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Marco Aurélio Cavalcanti Pacheco - One of the best experts on this subject based on the ideXlab platform.
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ANEPI: Economic Analysis of Oil Field Development Projects under Uncertainty
Studies in Computational Intelligence, 2020Co-Authors: Alexandre A. Emerick, Marley M. B. R. Vellasco, Marco Aurélio Cavalcanti Pacheco, Marco Antonio Guimarães Dias, Juan Guillermo Lazo LazoAbstract:The analysis of an option to develop (set up for production) a previously delimited Oil Field requires investments whose costs and whose benefits depend on the alternative chosen. Some alternatives include more wells than others; others present a different geometric distribution of the wells. There are also different types of wells (vertical, directional, horizontal, multilateral, etc.) which involve different types of investments and benefits. The combination of these aspects with others, such as: platform types; production flow system; drilling speed (rig availability); lifting method (gas lift, centrifugal pumping, etc.), Oil recovery method, etc., makes this a complex optimization problem. In addition, alternatives to invest in information and even alternatives to simply wait for market conditions to improve must be taken into account. Flexibility is another aspect that needs to be considered in the concept of Oil Field Development as a means by which to ensure that it will be possible to incorporate a future increase in production (expansion option) through additional optional wells, depending on the market conditions and on how the reservoir responds to the first months/years of production.
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Analysis of Alternatives for Oil Field Development under Uncertainty
Studies in Computational Intelligence, 2020Co-Authors: Juan Guillermo Lazo Lazo, Marco Aurélio Cavalcanti Pacheco, Alexandre A. Emerick, Dan Posternak, Thiago Souza Mendes Guimarães, Marley M. B. R. VellascoAbstract:The objective of this area of the project was to develop the foundations of a modular system for alternatives analysis that would allow the integration of the models presently studied (models for investment alternatives, expansion options and options to invest in information). The system makes it possible to work with several different Oil Fields, where each Field can have several investment alternatives and each investment alternative can, for example, present options to invest in information and options to invest in several expansion wells. Technical uncertainties are represented by fuzzy numbers and the problem is solved by Monte Carlo simulation.
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intelligent systems in Oil Field Development under uncertainty
2009Co-Authors: Marco Aurélio Cavalcanti Pacheco, Marley B R VellascoAbstract:The decision to invest in Oil Field Development is an extremely complex problem, even in the absence of uncertainty, due to the great number of technological alternatives that may be used, to the dynamic complexity of Oil reservoirs - which involves multiphase flows (Oil, gas and water) in porous media with phase change, and to the complicated combinatorial optimization problem of choosing the optimal Oil well network, that is, choosing the number and types of wells (horizontal, vertical, directional, multilateral) required for draining Oil from a Field with a view to maximizing its economic value. The present book is a result of about 4 years of research in this area through a partnership between the Applied Computational Intelligence Laboratory (ICA) of the Department of Electrical Engineering at PUC-Rio, and Petrobras, through its R&D (research and Development) program called PRAVAP (Advanced Oil Recovery Program), which is linked to its research center (CENPES). The book makes use of computational intelligence techniques, especially genetic algorithms, genetic programming, neural networks, fuzzy logic and neuro-fuzzy systems for purposes of solving this investment under uncertainty problem. These techniques are combined with modern finance theory, particularly with the real options theory, also known as the investment under uncertainty theory, in such a way as to provide practical as well as theoretically rigorous solutions. This partnership, through which countless master's and doctoral theses were produced at PUC-Rio and computational methodologies and programs were developed for Petrobras, has been summarized in this original and comprehensive work, now available to a wider audience of researchers and interested readers.
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SELECTION OF ALTERNATIVES FOR Oil Field Development BY GENETIC ALGORITHMS
2002Co-Authors: Yvan Jesus Tupac, Marley M. B. R. Vellasco, Marco Aurélio Cavalcanti PachecoAbstract:This paper presents a Genetic Algorithm application for selecting the best alternative for Oil Field Development under certainty. The alternatives in this study are related to the arrangement of wells in a known and delimited Oil reservoir and serve as a basis for calculating the net present value, which is used to assess the optimization process: the optimal alternative is the one that maximizes the Net Present Value of the Field. The results obtained have revealed that the Genetic Algorithm model was able to find good alternatives for the Oil Field Development, achieving good results for the Net Present Value.
