Refinery Operations Research Articles

Hydrocracking of complex mixtures: From bulk properties, over fundamental kinetics to detailed product composition

Crude-Oil-to-Chemicals (COTC) is a novel concept in the oil industry in which the production of base chemicals is preferred over fuels. This concept requires an intensive integration of refinery and petrochemical operations and, in most cases, hydroconversion and steam cracking play an essential role. In the present work, particularly the role of hydroconversion is assessed in selected COTC scenarios via a simulation framework based on fundamental modeling that seamlessly integrates a Single-Event Microkinetics description of the cracking reactions with a molecular reconstruction strategy based on Shannon Entropy maximization for determining the detailed feedstock composition. Dealkylation and ring opening reactions have been identified as the crucial ones to produce good steam cracker feeds, i.e., mixtures of paraffins in the C3-C21 range, especially n-paraffins. Simulation results show that for a typical VGO paraffins yield in the desired fraction increases from 8.9% wt/wt to 19.6% wt/wt with an increase of +5 kJ/mol in the acidity strength of the catalyst (ΔHprot) and an increase of +10°C in the operation temperature. In general, it was found that the yield of the total C3-C21 fraction increased by +1.42 wt% per kJ/mol decrease of the ΔHprot of the catalyst, while per °C temperature increase the yield of the same fraction increased by of + 0.46 wt%.

Crude-specific Optimal Operation of Hydrodesulfurization

Crude oil has different characteristics according to its origin, and this difference causes suboptimal operation if not considered. Similar to other refinery operations, hydrodesulfurization suffers from lacking this knowledge. Information on the true boiling point curve of the feed, next to its sulfur concentration, can be used to optimize the operating temperature. In this work, an optimization problem is demonstrated for two manipulated temperatures of the system and solved by using a gradient-based and a gradient-free algorithm. While the gradient based solution has a single objective of minimum sulfur content, the gradient-free solution has three objectives: minimum sulfur, inlet temperature, and secondary hydrogen flow rate. A continuous lumping model is used to predict the temperature and sulfur responses of a real hydrodesulfurization plant. An adaptive approach is preferred for the model to cope with the catalyst deactivation interference on the product sulfur content constraint. The effect of changing feed on optimality is demonstrated by using eight types of feeds with varying true boiling point and sulfur content. In addition to that, the impact of catalyst age is shown on similar feed processed on different dates.

Fluid catalytic co-processing of bio-oils with petroleum intermediates: Comparison of vapour phase low pressure hydrotreating and catalytic cracking as pretreatment

For co-processing of bio-oil and conventional fossil feed in existing refinery fluid catalytic cracking (FCC) units, little attention has been paid to the increased aromatics and basic nitrogen content in the feed associated with the introduction of bio-oil and how it affects FCC performance. In this contribution, the effect of blending two bio-oils obtained from different catalytic treatment of wheat-straw pyrolysis vapors with atmospheric residue was tested using a microactivity testing unit (MAT). The catalysts used for the pyrolysis vapor phase upgrading included i) a Na/γ-Al2O3 deoxygenation catalyst, and ii) a Pt/TiO2 catalyst in combination with H2 atmosphere. The oxygen content of both bio-oils was similar at ~ 7–8 wt%, but the Na/γ-Al2O3 bio-oil had a lower total acid number (TAN) of 5 mg KOH/g and a higher basic nitrogen (BN) content of 0.7 wt% compared to the Pt/TiO2 bio-oil (15 mg KOH/g, 0.4 wt% BN).The processing of the upgraded bio-oils in blends with atmospheric residue in MAT increased the yields of dry gas, CO, CO2, and coke at the expense of naphtha (decrease by 2.8 percentage points) and decreased the conversion by ~ 2.5 percentage points. This is attributed to the high aromaticity and basic nitrogen content of the two bio-oils. The lower basic nitrogen content and higher degree of saturation for the Pt/TiO2 bio-oil may explain its slightly higher conversion (by ≤ 1 percentage points) compared to the Na/γ-Al2O3 bio-oil.This contribution provides important information for refinery operators interested in FCC co-processing of fossil oils and biomass-derived pyrolysis oils with elevated content of nitrogen and aromatics.

