Yury Redutskiy

• Matušinec, Josef; Hrabec, Dušan; Šomplák, Radovan; Nevrly, Vlastimir; Pecha, Jiří; Smejkalová, Veronika & Redutskiy, Yury (2020). Cooking Oil and Fat Waste Management: A Review of the Current State. Chemical Engineering Transactions.  ISSN 1974-9791.  81, s 763- 768 . doi: 10.3303/CET2081128 Show summary

  Waste management is a continuously growing area connecting industry and academia nowadays. There are, however, still many issues and sub-areas requiring in-depth analysis and development of new approaches and solutions. One of them is the management of waste cooking oils and fats originated from households. While most of the solid waste is addressed within the circular economy proposal, the fat waste recycling consideration is still in its early stage, as the relevant European Union legislation has only recently been adopted. Disposing of oil and fat waste in a traditional way often leads to sewage problems. However, if utilised, this waste may be a valuable source of energy and material recovery. While maintaining the reverse supply chain viewpoint (from waste producers through the collection to treatment and utilisation), this paper reviews the current state of the waste cooking oils and fats management and identifies the drawbacks in existing collection and handling methods. The review shows that current approaches have shortcoming mainly due to poorly organised collection container networks and provides insights into the importance of effective prognosis of the cooking oil and fat waste whose collection and handling is still in the development. The Czech Republic current state and the future outlook is discussed and commented with regards to the expected growth of production and separation of these wastes. The review stresses the challenges of establishing and coordinating the supply chain segments, which will benefit from applying mathematical modelling to facilitate decision-making.

• Redutskiy, Yury (2018). Pilot study on the application of employee scheduling for the problem of safety instrumented system design and maintenance planning for remotely located oil and gas facilities. Engineering Management in Production and Services.  ISSN 2543-6597.  10(4), s 55- 64 . doi: 10.2478/emj-2018-0022 Show summary

  The technology of production, transportation, and processing of oil and gas involves various hazardous processes. To mitigate the risk that these processes pose, the technological solutions work closely with the automated control and safety systems. The design and organisation of maintenance for the automated safety instrumented systems (SIS) have a significant bearing on the overall safety of operations in this industry. Over the past few decades, many hydrocarbon resources have been discovered in unconventional environments, such as remote, offshore, and arctic locations. Transportation of engineering personnel to these remote locations and back, and thereby, the organisation of the shift work poses additional challenges for the petroleum sector. Under such circumstances, the workforce-related costs play a considerable role in the overall cost of the technological solution and thereby the decisions regarding the workforce organisation should be addressed in the framework of evaluating and choosing the appropriate safety measures. That is why the research presented in this paper aims to address the lifecycle of the technological solution integrating the problems of SIS design, maintenance planning, and employee scheduling into a single decision-making framework to optimise the set of technical and organisational safety measures inherent in the SIS. The performance and maintenance of the SIS are described with a Markov model of device failures, repairs and technological incidents occurrence. The employee scheduling part of the mathematical model utilises the set-covering formulation of maintenance crews taking particular trips. A black-box optimisation algorithm is used to find reasonable solutions to the integrated problem of engineering design and workforce planning. The decisions include the choices of the components and structures for the safety system, the facility overhaul frequencies, the maintenance personnel size, as well as the schedules of trips and shifts for the crews.

• Redutskiy, Yury (2017). Conceptualization of smart solutions in oil and gas industry. Procedia Computer Science.  ISSN 1877-0509.  109, s 745- 753 . doi: 10.1016/j.procs.2017.05.435 Show summary

  Technological solutions called “smart wells” and “smart fields” have been applied in petroleum industry for nearly two decades. They aim to improve the knowledge of petroleum production processes, and thereby improve the efficiency of operations. Researchers and companies in pursuit of their goals tend to use one-sided implications and numerous synonyms when describing the substance of the term, which leads to an occasional confusion. In order to study the concept of smart field from a general perspective, a literature review has been conducted, and main characteristic attributes of such solutions have been revealed. Selected marketed products offered by engineering companies have been analyzed as examples of the technology implementations. A definition has been proposed along with its practical implications for the companies management. Additionally, an attempt has been made to place these solutions in a broad scientific context of intelligence and sustainability in contemporary business processes.

