The distribution and characterization of microscopic residual oil have long been considered a bottleneck in the development of high-water-cut oilfields. This study presents a systematic review and analysis of the advances and challenges in research methods for microscopic residual oil in the late stage of oilfield development. Accordingly, we propose tailored methods and establish an index system for selecting optimal techniques, thereby providing the foundation for scientifically robust strategies to tap residual oil potential in the oilfields. The results indicate that physical experiments remain central to uncovering the microscopic occurrence patterns and complex seepage mechanisms of residual oil. Their effective application depends on the characterization objectives. Numerical simulation techniques, based on the mechanisms underlying physical experiments, allow for the simulation of dynamic fluid distribution and the prediction of residual oil potential using mathematical and physical models. Compared to traditional methods, machine learning-based techniques offer distinct advantages in the intelligent processing of experimental images, pore structure identification, fluid phase differentiation, residual oil morphology recognition, and the prediction of residual oil distribution. Current research trends show a shift toward the deep integration of physical experiments, numerical simulations, and machine learning. To address the complex challenges of tapping residual oil potential in the late stage of oilfield development, future breakthroughs are required in three key areas. First, physical experiment techniques should be advanced toward higher resolution, more realistic experimental conditions, and broader data dimensions. Second, numerical simulation techniques should be enhanced to achieve greater accuracy and computational efficiency in characterizing seepage mechanisms under complex geological conditions. Third, machine learning-based techniques should highlight the intelligent identification and cognitive understanding of the occurrence morphologies and evolutionary patterns of microscopic residual oil. It is necessary to develop a decision-making model that combines high-precision in situ experiments, multi-scale simulations, and forward-looking strategies. Such a model will play a critical role in surging the tapping efficiency of residual oil potential in high-water-cut oilfields.

To improve oil displacement efficiency under deep reservoir conditions, foam flooding technology represents a critical strategy through the establishment of a stable, long-lasting foam system. A central challenge in this application is to characterize the evolution dynamics of foam under extreme reservoir conditions such as high temperature and salinity. In this study, a performance evaluation experiment of foams generated by different types of surfactants was carried out by using the Waring-blender method. The foam stability characteristics were analyzed on the basis of foam volume, half-life of the liquid solution, and the foam comprehensive index and other related parameters. Based on the microscopic action mechanism of gas-liquid interface, the change pattern of foam performance with concentration, salinity and the coordinated action of core-shell particles were investigated. Both candidate surfactants exhibited good resistance to temperature and salinity. Among them, one surfactant demonstrated superior overall performance, with the foam comprehensive index reaching its peak at an optimal mass concentration of 0.5%. In high-salinity environments, the synergistic interaction between core-shell particles and surfactant molecules significantly enhances foam stability. In particular, the combination of this surfactant with core-shell particles at a mass fraction of 0.5% resulted in a notably higher foam comprehensive index, suggesting its strong application potential. This study quantitatively analyzes the synergistic stability effects of salinity, core-shell particles and surfactant, and reveals the synergistic stability mechanism of salt ion compression electric double layer and particle interface adsorption, providing important theoretical guidance for the development and application of deep reservoir foam flooding.

Generally,huge amounts of fracturing fluid are used in a shale gas well but the flowback efficiency is low. Since the distribution characteristics of imbibed fracturing fluid in shale are complex,they need further evaluation. This paper takes the Longmaxi Shale as the research object,including matrix cores,natural fracture cores and cores of artificial fracture with proppant. Stress sensitivity experiments are carried out on the above three kinds of cores under different degrees of imbibition and retention state of fracturing fluid. The results show that when the degree of aqueous phase retention is 0-0.78 pore volume,water mainly appears in the pores with a diameter of 2-50 nm. As the water saturation increases to more than 0.9 pore volume,the amounts of aqueous phase in the pores or fractures with a hydraulic diameter of 100-1,000 nm and larger than 1,000 nm increase significantly. Both the stress sensitivity of nanopores and natural fractures are enhanced by aqueous phase retention. With the increase in effective stress,the permeability damage rate of artificial fracture cores with proppant is inversely proportional to the degree of fracturing fluid retention. Aqueous phase retention in the pores with a diameter of 2-50 nm significantly contributes to the stress sensitivity of matrix cores. With the increase in effective stress,aqueous phase retention in pores with diameter larger than 100 nm increases the stress sensitivity of natural fracture cores. It is recommended that the retention degree of fracturing fluid in a shale gas reservoir should be controlled below 0.5 pore volume. In this case,the stress sensitivity of natural fractures will be less aggravated by fracturing fluid retention,and the stress sensitivity of artificial fracture with proppant will be reduced to a certain extent.