As an unconventional energy source, the development of shale oil plays a positive role in global energy, while shale oil is widespread in organic nanopores. Kerogen is the main organic matter component in shale and affects the flow behaviour in nanoscale-confined spaces. In this work, a molecular dynamic simulation was conducted to study the transport behaviour of shale oil within kerogen nanoslits. The segment fitting method was used to characterise the velocity and flow rate. The heterogeneous density distributions of shale oil and its different components were assessed, and the effects of different driving forces and temperatures on its flow behaviours were examined. Due to the scattering effect of the kerogen wall on high-speed fluid, the heavy components (asphaltene) increased in bulk phase regions, and the light components, such as methane, were concentrated in boundary layers. As the driving force increased, the velocity profile demonstrated plug flow in the bulk regions and a half-parabolic distribution in the boundary layers. Increasing the driving force facilitated the desorption of asphaltene on kerogen walls, but increasing the temperature had a negative impact on the flow velocity.

Underground hydrogen (H2) storage has become increasingly popular in recent years; however, H2 leakage is a critical concern. A conventional reservoir is sealed by a dense caprock; the long-chain hydrocarbons cannot escape through the caprock because of the complex molecular structure and large molecular size, but H2 leakage can still occur, particularly through the nanopores of the caprock. In this study, we investigate the H2 leakage problem using the molecular dynamics (MD) and MD–Monte Carlo (MDMC) methods. The results of our MDMC algorithm concur with the MD simulation results, indicating that the MDMC algorithm can feasibly predict the H2 leakage process. Caprock defects are repaired by water (H2O) clusters owing to the hydrogen bonding and adsorption of H2O on the caprock surface. Methane (CH4) forms an absorption layer on the caprock, inhibiting the probability of contact between H2 and the rock surface. We further explain the spatial distribution of different gas components using their potential energies and interaction forces. The molecular sealing mechanism is also proposed accordingly, and the H2O cluster and CH4 adsorption layer form the double barrier for H2 leakage. The evaporation of H2O at high temperatures weakens the stability of the H2O cluster, and smaller pore sizes (<10.0 Å) within the caprock prevent H2 leakage. H2 leakage can be further inhibited by increasing the H2O content in a H2 storage project. Thus, a specific amount of H2O and CH4 gas can alleviate the H2 leakage problem.

Over recent decades, studies in porous media have focused on many fields, typically in the development of oil and gas reservoirs. The imbibition phenomenon, a common mechanism affecting multi-phase flows in porous media, has shown more significant impacts on unconventional reservoir development, where the effect of the pore space increases with decreased pore sizes. In this paper, a comprehensive SPH method is applied, considering the binary interactions among the particles to study the imbibition phenomenon in porous media. The model is validated with physically meaningful results showing the effects of surface tension, contact angle, and pore structures. A heterogeneous porous medium is also constructed to study the effect of heterogeneity on the imbibition phenomenon; it can be referred from the results that the smaller pore throats and wetting surfaces are more preferred for the imbibition. The results show that the SPH method can be applied to solve the imbibition problems, but the unstable problem is still a sore point for the SPH method.

Membrane has been considered an effective tool for oil–water separation. By using the smoothed particle hydrodynamics (SPH) method, the effects of membrane structure on fluid separation were studied thoroughly in this paper. The oil–water two-phase fluid was generated as particles, while the membrane was built with solid particles, which was able to select the fluid particles. In general, the developed SPH method in this paper can evaluate separation performance with different membrane shapes, pore size distributions, membrane thickness and fluid properties. We suggest to the industry a potential approach to promote separation based on our simulation results, including adding the external force in the selected direction and demulsification for the bulk phase liquid particles. The triangular membrane performs well with the conditions for various parameters, as a result of its insensitivity to inhibiting factors. The effectiveness and robustness of the proposed SPH scheme was validated by a number of numerical experiments, and we assessed the optimized membrane structure and operation manners in order to improve separation efficiency and long-term safety.

Understanding the complex behavior of fractured rock systems is critical for applications in energy development, geological sequestration, and tunnel construction. Microscale fracture surface morphology influences flow and mechanical behaviors, while upscaling frameworks. Despite progress in hydro-mechanical and thermo-hydro-mechanical coupling models, two-way mechanical-chemical interactions remain underexplored. Discrete fracture networks offer a robust statistical framework for modeling subsurface fracture systems. Advances in machine learning have accelerated the simulation and optimization of fractured geothermal systems, addressing the computational limitations of high-fidelity models. These methods support multi-objective design, enhance life cycle assessments, and provide insights into optimal geothermal management strategies. Fractured rocks serve as preferential pathways for fluid flow and heat transport, significantly influencing permeability and mechanical stability. However, the inherent complexity of coupled thermo-hydromechanical-chemical processes in these systems presents major challenges. Nonlinear fracture mechanics, stress perturbations, and chemical interactions drive dynamic changes in fracture connectivity and permeability, further complicated by recursive feedback mechanisms. By integrating numerical tools, machine learning techniques, and advanced discrete fracture network models, the fractured rock system could be optimized and clearly analyzed. Document Type: Perspective Cited as: Jiang, C., Chen, G., Zhu, W., Liu, J. Numerical simulation and optimization design of complex underground fracture network. Advances in Geo-Energy Research, 2025, 16(1): 1-3. https://doi.org/10.46690/ager.2025.04.01