The Effect of Solvents on the Viscosity of an Alberta Bitumen at In Situ Thermal Process Conditions
- Hamed Reza Motahhari (University of Calgary) | Florian F. Schoeggl (University of Calgary) | Harvey W. Yarranton (University of Calgary) | Marco A. Satyro (Virtual Materials Group Inc.)
- Document ID
- Society of Petroleum Engineers
- SPE Heavy Oil Conference-Canada, 11-13 June, Calgary, Alberta, Canada
- Publication Date
- Document Type
- Conference Paper
- 2013, Society of Petroleum Engineers
- 4.3.3 Aspaltenes, 5.4.10 Microbial Methods, 5.2.2 Fluid Modeling, Equations of State, 5.5 Reservoir Simulation, 5.4.6 Thermal Methods, 4.1.5 Processing Equipment, 4.6 Natural Gas, 4.1.1 Process Simulation, 5.3.9 Steam Assisted Gravity Drainage, 4.3.4 Scale, 6.5.7 Climate Change, 1.8 Formation Damage, 5.2 Reservoir Fluid Dynamics, 5.2.1 Phase Behavior and PVT Measurements, 5.4.7 Chemical Flooding Methods (e.g., Polymer, Solvent, Nitrogen, Immiscible CO2, Surfactant, Vapex), 4.1.2 Separation and Treating, 7.4.3 Market analysis /supply and demand forecasting/pricing, 2.2.2 Perforating
- Viscosity measurement, SAGD, Bitumen, Viscosity model, Solvent
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The design and optimization of solvent assisted thermal recovery processes for heavy oil and bitumen require accurate predictions of viscosity as a function of temperature, pressure, and composition. In this case study, the performance of the Expanded Fluid (EF) viscosity model is tested on viscosity data for an Alberta bitumen diluted with carbon dioxide (5.2 wt%), ethane (5.1 wt%), propane (7.6 and 16 wt%), n-butane (14.5 wt%), n-pentane (15 and 30 wt%) and n-heptane (15 and 30 wt%) at temperatures from 20 to 175°C and pressures up to 10 MPa. The main input to the EF model is the density of the fluid and densities were measured at the same conditions as the viscosity measurements.
The viscosity of the bitumen was fitted with average absolute relative deviation (AARD) of 8%. The viscosities of the diluted bitumen mixtures were predicted without tuning with an overall AARD of 17% when using measured densities as an input. The viscosity predictions were improved to an AARD of 7% using generalized viscosity binary interaction parameters. When using densities calculated with an excess volume based mixing rule, the viscosity predictions were slightly more deviated with an overall AARD of 10%.
The EF model predictions were used to evaluate the effectiveness of n-alkane solvents in reducing bitumen viscosity at in situ steam-solvent process conditions. The solubility of the solvent in bitumen was found to be the main factor controlling the mixture viscosity. The less volatile the solvent is, the greater is the viscosity reduction at a given pressure and temperature. As the process temperature increases, the greater is the viscosity reduction from a given solvent due to increased solubility at higher steam saturation pressures.
Heavy oil and bitumen are challenging to produce due to their high viscosity. While the viscosity of conventional oils ranges from approximately 1 to 100 mPa.s, the viscosity of heavy oils and bitumen can be up to more than 1 million mPa.s at ambient temperature. Typically, heating and/or dilution with solvent is required to reduce the viscosity so that these fluids can be recovered and processed.
Thermal recovery methods are proven technologies that can achieve high oil recovery but are energy and water intensive. Examples of thermal methods are cyclic steam stimulation, CSS, and steam-assisted gravity drainage, SAGD, (Butler, 1997). Solvent-based and steam-solvent recovery processes are potential alternatives to thermal methods because they reduce energy consumption and greenhouse emissions (Singhal et al., 1997; Luhning et al. 2003). Solvent based processes have been the subject of considerable recent research (Upreti, 2007), particularly VAPEX (Butler and Mokrys, 1989) but have not yet been attempted in large-scale field applications. The development of steam-solvent processes, in which both steam and solvent are injected, has progressed further. Examples of steam-solvent processes are Expanding Solvent SAGD, ES-SAGD, (Nasr and Ayodele 2006), Solvent Aided Process, SAP, (Gupta et al. 2002, 2003), Liquid Addition to Steam for Enhanced Recovery, LASER, (Leaute 2002), and Steam Alternating Solvent Process, SAS, (Zhao 2004). Not only numerical reservoir simulations and laboratory experimental studies but also field trials have been reported for several steam-solvent processes (Leaute and Carey 2005, Gupta et al. 2005).
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