The transition to a low-carbon energy system and the emergence of a hydrogen economy have increased the need for large-scale, reliable subsurface storage of carbon dioxide, hydrogen, and natural gas. Selecting suitable storage sites requires balancing geological, technical, environmental, economic, and social criteria, while accounting for the distinct physical and chemical behaviors of each gas and the intended service. This paper adopts a unified, gas-aware framework to synthesize site-selection criteria and decision-support methods for subsurface gas storage across the principal geological options: deep saline aquifers, depleted hydrocarbon reservoirs, and salt caverns. The study examines decision-making approaches ranging from conventional multi-criteria decision-making and fuzzy extensions to Geographic Information System-based spatial analysis, reservoir simulation, and emerging machine-learning techniques for large-scale screening and uncertainty quantification and mitigation. Drawing on global case studies, it identifies methodological limitations, gas-specific knowledge gaps, and data challenges that constrain confident site selection, particularly for hydrogen storage in deep saline aquifers and depleted reservoirs, including reactivity and microbial consumption risks, purity and mixing constraints, and cushion-gas economics. Future directions emphasize the need for integrated, explainable, and adaptive decision frameworks tailored to gas-specific behaviors and storage contexts; expanded large-scale H₂ demonstrations in saline aquifers and depleted reservoirs; tighter coupling of monitoring, modeling, and decision tools throughout the project lifecycle; and regulatory frameworks that clarify long-term liability and strengthen public engagement and trust. Collectively, these insights provide a structured basis for developing robust and transparent decision pathways for strategic subsurface storage in support of energy-transition objectives.

Foam has wide applications in oil and gas resource development, environmental engineering, and chemical industries due to its favorable rheological properties and interfacial characteristics. However, foam stability is influenced by a complex interplay of external and intrinsic factors, including surfactant type, gas-to-liquid ratio, temperature, and pressure. The combined effects of these factors can significantly alter foam characteristics, with each influencing the other in ways that can either enhance or destabilize foam. This research investigates these factors in detail, exploring how they interact to impact foam stability and how their optimization can enhance foam performance for various applications. The study delves into the role of interfacial tension in foam stability, highlighting how surfactant properties, gas composition, and liquid characteristics contribute to foam formation and stability. The study also reviews advancements in foam technology, particularly in oil production, CO₂ storage, environmental pollution management, and the creation of novel materials, while examining strategies for boosting foam stability under extreme conditions. Findings indicate that the gas-to-liquid ratio, surfactant type, temperature, and pressure all play key roles in foam stability, and fine-tuning these parameters can lead to significant improvements in foam performance. In harsh environments, maintaining foam stability presents substantial challenges. This research further proposes methods to enhance foam stability. Foam technology demonstrates broad potential in fields like oil recovery and wastewater treatment, where optimized foam stability can improve both reservoir recovery and treatment efficiency. This review summarizes the latest advancements in foam stability research, providing valuable insights for the further development of foam technology.

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.

This study addresses the critical need for reliable tools to calculate the thermophysical properties of pure gaseous hydrogen across a wide range of temperatures and pressures. This work proposes accurate and user-friendly functions of temperature and pressure based on a meticulous analysis of an extensive dataset sourced from the open literature. These functions are designed to predict volumetric, transport, and derived properties. The dataset comprises 3,396 data points for density, 940 data points for viscosity, and 2,287 data points for thermal conductivity, covering an extensive temperature and pressure spectrum. For density, the data covers a temperature range from 97 to 873 K and pressures ranging from atmospheric to 1.983 GPa. Viscosity data span temperatures from 100 to 1,100 K and pressures from atmospheric to 217 MPa, while thermal conductivity data extend from 98 to 873 K, with pressures ranging from atmospheric to 99 MPa. The data have been meticulously curated to ensure reliability and representativeness. The proposed correlations exhibit exceptional accuracy, as evidenced by the Absolute Average Deviation results: 0.66% for density, 1.21% for viscosity, and 1.65% for thermal conductivity. To ensure the reliability, the correlations were validated against data from REFPROP 10. In addition to the absolute average deviations, maximum absolute deviations, Coefficients of Determination, and the Percentage of Accuracy-Precision are also included. The proposed correlations have been formulated and validated for a range of key parameters, including isothermal compressibility, volume expansion, fugacity coefficient, enthalpy, entropy, Helmholtz energy, Gibbs energy, adiabatic bulk modulus, speed of sound, as well as kinematic viscosity and thermal diffusivity.

Velocity fields in flow in permeable media are of great importance to many subsurface processes such as geologic storage of CO ${}_2$, oil and gas extraction, and geothermal systems. Steady-state flow is characterized by velocity fields that do not change significantly over time. The flow field transitions to a new steady state once it experiences a disturbance such as a change in flow rate or in pressure gradient. This transition is often assumed to be instantaneous, which justifies the expression of constitutive relations as functions of instantaneous phase saturations. This work examines the evolution of velocity fields in a surrogate quasi-2D permeable medium using a microfluidic device, a microscopy system, and a high-speed camera. Tracer particles are injected into the medium along with Deionized water. The evolution of the velocity field is examined by tracing these particles in the captured images using the standard high-density particle image velocimetry algorithm founded on cross-correlation. The results suggest that the transition between steady states for an incompressible fluid takes a finite and non-negligible amount of time that is independent of the magnitude of the change in pressure gradient. The existence of transient states and the nature of the response during these states are readily interpreted by the principle of least action where flow gradually establishes an optimal configuration such that energy dissipation is minimized. The findings provide evidence against the applicability of the assumption that flowing phases relax instantaneously to their steady states and, hence, against the accuracy of the classical multiphase extension of Darcy’s law.