Determination of binary diffusion coefficients between hot liquid solvents and bitumen with X-ray CT

Abstract

Abstract The Steam Assisted Gravity Drainage (SAGD) process has been used for in-situ thermal bitumen recovery in Canada. Nevertheless, there are several drawbacks that could impair the SAGD performance. One of the main drawbacks of SAGD is nontrivial consumption of energy to generate steam. To curtail the consumption of steam, many SAGD variants have been proposed. For example, Vapor Extraction (VAPEX) was proposed as a solvent-based cold production method and Solvent-Assisted SAGD (SA-SAGD) was proposed as a solvent-assisted hybrid method. In those solvent-based/assisted methods, the dissolution of solvents in bitumen enhances the in-situ oil mobility. The speed of the mixing between solvents and bitumen in solvent-based/assisted recovery processes is dictated by dispersive mass flux which is proportional to the transverse dispersion coefficient. Diffusion coefficient, tortuosity and transverse dispersivity should be quantified to characterize the transverse dispersion coefficient. In this research, the diffusion coefficients of solvents in Athabasca bitumen were determined with X-ray computed tomography (CT). A medical X-ray CT scanner was used to capture the diffusion phenomenon occurring between fresh liquid solvents and bitumen. The experiments were designed to reproduce the in-situ high pressure, high temperature condition (3.5 MPa, 135C) where solvent and bitumen actually interact at the vapor chamber edge in the SA-SAGD process. Using our new °experimental system, we successfully measured molecular diffusion coefficients at the condition of the vapor chamber edge for the first time. In conclusion, the binary diffusion coefficients between solvents and bitumen were successfully measured at the condition where the mixing of solvents and bitumen actually occurs in the SA-SAGD process. The characterized diffusion coefficients will be input parameters for the reservoir simulation and semi-analytical models.