Examining performance of different two-phase fluid distributions simulation methods based on digital rock technology

Abstract

The accurate calculations of petrophysical properties are essential to evaluate oil/gas reservoirs. As an advanced non-destructive method, digital rock technology has been widely applied in simulating various rocks' petrophysical properties, such as the behaviors of resistivity and acoustic responses. Fluid distributions within the pore space are essential input data for such simulations. However, the 3D fluid distributions simulated by different methods may not be identical, leading to imprecise petrophysical interpretations. Therefore, it is necessary to compare the results of different methods on the same pore space to investigate their advantages and disadvantages. In our research, we used digital rock technology to compare different simulation methods of two-phase fluid distributions. We first adopted a sandstone core and acquired the actual oil and brine distributions in pores based on the micro-computed tomography scan images. Herein, a new simple and fast method was put forward to fix the rough connection between the oil and the brine phases. In the present study, five two-phase fluid distribution simulation methods were investigated including the steady-state pore morphology method, unsteady-state pore morphology method, network modeling method, steady-state lattice Boltzmann method, and unsteady-state lattice Boltzmann method. Then, we applied these methods on the same pore space and analyzed the results. Finally, the calculated resistivity indexes based on these methods were compared. It turns out that although the results of all different methods captured the main distribution characteristics of oil and brine phases, only the steady-state pore morphology method, unsteady-state pore morphology method, and steady-state lattice Boltzmann method provided the most useful two-phase fluid distribution and saturation exponent for our studied sandstone. These results can not only enhance our knowledge of different simulation methods’ performance but also help to choose the best method for a desired petrophysical characterization task.