Costs vs. Flexibility of Process Heat Recovery Solutions Considering Short-Term Process Variability and Uncertain Long-Term Development

To significantly decrease fossil carbon emissions from oil refineries, a combination of climate mitigation options will be necessary, with potential options including energy efficiency, carbon capture and storage/utilization, biomass integration and electrification. Since existing refinery processes as well as many of the potential new processes are characterized by large heating demands, but also offer large opportunities for process excess heat recovery, heat integration plays a major role for energy efficient refinery operation after the implementation of such measures. Consequently, the process heat recovery systems should not only be able to handle current operating conditions, but also allow for flexibility towards possible future developments. Evaluation of the flexibility of process heat recovery measures with both these perspectives enables a more accurate screening and selection of alternative process design options. This paper proposes a new approach for assessing the trade-off between total annual cost and potential operating flexibility for the heat exchanger network in short-as well as in long-term perspectives. The flexibility assessment is based on the evaluation of a flexibility ratio (similar to the conventional flexibility index) to determine the range in which operating conditions may vary while at the same time achieving feasible operation. The method is further based on identification of critical operating points to achieve pre-defined flexibility targets. This is followed by optimization of design properties (i.e., heat exchanger areas) such that feasible operation is ensured in the critical operating points and costs are minimized for representative operating conditions. The procedure is repeated for a range of different flexibility targets, resulting in a curve that shows the costs as a function of desired flexibility ratio. The approach is illustrated by an example representing a heat exchanger network retrofit at a large oil refinery. Finally, the paper illustrates a way to evaluate the cost penalty if the retrofit is optimized for one operating point but then operated under changed conditions. Consequently, the presented approach provides knowledge about cost and flexibility towards short-term variations considering also changes in operating conditions due to long-term development.

Challenges in determining the renewable content of the final fuels after co-processing biogenic feedstocks in the fluid catalytic cracker (FCC) of a commercial oil refinery

The long-distance transport sector will be difficult to electrify and will likely require lower-carbon intensive, drop-in fuels if the sector is to effectively decarbonize. Policies such as the low carbon fuels standard (LCFS) have proven to be particularly effective in encouraging oil companies to produce lower carbon intensity (CI) fuels that the long-distance transport sector can use. One way to reduce the carbon intensity of the fuels is to co-process lower carbon intensive feedstock at various insertion points within a refinery (e.g. the hydrotreater or the fluid catalytic cracker (FCC)). However, to obtain “credits” from the appropriate regulator the carbon intensity of the final fuel and the renewable content must be determined. To date several processes, such as material balance and C14/C13-tracking, have been used to determine the renewable content of the final fuels, with each of these methods having their own strengths and weaknesses. As described here, challenges such as the lack of consistent terminology, through to variations in the “background noise” encountered in typical refinery operation, have complicated carbon intensity and renewable content determinations. However, when a co-processing approach is used in a routinely operating refinery, a multiple regression-based mass balance approach (based on observed yield) combined with C14 analysis is able to determine the renewable content of the final fuels.

PONDASI BALIK KOTAK DITANAH LUNAK

The problem is the difficulty in determining the type and method of manufacture and installation of foundation on soft soils. The research objective is to provide an overview of the type of foundation, the method of manufacture and the method of installation of the foundation which is suitable and suitable in the soft soil environment. This research method uses used research methods with trial and error, and with a case study approach method, namely the case of difficulties in overcoming the problem of the availability of permanent structural support foundations and refinery operation equipment on soft soil. The results showed that the type and shape of the foundation that is suitable and to solve the problem is the foundation behind the box. This foundation specification is an inverted box with reinforced concrete material and certain dimensions with cover plates. The results of this used research also show that the inverted box type of foundation is suitable for supporting equipment supporting refinery operations such as pipe supports and other refinery operation equipment.

