Mingguo Peng

CO₂ flooding in low-permeability and tight oil reservoirs is frequently compromised by severe gas channeling, which significantly reduces oil recovery and sweep efficiency. While foam flooding can effectively mitigate CO₂ channeling by trapping CO₂ within lamellae, its stability deteriorates under harsh high-temperature, high-salinity reservoir conditions, compromising its effectiveness. Furthermore, foam flow in porous media involves constant foam generation, collapse and propagation, making its flow behaviors difficult to predict. To address these challenges, a new foaming agent with satisfactory regenerative capability is developed to maintain gas mobility control under harsh reservoir conditions. The multiphase flow behaviors during CO₂ foam flooding are predicted using pore network modeling to obtain the corresponding relative permeability curves, which are further incorporated into a reservoir simulator to evaluate field-scale foam flooding performances, as well as optimize injection strategies. This multi-scale modeling approach establishes a quantitative link between pore-scale foam behaviors and field-scale oil recovery performances, offering new insights into carbon capture and utilization with enhanced oil recovery in low-permeability and tight reservoirs. Document Type: Original article Cited as: Peng, M., Zhou, Y., Yang, J., Wang, J., Lin, Z., Zhao, J. Experimental investigation and multi-scale simulations of CO₂ foam flooding for enhanced oil recovery. Capillarity, 2025, 16(2): 39-50. https://doi.org/10.46690/capi.2025.08.02

The Arctic region is rich in oil and gas resources and has great potential for development. It has become a new hot spot for international development. However, the harsh climatic and geological conditions and fragile ecosystems in the Arctic region put forward stringent technical requirements for oil and gas development. Polar permafrost has an impact on the growth of plant roots and the absorption of water. When drilling activities are carried out, the permafrost layer may be broken, resulting in the erosion of polar soil and disorder of the water balance, thus affecting local vegetation and ecosystems. Moreover, the legal system of polar environmental protection is lacking, and it is necessary to form a perfect risk assessment method to improve the relevant laws and regulations. Therefore, it is very important to study the environmental risk identification technology for polar drilling. For polar drilling, it is necessary to establish a risk source classification and identification method for environmental pollution events. However, at present, it mainly faces the following challenges: poor polar environment, lack of monitoring data, and lack of a legal system for polar environmental protection. By systematically discussing risk identification technology, the application and applicable models of different types of risk evaluation methods are categorized and summarized, the advantages and disadvantages of different types of risk evaluation methods and their application effects are analyzed based on the unique environment of the polar regions, and then the development direction of the future environmental risk identification technology for polar drilling is proposed. In order to accelerate the development of polar drilling environmental risk identification technology, research should be focused on the following three aspects: ① Promoting the multi-dimensional integration of polar drilling environmental pollution index data, to make up for the short board of less relevant data in the polar region. ② Combining the machine modeling algorithm with risk evaluation of polar drilling environmental pollution to improve the scientificity and accuracy of the evaluation results. ③ Establishing a scientific and accurate polar drilling environmental pollution risk identification system to reduce pollution risk.

With the ongoing rise in global energy demand, the importance of enhanced oil recovery in oilfield development is becoming increasingly prominent. However, traditional chemical flooding agents face bottlenecks such as poor adaptability to application environments, unclear coupling mechanisms regarding multiple factors, as well as long research and development cycles. This paper systematically discusses the innovative paradigm of oilfield chemical agent development driven by artificial intelligence and proposes four core technological breakthroughs. Firstly, artificial intelligence-empowered molecular simulation technology can reveal the behavior mechanisms of flooding agents under extreme conditions. Secondly, intelligent molecular design using generative adversarial networks and reinforcement learning breaks through the traditional trial-and-error model. Thirdly, the construction of a data-mechanism dual-driven multi-objective optimization model achieves the collaborative prediction of physicochemical properties, economic benefits and environ mental friendliness. Lastly, an integrated system of robotic chemist and high-throughput experimental platforms forms a closed-loop system of “artificial intelligence design - automated synthesis- online detection”, yielding a complete ecosystem. The analysis of the current technological development challenges and future development directions reveals that the artificial intelligence-empowered intelligent Research and Development system is expected to promote the transformation of chemical flooding technology toward efficiency, environmental protection and sustainable development, providing a new standard for intelligent oil and gas field development. Document Type: Invited review Cited as: Wei, K., Zhou, M., Huang, J., Zhang, Q., Ding, B., Lyu, W., Peng, M. Chemical agents designed for oilfield development: A new paradigm empowered by artificial intelligence. Advances in Geo-Energy Research, 2025, 17(1): 1-16. https://doi.org/10.46690/ager.2025.07.01

