Machine learning potential insights into mechanical response and heat transfer in CO2 hydrate

Accurate prediction of the mechanical and thermal properties of CO2 hydrates is essential for their applications in carbon sequestration and refrigeration, yet remains challenging with empirical forcefields. In this work, a deep potential machine learning potential for CO2 hydrate, trained on density functional theory datasets, is for the first time developed to serve as a unified and accurate computational framework. The as-developed deep potential machine learning potential achieves near-density functional theory accuracy in energy, force, and virial stress predictions while enabling large-scale molecular dynamics simulations at significantly reduced computational cost. Uniaxial stress-strain analyses demonstrate that the model captures the tensile strength and progressive ductile-like failure behavior. Thermal conductivity prediction agrees closely with experimental measurements within 2% deviation, outperforming empirical forcefields. Vibrational dynamics and phonon analyses reveal that the deep potential machine learning potential more accurately describes the anharmonicity and phonon scattering, especially in high-frequency modes, yielding physically realistic thermal transport behavior. This work establishes deep potential machine learning potential as a robust tool for advancing CO2 hydrate-based technologies by providing a path for accurate and efficient multi-property prediction.Document Type: Original articleCited as: Xiong, K., Li, Y., Lin, Z., Luo, G., Wu, J. Machine learning potential insights into mechanical response and heat transfer in CO2 hydrate. Advances in Geo-Energy Research, 2025, 18(1): 38-50. https://doi.org/10.46690/ager.2025.10.0

Saturation-functions models in CO2-brine system: A comparative study

CO2 injections into deep saline aquifers create a multiphase flow system within the porous media. In this context, relative permeability and capillary pressure, as saturation functions, are key parameters that control flow dynamics, simulation accuracy, and operational decisions. Since various models have been proposed for the saturation functions, this study aims to assess the existing models and investigate which model performs best under different circumstances. To this end, we first gathered a comprehensive data set to evaluate the existing models. Following that, the nonlinear fitting of experimental data was used to obtain the parameters of each model. Finally, the root-mean-square error and correlation coefficients were used to assess the accuracy of the fit. Based on the results of capillary pressure analysis, the models can be classified into two main categories. The first category includes models with power-law behavior suitable for homogeneous formations (single curvature), such as Brooks-Corey, Li-Horne, Lambda, Thomeer, Leverett J-function, and modified J-function models. The second category includes Van Genuchten, Kosugi, Skelt-Harison, Johnson, and Jing-Van Wunnik, which can be applied to homogeneous and heterogeneous formations (capture more than one curvature). Regarding relative permeability, the L.E.T., Chierici, Van Genuchten, and Corey models exhibit comparable performance across all scenarios. Corey offers simplicity with minimal parameters, while Van Genuchten provides more adaptability for complex data sets with more physically based parameters.Document Type: Original articleCited as: Faramarzi, M., Tabatabaei, S. M., Sedaee, B., Attari, N., Panahi, S. A. Saturation-functions models in CO2-brine system: A comparative study. Capillarity, 2025, 14(2): 35-52. https://doi.org/10.46690/capi.2025.02.0

A multi-field coupling model for CO₂ enhanced shale gas recovery integrating chemical dissolution and mechanical weakening effects

CO₂ enhanced shale gas recovery technology can effectively promote gas production and achieve CO₂ storage. The coupling relationship among the thermo-hydro-mechanical fields within the reservoir exhibits dynamic evolution during CO₂ injection. Additionally, the geochemical interactions between shale and CO₂ cause mineral dissolution and mechanical weakening, significantly influencing the shale reservoir characteristics. However, the impact mechanism of this coupling effect on CO₂ enhanced shale gas recovery is still unclear. This study first establishes and validates a thermo-hydro-mechanical-chemical coupling model. Then, the impacts of CO₂ injection on the reservoir physical characteristics and gas recovery under different influencing factors are investigated. The findings indicate that the relative permeability of the matrix and fractures in shale demonstrates an initial rapid increase, followed by a gradual decline during CO₂ injection. This complex behavior is governed by the comprehensive impacts of effective stress evolution, competitive adsorption, chemical dissolution, and mechanical weakening. During the initial injection period, gas production and CO₂ storage increase rapidly as CO₂ injection pressure increases and injection temperature decreases, primarily governed by the effective stress and disso lution effect. During the middle and late injection periods, competitive adsorption-induced swelling and mechanical weakening effects are dominant, rendering the process highly sensitive to reservoir stress. At this stage, excessive injection pressure and excessively low temperatures accelerate permeability reduction. Consequently, when evaluating the efficacy of CO₂ enhanced shale gas recovery, it is essential to incorporate the coupling relationship between the chemical dissolution-mechanical weakening effect and thermo hydro-mechanical fields of shale reservoir.Document Type: Original articleCited as: Yang, K., Sun, Y., Zhou, J., Chen, Q., Deng, G., Li, D. A multi-field coupling model for CO₂ enhanced shale gas recovery integrating chemical dissolution and mechanical weakening effects. Advances in Geo-Energy Research, 2025, 18(2): 180-194. https://doi.org/10.46690/ager.2025.11.0

