In low permeability reservoirs, CO₂ flooding usually leads to gas channeling, whereby a significant amount of CO₂ bypasses the oil-bearing formation and fails to effectively displace oil. Introducing water-alternating-gas (WAG) flooding, utilizing water phase stability-driven processes, serves to suppress gas channeling and enhance oil recovery rates. Implementing WAG flooding, which utilizes water phase stability-driven processes, helps suppress gas channeling and improve oil recovery rates. The timing of implementing WAG flooding is crucial. Initiating WAG flooding prematurely can limit the efficiency of CO₂ displacement, while initiating it with delays may result in severe gas channeling, resulting in decreased production and increased environmental risks. Finding the balance point is the challenge. The balance point can effectively control gas channeling without reducing the efficiency of CO₂ flooding. In this paper, the timing of WAG flooding in low permeability reservoirs is studied in detail. Firstly, this study conducted experimental research to investigate the CO₂ displacement process in both homogeneous and heterogeneous cores. Furthermore, it validated the correlation between the timing of WAG injection and the heterogeneity of the cores. The experimental results indicated the existence of an optimal timing for WAG injection, which is correlated with the degree of heterogeneity. Numerical simulation studies were performed to simulate the characteristics of the light oil–CO₂ system using the Peng–Robinson (PR) equation. Furthermore, a history matching analysis was performed to validate the experimental results and investigate the correlation between WAG injection and the degree of heterogeneity. The study concluded that as the degree of heterogeneity increases, initiating WAG injection earlier leads to a more significant suppression of gas channeling, increased water–gas interaction, improved gas–oil contact, and enhanced the synergistic effect of increasing the resistance and pressure of WAG flooding and controlling gas channeling. This finding has significant practical implications, as the optimization of WAG injection timing can enhance oilfield production efficiency.

During micro-scale tracer flow in porous media, the permeability and fluid velocity significantly affect the fluid dispersion properties of the media. However, the relationships between the dispersion coefficient, permeability, and fluid velocity in core samples are still not clearly understood. Two sets of experiments were designed to study the effects of tracer fluid flow velocity and porous medium permeability on the dispersion phenomenon in a core environment, using natural and sand-filled cores, respectively. From experimental data-fitting by a mathematical model, the relationship between the dispersion coefficient, flow velocity, and permeability was identified, allowing the analysis of the underlying mechanism behind this phenomenon. The results show that a higher volumetric flow rate and lower permeability cause a delay in the tracer breakthrough time and an increase in the dispersion coefficient. The core experimental results show that the dispersion coefficient is negatively correlated with the permeability and positively correlated with the superficial velocity. The corresponding regression equations indicate linear relations between the dispersion coefficient, core permeability, and fluid velocity, resulting from the micron scale of grain diameters in cores. The combination of high velocity and low permeability yields a large dispersion coefficient. The effects of latitudinal dispersion in porous media cannot be ignored in low-permeability cores or formations. These findings can help to improve the understanding of tracer flow in porous media, the design of injection parameters, and the interpretation of tracer concentration distribution in inter-well tracer tests.

Much research has been carried out on nanoscale polymer microspheres (PMs) in laboratories in recent years. However, there are limited reports on the practical application of nanoscale PMs in ultralow permeability reservoirs. This paper reports a field application case of nanoscale PMs for in-depth profile control in the ultralow permeability oil reservoir. In the paper, the characteristics of the reservoir and the problems faced during development are analyzed in detail. Then, the PMs with calibration diameters of 300 nm and 800 nm are researched by evaluation experiments, and are selected for in-depth profile control in the ultralow permeability oil reservoir. Finally, according to the effect of the pilot application, the performance of PMs is evaluated, and a more suitable size for the pilot test reservoir is determined. The experiment's results show that the PMs have a good capacity for swelling and plugging. For the PMs with a calibration diameter of 300 nm, the final equilibrium swelling ratio is 56.2 nm·nm⁻¹, and the maximum resistance coefficient and the blocking rate after swelling are 3.7 and 70.31%, respectively. For the PMs with a calibration diameter of 800 nm, the final equilibrium swelling ratio is 49.4 nm·nm⁻¹, and the maximum resistance coefficient the blocking rate after swelling are 3.5 and 71.42%, respectively. The performance evaluation results show that nanoscale PMs can be used for in-depth profile control in the ultralow permeability oil reservoir. After the application of PMs in the pilot test area, the average water cut decreased by 10.4%, the average liquid production of single well-increased by 0.9 t/d, and the average thickness of the water-absorbing layer increased by 1.77 m. Comparing the dynamic data variation of well-groups using the PMs with the calibration diameter as 800 nm and the calibration diameter as 300 nm, it indicates that, for the pilot test area, PMs with a calibration diameter of 300 nm are more suitable than PMs with a calibration diameter of 800 nm.

Polymer microsphere (PM) profile control has been attributed to improving sweep efficiency during the oil development process. The critical factors for PM conformance control are the plugging properties controlled by matching the relationship between the throat diameter and particle size and the injection parameters. A new matching relationship between the reservoir and PM based on the function of blocking rate and the ratio of throat diameter to microsphere diameter (C_R) is established to choose the most appropriate PM size. The blocking rate indicates that it will get the most excellent plugging effect when C_R is 0.5. The displacement experiments under different injection concentrations and other injection volumes show that the blocking rate is increased by injection concentration and finally stabilized. A similar trend is presented between the injection volume and plugging rate. The optimal injection concentration is 0.5%, and the optimal injection volume is 0.3 PV. According to the new size selection method and injection parameter optimal method, PM100 chooses to conduct field application. PM100 presents a good performance with a success rate of 37.5% and a validity period of more than 120 days, and its daily oil production rate increased 1.7 times, on average, and finally, the total oil increase is 556 t. The optimal size microsphere shows a good EOR effect, which indicates that this size selection method is reasonable.

Oil recovery is an essential parameter for reservoir development performance evaluation, but there is no specific research on the theoretical oil recovery prediction model of polymer microspheres (PMs)’ conformance control. This research aims to establish an oil recovery prediction model that depends on the definition of oil recovery based on stream tube theory. PMs’ enhanced oil recovery mechanism is to plug the pore throat to expand the swept area. The assumption that the stream tube between injection and production wells is trapezoidal is proposed. Based on this premise, the area sweep efficiency equation suitable for the rhombus inverse nine-spot well pattern is established based on the stream tube theory. The vertical sweep efficiency equation is optimized by introducing the equivalent mobility ratio. Additionally, the model’s adaptability and validity are studied. The analysis results show that oil recovery decreases with increasing injection rate, injection concentration, and PMs size but increases with the increasing injection period. The theoretical oil recovery is 1.37%, and the actual oil recovery of the field application is 1.22%, with an error of 0.15%. This model has good consistency with the actual physical process of the field application. The oil recovery prediction model can provide oil recovery and optimize PMs’ conformance control injection scheme. This study fills the gap in the mathematical model for oil recovery prediction of PMs’ conformance control.