Orals: Thu, 7 May, 10:45–12:30 | Room 0.51
Underground hydrogen storage (UHS) for energy supply-demand management is a relatively new topic compared to the natural gas storage. It is gaining increasing interests due to the ‘hope’ that hydrogen may indeed be the missing link of scalable low-carbon energy systems. Successful deployment of UHS depends on reliable performance analyses, which depend on rigorous understanding of the relevant cyclic processes at various scales. Beyond this, geophysical field and lab data sets, collected on different scales, need to be conveniently utilized and integrated in the dynamic simulations in order to construct the multiscale models and calibrate their many parameters. Furthermore, simulations are often performed on highly heterogeneous upscaled reservoir models which raise the question of how reliable our predictions for the uncertain systems can be.
To address this challenge, in this invited talk, a multiscale experimental-numerical framework for rapid site selection and performance analyses of UHS is presented. The framework addresses the thermo-chemical properties at molecular scale, trapping and transport mechanisms at micro-meter scale, and the system performance at continuum reservoir scale. The nonlinear, time-dependent mechanical response of the host rocks is also analysed, with the focus on model construction and parameter calibration, including field validation. Emphasizing the importance of reliable performance assessments under uncertainty, some key gaps in this evolving technology will be also addressed.
How to cite: Hajibeygi, H.: Building confidence in simulation of underground hydrogen storage: recent advancements and remaining gaps, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11087, https://doi.org/10.5194/egusphere-egu26-11087, 2026.
Achieving large-scale underground hydrogen storage and carbon-dioxide sequestration is central to the energy transition and climate-neutrality goals. Reliable prediction of multiphase flow in geological formations is essential for the design and safety of such systems and largely relies on accurate estimation of fluid-rock properties. However, conventional coreflooding approaches for determining permeability and relative permeability suffer from some significant drawbacks such as pressure measurement errors, end effects, gravity override and rock damage, and yield rate-dependent relative permeability curves that are not intrinsic to the rock–fluid system. Furthermore, small-scale sub-core heterogeneity should be considered in the property estimation studies and gravity-capillary driven flow should be a focal point, as it prevails in H2/CO2 storage far from wells or after injection and production has been terminated, leaving the fluids to migrate due to buoyancy and capillary forces.
We present a new buoyancy-based method for estimating three-dimensional permeability (k(x,y,z)) and intrinsic relative-permeability curves (kr) of core samples, without imposing external flow. The approach focuses on gas-water redistribution in a sealed vertical core due to gravity and capillary forces. The method inverts transient and equilibrium saturation fields obtained during the flow using imaging to recover both k(x,y,z) and kr. Synthetic tests on numerical simulations of H2-water flow are conducted and show that the permeability field is reconstructed with an error below 4% for almost all cases. Intrinsic kr curves are also accurately recovered using the new method, with some errors observed for highly nonlinear curves. Parametric analyses shows that the method is generally robust and accurate, providing insight on the unique gravity-capillary driven core-flow. The new approach has numerous advantages over conventional coreflooding and could establish a pathway for more reliable characterization of geological hydrogen and CO2 storage sites.
How to cite: Rabinovich, A. and Wei, Y.: Coreflooding without flooding: Buoyancy-based multiphase-flow core analysis for H2/CO2 storage sites, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2637, https://doi.org/10.5194/egusphere-egu26-2637, 2026.
Underground hydrogen storage (UHS) in depleted gas reservoirs is increasingly considered as a viable option for large-scale and seasonal energy storage. While such reservoirs benefit from existing infrastructure and extensive subsurface characterisation, uncertainties remain regarding hydrogen–rock–brine interactions and their potential impact on hydrogen retention and reservoir integrity. In particular, the presence of reactive mineral phases may lead to abiotic hydrogen consumption and spatially variable geochemical behaviour that is difficult to assess at the reservoir scale.
This study investigates hydrogen–rock–brine geochemical interactions in a mixed-mineralogy clastic reservoir from an onshore depleted gas field in the Adriatic Basin, Italy. The reservoir is a Pliocene turbiditic sandstone with good petrophysical properties and a heterogeneous mineralogical composition, including a substantial carbonate fraction. Static geochemical modelling was performed using PHREEQC to evaluate mineral stability and potential hydrogen consumption under representative reservoir conditions.
The modelling results indicate that silicate minerals are largely stable in the presence of hydrogen, whereas carbonate minerals (calcite and dolomite) dissolve under equilibrium conditions, suggesting that carbonate-rich intervals may represent zones of enhanced reactivity. To explore how these mineral-scale results may translate to the reservoir scale, reactive facies were defined based on total carbonate content and implemented within a 3D geostatistical reservoir model. This approach allows the spatial distribution of relative geochemical reactivity to be assessed across the field.
The results provide a first-order assessment of potential abiotic geochemical hydrogen loss and its spatial variability. The study highlights the importance of mineralogical heterogeneity when evaluating depleted gas reservoirs for hydrogen storage and demonstrates how geochemical modelling results can be incorporated into reservoir-scale frameworks.