• Redutskiy, Yury (2017). Integration of oilfield planning problems : infrastructure design, development planning and production scheduling. Journal of Petroleum Science and Engineering.  ISSN 0920-4105.  158(September), s 585- 602 . doi: 10.1016/j.petrol.2017.08.066 Show summary

  The oil and gas industry faces considerable technological challenges nowadays, mainly associated with nonconventional reserves and offshore environments. To ensure the economic efficiency of operations under such complicated conditions, industrial solutions called “smart fields” were introduced. A vital part of these solutions is strategic planning which aims to coordinate field development and hydrocarbons production operations to optimize the entire field lifecycle, given the chosen planning criterion (e.g., net present value of the project). Still, in many cases engineering design is conducted with a conservative approach of solving one problem at a time. In this study, a multi-period mixed integer nonlinear problem (MINLP) covering the relevant issues of both development and production phases, is introduced. The contribution of the proposed model to the area of oilfield development planning is related to the model’s simultaneously incorporating technological details regarding the infrastructure layout, pressures and flows in the gathering system, and artificial lift performance, all of which ultimately aims to provide realistic production scheduling results and cost evaluation. The composed model is used to study the benefits of joint development and production planning in comparison to planning these two phases of the project separately. This research is relevant to the engineering design departments and contractors for the preliminary design stage of the engineering project when the infrastructures layout and capacities are chosen, and rough estimates of costs and revenues are calculated.

• Redutskiy, Yury (2017). Modelling and design of safety instrumented systems for upstream processes of petroleum sector. Procedia Engineering.  ISSN 1877-7058.  182, s 611- 618 . doi: 10.1016/j.proeng.2017.03.165 Show summary

  The adequacy of the decision-making regarding the specification of Safety Instrumented Systems (SIS) deployed for hazardous processes, contributes to avoiding incidents and corresponding losses. This paper proposes an approach to mathematically and economically substantiated design of SIS. Markov analysis is used for the stochastic process of SIS failures and technological incidents occurrence. The model is used further for multi-objective optimization of SIS design. The research is relevant to engineering departments and contractors, who specialise in planning and designing the technological solution.

• Redutskiy, Yury (2017). Oilfield development and operations planning under geophysical uncertainty. Engineering Management in Production and Services.  ISSN 2543-6597.  9(3), s 10- 27 . doi: 10.1515/emj-2017-0022 Show summary

  The oil and gas industry nowadays is challenged by dealing with nonconventional reserves and offshore environments. Decision-making associated with projects in the petroleum sector has to handle various technological issues, risks, and uncertainty. The Smart Fields approach was introduced to cope with complicated production conditions and make the production of hydrocarbons economically efficient. A significant part of this approach is proactive planning which implies taking into account the uncertainty, or lack of knowledge of the recoverable reserves, future hydrocarbon prices and various operational issues inherent in the projects. In this study, a multi-stage stochastic programming approach is employed to cover the relevant engineering issues of oilfield development and petroleum production while addressing the geophysical uncertainty related to the developed deposit. The proposed model covers such aspects as well drilling, gathering pipeline infrastructure planning, capacity selection for the infrastructure and the processing units, as well as planning the production operations with consideration of artificial lift efficiency. The model aims to optimise the entire field lifecycle, given the chosen planning criterion, that is an economic criterion of the project’s net present value. The contribution of the developed model to the area of planning in the petroleum industry is the detailed consideration of the technology: the flows and pressures in the planned infrastructure, reservoir behaviour, and the artificial lift performance. The goal of including these technological details is to apprehend the economic trade-off between investments, operating costs and the prospective revenues, given the lack of knowledge of the geophysical properties of the developed deposit. The stochastic modelling implemented in this study is relevant to the development projects in nonconventional environments, where several deposits of various sizes are present; however, not each deposit's properties get to be studied in detail.

• Redutskiy, Yury (2017). Optimization of safety instrumented system design and maintenance frequency for oil and gas industry processes. Management and Production Engineering Review.  ISSN 2080-8208.  8(1), s 46- 59 . doi: 10.1515/mper-2017-0006 Show summary

  Oil and gas industry processes are associated with significant expenditures and risks. Adequacy of the decisions on safety measures made during early stages of planning the facilities and processes contributes to avoiding technological incidents and corresponding losses. Formulating straightforward requirements for safety instrumented systems that are followed further during the detailed engineering design and operations is proposed, and a mathematical model for safety system design is introduced in a generalized form. The model aims to reflect the divergent perspectives of the main parties involved in oil and gas projects, and, therefore, it is formulated as a multi-objective problem. Application of black box optimization is suggested for solving real-life problem instances. A Markov model is applied to account for device failures, technological incidents, continuous restorations and periodic maintenance for a given process and safety system configuration. This research is relevant to engineering departments and contractors, who specialize in planning and designing the technological solution.