Comprehensive Assessment of Behavioral Risk Factors within the Health Risk Management System for Oil Refinery Operators

Summary. Introduction: Comprehensive risk management considering behavioral risk factors is a possible way to minimize adverse health effects of occupational factors. The purpose of the study was assess behavioral risk factors and to develop appropriate measures for preventing occupational diseases in oil refinery operators. Materials and methods: The observation groups included crude oil treatment operators of Ritek LLC in the Volgograd Region located in the subarid climatic zone. The first group consisted of 100 workers under the age of 35 while the second group consisted of 106 workers aged 36-60. Previously published studies were used to substantiate priority occupational risk factors for the operators. To assess lifestyle habits, we conducted a questionnaire-based survey and analyzed data in terms of their statistical significance and real controllability using a multidimensional confirmatory factor analysis. Results: We established that the priority occupational health risks of operators in the climatic conditions of the Volgograd Region included labor severity and intensity (3.1) and hot environment (3.2) posing a high occupational risk of disrupting the thermal state (overheating) of workers. We also identified typical behavioral risk factors, the prevalence and quantitative burden of which was age-specific. In the younger age group, bad habits and poor healthcare activity (reluctance to seek medical advice) generated the highest burdens (943 conditional units each) while in the older age group, major burdens were generated by bad habits and malnutrition (849 and 501 units, respectively). The developed mathematical model proved that a comprehensive health risk management for workers exposed to occupational hazards is feasible by correcting certain behavioral risk factors: a 10 % and 50 % decrease in the burden of bad habits and poor healthcare activity led to a 1.1 and 1.5-fold decrease in the extent of health risk, respectively. Conclusion: The study revealed the most significant behavioral risk factors affecting health of oil refinery operators and substantiated options of the most optimal interaction between the elements of the system reducing the overall risk to human health. Comprehensive health risk management based on optimal interaction of system elements (both occupational and behavioral risk factors) reduces health risks for oil refinery operators.

Modelling Variation in Petroleum Products’ Refining Footprints

Energy-related greenhouse gas emissions dominate the carbon footprints of most product systems, where petroleum is one of the main types of energy sources. This is consumed as a variety of refined products, most notably diesel, petrol (gasoline) and jet fuel (kerosene). Refined product carbon footprints are of great importance to regulators, policymakers and environmental decision-makers. For instance, they are at the heart of current legislation, such as the European Union’s Renewable Energy Directive or the United States’ Renewable Fuels Standard. This study identified 14 datasets that report footprints for the same system, namely, petroleum refinery operations in Europe. For the main refined products, i.e., diesel, petrol and jet fuel, footprints vary by at least a factor of three. For minor products, the variation is even greater. Five different organs of the European Commission have estimated the refining footprints, where for the main products, these are relatively harmonic; for minor products, much less so. The observed variation in carbon footprints is due mainly to differing approaches to refinery modelling, especially regarding the rationale and methods applied to assign shares of the total burden from the petroleum refinery operation to the individual products. Given the economic/social importance of refined products, a better harmony regarding their footprints would be valuable to their users.

Improving the thermo-physical and rheological properties of crude oil (CO) by the synthesized CuO/SiO2/CaP nanocomposite for drag reduction through horizontal pipelines

The thermo-physical properties and rheological behavior of crude oil (CO) have substantial efficacies on transportation, processing, and refinery operation. SiO2 (silica)–CaP (calcium phosphate)–CuO (copper oxide) nanocomposite was synthesized by the sono-co-precipitation technique. In this work, the impact of nanocomposite volume fraction as well as temperature on the thermo-physical and also rheological characteristics of SiO2–CaP–CuO-based CO nanofluid were evaluated. All experimental tests were done in the temperatures and nanocomposite concentrations of 25–55 °C and 0.05–0.75 vol.%, respectively. Also, the drag reduction of the nanofluid in horizontal pipelines was elucidated by the SiO2–CaP–CuO-based CO nanofluid at 25 °C. The highest dynamic viscosity enhancement was found to be about 44.57% for 0.75 vol.% nanocomposite particles. The nanofluids thermal conductivity augmented with nanocomposite volume fraction increment. The greatest increment in nanofluids thermal conductivity was obtained about 17.26% at 0.75 vol.%. Moreover, four correlations were expanded for the dynamic viscosity and thermo-physical characteristics of the nanofluids with relative average deviation (RAD) percentage of less than 1%, which depended on temperature and nanocomposite volume concentration. The empirical relationships indicated a satisfactory compliance with the laboratory data. Additionally, outcomes demonstrated that the drag reduction of hybrid nanofluid in the horizontal pipeline under fully turbulent flow increased with enhancing the nanofluid concentration. Drag reduction of the nanofluids in the rough pipelines was higher than that in the smooth pipeline at the same Reynolds number in the range of 6500–42,000 and different pipe’s diameter (0.5–1 in.). No considerable increase and/or a reduction in hybrid nanofluid thermal conductivity was found for the recovered nanocomposite in various volume concentrations. The highest dynamic viscosity reduction after three times recovery treatment was obtained about 0.7% for 0.5 vol.% nanocomposite particles.