Winardi Sani - One of the best experts on this subject based on the ideXlab platform.
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Risk Management Framework in Oil Field Development Project by Enclosing Fishbone Analysis
International Journal on Advanced Science Engineering and Information Technology, 2017Co-Authors: Abdul Hamid, Ishak Baba, Winardi SaniAbstract:Fishbone analysis process is a conceptual stage in engineering role and product design. It’s a systematic method to analysis a failure system that were longer used in electronic industry application but not limit to use in Oil and gas industry. In risk management concept that a failure as a risk shall prevent and identify in beginning process that may require to minimize them to happen in product and application in Oil Field equipment. The main interest of this paper is to propose for the potential of fishbone model can be insert and enclose onto risk management system and then implement in Oil Field Development project in Oil and gas industry. This paper is provided base on research and experiences into risk management and learned from practical team and their opinion in industry which matched by an application in Oil Field Development equipment such as actuators, valves and Christmas tree that follow to industry standard such as API 6A guidelines. A frame work of implementation phase for risk management fishbone in Oil Field Development project in industry were reviewed and added value by improving an effective communication and skills of the project and engineering team to the stakeholder and organization. The frame work that added a Fishbone analysis method in engineering role may become a standard model and may work as reference for academic and practitioners to help evaluate which risk management need to emphasize in order to maximize the organization in industry outcome from each stage of model. The frame work model may also use for reference of develop the Oil Field Development project with simply process and can be develop with same concept for the next wide Development project in industry.
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proposal for the risk management implementation phase in Oil Field Development project by adding value on the refurbishment of critical equipment
MATEC Web of Conferences, 2017Co-Authors: Abdul Hamid, Ishak Baba, Winardi SaniAbstract:Refurbishment process is a conceptual stage in product life cycle. It is utilized in existing equipment in the Field by adding value to recondition and repaired equipment. The main interest of this paper is to implement and design risk management implementation phase in Oil Field Development project on the refurbishment of critical equipment in Oil and gas industry. This paper is provided base on research and experiences in risk management and learned from practical team in industry which matched by an application in Oil Field Development project in refurbishment of critical equipment. A framework of implementation phase for risk management in Oil Field Development project in refurbishment critical equipment were reviewed and added value on communication skills of the project team to the stakeholder and organization, which support to external body and vice-versa. Risk management framework can be used for reference of refurbishment process with simply process and developed with same concept for the next wide Development project in industry.
David Reay - One of the best experts on this subject based on the ideXlab platform.
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optimization of waste heat utilization in Oil Field Development employing a transcritical organic rankine cycle orc for electricity generation
Applied Thermal Engineering, 2013Co-Authors: D Zabek, John David Penton, David ReayAbstract:Abstract This study describes the low temperature waste heat exploitation during enhanced crude Oil Development providing a 600–900 kW continuous electric power supply under deteriorating and oscillating thermal boundary conditions. The aim of this project was to optimize the heat-to-power conversion process by maximizing the net power output employing a transcritical Organic Rankine Cycle (ORC) with R134a as working fluid. Volatile supercritical thermo-physical fluid properties demand a review of heat transfer and expansion procedures. In order to design a comprehensive and dynamic unit configuration, a flexible cycle layout with an adjustable working fluid mass flow is required. The optimization developed a positive heat exchange/pressure correlation for the net power output with reasonable cycle efficiencies of around 10% employing moderate device sizes. Changing ambient temperatures from a winter night with 10 °C to a summer day with 28 °C ambient temperature, on the US West Coast, leads to net power differences of up to 200 kW for an identical cycle configuration. Positive and negative effects result from these temperature oscillations while the heat sink temperature decreases, as does the bottom pressure. Extended available temperature and pressure differences lead to higher power outputs and cycle efficiencies. Considering higher ambient temperatures, the efficiency and power increase per heat transfer performance increase is higher than at low ambient temperatures. For this reason a “large” heat exchanger is more beneficial under warm ambient conditions than under cold ones. In addition, “large” configurations do not easily run the risk of subcritical cycle operation unlike small configurations. It is therefore important to examine the ORC machine performance over a full range of ambients. Considering a likelihood of heat source temperature degradation, an aggressive cycle design does not pay off. The selection of larger heat transfer devices almost equalizes the net power output compared to smaller ones after a heat source temperature deterioration of ∼ 6 K. Sensitivity analyses in the way presented here are an indispensable tool for achieving optimal cycle layout and operation.