Although gas flooding has been successfully applied for enhanced oil recovery throughout the world, most of its applications are conducted in low, ultralow, and tight oil reservoirs with light oil. Studies focused on a low-permeability reservoir with medium viscous oil are rarely reported, and there is little experience in the development of this type of reservoir for reference. Based on the special characteristics of low-permeability formation coupled with medium viscous oil in Niuquanhu Block, China, the gas-oil interactions of different gases are first evaluated through the pressure-volume-temperature (PVT) analysis. Then, the minimum miscibility pressure (MMP) of different gases is compared using slim tube experiments and a numerical simulation method. The oil recovery of different gas floodings is studied using core flooding experiments, and then the output oil compositions of different gas floodings are analyzed using a total hydrocarbon chromatograph. The PVT analysis results show that the interactions between hydrocarbons and medium viscous oil are the strongest compared with other gases. Under formation conditions, about 70 mol % hydrocarbons is dissolved in the medium viscous oil, leading to a 69% reduction of oil viscosity and a 48% increment of oil swelling, which is 1.19 and 1.35 times those of CO₂. The reduction of oil viscosity and increment of oil swelling of hydrocarbons are 1.64 and 2.02 times those of CH₄. And the reduction of oil viscosity and increment of oil swelling of hydrocarbons are 2.23 and 2.67 times those of N₂. Slim tube experiments show that the MMPs of hydrocarbon flooding, CO₂ flooding, CH₄ flooding, and N₂ flooding are 28.5, 36.8, 46.4, and 61.6 MPa, respectively. Therefore, compared with the other three types of gases, hydrocarbon flooding has the lowest MMP for low-permeability reservoirs with medium viscous oil. The errors between the MMPs of hydrocarbon flooding, CO₂ flooding, CH₄ flooding, and N₂ flooding obtained by the numerical simulation method and the results obtained by the slim tube experiment method are 0.71, 0.82, 0.87, and 0.98%, respectively. The numerical simulation results of the slim tube experiment show that the flooding pressure and oil recovery curves of different gas floodings all have inflection points. Under the existing condition, the inflection point pressure value is unchanged by changing the PV values of different gas injections. According to the results of a series of core flooding experiments and the analysis of the output oil compositions of different gas floodings, the oil recoveries of hydrocarbon flooding, CO₂ flooding, CH₄ flooding, and N₂ flooding are 57.02, 51.11, 36.88, and 21.35%, respectively, and the extraction ability of different gases to light hydrocarbon components is ranked as hydrocarbons > CO₂ > CH₄ > N₂. The findings revealed in this paper can provide technical support for gas flooding development in similar low-permeability reservoirs with medium viscous oil.

Pre-ozonation can enhance the removal of algae in source water during cyanobacterial blooms; however, little is known about the influence of the co-existing allochthonous natural organic matter (NOM) on algal removal and algal organic matter (AOM) behavior during ozonation. This study aims to elucidate in the presence and absence of allochthonous NOM and the effects of varying ozone doses on Synechococcus sp. cell removal, membrane integrity, and dissolved organic matter (DOM) release and removal. The results indicate that ozone effectively disrupted algal cell membranes, reducing algal density; however, the presence of allochthonous NOM delayed cell rupture by competing for ozone due to aromatic humic-like substances. Pterin-like and protein-like fluorescent compounds were released upon cell disruption. Due to that, excess ozone led to the oxidation of the released pterin-like compounds, with characteristic fluorescence changes correlating to ozone dosage; these changes are potential to be used as an indicator to determine the optimized ozone dosage, avoiding more adverse release of intracellular AOM to form disinfection byproducts.

As a critical component in industrial production, pipelines face the risk of failure due to long-term corrosion. In recent years, acoustic emission (AE) technology has demonstrated significant potential in online pipeline monitoring. However, the interference of flow-induced noise seriously hinders the application of acoustic emission technology in pipeline corrosion monitoring. Therefore, a pattern-recognition model for online pipeline AE monitoring signals based on blind source separation (BSS) and a convolutional neural network (CNN) is proposed. First, the singular spectrum analysis (SSA) was employed to transform the original AE signal into multiple observed signals. An independent component analysis (ICA) was then utilized to separate the source signals from the mixed signals. Subsequently, the Hilbert–Huang transform (HHT) was applied to each source signal to obtain a joint time–frequency domain map and to construct and compress it. Finally, the mapping relationship between the pipeline sources and AE signals was established based on the CNN for the precise identification of corrosion signals. The experimental data indicate that when the average amplitude of flow-induced noise signals is within three times that of corrosion signals, the separation of mixed signals is effective, and the overall recognition accuracy of the model exceeds 90%.