Corrosion prevention of crude and vacuum distillation column overheads in a petroleum refinery: A field monitoring study

AbstractThe aim of the present work is to monitor dew point corrosion of crude and vacuum distillation column overhead section in a petroleum refinery. The material of construction of overhead line pipe was carbon steel. The state of art of crude unit process was introduced. The corrosion and associated hydrolyzing mechanisms were briefly described. The crude processing in a petroleum refinery was extremely dynamic and thus field monitoring attempts were made, which provides some useful information on structural integrity of column downstream equipments. The demulsifier, neutralizer, and corrosion inhibitor were mixed in crude unit at specific locations for corrosion prevention. Field monitoring includes evaluation of pH and chloride content of desalter extracted water and overhead condensed water, Base Sediment & Water (BS&W) and chloride content of as‐received & desalted crude, and iron content of overhead condensed water. Furthermore, corrosion coupon was installed in overhead section to obtain the actual corrosion rate. All the field study was conducted for a specified period. The acidity, chloride concentration, and iron loss of condensed water confirmed that acidic corrosion was under control. The corrosion rate of the installed coupons confirmed that corrosion rate was within the specified limit. The results revealed in this paper intended for refinery operators and corrosion engineers involved in understanding of actual process parameters in prevention of overhead acidic corrosion.

Refinery Operations Optimization Integrated Production Process and Gasoline Blending

Operations optimization is key element of refinery production. The core production activities are operations of process units and product blenders. Operations Optimization of oil processing and product blending was researched in this paper. Using discrete time presentation, a MILP optimization model was built. By formulating operations of processing units and blending units, materials production and storage, energy generation and consumption, co-optimization of materials processing and product blending was realized. Utilizing the proposed model to optimize production operations of a refinery, simulation results show the formulation’s efficiency.

Dispersion Model Evaluation of SO2 Emission From Stack in Oil Refinery Plant Using AERMOD 8.9.0

Background: In the operation of oil refineries, one of the main pollutants in stack emission is SO2. Dispersion modeling is a necessary tool for simulation of air pollutant concentration, which is the main part of urban air quality management. Objectives: The ability of air quality models is well established where sufficient input data are available. The present study is performed to assess the SO2 emission from the Tehran oil refinery. Methods: The release pattern of SO2 was simulated by the AERMOD model in the desired zone, with an area of 25 × 25 km2. Modeling was run in the 1, 3, 8, and 24 average times for two warm and cold seasons. Predicted and observed pollutant concentrations were compared for validation of the results by the EPA statistical index. Four receptors were selected to compare the predicted and observed values. Results: Correlation coefficient values for SO2 were 0.92 and 0.95 for the warm and cold seasons, respectively. The maximum concentration of SO2 was on the local scale of 25 × 25 km2. Conclusions: The results showed that modeling is appropriate for conducting point sources in the oil refinery. 1 and 24 h averaging time from the model for SO2 concentrations were lower than standard levels; therefore, in the study area, the AERMOD model performance for prediction of SO2 concentrations was acceptable. Although most of the measurements were lower than standard values, due to the possibility of air pollution transmission to the urban area, their control should be considered.

Management Strategy in Maintaining a Good Relationship with Stakeholders by Implementing the Corporate Social Responsibility (CSR) Program at PT Pertamina (Persero) Refinery Unit IV Cilacap