Valentin Lychagin - One of the best experts on this subject based on the ideXlab platform.
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optimal management of Oil Field Development in the buckley leverett model
Automation and Remote Control, 2018Co-Authors: Atlas V Akhmetzianov, Alexei G Kushner, Valentin LychaginAbstract:We consider the problem of two-phase filtering (Oil and water) in a horizontal layer of an Oil deposit. We propose an asymptotic method for calculating both the filtering process and related optimal control problems, namely the problems of choosing optimal control actions to achieve maximum Oil production at a given level of water resource consumption or a minimum water flow rate that provides the level of Oil production required by the plan.
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Optimal Management of Oil Field Development in the Buckley–Leverett Model
Automation and Remote Control, 2018Co-Authors: Atlas V Akhmetzianov, Alexei G Kushner, Valentin LychaginAbstract:We consider the problem of two-phase filtering (Oil and water) in a horizontal layer of an Oil deposit. We propose an asymptotic method for calculating both the filtering process and related optimal control problems, namely the problems of choosing optimal control actions to achieve maximum Oil production at a given level of water resource consumption or a minimum water flow rate that provides the level of Oil production required by the plan.
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Thermodynamics and Optimal Control of Porous Media Flows in Oil Field Development
Doklady Mathematics, 2018Co-Authors: A. V. Akhmetzyanov, Alexei G Kushner, Valentin LychaginAbstract:The nonisothermal two-phase porous media flow of Oil and hot water in a horizontal Oil reservoir is considered. An asymptotic method for calculating the flow and solving related optimal control problems is proposed. Namely, the problem of choosing optimal control actions to maximize the Oil production for a given level of financial costs and to minimize the costs for a given level of Oil production is considered.
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two dimensional non isothermal filtration and optimal control of Oil Field Development
IFAC-PapersOnLine, 2018Co-Authors: Atlas V Akhmetzianov, Alexei G Kushner, Valentin LychaginAbstract:Abstract In this paper we consider the Buckley-Leverett filtration model for a two-phase system (for instance, water Oil) in a plane domain of porous media with injection and producing wells. Buckley-Leverett’s equations supplemented by the law of conservation of thermal energy Asymptotic solutions for two-phase flows in porous media are studied. Dimensionless numbers for characterization of these flows are introduced. These numbers we use to construct asymptotic presentations of solutions. We give explicit formulae for the initial terms of this asymptotic which we use for optimal control of Oil-Field Development.
Marley B R Vellasco - One of the best experts on this subject based on the ideXlab platform.
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intelligent systems in Oil Field Development under uncertainty
2009Co-Authors: Marco Aurélio Cavalcanti Pacheco, Marley B R VellascoAbstract:The decision to invest in Oil Field Development is an extremely complex problem, even in the absence of uncertainty, due to the great number of technological alternatives that may be used, to the dynamic complexity of Oil reservoirs - which involves multiphase flows (Oil, gas and water) in porous media with phase change, and to the complicated combinatorial optimization problem of choosing the optimal Oil well network, that is, choosing the number and types of wells (horizontal, vertical, directional, multilateral) required for draining Oil from a Field with a view to maximizing its economic value. The present book is a result of about 4 years of research in this area through a partnership between the Applied Computational Intelligence Laboratory (ICA) of the Department of Electrical Engineering at PUC-Rio, and Petrobras, through its R&D (research and Development) program called PRAVAP (Advanced Oil Recovery Program), which is linked to its research center (CENPES). The book makes use of computational intelligence techniques, especially genetic algorithms, genetic programming, neural networks, fuzzy logic and neuro-fuzzy systems for purposes of solving this investment under uncertainty problem. These techniques are combined with modern finance theory, particularly with the real options theory, also known as the investment under uncertainty theory, in such a way as to provide practical as well as theoretically rigorous solutions. This partnership, through which countless master's and doctoral theses were produced at PUC-Rio and computational methodologies and programs were developed for Petrobras, has been summarized in this original and comprehensive work, now available to a wider audience of researchers and interested readers.