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• Redutskiy, Yury (2018). Risk Management Perspective on Workforce Scheduling for Safety Systems Maintenance for Oil and Gas Facilities Located in Poorly Accessible Regions. Show summary

  Oil and gas resources development is nowadays associated with nonconventional environments such as deep-sea reserves, arctic locations and other remote and unpopulated areas poorly accessible by transportation. The hydrocarbon production technology is highly hazardous and associated with considerable risk for personnel, technological equipment, and environment. Safety Instrumented Systems (SIS) are put in place to ensure the proper and safe operations. In order for the SIS to perform its function, it requires periodic maintenance. This research highlights the importance of simultaneously addressing the issues of SIS design and maintenance planning for the remotely located oil and gas facilities. The decision-making model aims to determine the SIS’s components, structures, maintenance frequency, staffing size required for continuous and periodic maintenance, and the workforce shift schedules. This decision-making is based on the ALARP principle of risk-reduction, suggesting a trade-off between the complexity of SIS’s structures, its maintenance rates and the labor costs associated with service personnel travelling and staying in the remote regions. A Markov model is employed along with cost evaluations within a black-box optimization algorithm to optimize the SIS’s lifecycle. The model was run with the data from a real project implemented by a Russian company. This research is relevant to engineering departments specializing in designing the SISs for the petroleum sector projects.

• Redutskiy, Yury (2018). Safety system design and maintenance planning for oil and gas facilities located in remote areas. Show summary

  Many hydrocarbon deposits have been discovered and, therefore, the facilities have been built in remote and arctic locations poorly accessible by transportation. The petroleum production technology is associated with considerable risks. Safety instrumented systems (SIS) aim to mitigate the risk of the hazardous operations the oil and gas facilities run. This research contributes to the area of engineering design by addressing the issues of SIS design and their maintenance for the remotely located facilities. The modelling in this research aims to ensure the safety of operations by simultaneously evaluating the decisions on the safety system’s components and structures, the facility overhaul frequencies, the servicepersons staffing size and the crew trips schedules for their shift work. The details of the SIS functioning and maintenance are incorporated into a Markov model used for safety quantification. The decision-making is done with the help of a black-box optimization algorithm. The objective function used in this research addresses the economic perspective on the lifecycle of the technological solution. The aim of the cost-minimization objective is to explore a trade-off between the capital investments into the complexity of the safety system, the operational expenditures associated with the system maintenance, and the expected losses in case a hazardous event occurs. The computational example used in this research adopted the data from a real project implemented by a Russian company. The results demonstrated that the suggested decision-making framework points to the reasonable SIS structures, which may be used as starting point for the further detailed SIS design. The transportation and the labor costs prove to play a considerable role in both lifecycle cost evaluation and the choice of the shift duration. The frequency of the planned shutdowns demonstrates to have a marginal bearing on the overall lifecycle cost evaluation. However, the overhaul frequency choice (once in 3 months, once in 6 months, or once a year) has a considerable impact on the solution’s reliability, and thereby on the magnitude of the expected losses should an incident occur. It also influences the expected facility downtime, which may be of consideration for the project periodic overhauls planning.

• Redutskiy, Yury (2017). Conceptualization of smart solutions in oil and gas industry. Show summary

  Technological solutions called “smart wells” and “smart fields” have been applied in petroleum industry for nearly two decades. They aim to improve the knowledge of petroleum production processes, and thereby improve the efficiency of operations. Researchers and companies in pursuit of their goals tend to use one-sided implications and numerous synonyms when describing the substance of the term, which leads to an occasional confusion. In order to study the concept of smart field from a general perspective, a literature review has been conducted, and main characteristic attributes of such solutions have been revealed. Selected marketed products offered by engineering companies have been analyzed as examples of the technology implementation. A definition has been proposed along with its practical implications. Additionally, an attempt has been made to place these solutions in a broad scientific context of intelligence and sustainability in contemporary business processes.

• Redutskiy, Yury (2017). Strategic planning problems for smart solutions in oil and gas industry. PhD theses in logistics. 2017:4.
• Redutskiy, Yury (2016). Modelling and design of safety instrumented systems for upstream processes of petroleum sector. Show summary

  The adequacy of the decision-making regarding the specification of Safety Instrumented Systems (SIS) deployed for hazardous processes, contributes to avoiding incidents and corresponding losses. This paper proposes an approach to mathematically and economically substantiated design of SIS. Markov analysis is used for the stochastic process of SIS failures and technological incidents occurrence. The model is applied further for multi-objective optimization of SIS design. The research is relevant to engineering departments and contractors who specialize in planning and designing the technological solution.

• Redutskiy, Yury (2014). Offshore oilfield design. Show summary

  We address modeling and optimization tools behind the Smart Oilfield technology, dominantly used for unconventional wells in offshore oil production. Decision upon location of the intra-oilfield pipelines network is made during the design phase of the oilfield development project. We apply a multi-stage combinatorial optimization algorithm for the pipelines structure design and for determining pipelines’ capacities. The algorithm is used to analyze how decisions made on different stages of the pipeline network design influence production efficiency during the phase of exploiting the reservoir.

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