Adipic acid is an important raw chemical for the commercial production of polyamides and polyesters. The traditional industrial adipic acid production utilizes nitric acid to oxidize KA oil (mixtures of cyclohexanone and cyclohexanol), leading to the emission of N₂O and thus causing ozone depletion, global warming, and acid rain. Herein, we reported an organically functionalized β-isomer of Anderson polyoxometalates (POMs) nanocluster with single-atom Mn, β-{[H₃NC(CH₂O)₃]₂MnMo₆O₁₈}⁻ (1), as a highly active catalyst to selectively catalyze the oxidation of cyclohexanone, cyclohexanol, or KA oil with atom economy use of 30% H₂O₂ for the eco-friendly synthesis of adipic acid. The catalyst has been characterized by single crystal and powder XRD, XPS, ESI-MS, FT-IR, and NMR. A cyclohexanone (cyclohexanol) conversion of >99.9% with an adipic acid selectivity of ~97.1% (~85.3%) could be achieved over catalyst 1 with high turnover frequency of 2427.5 h⁻¹ (2132.5 h⁻¹). It has been demonstrated that the existence of Mn³⁺ atom active site in catalyst 1 and the special butterfly-shaped topology of POMs both play vital roles in the enhancement of catalytic activity.

This study presents a novel Enhanced Oil Recovery (EOR) method using Smart Black Nanocards (SLNs) to mitigate the environmental impact of conventional thermal recovery, especially under global warming. Unlike prior studies focusing on wettability alteration via adsorption, this research innovatively models ‘oil film detachment’ in a reservoir simulator to achieve wettability alteration. Using the CMG-STARS (2020) simulator, this study highlights SLNs’ superior performance over traditional chemical EOR and spherical nanoparticles by reducing residual oil saturation and shifting wettability toward water-wet conditions. The structural disjoining pressure (SDP) of SLNs reaches 20.99 × 10³ Pa, 16.5 times higher than spherical particles with an 18.5 nm diameter. Supported by the Percus–Yevick (PY) theory, the numerical model achieves high accuracy in production history matching, with oil recovery and water cut fitting within precision error ranges of 0.02 and 0.05, respectively. This research advances chemical EOR technologies and offers an environmentally sustainable, efficient recovery strategy for low-permeability and heavy oil reservoirs, serving as a promising alternative to thermal methods.

Applying chemical enhanced oil recovery (EOR) to shale and tight formations is expected to accelerate China’s Shale Revolution as it did in conventional reservoirs. However, its screening and modeling are more complex. EOR operations are faced with choices of chemicals including traditional surfactant solutions, surfactant solutions in the form of micro-emulsions (nano-emulsions), and nano-fluids, which have similar effects to surfactant solutions. This study presents a systematic comparative analysis composed of laboratory screening and numerical modeling. It was conducted on three scales: tests of chemical morphology and properties, analysis of micro-oil-displacing performance, and simulation of macro-oil-increasing effect. The results showed that although all surfactant solutions had the effects of reducing interfacial tension, altering wettability, and enhancing imbibition, the nano-emulsion with the lowest hydrodynamic radius is the optimal selection. This is attributed to the fact that the properties of the nano-emulsion match well with the characteristics of these shale and tight reservoirs. The nano-emulsion is capable of integrating into the tight matrix, interacting with the oil and rock, and supplying the energy for oil to flow out. This study provides a comprehensive understanding of the role that surfactant solutions could play in the EOR of unconventional reservoirs.

Gel treatments have been widely applied to control water production in oil and gas reservoirs. However, for water shutoff in dense gas reservoirs, most gel-based treatments focus on individual wells rather than the entire reservoir, exhibiting limited treatment depth, poor durability, and inadequate repeatability Notably, formation damage is a primary consideration in treatment design—most dense gas reservoirs have a permeability of less than 1 mD, making them highly susceptible to damage by formation water, let alone viscous polymer gels. Constrained by well completion methods, gelant can only be bullheaded into deep gas wells in most scenarios. Due to the poor gas/water selective plugging capability of conventional gels, the injected gelant tends to enter both gas and water zones, simultaneously plugging fluid flow in both. Although several techniques have been developed to re-establish gas flow paths post-treatment, treating gas-producing zones remains risky when no effective barrier exists between water and gas strata. Additionally, most water/gas selective plugging materials lack sufficient thermal stability under high-temperature and high-salinity (HTHS) gas reservoir conditions, and their injectivity and field feasibility still require further optimization. To address these challenges, treatment design should be optimized using non-selective gel materials, shifting the focus from directly preventing formation water invasion into individual wells to mitigating or slowing water invasion across the entire gas reservoir. This approach can be achieved by placing large-volume gels along major water flow paths via fully watered-out wells located at structurally lower positions. Furthermore, the drainage capacity of these wells can be preserved by displacing the gel slug to the far-wellbore region, thereby dissipating water-driven energy. This study evaluates the viability of placing gels in fully watered-out wells at structurally lower positions in an edge-water drive gas reservoir to slow water invasion into structurally higher production wells interconnected via numerous microfractures and high-permeability streaks. The gel system primarily comprises polyethyleneimine (PEI), a terpolymer, and nanofibers. Key properties of the gel system are as follows: Static gelation time: 6 h; Elastic modulus of fully crosslinked gel: 8.6 Pa; Thermal stability: Stable in formation water at 130 °C for over 3 months; Injectivity: Easily placed in a 219 mD rock matrix with an injection pressure gradient of 0.8 MPa/m at an injection rate of 1 mL/min; and Plugging performance: Excellent sealing effect on microfractures, with a water breakthrough pressure gradient of 2.25 MPa/m in 0.1 mm fractures. During field implementation, cyclic gelant injections combined with over-displacement techniques were employed to push the gel slug deep into the reservoir while maintaining well drainage capacity. The total volumes of injected fluid and gelant were 2865 m³ and 1400 m³, respectively. Production data and tracer test results from adjacent wells confirmed that the water invasion rate was successfully reduced from 59 m/d to 35 m/d. The pilot test results validate that placing gels in fully watered-out wells at structurally lower positions is a viable strategy to protect the production of gas wells at structurally higher positions.

The interaction between clay minerals and electrolyte solutions critically affects waterflooding efficiency in enhanced oil recovery (EOR). This study systematically investigated the adsorption and thermodynamic properties of montmorillonite, illite, and kaolinite in different cationic solutions (K⁺, Na⁺, Ca²⁺, Mg²⁺), integrating adsorption isotherm analysis with immersion calorimetry for the first time. Montmorillonite showed the highest adsorption capacity, with the cation affinity following K⁺ > Na⁺ > Ca²⁺ > Mg²⁺. The highest immersion enthalpy was observed in KCl solution, indicating the dominant roles of ionic radius and solvation energy. Cation adsorption induced deformation of clay lamellae and modification of Si-O and Al-OH groups. These findings suggest that optimizing injected ion composition can enhance reservoir stability and waterflood performance, providing thermodynamic insights for EOR process optimization.

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