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Francisco “Paco” Vargas\nDepartment of Chemical & Biomolecular Engineering
\nRICE University, Houston, Texas, USA
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“Advances in modeling asphaltene deposition and development of integrated strategies for its mitigation”
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\nDepartment of Chemical & Biomolecular Engineering
\nRICE University, Houston, Texas, USA
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Abstract
\n\nAsphaltene deposition is a flow assurance issue that threatens the continuous production of crude oil.
\nThis problem is likely to get worse because of the current tendency to produce from deeper waters and also due to the implementation of enhanced oil recovery operations based on miscible injection of CO2 or hydrocarbon gas.
\n\nDespite all the efforts devoted to the understanding of this complex situation, the challenge still persists and most of the proposed solutions are case specific.
\nEven the chemicals that are used to inhibit the formation of asphaltene deposits are commercially evaluated by trial and error methods, and the knowledge about the mechanisms of action of such oilfield chemicals is very limited.
\n\nIn this talk I will present some of the factors that contribute to the complexity of the problem and the most important challenges that need to be addressed in order to find cost / effective solutions to mitigate and remediate asphaltene deposition.
\nI will also describe a very successful modeling technique based on the PC-SAFT Equation of State that can accurately predict the precipitation of asphaltenes and a wide range of PVT properties of crude oil systems.
\nAlso, through a couple of case studies I will show how this modeling method has been successfully implemented for the optimal design and execution of asphaltene projects.
\nFurthermore, I will review the current commercial technologies that intend to mitigate asphaltene deposition and discuss their short-comings as well as novel strategies that are being developed to predict, prevent and remediate this challenging flow assurance issue.
\n\nBy combining state-of-the-art experimental techniques and the most advanced modeling methods we aim to contribute to the solution of one of the most challenging problems faced by the oil industry nowadays.
\n“Advances in modeling asphaltene deposition and development of integrated strategies for its mitigation”
\n
\n
\n
\nDepartment of Chemical & Biomolecular Engineering
\nRICE University, Houston, Texas, USA
\n
\n
\n
Abstract
\n\nAsphaltene deposition is a flow assurance issue that threatens the continuous production of crude oil.
\nThis problem is likely to get worse because of the current tendency to produce from deeper waters and also due to the implementation of enhanced oil recovery operations based on miscible injection of CO2 or hydrocarbon gas.
\n\nDespite all the efforts devoted to the understanding of this complex situation, the challenge still persists and most of the proposed solutions are case specific.
\nEven the chemicals that are used to inhibit the formation of asphaltene deposits are commercially evaluated by trial and error methods, and the knowledge about the mechanisms of action of such oilfield chemicals is very limited.
\n\nIn this talk I will present some of the factors that contribute to the complexity of the problem and the most important challenges that need to be addressed in order to find cost / effective solutions to mitigate and remediate asphaltene deposition.
\nI will also describe a very successful modeling technique based on the PC-SAFT Equation of State that can accurately predict the precipitation of asphaltenes and a wide range of PVT properties of crude oil systems.
\nAlso, through a couple of case studies I will show how this modeling method has been successfully implemented for the optimal design and execution of asphaltene projects.
\nFurthermore, I will review the current commercial technologies that intend to mitigate asphaltene deposition and discuss their short-comings as well as novel strategies that are being developed to predict, prevent and remediate this challenging flow assurance issue.
\n\nBy combining state-of-the-art experimental techniques and the most advanced modeling methods we aim to contribute to the solution of one of the most challenging problems faced by the oil industry nowadays.
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