exfoliated and has a thin sheet-like structure that is synthesized from 2200 °C heat-treated PC. The HR-TEM image shows a few layers of sheet-like structure for both GO and rGO and the SAED pattern shows fused for GO and the hexagonal ring pattern for rGO, indicating the presence of both amorphous and crystalline structures. The obtained rGO possesses a low band gap (2.45 eV) that is attributed to the semiconducting behavior. BET analysis reveals that synthesized GO possesses a decent specific surface area (211.2 m2/g). The upshot shows that PC has the potential to replace the costly natural graphite for the synthesis of GO and rGO having excellent properties. The obtained rGO demonstrates excellent bifunctional electrocatalyst materials for hydrogen and oxygen evolution reactions (HER and OER). The rGO/Ni-Foam electrode shows a low overpotential of 169 mV for HER and 400 mV for OER at 10 mA/cm2 current density in 1.0 M KOH electrolyte solution along with the lowest Tafel slope of 108.23 mV/dec and 104 mV/dec for HER and OER respectively shows faster kinetic rate towards water splitting. This study displays the vast possibility of utilizing PC to synthesize value-added products and its application as an electrocatalyst.

Soft Sensing of LPG Processes Using Deep Learning.

This study investigates the integration of soft sensors and deep learning in the oil-refinery industry to improve monitoring efficiency and predictive accuracy in complex industrial processes, particularly de-ethanization and debutanization. Soft sensor models were developed to estimate critical variables such as the C2 and C5 contents in liquefied petroleum gas (LPG) after distillation and the energy consumption of distillation columns. The refinery's LPG purification process relies on periodic sampling and laboratory analysis to maintain product specifications. The models were tested using data from actual refinery operations, addressing challenges such as scalability and handling dirty data. Two deep learning models, an artificial neural network (ANN) soft sensor model and an ensemble random forest regressor (RFR) model, were developed. This study emphasizes model interpretability and the potential for real-time updating or online learning. The study also proposes a comprehensive, iterative solution for predicting and optimizing component concentrations within a dual-column distillation system, highlighting its high applicability and potential for replication in similar industrial scenarios.

Reliability Estimation Using EM Algorithm with Censored Data: A Case Study on Centrifugal Pumps in an Oil Refinery

Centrifugal pumps are widely employed in the oil refinery industry due to their efficiency and effectiveness in fluid transfer applications. The reliability of pumps plays a pivotal role in ensuring uninterrupted plant productivity and safe operations. Analysis of failure history data shows that bearings have been identified as critical components in oil refinery pump groups. Analyzing historical failure data for such systems is a complex task due to censored data and missing information. This paper addresses the complexity of estimating the Weibull distribution parameters using the maximum likelihood method under these conditions. The likelihood equation lacks an explicit analytical solution, necessitating numerical methods for resolution. The proposed approach presented in this article leverages the expectation maximization (EM) algorithm for estimating the Weibull distribution parameters in a real-world case study of a complex engineering system. The results demonstrate the superior performance of the EM algorithm with censored data, showcasing its ability to overcome the limitations of traditional methods and provide more accurate estimates for reliability metrics. This highlights the importance of obtaining results through these methodologies in the analysis of reliability and in facilitating more informed decision making in complex systems.

Mechanical and microstructure behaviour of aluminum nanocomposite fabricated by squeeze casting and ultrasonic aided squeeze casting: A comparative study

In the search for novel, affordable and efficient reinforcement, it is challenging to identify rare materials that seek to agree and enrich each other. The spent catalyst waste exhausted from the oil refinery industries has been examined as a reinforcement for recycling and reuse. In this investigation, aluminum composites were fabricated through two distinct casting processes: ultrasonic-aided squeeze casting and conventional squeeze casting. The aluminum composites were generated by reinforcing them with two different concentrations of waste spent catalyst (WSC) and silicon carbide (SiC) (1.0 wt. % and 2 wt. %) with an average particle size of 288 and 272 nm, respectively. The reinforcing particle was introduced into the matrix by a novel powder injection technique. The mechanical and microstructural characteristics of aluminum nanocomposites obtained by both techniques were studied and compared. The composite microstructure produced by the squeeze casting with ultrasonic vibration enhances the homogenous dispersion of reinforcing particles. X-ray diffraction (XRD) and energy dispersive x-ray analysis (EDAX) reveal no sign of oxide and impurities formations or secondary phase in the composites. Optical microscopy revealed that the addition of reinforcement particles and aggressive ultrasonic vibration resulted in grain refinement of the α-Al dendrites. The tensile strength and hardness of the aluminum composites fabricated with ultrasonic vibration increased by 64.47 % and 65.59 % compared to the composite obtained without ultrasonic vibration. Different strengthening mechanisms have been used to determine the strength of the aluminum composites. The strengthening contribution, mainly due to the thermal mismatch between the matrix and the reinforcement particles, considerably enhanced the strength of the composites. Moreover, the entire test results reveal that the ultrasonic-aided squeeze-casting improves the microstructure and mechanical characteristics of the composites compared to the squeeze-casting approach.

