CCUS-EOR combines emission reduction with economic benefits, making it one of the key technologies for addressing global climate change. Addressing the lack of systematic comparative studies on the differences in geological endowments and engineering conditions between China and North America in existing literature, this paper systematically reviews the progress of North American CO₂-EOR in areas such as gas source structure transformation, capture technologies, and pipeline network construction, based on a self-constructed database of typical projects. It then conducts a quantitative comparative analysis of typical projects in China and the United States from three dimensions: reservoir geological endowment, gas source composition, and infrastructure. The study reveals that the advancement of U.S. CO₂-EOR projects benefits from increasing industrial CO₂ supply and the construction of cross-regional pipeline networks. Comparative analysis indicates that North American projects primarily feature miscible displacement in medium-to-low temperature and light oil reservoirs. This contrasts fundamentally with the characteristics of China’s continental reservoirs, which exhibit “strong heterogeneity, high viscosity, and high minimum miscibility pressure (MMP)”. Currently, China’s CCUS-EOR is transitioning from engineering demonstration to commercial application. However, gaps persist compared to more mature international systems in areas such as low-concentration CO₂ capture, pipeline network construction for source-sink matching, and suitability for continental reservoir EOR. Moving forward, China can draw on U.S. CCUS-EOR development experience, accelerate research on relevant technologies tailored to its continental reservoir characteristics, and establish a differentiated whole-industry-chain CCUS-EOR technology system.

Songliao Basin hosts abundant shale oil and gas resources, yet the phase behavior of the fluids is still unclear since the confinement effect of the shale reservoir alters the adsorption effect on the pore walls. In this study, molecular dynamics (MD) simulations were employed to clarify this issue. A binary mixture was built to represent Gulong shale oil and the phase state properties under the confinement effect were evaluated. In addition, a series of pure alkane models were constructed to analyze the influence of hydrocarbon type, temperature, and mineral composition on phase behavior. The simulation results showed that the typical Gulong shale fluid remains liquid state in the nanopores. Owing to the confinement effect, both viscosity and density under nano space decrease sharply compared to those at bulk space. Therefore, field development should somewhat rely on high-pressure stimulation to create flow paths, followed by CO₂ huff-and-puff technology to maintain production pressure. In addition, fluid composition, temperature, and mineral type are the primary factors governing the magnitude of the confinement effect.

The formation and evolution of the miscible zone are critical to displacement efficiency in CO₂ miscible flooding. A thorough understanding of its dynamic behavior provides essential guidance for optimizing injection and production strategies, improving oil recovery, and achieving sustainable and efficient reservoir development. This paper systematically reviews relevant research advances, summarizing the formation mechanisms and characterization methods of the miscible zone, along with its migration behavior from both experimental and numerical simulation perspectives. Analysis reveals that CO₂ and crude oil achieve dynamic miscibility through multiple contacts, with the miscible zone being predominantly governed by convective-diffusive processes after its formation. Under ideal conditions, the miscible front advances uniformly in an arc-like shape. As temperature increases, the initially miscible phases may gradually separate but can reachieve miscibility upon reaching a certain temperature threshold. To further enhance the application effectiveness of CO₂ miscible flooding technology, future research should focus on accurate prediction of the minimum miscibility pressure (MMP), standardized characterization of the miscible zone, and development of effective control strategies for the miscible zone.

The development of oil and gas resources in global petroliferous basins has extended from shallow to deep reservoirs. Dew point pressure (Pd) is a vital parameter for fluid characterization and field development. Accurately and quickly obtaining Pd is crucial for the development of ultra-deep condensate gas reservoirs. The objective of this work is to predict the Pd of condensate gas by an artificial neural network (ANN) model. Ten ultra-deep condensate gas samples were analyzed using an experimental method and the Pd at reservoir temperature was obtained. A total of 113 datasets including 103 collected datasets and 10 measured datasets were adopted for ANN model training and testing. The results show that the average absolute percent relative error (AAPRE) of the developed ANN model between the measured and predicted values on the test set was 4.9589%. The predicted accuracy between the ANN model and widely used equations of state was compared. The results of statistical and graphical analysis show that the ANN model achieves the minimum prediction error. This ANN model can provide the necessary guidance for predicting the Pd for the development of different kinds of reservoirs.