How to cite: Dzulkefli, M., Maffeis, I., Marzano, F., Alcalde, J., and Iacopini, D.: Investigation of hydrogen-rock-brine geochemical reactions in depleted gas reservoir: A study from an Italian case. , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20286, https://doi.org/10.5194/egusphere-egu26-20286, 2026.
The shift from fossil fuels to renewable energy is essential for mitigating climate change and meeting the Paris Agreement goals. However, the inherent intermittency of solar and wind energy necessitates robust, large-scale storage solutions to balance supply and demand. Converting excess renewable energy into hydrogen for UHS in geological formations offers a high-capacity and long-duration storage option. Despite its potential, the introduction of hydrogen into the geological system presents uncertainties. One of these concerns is the long-term wellbore integrity, particularly at wellbore interfaces, which act as the primary barrier to fluid containment and leakage prevention.
This study investigates how hydrogen exposure and cyclic injection–production affect rock-cement bond integrity under simulated subsurface conditions. Experiments were performed on rock-cement composites prepared with Class G cement and two reservoir sandstone analogues representative of North Sea formations, with the rock-cement interface perpendicular to the plug cross section. Corsehill sandstone, clay rich ~50 mD, and Bentheimer sandstone, quartz rich ~600 mD. A subset of samples was exposed to hydrogen at 70 °C and 18 MPa for 50 days. To represent operational cyclicity relevant to UHS, samples were tested under triaxial loading and subjected to 5 and 20 pore pressure cycles. Nitrogen-exposed and unexposed sister plugs were used as controls to isolate hydrogen-specific effects. A comprehensive suite of measurements, including flow testing, fluid sampling, and acoustic velocity monitoring, was used to quantify interfacial degradation and assess the effects of cycling rate and cycle number. Following the experiments, several samples were analysed using micro-CT to characterise fracture patterns in the rock-cement interfacial transition zone.
Results show that permeability decreases during pore pressure cycling, with the largest reduction occurring during the first cycle, 30% for cement-Corsehill and 12% for cement-Bentheimer samples. Slower cycling rate result in a greater reduction in permeability over successive cycles. At higher cycle numbers, permeability increases at later stages, consistent with enhanced dissolution, as supported by the ICP results. In several samples, fractures observed within the cement and propagated parallel to the cement-rock interface, indicating that cement adjacent to the interface is the mechanically weakest zone, while the interface itself remains intact. These responses also controlled by the reservoir rock properties, and the higher permeability samples show stronger bond integrity.
These findings demonstrate that operational cycling conditions and site-specific geological properties are key controls on wellbore integrity, with direct implications for the safe and long-term deployment of UHS.
How to cite: Abedi, S., Soustelle, V., Saricam, I., Ataei Fath Abad, S., Hassanpouryouzband, A., and Edlmann, K.: Cement-Rock Bond Integrity under Injection-Production Cycling in Underground Hydrogen Storage (UHS), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8423, https://doi.org/10.5194/egusphere-egu26-8423, 2026.
Underground hydrogen storage (UHS) is expected to play a key role in the emerging hydrogen economy by providing large-scale storage capacity with lower leakage risk than above-ground alternatives. While geological storage has been extensively studied for natural gas (CH4) and carbon dioxide (CO2), the physical behaviour of hydrogen (H2) in the subsurface remains less understood. Owing to its lower density and viscosity and higher diffusivity, H2 is expected to induce different coupled hydro-mechanical (HM) responses than these well-studied fluids, with potential implications for fault stability and risks of induced seismicity. This study employs a with linear elasticity and strain-dependent permeability to simulate hydrogen injection in a fractured carbonate reservoir, using the Hontomin CO2 storage pilot site (Spain) as a geological analogue. The reservoir and caprock are represented as homogeneous continua, while major faults are modelled explicitly with varying permeability, controlling pressure diffusion and compartmentalisation. Two contrasting fault systems are considered: one critically stressed and highly sensitive to stress perturbations, and one initially more stable. The associated potential for induced seismicity is first assessed using mobilized friction to evaluate fault stability under evolving stress and pore-pressure conditions. The model is then integrated with a rate-and-state friction model framework to quantify stress-driven changes in terms of seismicity rates. The results show that pore-pressure redistribution, reservoir geometry and frictional properties are key controls on both co-injection and post-injection seismicity. Distant faults may reactivate after injection shut-in due to delayed pore-pressure diffusion and poroelastic stress. Seismicity is more likely to occur on faults with large offsets and low permeability, where pore pressure dissipation is limited. The seismic response is strongly governed by the initial proximity of faults to failure rather than injection behaviour alone. These findings highlight the necessity of detailed site-specific geological and geomechanical characterisation for assessing UHS feasibility and mitigating seismic risk. Ongoing work extends the modelling approach towards seismic waveform simulations to assess the detectability of H2 plume evolution and migration.
