Static and Dynamic Comparison of Equation of State Solid Model and PC-SAFT for Modeling Asphaltene Phase Behavior
- Ali Abouie (The University of Texas at Austin) | Mohsen Rezaveisi (The University of Texas at Austin) | Saeedeh Mohebbinia (The University of Texas at Austin) | Kamy Sepehrnoori (The University of Texas at Austin)
- Document ID
- Society of Petroleum Engineers
- SPE Western Regional Meeting, 23-26 May, Anchorage, Alaska, USA
- Publication Date
- Document Type
- Conference Paper
- 2016. Society of Petroleum Engineers
- 5.5 Reservoir Simulation, 1.8 Formation Damage, 5.2.1 Phase Behavior and PVT Measurements, 5.2 Reservoir Fluid Dynamics, 5 Reservoir Desciption & Dynamics, 5.2.2 Fluid Modeling, Equations of State, 1.8 Formation Damage, 4.3.3 Aspaltenes
- Compositional Reservoir/Wellbore, Asphaltene Precipitation, Wettability alteration, PC-SAFT
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- 485 since 2007
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Asphaltene deposition is known to be one of the major problems in oil fields. Asphaltene precipitation and deposition from the reservoir fluid can block pore throats or change the formation wettability in the reservoir. Furthermore, asphaltene precipitation and deposition result in partial to total plugging in the wellbore. Recent studies have shown that PC-SAFT EOS is a more appropriate and comprehensive thermodynamic model for simulation of asphaltene precipitation. The main objective of this paper is to implement PC-SAFT EOS into a compositional wellbore simulator to model asphaltene precipitation. Flocculation and deposition models are also integrated with the thermodynamic model to simulate the dynamics of asphaltene deposition along the wellbore. In addition, the capabilities of PC-SAFT and common-used Peng-Robinson equation of state are compared through fluid characterization to reproduce experimental precipitation data.
The simulation results indicate asphaltene deposition profile and consequent decline in production rate. It is shown that the profile of asphaltene deposition is mostly governed by the precipitation condition and the deposition rate. Moreover, prediction capability of cubic equation of state is shown to give approximately similar results if additional precipitation data is available (e.g. lower onset pressure and maximum amount of precipitation). The prediction results of the developed tool are highly crucial to monitor the well performance, optimize the operating conditions of the field, and propose the remediation technique.
|File Size||1 MB||Number of Pages||22|
Hemmati-Sarapardeh, A., Alipour-Yeganeh-Marand, R., Naseri, A., Safiabadi, A., Gharagheizi, F., Ilani-Kashkouli, P., and Mohammadi, A. H. 2013. Asphaltene Precipitation Due to Natural Depletion of Reservoir: Determination Using a SARA Fraction based Intelligent Model. Fluid Phase Equilibria, 354, 177–184.