Electro-Acoustic Solvent-Based Method for Enhancing Heavy Oil Recovery

Abstract

Abstract A novel multi-physics approach is proposed to enhance performance of solvent extraction methods in heavy oil reservoirs by utilizing the enhanced mixing and spreading during acoustic excitation. In the modeling, the macroscopic flow equation is coupled to the conservative form of the advection-dispersion model while it is linked with an external time harmonic body load in a poroelastic domain. Linking the latter elements of the modeling is fully coupled and both impacts of the pressure load on the rock stress as well as the induced pore pressure by the rock strain are considered. Numerical simulation results are obtained by solving coupled macroscopic equations using the finite element method for a quarter five-spot source-sink geometry. Based on the numerical solutions, normalized concentration profiles of the displacing fluid as well as plots of resident and effluent concentrations are obtained for qualitative and quantitative analyses. Simulation results of the recovery enhancements are compared to conventional solvent-based methods of enhanced heavy oil recovery in terms of energy trade-off. Acoustically assisted solvent flooding reduces the required volume of injected solvent through enhancing dispersive mixing. The acoustic excitation at a relative amplitude of 200, which is applicable to field scale applications, can result in an additional 12 % enhancement in displacing an in-place fluid via an assisted solvent extraction process as compared to the equivalent silent displacement. Such enhancement happens both before and after breakthrough. Higher amplitudes and frequencies and wave propagations transverse to the flow direction increase the enhancement. Combining acoustic stimulations and electromagnetic (EM) heating may further enhance the recovery. The required equations to incorporate EM heating are provided as well. In the proposed multi-physics approach, both the required amounts of solvent and the greenhouse gas (GHG) emissions can be reduced. Electricity usage by the elements of excitations will be the key contributors in reducing GHG emissions’ footprints of heavy oil extraction. The simulation results of the developed model can provide an estimation of input parameters in economic analysis such as the cumulative delivered energy to oil ratio that is an essential component in calculating GHG emissions.