PT Pertamina (Persero) Refinery Unit IV Cilacap, is the largest refinery in Indonesia which has a production capacity of 348,000 barrels per day and this refinery is very strategic because it supplies 34% of national fuel needs or 60% of fuel needs in Java. In implementing its CSR program, it has 4 pillars, namely Healthy Pertamina, Smart Pertamina, Green Pertamina and Berdikari Pertamina, each of which has its own concentration. The application of CSR is not only based on requirements, seeing the real condition of the surrounding community. The CSR program is an environmental social responsibility to the surrounding community from the company's operational activities. In the implementation of CSR programs in the Refinery Unit IV Cilacap, it was carried out with the University of Gajah Mada in Yogyakarta such as the implementation of social mapping and personnel assistance such as the Community Development Officer (CDO). The CSR Implementation Strategy Program is prioritized for communities around Ring 1 or those that receive direct impacts from refinery operations. The implementation of CSR is also done through focus group discussions with relevant stakeholders such as the Cilacap Regency Government, Community Social Institutions, and also other companies related to the work area. Where the implementation of CSR must be interconnected and synergized so that the Government's short-term and long-term programs to advance the budget and development or the Human Development Index (HDI) can be implemented properly. This research program is a CSR implementation program at PT. Pertamina (Persero) RU IV Cilacap can help a good relationship with stakeholders around the operational business can run well and the surrounding community benefits from the existence of CSR programs

Scheduling of crude oil refinery operation with desalting as a separate task

AbstractA crude oil refining is a capital intensive process and releases a huge amount of environmentally unfriendly side‐products. Scheduling of crude oil that determines the optimal unloading of crude from vessels to storages, transfer to blending tanks, and charging to distillation units (CDUs) in a way that minimizes the total operating cost has become the focus of the studies in the last few decades. In this paper, we present a model that extends the literature work of a unit‐specific event‐based model to incorporate desalting as a separate task and allows a desalting tank to feed multiple CDUs. The formulation is based on a state task network (STN) that uses a unit‐specific event‐based time representation. It considers different scenarios like simultaneous or sequential discharging of products and by‐products from a desalting tank and whether a desalting tank feeding to multiple CDUs is allowed simultaneously or not. The proposed model leads a step closure to the reality and enables to know the amount of wash water needed, and the sludge disposed off for treatment in addition to the ordinary crude oil scheduling formulation. The performance of the proposed formulation is demonstrated using four case studies.

IoT-Enabled Service for Crude-Oil Production Systems Against Unpredictable Disturbance

Internet of Things (IoT) has become a new paradigm of communication to reform traditional industries, in which distributed data automatically collected via IoT in a low cost enables many new IT services that were even impossible decades ago. This research reports on an IoT-enabled production management service for crude-oil industry. In practice, even if an optimal management decision is achieved, disruptions, such as possible oil-device failures, inclement weathers and other disturbances, arise frequently and then weaken efficiency and stability of supplement. With the help of IoT, a near-real-time management service comes into being, although the adoption of IoT brings new challenges to management of disruptions. The contributions of this article are as follows: First, a service framework is proposed for refinery which combines MQTT and Azure cloud, enabling reliable data/command delivery. Second, a smart disruption management service system is developed, which consists of monitor and alarm module, disruption management module, and rescheduling procedure module. The rescheduling procedure module takes into account the network of the refinery operations, and is easy to accommodate changes in the refinery configuration for unforeseen disruptions. The experimental results show that the proposed disruption management method balances efficiency and stability compared to traditional methods.

Decision Tree to Predict the Color Quality of Refined Bleached Deodorized Palm Oil (RBPO)

There are many factors that can affect the quality of Refined Bleached Deodorized Palm Oil produced. Every step in RBDPO processing must be mastered very precisely in terms of process conditions such as temperature, flowrate, dose, pressure, etc. This condition can vary from one facility to another and therefore requires the company’s own specifications / rules to implement and integrate all production process facilities until the product is produced. The focus of the study on this particular task is the quality problems faced by companies in the Refinery section where research is carried out using data mining concepts to predict data logsheets that are written every 24 hours by refinery operators. The data can be used as a tool to predict the color quality of Refined Bleached Deodorized Palm Oil (RBPO). The use of Data Mining in this study is to facilitate operators in managing machine settings to achieve the quality required by the company directly. So that the Refinery section does not need to wait for the results of laboratory tests which require approximately 2 hours to find out the RBDPO quality results.

