CO₂ flow in porous media is vital for both enhanced oil recovery and underground carbon storage. For improving CO₂ mobility control and thus improved reservoir sweep efficiency, Water-Alternating-Gas (WAG) injection has often been applied. The effectiveness of WAG diminishes, however, due to the presence of micro-scale reservoir heterogeneity which results in an early breakthrough of gas. We propose Polymer-assisted WAG (PA-WAG) as an alternative method to reduce gas mobility, while also reducing the mobility of the aqueous phase, and consequently improving the performance of WAG. In this method, high molecular weight water-soluble polymers are added to the water slug. The goal of this work was to investigate the feasibility of PA-WAG and study the transport processes in porous media. An ATBS-based polymer (SAV 10 XV) was chosen as polymer and CO₂ at immiscible conditions as gas. The objective of the experiments was to compare the performance of CO₂, WAG, and PA-WAG injection schemes by conducting a series of X-ray computed tomography (CT)-aided core-flood experiments in Bentheimer cores. Core-flood results clearly demonstrated the beneficial effects of PA-WAG over WAG and continuous CO₂ injection. Continuous injection of CO₂ led to the recovery factor (RF) of only 39.0 ± 0.5% of the original oil in place (OOIP). In-situ visualization of CO₂ displacement showed strong gravity segregation and viscous fingering because of the contrast in the viscosities and densities of CO₂ and oil. The injection of WAG almost doubled the oil recovery (i.e., RF=76.0 ± 0.5%); however, the water and gas breakthroughs still occurred in the early stage of the injection (0.22 PV for water and 0.27 PV for CO₂). The addition of the polymer to the aqueous phase delayed both the water and CO₂ breakthrough (0.51 PV for water and 0.35 PV for CO₂). This resulted in an additional 10% in the recovery factor. Using a single injection method, polymer adsorption was found to be 79.0 ± 0.5 μg polymer/g rock. The polymer adsorption can reduce the micro-scale permeability and as a result, mitigates the gas channeling. This in turn leads to the delay in CO₂ breakthrough during PA-WAG injection as was evident from in-situ visualization. This experimental study demonstrated a positive response of PA-WAG compared to WAG and paves the way for its implementation in field applications.

The partitioning inter-well tracer test (PITT) is a method to determine average oil saturation between an injector-producer pair. Tracer tests can be used to quantify incremental oil recovery in enhanced oil recovery (EOR) pilots and for reservoir surveillance purposes. Various interpretation methods can be applied: peak arrival time comparison, Residence Time Distribution Analysis (RTDA), extrapolation methods and projection methods. Various sensitivities influence the outcome, accuracy and consistency of these methods. First and foremost, reservoir geometry and heterogeneity have significant impact on the shape of the tracer response curve, and on the accuracy of the subsequent oil saturation estimation. The presence of multiple flow paths can be clearly identified from tracer responses and oil saturation of each flow path can be determined individually by use of extrapolation and projection methods. Thus, potential permeability baffles or barriers can be identified and static reservoir models can be improved by evaluating tracer response data. Further key sensitivities are sampling duration, sampling frequency and measurement errors. An incomplete tracer response can lead to significant loss of accuracy of oil saturation determination by RTDA. A low sampling frequency has severe impact on the accuracy of oil saturation estimation, especially if large measurement errors are present. For timely execution of an EOR project, an early estimation of oil saturation is desirable. In this study, a new and robust analytical projection method is proposed that enables early time estimation of oil saturation based on limited data. The projection method is based on a translation of the non-partitioning tracer response curve to the partitioning tracer curve using a time and amplitude scalar. Robustness of this method is achieved by performing a least squares optimization that takes into account all available data in order to find optimal fitting time and amplitude scalars for tracer data translation. This projection method provides accurate early time oil saturation estimations based on limited partitioning tracer data. Especially if responses are incomplete, contain multiple peaks caused by reservoir heterogeneities, have a low sampling frequency and contain large measurement errors, the least squares projection method provides a more accurate oil saturation estimate than the other methods.