Digital rock physics and fluid flow in the context of the energy transition

On November 16, 2025, the editorial office of Advances in Geo-Energy Research (AGER) successfully held the 100th AGER Forum, jointly supported by several academic partners, and attended by more than 10,000 people online. With the theme focusing “Digital rock physics and fluid flow in the context of energy transition”, the event gathered renowned experts from UK, Belgium and China to discuss frontier progress in fluid flow, pore-scale simulation, and geo-energy storage research. The forum emphasized that digital rock physics and multiscale imaging technologies are becoming essential research tools in next-generation low-carbon energy systems. The AGER forum included expert lectures and interactive discussions, enhancing the influence of AGER within the global geo-energy f ield. The 100th Forum marks an important milestone in the development of the journal. In the future, the AGER Forum will continue serving as a platform for advancing science and technology in the field of geo-energy.Document Type: PerspectiveCited as: Blunt, M. J., Sun, S., Boone, M. A., Zhang, L., Cai, J. Digital rock physics and fluid flow in the context of the energy transition. Advances in Geo-Energy Research, 2025, 18(3): 299-302. https://doi.org/10.46690/ager.2025.12.1

Efficient optimization of coupled geothermal reservoir modeling and power plant off-design based on deep learning

The accurate evaluation of the electricity output of geothermal power plants requires effective coupling between the geothermal reservoir and power plant. Existing coupling models integrate numerical simulation models of the reservoir and power plant; however, they are computationally expensive for electricity prediction (forward modeling) and integrated reservoir-power plant optimization. Therefore, this study aimed to enhance the efficiency of the coupled reservoir-power plant model for forward modeling and optimization by replacing simulation forward models with deep-learning-based surrogate models. Two independent surrogate models of the reservoir and power plant were trained and assembled into one coupled forward model. Moreover, a multiobjective optimizer was integrated with the coupled forward model to optimize reservoir operations and power plant designs to achieve the highest electricity output or the best economic outcome. Surrogate models for the reservoir and power plant accurately predicted the geothermal production temperature and electricity output while approximately achieving speedups of 1.23×105  and 1.77×105 times over those of the corresponding simulation models, respectively. Furthermore, optimization using our surrogate-based coupled model was 1.31 × 106 times faster than that using the simulation-based coupled models. Optimization results revealed that low injection temperature, large well distance, and stable reservoir injection and production rates contributed to better power plant performance. High design geothermal temperature, mass flow rate, and ambient temperature favored electricity generation, particularly in power plants located in hot regions. Our work remarkably accelerates the feasibility assessment and decision-making procedures for geothermal reservoirs and power plants.Document Type: Original articleCited as: Liu, Z., Gudala, M., Yan, B. Efficient optimization of coupled geothermal reservoir modeling and power plant off-design based on deep learning. Advances in Geo-Energy Research, 2025, 18(1): 84-98. https://doi.org/10.46690/ager.2025.10.0

Recent progress of coal seam water injection technology for dust prevention: A comprehensive review

Coal seam water injection constitutes a fundamental measure for ensuring safe and efficient coal mine production, preventing pneumoconiosis hazards, and protecting the environment. However, systematic reviews integrating its dust reduction theories and technologies remain scarce. This paper reviews the foundational theories and technological advancements in coal seam water injection for dust control, revealing the regulatory mechanisms of dust reduction through coal’s seepage-wetting behavior from dual perspectives of the internal structural features of coal and the evolving stress-water pressure environment. Additionally, it evaluates the technologies for modifying coal’s physical properties and technologies for injected fluids modification. Finally, it identifies the challenges faced by coal seam water injection technology and proposes future research directions. Our review found that pore-fracture network connectivity governs water transport pathways, while dynamic equilibrium between interfacial tension and chemical group interactions determines wetting efficiency at the microscopic level. Macroscopically, hydro-mechanical coupling effects induce multi-stage fracture network evolution through stress redistribution, forming multi-level interconnected topological structures that significantly enhance wetting homogeneity. From a technological perspective, this study establishes a geology-adaptive technical framework based on coal seam characteristics and physicochemical parameter compatibility. The review promotes the transition of water injection technologies from experience-driven “extensive pressurization” to data-driven “precision wetting,” providing a theoretical foundation for developing safe, green, intelligent, and source-controlled dust reduction technologies.Document Type: Invited reviewCited as: Wang, H., Wang, H., Tan, J., Du, J., Zhou, W., Zhang, Y. Recent progress of coal seam water injection technology for dust prevention: A comprehensive review. Advances in Geo-Energy Research, 2025, 16(3): 181-198. https://doi.org/10.46690/ager.2025.06.0