Per- and Polyfluoroalkyl Substances (PFAS) bioaccumulate in the human body, presenting potential health risks and cellular toxicity. Their transport mechanisms and interactions with tissues and the circulatory system require further investigation. This study investigates the interaction mechanisms of six PFAS with Human Serum Albumin (HSA) using multi-spectroscopy, DFT and a molecular dynamics approach. Multi-spectral analysis shows that perfluorononanoic acid (PFNA) has the best binding capabilities with HSA. The order of binding constants (298 K) is as follows: “Perfluorononanoic Acid (PFNA, 7.81 × 10⁶ L·mol⁻¹) > Perfluoro-2,5-dimethyl-3,6-dioxanonanoic Acid (HFPO-TA, 3.70 × 10⁶ L·mol⁻¹) > Perfluorooctanoic Acid (PFOA, 2.27 × 10⁵ L·mol⁻¹) > Perfluoro-3,6,9-trioxadecanoic Acid (PFO3DA, 1.59 × 10⁵ L·mol⁻¹) > Perfluoroheptanoic Acid (PFHpA, 4.53 × 10³ L·mol⁻¹) > Dodecafluorosuberic Acid (DFSA, 1.52 × 10³ L·mol⁻¹)”. Thermodynamic analysis suggests that PFNA and PFO3DA’s interactions with HSA are exothermic, driven primarily by hydrogen bonds or van der Waals interactions. PFHpA, DFSA, PFOA, and HFPO-TA’s interactions with HSA, on the other hand, are endothermic processes primarily driven by hydrophobic interactions. Competitive probe results show that the main HSA–PFAS binding site is in the HSA structure’s subdomain IIA. These findings are also consistent with the findings of molecular docking. Molecular dynamics simulation (MD) analysis further shows that the lowest binding energy (−38.83 kcal/mol) is fund in the HSA–PFNA complex, indicating that PFNA binds more readily with HSA. Energy decomposition analysis also indicates that van der Waals and electrostatic interactions are the main forces for the HSA–PFAS complexes. Correlation analysis reveals that DFT quantum chemical descriptors related to electrostatic distribution and characteristics like ESP and ALIE are more representative in characterizing HSA–PFAS binding. This study sheds light on the interactions between HSA and PFAS. It guides health risk assessments and control strategies against PFAS, serving as a critical starting point for further public health research.

The requirement of simple, efficient and accurate detection of tetracycline (TC) in water environments poses new challenges for sensing platform development. Here, we report a simple method for TC sensing via fluorescence detection based on metal–organic coordination polymers (MOCPs, (4-Hap)₄(Mo₈O₂₆)) coated with nitrogen-doped carbon dots (NCDs). These NCDs@(4-Hap)₄(Mo₈O₂₆) composites showed excellent luminescence features of NCDs with stable bright-blue emission under UV light. The results of the sensing experiment showed that the fluorescence of NCDs@(4-Hap)₄(Mo₈O₂₆) can be quenched by TC (166 µM) with 94.1% quenching efficiency via the inner filter effect (IFE) in a short time (10 s), with a detection limit (LOD) of 33.9 nM in a linear range of 8–107 µM. More significantly, NCDs@(4-Hap)₄(Mo₈O₂₆) showed a high selectivity for TC sensing in the presence of anions and metal cations commonly found in water environments and can be reused in at least six cycles after washing with alcohol. The potential practicality of NCDs@(4-Hap)₄(Mo₈O₂₆) was verified by sensing TC in real water samples with the standard addition method, and satisfactory recoveries from 91.95% to 104.72% were obtained.

The treatment of livestock manure caused by the expansion of the breeding industry in China has attracted wide attention. Heavy metals in pig manure can pollute soil and water and even transfer to crops, posing harm to humans through the food chain. In this study, corn straw was selected as the additive and introduced into the anaerobic digestion. Sepiolite (SE), ferric oxide (Fe₂O₃), attapulgite (AT) and ferric sulfate (FeSO₄) were used as passivators to compare the effects of these inorganic passivators on gas production and passivation of heavy metals during the process of the anaerobic digestion. When the dry mass ratio of pig manure to straw is 8:2, the gas production efficiency is optimal. SE, AT and ferric sulfate have a much stronger ability to improve gas production performance than Fe₂O₃. The total gas production increased by 10.34%, 6.62% and 4.56%, and the average methane production concentration increased by 0.7%, 0.3% and 0.4%, respectively. The influence of SE, AT and ferric sulfate on the passivation of heavy metals is much better than Fe₂O₃, and the fractions in biological effective forms of Cu and Zn reduced by 41.87 and 19.32%, respectively. The anaerobic digestion of mixed materials is conducive to the gas production and the passivation of heavy metals. Therefore, SE, AT and ferric sulfate are selected as composite passivators, and the optimal ratio of inorganic composite passivators i: AT 7.5 g/L, ferric sulfate 5 g/L and SE 7.5 g/L, according to the results of orthogonal experiments. This study can provide a theoretical basis for the safe application of biogas fertilizers.