Polymers play a key role in several EOR processes such as polymer flooding, surfactant-polymer flooding and alkaline-surfactant-polymer flooding due to their critical importance of mobility control in achieving high oil recovery from these processes. Numerical simulators are used to predict the performance of all of these processes and in particular the injection rate of the chemical solutions containing polymer; since the economics is very sensitive to the injection rates. Injection rates are governed by the injection viscosity, thus, it is very important to model the polymer viscosity accurately. For the predictions to be accurate, not only the viscosity model must be accurate, but also the calculation of equivalent shear rate in each gridblock must be accurate because the non-Newtonian viscosity models depend on this shear rate. As the size of the gridblock increases, the calculation of this velocity becomes less numerically accurate, especially close to wells.
This research presents improvements in polymer viscosity model. Using the improvements in shear thinning model, the laboratory polymer rheology data was better matched. For the first time, polymer viscosity was modeled for complete range of velocity using the Unified Viscosity Model for published laboratory data. New models were developed for relaxation time, time constant and high shear viscosity during that match. These models were then used to match currently available HPAM polymer's laboratory data and predict its viscosity for various concentrations for full flow velocity range.
This research presents the need for injectivity correction when large grid sizes are used. Use of large grid sizes to simulate large reservoir due to computation constraints induces errors in shear rate calculations near the wellbore and underestimate polymer solution viscosity. Underestimated polymer solution viscosities lead to incorrect injectivity calculation. In some cases, depending on the well grid block size, this difference between a fine scale and a coarse simulation could be as much as 100%. This study focuses on minimizing those errors. This methodology although needs some more work, but can be used in accurate predictions of reservoir simulation studies of chemical enhanced oil recovery processes involving polymers. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/ETD-UT-2010-12-2586 |
| Date | 17 February 2011 |
| Creators | Sharma, Abhinav, 1985- |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Type | thesis |
| Format | application/pdf |
Page generated in 0.0021 seconds