Optimization design of crude oil distillation unit using bi-level surrogate model

Crude Oil Distillation Unit (CDU) is one of the most important separation installations in the petroleum refinery industries. In this work, a Bi-level Surrogate column model Aided Constrained Optimization Design (Bi-SACOD) is proposed for time-consuming objectives and constraints in the evolutionary optimization design of CDUs. The main components of Bi-SACOD include bi-level surrogate model construction (Bi-SMC), bi-level model management (Bi-MM), and particle swarm optimization (PSO) mixed-integer constrained evolutionary (PSO-MICE) search. Bi-SMC implements surrogate column model construction and feasible domain identification. Bi-MM combines surrogate column models with rigorous CDU simulations to perform model management, and PSO-MICE implements optimum search works. The optimization results of the CDUs indicate that Bi-SACOD outperforms the single-level surrogate column model approaches, and are more consistent with the rigorous CDU model optimization approach, whereas the evaluation numbers of the time-consuming rigorous models are significantly reduced.

New oil derivative refractive index sensor using ribbon of multi-walled carbon nanotubes

In this work, we propose a new liquid refractive index (RI) sensor based on one-dimensional (1D) regular array of multi-walled carbon nanotubes (MWCNTs) for sensing oil derivatives (ODs), for the first time. The proposed sensor is a ribbon consisting of 10 MWCNTs grown inside an AAO (Al2O3) template as the host material, which can sense the change of host material RI with high precision up to △n = 0.0015 corresponding to the sensitivity S = 930 nm/RIU. Replacing the host material with ODs changes the reflection in the range of visible wavelengths. The reflection spectrum of sensor is calculated for the RI range of 1.3888–1.5306 belonging to various ODs. The RI difference △n = 0.1418 between Butanol (C4H10O) and Nitrobenzene (C6H5NO2) host materials results in 130 nm wavelength shift. By removing one or two cylinders of MWCNTs and creating a point defect within the sensor structure, whereas ODs are injected into the defect area, we achieved a sensitivity up to 430 nm/RIU. The proposed sensor with un-reactive nature of MWCNTs can be used in environments with high temperature and pressure such as oil refinery industry.

Oil in statu nascendi. The state of the oil industry in Galicia in 1853

In the autumn of 1853, the Krakow Chamber of Commerce entrusted its member Antoni Szwarz with the task of conducting a personal survey of industrial and commercial facilities in Western Galicia. His mission was to gather statistical data from these economic sectors. The official surveyor’s findings provided a credible picture of the material state, industrial infrastructure, and economic awareness regarding the oil deposits in Galicia. Interestingly, these oil reserves were often underappreciated and remained largely untapped. Antoni Szwarz’s report also offers a parallel perspective on the experiences of Ignacy Łukasiewicz, who explored the oil-bearing regions of Eastern Galicia around the same time (between 1852 and 1853). It was during this period that the symbolic era of oil began, marked by the discovery and patenting of fractional distillation methods by Polish pharmacists Ignacy Łukasiewicz and Jan Zeh, as well as the development of a prototype oil lamp. This lamp was intended to consciously create and popularize demand for a superior illuminating fuel—namely, the oil fraction.The events of 1853 laid the foundation for professional oil mining, refinery industry, and mass distribution of petroleum products. Łukasiewicz continued this journey by establishing a pioneering oil mine in Bóbrka near Krosno in 1854. An official economic report published in the press a few months before these groundbreaking steps serves as a testament to the state of official knowledge at the national level during the transition years of 1853 and 1854. It also reflects the economic innovation driven by oil and Łukasiewicz’s discoveries in the region and beyond. Key words: oil industry, Western Galicia industry, Ignacy Łukasiewicz, 19th-century oil mining, Bóbrka 1854, “Czas” 1854, Kobylanka

