The development of unconventional oil and gas resources is becoming increasingly challenging, with artificial intelligence (AI) emerging as a key technology driving technological advancement and industrial upgrading in this field. This paper systematically reviews the current applications and development trends of AI in unconventional oil and gas exploration and development, covering major research achievements in geological exploration; reservoir engineering; production forecasting; hydraulic fracturing; enhanced oil recovery; and health, safety, and environment management. This paper reviews how deep learning helps predict gas distribution and classify rock types. It also explains how machine learning improves reservoir simulation and history matching. Additionally, we discuss the use of LSTM and DNN models in production forecasting, showing how AI has progressed from early experiments to fully integrated solutions. However, challenges such as data quality, model generalization, and interpretability remain significant. Based on existing work, this paper proposes the following future research directions: establishing standardized data sharing and labeling systems; integrating domain knowledge with engineering mechanisms; and advancing interpretable modeling and transfer learning techniques. With next-generation intelligent systems, AI will further improve efficiency and sustainability in unconventional oil and gas development.

High molecular polymers have been widely studied and applied in the field of enhanced oil recovery (EOR). At present, the focus of research has been changed to the design of polymer networks with unique properties such as anti-temperature and anti-salinity, good injection and so on. Supramolecular polymers have high viscoelasticity as well as excellent temperature, salt resistance and injection properties. Can supramolecular polymers become another material choice for polymer flooding to enhance oil recovery? The present review aims to systematically introduce supramolecular polymers, including its design strategy, interactions and rheological properties, and address three main concerns: (1) Why choose supramolecular polymers? (2) How do we synthesize and characterize supramolecular polymers in the field of oilfield chemistry? (3) What has been the application progress of supramolecular polymers in improving oil recovery? The introduction of a supramolecular interaction system provides a new idea for polymer flooding and opens up a new research direction to improve oil recovery. Aiming at the “reversible dynamic” supramolecular polymers, the supramolecular polymers are compared with the conventional covalent macromolecular polymer networks, and the challenges and future research directions of supramolecular polymers in EOR are discussed. Finally, the author’s viewpoints and perspectives in this emerging field are discussed.

The research and application of CO₂ storage and enhanced oil recovery (EOR) have gradually emerged in China. However, the vast unconventional oil and gas resources are stored in reservoir pores ranging from several nanometers to several hundred micrometers in size. Additionally, CO₂ geological sequestration involves the migration of fluids in tight caprock and target layers, which directly alters the transport and phase behavior of reservoir fluids at different scales. Micro- and nanoscale fluidics technology, with their advantages of in situ visualization, high temperature and pressure resistance, and rapid response, have become a new technical approach to investigate gas–liquid interactions in confined domains and an effective supplement to traditional core displacement experiments. The research progress of micro–nano fluidics visualization technology in various aspects, such as CO₂ capture, utilization, and storage, is summarized in this paper, and the future development trends and research directions of micro–nano fluidics technology in the field of carbon capture, utilization, and storage (CCUS) are predicted.

Wettability, as a vital tool for analyzing and describing oil flow, plays a significant role in determining oil/water relative permeability, residual oil distribution, and on–site recovery efficiency. Although the contact angle method is widely used for measuring wetting behavior, it is susceptible to the effects of surface roughness, oil–water saturation, and the distribution of mixed wetting within the range of droplet sizes. Additionally, millimeter–scale droplets fail to accurately represent the wetting distribution and the influencing factors at the micro/nano–scale. Therefore, this study presents a comprehensive investigation of the microstructure and wettability of shale samples. The characterization of the samples was performed using scanning electron microscopy (SEM) and atomic force microscopy (AFM) techniques to gain insights into their microscopic features, surface properties, and wettability. Results demonstrate the following: (1) Quartz and clay minerals tended to exhibit rough surface topography, appearing as darker areas (DA) under scanning electron microscopy (SEM). It is worth noting that plagioclase minerals exhibited brighter areas (BA) under SEM. (2) An increase in the content of minerals such as quartz and clay minerals was observed to decrease the surface oil wetting behavior. In contrast, plagioclase feldspar exhibited an opposite trend. (3) Based on the adhesive forces of the samples towards oil or water, a wetting index, I, was established to evaluate the wettability of shale at a microscale. The dimensionless contact angle W, obtained by normalizing the contact angle measurement, also consistently indicated oil wetting behavior. (4) By comparing the differences between I and W, it was observed that surface roughness significantly affected the behavior of water droplets. The presence of roughness impeded the contact between the solid and liquid phases, thus influencing the accuracy of the wetting results. Organic matter also plays a significant role in influencing surface wettability, and its distribution within the shale samples can lead to localized variations in wettability.

Adhesion is an intrinsic property of rocks and liquids. Investigating the factors contributing to its formation and the mechanisms governing its action is crucial for elucidating the adhesion work between solids and liquids. The adhesion work, serving as a parameter that characterizes the energy changes during the solid–liquid contact process, is a vital tool for probing this phenomenon. However, conventional measurements of the adhesion work are significantly influenced by surface roughness and fail to differentiate local variations in the adhesion performance. This limitation obscures our understanding of the primary adsorption sites and mechanisms between solids and liquids, posing significant challenges to the study of rock surface properties. In this study, in conjunction with scanning electron microscopy and contact angle analyses, we elucidated for the first time the locations where voids form during the solid–liquid contact process, the lithological composition of rough areas, and their impact on the adhesion work between water/oil and the surfaces. Additionally, employing atomic force microscopy (AFM), we examined the variations in water/oil–solid adhesion work across different characteristic regions, thereby characterizing the overall hydrophilic/hydrophobic properties of the rock core. Specific conclusions are as follows: (1) A negative correlation exists between roughness and the contact angle adhesion work, with heterogeneity impeding liquid-rock contact; (2) By comparing the strength of water–solid/oil–solid adhesion work within localized areas, we delineated the adhesion work characteristics of samples and their primary generation sites, with oil–solid adhesion work in target blocks predominantly originating from quartz, clay minerals, and organic matter; (3) The influence of pore throat development on the overall adhesion work of samples was clarified, demonstrating that an increase in the proportion of internal rock pores enhances the surface oil–solid adhesion work; (4) A dimensionless wetting index I was established to mitigate the impact of roughness on the expression of adhesion work, exhibiting a strong correlation with traditional evaluation methods.