An effective and rapid approach to predict molecular composition of naphtha based on raw NIR spectra

Molecular management has become an important trend in petroleum refining, which relies on the information of petroleum composition. In this contribution, a simple and effective analytical approach is proposed for the rapid prediction of the more detailed molecular composition of naphtha samples based on raw near infrared (NIR) spectroscopy for the first time. The 101 samples of reformed naphtha were collected and determined, and Tchebichef curve moments (TCMs) were calculated directly from the raw NIR spectra and employed to establish linear models for the quantitative analysis of 26 hydrocarbons (PIONA) with different carbon numbers and components. For the obtained models, the average of RMSE of prediction is 0.10. According to the ratio of performance to deviation (SD/RMSEp), the 23 obtained TCM models achieved “excellent” predictive quality. By means of the conventional PLS method with spectral pretreatment, there were only 15 models with “excellent” predictive quality, which indicated that TCM method without any spectral preprocessing could provide more simple, accurate and reliable analytical results, and meet the requirements of fast assessment. This work suggests the feasibility of the proposed method for the rapid and non-destructive analysis of molecular composition in naphtha, which is significant in the determination of refinery operating conditions.

A proactive approach to quantitative assessment of disruption risks of petroleum refinery operation

Petroleum refinery consists of numerous process units in operation, which are subjected to diverse accident risks in day-to-day operations under extreme operating conditions. Due to the complexity of petroleum refinery operations, any failure can lead to major accident and a huge financial loss for a petroleum refining company. However, petroleum refinery operations can be disrupted by various risk elements from the organization, technical, operational and external latent conditions. Risk elements are often inherent in operations, which can be based on uncertain knowledge, oversight and lack of perception of interactive events that can lead to disruption. In order to circumvent events that can cause disruption in a petroleum refinery, the criticality of the risk elements and their attributes that are associated with Petroleum Refinery Process Units (PRPU) operations need to be investigated. Therefore, there is a need to identify and assess the most critical risk elements and attributes that can interact to cause the disruption of operational reliability and availability of a petroleum refinery process unit. Hence, this article proposes a robust fuzzy linguistic assessment methodology for identification and assessment of PRPU risk elements and their attributes. The methodology deals with the main challenges of utilising expert’s subjective judgements, in terms of the assessment of PRPU risk elements under uncertain situations. The result of the evaluation and ranking of PRPU risk elements and their attributes can provide salient risk information to duty holders and decision makers in the petroleum refinery in order to prioritise resources for risk management of the most critical attributes of the risk elements.

Confronting Complexity with Regulatory Excellence: Recommendations in the Wake of the Philadelphia Refinery Explosion

Following the June 2019 explosion at the Philadelphia Energy Solutions (PES) refinery, the city of Philadelphia now confronts major challenges associated with the future of the refinery site. Whether the site is reopened as a refinery or other chemical-processing operation, or redeveloped for other uses, the city will face challenges endemic to all kinds of public policy issues: complexity, uncertainty, dynamism, tradeoffs, and value choices. This testimony, delivered to the City of Philadelphia Refinery Advisory Group’s Environment Committee, offers three main suggestions to help guide Philadelphia officials in dealing with the future of the PES refinery site. First, city officials will need to coordinate with the private sector organizations with a direct financial stake in the site as well as the various state and federal government agencies with regulatory oversight responsibilities related to the site’s future. Second, city officials will also need to keep in close communication with labor groups, local businesses, nonprofit and community groups, and city residents — not merely listening to their concerns but demonstrating that they have been heard. Finally, officials will need to evince compassion in understanding what is at stake for all those who live and work in Philadelphia who are affected by the future of the refinery site. Overall, this testimony emphasizes that the challenges confronting Philadelphia officials are similar to those raised by other complex risk management scenarios — and that any regulator or other public official confronting such challenges should be guided by principles of regulatory excellence.

Modeling the Hydrocracking Process with Deep Neural Networks

In the refinery process, a vast amount of data is generated in daily production. How to make full use of these data to improve the simulation’s accuracy is crucial to enhancing the refinery operating level. In this paper, a novel deep learning framework integrating the self-organizing map (SOM) and the convolutional neural network (CNN) is developed for modeling the industrial hydrocracking process. The SOM is used to map input variables into two-dimensional maps to extract process features. Then, these maps are fed into the CNN to predict the outputs of the hydrocracking process. The SOM adopted is free of training, which reduces the computational complexity, simplifies the application, and improves the prediction accuracy. Practical guidance on the application of the proposed framework is provided by comparing and analyzing different structures and parameters. Finally, an online modeling scheme is developed and applied in an actual hydrocracking process. Experimental results demonstrate that the proposed framework has great performance in modeling the hydrocracking process and provides a good reference for process optimization.