Simulation and history-matching of polymer-assisted water alternating CO2 injection using MRST

Abstract

CO2 flooding is a widely employed method for enhancing oil recovery. However, it faces challenges stemming from differences in viscosity and density between oil and CO2, leading to poor sweep efficiency. This can result in issues such as viscous fingering, channelling, and gravity segregation, causing premature breakthroughs and excessive gas production. To address these concerns, the Polymer Assisted Water Alternating Gas (PA-WAG) technique combines the advantageous attributes of CO2 flooding, such as solubility and displacement, with the effective mobility control provided by polymer flooding. This results in a chemically enhanced Water Alternating Gas (WAG) flooding approach. A study by van Wieren et al. (2022) delved into the effectiveness of PA-WAG in addressing CO2 flow challenges and improving sweep efficiency by conducting core-flood experiments. This work builds upon that study by employing numerical simulations to replicate the core-flood experiments. These simulations shed light on the fundamental physical mechanisms during the PA-WAG injection process while also facilitating the calibration of flow parameters for practical implementation on a larger scale. The primary goal of this study was to comprehensively model three distinct enhanced oil recovery (EOR) techniques: polymer injection, CO2 flooding, and PA-WAG, all applied specifically to the Bentheimer sandstone cores. The objective was to history-match CT (Computed Tomography) scan saturation data, observed pressure drops, and oil recovery. A 2-dimensional (2D) model was constructed for each experiment, with CT scan images used to allocate varying porosity and permeability values to individual grid blocks. This enabled monitoring saturation distributions from the initial primary drainage phase onward. In the history matching of the primary drainage phase, parameters for relative permeabilities were determined from the Brooks-Corey equation, leveraging CT scan saturation data. The scaling of relative permeabilities based on CT scan saturations effectively accounted for capillary end effects observed in the core-flood experiments. During the history-matching of the polymer injection process, it was demonstrated that polymer-specific parameters, as determined from experimental data, could effectively modify waterflood relative permeabilities, thereby reducing the mobility ratio and accurately capturing the advancement of the polymer front. The formation of emulsions towards the end of polymer injection led to a notable increase in pressure drop, necessitating the incorporation of a high Residual Resistance Factor (RRF) to accommodate permeability reduction. In the case of history-matching for the CO2 flood, the black oil model successfully replicated the process of immiscible gas injection. It aptly captured gravity segregation while utilising CT scan saturation scaled relative permeabilities to assess the impact on oil recovery. The study unveiled that the relative permeability of gas under immiscible conditions was relatively lower than in miscible and near-miscible conditions. Simulating the PA-WAG injection by combining polymer and CO2 models effectively reproduced the core-flood experiments. The study substantiated the role of gas trapping in reducing the relative permeability of gas as a function of injection time, consequently leading to heightened pressure drops during subsequent polymer slug injections. The study showcased the efficacy of integrating black oil models for polymer and CO2 injection to successfully simulate PA-WAG injection and achieve unity with core-flood experiments yielding valuable insights into the physical processes underlying the technique.