Recovery mechanisms and formation influencing factors of miscible CO2 huff-n-puff processes in shale oil reservoirs: A systematic review

Current methods for measuring three-phase relative permeability and its influencing factors

The occurrence state of oil, gas, and water plays a crucial role in exploring shale reservoirs. In this study, molecular dynamics simulations were used to investigate the occurrence states of these fluids in shale nanopores. The results showed that when the alkane is light oil, in narrow pores with a width less than 3 nm, oil molecules exist only in an adsorbed state, whereas both adsorbed and free states exist in larger pores. Due to the stronger interaction of water with the rock surface, the adsorption of oil molecules near the rock is severely prohibited. Oil/water/gas occurrence characteristics in the water-containing pore study indicate that CO₂ gas can drive free oil molecules out of the pore, break water bridges, and change the occurrence state of water. During displacement, the gas type affects the oil/gas occurrence state. CO₂ has strong adsorption capacity, forming a 1.45 g/cm³ adsorption layer on the rock surface, higher than oil’s density peak of 1.29 g/cm³. Octane solubility in injected gases is CO₂ (88.1%) > CH₄ (76.8%) > N₂ (75.4%), with N₂ and CH₄ having weak competitive adsorption on the rock. The investigation of different shale reservoir conditions suggests that at high temperature or low pressure, oil/gas molecules are more easily displaced, while at low temperature or high pressure, they are tightly adsorbed to the reservoir rock. These findings contribute to the understanding of fundamental mechanisms governing fluid behavior in shale reservoirs, which could help to develop proper hydrocarbon recovery methods from different oil reservoirs.

Biosurfactants are a group of surface-active compounds that can be produced by diverse microorganisms. They have been widely used in various industrial fields. Reducing production costs, improving efficiency, and collecting more diverse producing strains have become major challenges in the biosurfactant industry. These challenges could be overcome by screening for more diverse and efficient biosurfactant-producing strains. The conventional methods for the isolation and functional characterization of microorganisms are laborious and biased toward fast-growing or strongly competitive microorganisms. Here, we established a high-throughput approach of single-cell-based cultivation and functional characterization of biosurfactant-producing bacteria (SCCBB). This approach combines single-cell cultivation with the detection of optical distortions. Using this approach, we isolated 431 strains with biosurfactant production potential from petroleum-contaminated soil and oilfield-produced water. The surfactant production capabilities of the strains were subsequently validated using surface tension measurements, TLC, and CMC measurements. To investigate the industrial production potential, we optimized the production conditions of a representative glycolipids-producing strain, Pseudomonas sp. L01, using response surface methodology (RSM). Optimal conditions yielded a crude biosurfactant yield of 8.43 g/L in a flask. Our work provides a high-throughput approach to the isolation and screening of biosurfactant-producing bacteria, as well as other functional bacteria in a wide range of fields.

Characterizing and simulating complex reservoirs, particularly unconventional resources with multiscale and non-homogeneous features, presents significant bottlenecks in cost, efficiency, and accuracy for conventional research methods. Consequently, there is an urgent need for the digital and intelligent transformation of the field. To address this challenge, this paper proposes that the core solution lies in the deep integration of physical mechanisms and data intelligence. We systematically review and define a new research paradigm characterized by the trinity of digital cores (geometric foundation), physical simulation (mechanism constraints), and artificial intelligence (efficient reasoning). This review clarifies the core technological path: first, AI technologies such as generative adversarial networks and super-resolution empower digital cores to achieve high-fidelity, multiscale geometric characterization; second, cross-scale physical simulations (e.g., molecular dynamics and the lattice Boltzmann method) provide indispensable constraints and high-fidelity training data. Building on this, the methodology evolves from surrogate models to physics-informed neural networks, and ultimately to neural operators that learn the solution operator. The analysis demonstrates that integrating these techniques into an automated “generation–simulation–inversion” closed-loop system effectively overcomes the limitations of isolated data and the lack of physical interpretability. This closed-loop workflow offers innovative solutions to complex engineering problems such as parameter inversion and history matching. In conclusion, this integration paradigm serves not only as a cornerstone for constructing reservoir digital twins and realizing real-time decision-making but also provides robust technical support for emerging energy industries, including carbon capture, utilization, and sequestration (CCUS), geothermal energy, and underground hydrogen storage.

The flow characteristics of dissolved gas driven processes in some heavy oil reservoirs, such as low gas–oil ratio and higher oil recovery rate than expected, are quite different from conventional oil production processes. Foamy oil is considered one of the main reasons behind such a production phenomenon. In this paper, the factors affecting the performance of foamy oil recovery were experimentally investigated in a sandpack medium with the assistance of computed tomography (CT) technology to help further the understanding of the mechanism. Five different experiments were applied and the results showed that (1) the linear pressure drop production model had a similar oil recovery to that of the step-down mode; (2) increasing the depletion rate could be more favorable to the oil recovery rate; (3) under a constant gas–oil ratio, raising the temperature had little impact on oil recovery, but showed obvious impact on the production curve; and (4) with higher permeability, there were more residual oil at the end of the displacement process. Lastly, a dry gas huff and puff experiment was conducted and the decreased oil saturation was observed in the inlet section, while no obvious effect was remarked in the outlet region of the medium.