Problems of industrial waste disposal in the Fergana region

In the article, the problems of waste disposal of production plants such as "Fergonazot" JSC, "Koqon spirt" JSC, "SWC" JSC, Fergana oil refinery and textile industry enterprises in Fergana region were studied and provided information on the results of the conducted research. Also, socially and environmentally effective methods of waste processing and disposal were researched. Work was carried out to calculate the efficiency of processing. Information on technological processes, tools, equipment and research methods for obtaining chalk, lime, gypsum, cement and other building materials through waste processing was presented.

Mechanism and design of fluid catalytic cracking ash-blended cementitious composites for high performance printing

As a common waste in the oil refinery industry, fluid catalytic cracking (FCC) ash is used to partially replace cement for high-performance high-speed 3D concrete printing (3DCP). Effects of FCC ash on hydration, rheology, and compressive strength were evaluated systematically, and the optimal substitution rate was determined as 20 wt. % of cement. A cylinder with 240 mm diameter and 500 mm height was successfully printed at a high speed of 100 mm/s with the optimal mixture in 5 min 53 s only. Moreover, the optimal mixture shows good leaching performance, and it also reduces CO2 emission by 21.45 % and materials’ cost by 17.98 % compared with the control. In addition to material optimization, the contributions of FCC ash to the early hydration and static yield stress were extensively analyzed. Complementary calorimetric and mineralogical investigations show that FCC ash accelerates the initial hydrolysis of cement and hydration of C3A and C3S. On the other hand, the quantitative analyses of static yield stress reveal the contributions of FCC ash on the colloidal force, volume fractions, particle size distribution, and ultimately static yield stress evolution. The developed 3D printable cementitious material possesses multiple advantages, including high-speed printing compatibility, enhanced sustainability, and high commercial values for oil refinery and construction industries. Based on the mineralogical property of FCC ash, the study also enlightens potential research and application of zeolite in 3D concrete printing in the future.

Microwave‐Assisted Bleaching of Olive Pomace Oil: Optimization of Bleaching Parameters and Comparison with Conventionally Bleached Oil

AbstractIn this research, microwave‐assisted bleaching of olive pomace oil is studied under different conditions. Microwave power, mixing time, and adsorbent dosage are optimized using the response surface central composite design, where the optimum conditions are 102 W, 20.07 min, and 4.15%, respectively. The microwave‐bleached oil is compared with the conventionally bleached oil in terms of color, oxidation parameters, sterol composition, and benzo[a]pyrene content. Microwave‐assisted bleaching of the olive pomace oil is performed by using 17% less adsorbent in an 83% shorter time compared to the conventional method. A bleaching performance comparable to the conventional method is achieved using the microwave‐assisted bleaching technique. Microwave‐assisted bleaching can thus be used as an alternative method for the bleaching of olive pomace oil.Practical applications: The microwave‐assisted bleaching method presents attractive advantages, including a shorter bleaching time and a lower amount of adsorbent used. In this respect, the current research contributes toward the conventional bleaching method in the vegetable oil refinery industry and creates a paradigm for future studies on the bleaching of vegetable oils.

Analytics for Recovery and Reuse of Solid Wastes from Refineries

Heavy fractions of petroleum have for long time been bypassed in favour of lighter fractions. Nowadays, in the framework of the “circular economy”, there is a growing interest in residual petroleum heavy fractions. The present work briefly reviews the use and characterization at laboratory scale of some low valuable solid or semi-solid products of the oil refinery industry: asphaltenes (bitumen/asphalt), pet-coke and pitch for use as fuels. The use of solid and semi-solid refinery residues, in particular, of coke as a coal substitute in thermochemical processes and of pitch and asphaltenes as material precursors, requires careful analysis, and an understanding of their structure at the molecular level is mandatory for the development of processing technology. Techniques for the characterization of typical petroleum heavy fractions such as pitches, asphaltenes and cokes are reviewed. An experimental protocol for investigating at the laboratory scale the thermochemical conversion behavior of solid and semi-solid refinery wastes is proposed.