On multi-block lattice Boltzmann method for high Knudsen number flows

This work introduces a new computational framework aimed at advancing the modeling of gas transport in confined porous media, particularly shale and tight geological formations that are characterized by their intricate network of meso- and micro-scale fractures and a broad distribution of organic pores. Accurate simulation of gas behavior in such media is challenging due to the complex interactions occurring at high Knudsen numbers, where conventional continuum-based methods fail and kinetic-theory approach becomes more suitable. To tackle these complexities, this work presents a lattice Boltzmann framework tailored for large computational domains with multi-scale pore structures from nano to micro scales. This framework incorporates slip boundary conditions and features an innovative multi-block approach to enable efficient simulations over a wide range of pore sizes, from nanometers to micrometers. The novel contributions of this work include: A scale-informed grid refinement strategy, the incorporation of shear stress terms, multi-block evolution algorithm, and a novel classification method for implementing specular reflection boundary conditions on irregular surfaces. Validation against Direct Simulation Monte Carlo and Molecular Dynamics data from the literature confirms the model’s accuracy in predicting gas behavior. Simulations of methane transport in tight porous media with irregular geometries highlight the framework’s effectiveness in modeling gas permeability across varying pressure conditions. Apparent permeability results across a range of Knudsen numbers demonstrate the versatility of this framework in capturing the physics of gas transport in confined porous media.Document Type: Original articleCited as: Rustamov, N., Mostaghimi, P., Aryana, S. A. On multi-block lattice Boltzmann method for high Knudsen number flows. Advances in Geo-Energy Research, 2025, 16(2): 143-157. https://doi.org/10.46690/ager.2025.05.0

Methane hydrate formation characteristics under different initial conditions and their impact on coal seam propertie

Due to the unique structural characteristics of hydrate, it has a potential application value in coal and gas outburst prevention in coal mines. Given the complexity of subsurface environments, it is essential to investigate the hydrate formation kinetics under varied initial conditions, as well as the subsequent impacts of hydrate formation on coal seam properties. This research mainly focuses on the hydrate formation process in coal samples with different coalification degrees under different initial pressure and water saturation conditions by using the designed hydrate formation system. The results show that gas consumption and hydrate saturation can be greatly enhanced by increasing the initial water saturation and pressure, which is favorable to reduce the coal seam gas pressure and improve the coal seam peak strength. The calculation results suggest that hydrate formation at varying saturation reduces the gas pressure by 53.05% ∼91.33% and increases the peak strength of coal across the tested confining pressure by 36.45% ∼ 59%. Furthermore, this study found that hydrate formation kinetics are significantly enhanced in lignite compared to that in anthracite, which may be attributed to structural variations associated with the coalification degree. The underlying mechanism requires further research in the future. The data obtained in this study regarding the effect of hydrate formation under different initial conditions on coal seam properties demonstrate the feasibility of preventing gas disasters in coal via controlling the initial conditions.Document Type: Original articleCited as: Sun, C., Liu, S., Li, S., Wang, K., Dong, Z., Kong, S. Methane hydrate formation characteristics under different initial conditions and their impact on coal seam properties. Advances in Geo-Energy Research, 2025, 16(3): 229-243. https://doi.org/10.46690/ager.2025.06.0

Experimental techniques for studying interfacial dynamics and sediment response during CH₄-CO₂ hydrate replacement

Methane hydrates are a largely untapped energy resource with the potential to support carbon sequestration through CH₄-CO₂ exchange. However, large-scale methane recovery from hydrate-bearing sediments remains constrained by key uncertainties related to sediment stability, multiphase fluid dynamics, and geomechanical responses during gas production. One of the key scientific challenges is to understand the transient interface dynamics and mechanical weakening of hydrate deposits during CH₄-CO₂ displacement, especially the unexplained effects of pore water meniscus surface evolution and its influence on sediment stability. This study reviews CH₄-CO₂ replacement methods, including microscale piezoelectric sensing, triaxial testing, and real-time resistivity monitoring. It quantifies displacement efficiency and hydrate dissociation geomechanics while analyzing interfacial dynamics and sediment behavior during exchange process.Document Type: PerspectiveCited as: Cao, S. C., Li, X., Jung, J., Li, X. Experimental techniques for studying interfacial dynamics and sediment response during CH₄-CO₂ hydrate replacement. Capillarity, 2025, 15(3): 53-57. https://doi.org/10.46690/capi.2025.06.0

Simulation and optimization of a coupled reservoir and multi-phase flow network model

This work considers a coupled system of the MATLAB Reservoir Simulation Toolbox, a multi-phase network simulator and topside processing facilities, with the intent to provide a research tool for studying integrated planning and optimization. To this end, a collection of open-source tools are presented that can be combined with MATLAB Reservoir Simulation Toolbox to model, evaluate and optimize the economy of integrated systems, including reservoir and network under different market (costs and revenue) scenarios. The tools are organized in four repositories containing code for cost/price scenario modelling, derivative-free trust region optimization, pipe/network simulation and reservoir-network coupling and examples. A brief background on each of these tools is given, followed by the presentation of a fully implicit approach for the reservoir-network coupling. Moreover, a description is given on how to set up coupled simulation models, and finally, a presentation of numerical examples, including an optimization example that utilizes the full set of above-mentioned tools.Document Type: Original articleCited as: Leinan, P. R., Ustad, T. S., Krogstad, S., Silva, T. L., Ortiz, M. M., Hellemo, L., Smith, I. E. Simulation and optimization of a coupled reservoir and multi-phase flow network model. Advances in Geo-Energy Research, 2025, 15(3): 203-215. https://doi.org/10.46690/ager.2025.03.0