How to cite: Peter, R., Boyet, A., Pacios, P., Vilarrasa, V., and Alcalde, J.: Potential for fault reactivation during Underground Hydrogen Storage., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18385, https://doi.org/10.5194/egusphere-egu26-18385, 2026.
Salt domes represent one of the most robust geological media for subsurface energy storage, including hydrogen, due to the low permeability, ductile behavior, and self-sealing properties of halite, as well as the extensive legacy infrastructure present along the U.S. Gulf Coast. Regional assessments of energy storage potential in salt basins have demonstrated large aggregate capacity, but these studies commonly rely on simplified geometric representations of salt bodies, most often treating domes as vertically uniform cylinders with minimal internal or external complexity. Such assumptions obscure the influence of salt dome morphology on both workable salt volume and cavern engineering feasibility, and can lead to over- or under-estimation of storage potential at the individual dome scale.
This study advances volumetric assessment methods by explicitly incorporating salt dome geometry and structural complexity into storage evaluations. Using a suite of modeled endmember geometries modify total salt volume, the distribution of salt within depth intervals suitable for cavern development, and the resulting cumulative cavern storage potential. These models are applied to selected salt domes from the East Texas Salt Basin, a region with a long history of salt tectonics research and subsurface storage applications. Results demonstrate that geometric features that promote overhang within the workable depth window, including positive conic taper and primary axis tilt, systematically increase usable salt volume and enable more efficient cavern placement. In contrast, domes characterized by strong ellipticity or negative taper experience disproportionate losses in workable salt, despite large total salt volumes.
In addition to external geometry, we integrate observations of caprock deformation from onshore Gulf Coast domes as indirect evidence for macro-scale intra-salt heterogeneity, including the possible presence of shear zones or salt spines. These features are not typically resolved in regional datasets but may influence solution-mining behavior and long-term cavern performance. By considering both morphological controls and structural indicators, this work provides a more realistic framework for estimating storage capacity and engineering constraints.
Overall, the results highlight the importance of transitioning from basin-scale screening to prospect-scale evaluation when assessing energy storage in salt domes. Incorporating dome-specific geometry and structural context reduces uncertainty in volumetric estimates, improves down-selection of candidate sites, and supports safer and more efficient cavern design. This approach is directly applicable to emerging hydrogen storage projects, as well as to conventional energy resources that include liquid hydrocarbons and natural gas. This study contributes to the development of scalable subsurface energy storage systems that support long-term decarbonization efforts, as well as energy security in general.
How to cite: Schuba, C. N. and Moscardelli, L.: Salt Dome Geometry, Caprock Deformation, and Implications for Subsurface Energy Storage, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7750, https://doi.org/10.5194/egusphere-egu26-7750, 2026.
The use of geological reservoirs in support of a sustainable energy system has been explored for decades. Geological carbon storage (GCS), underground gas storage (UGS), and underground hydrogen storage (UHS) are prominent examples of such applications. Among the available geological settings, saline aquifers represent a feasible large-scale option for subsurface storage.
To reliably assess reservoir performance and conduct sensitivity analyses, physics-based simulation toolboxes with accurate thermophysical and petrophysical descriptions (density, viscosity, solubility, relative permeability, etc) are essential, in addition to field and laboratory studies. DARSim (Delft Advanced Reservoir Simulator) is an open-source, MATLAB-based simulator capable of fully compositional flow modeling. Combined with the algebraic dynamic multilevel (ADM), it provides an effective framework for multiscale reservoir simulations.
This work begins with a comparative analysis of CO2, CH4, and H2 flow in brine-saturated porous media to examine how differences in gas properties influence reservoir-scale flow behavior, and trapping mechanisms. The study first reproduces the FluidFlower benchmark, a numerical–experimental study originally developed for CO2, for all three gases. Subsequently, an upscaled version of the benchmark is investigated to evaluate model performance using a multiscale strategy. The adaptive multilevel method (ADM) efficiently captures key subsurface processes, including buoyancy-driven migration and phase partitioning. By dynamically refining regions with strong gas mass fraction gradients and coarsening smoother areas, ADM balances computational efficiency with the accuracy required to represent essential flow and transport behavior in heterogeneous reservoirs.
How to cite: Misaghi Bonabi, A., Haagenson, R., Vuik, K., and Hajibeygi, H.: Comparative analysis of carbon dioxide, methane, and hydrogen plume migration in aquifers, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17382, https://doi.org/10.5194/egusphere-egu26-17382, 2026.
Reliable monitoring of subsurface CO₂ plumes is essential for ensuring the safety, efficiency, and regulatory compliance of carbon capture and storage (CCS) operations. While time-lapse seismic monitoring and numerical simulations are widely used, both approaches face limitations related to cost and uncertainty. Laboratory-scale experiments provide a valuable complementary pathway by enabling controlled, repeatable studies with real-world physics. Here, we present a new open-access laboratory facility designed to investigate seismic monitoring strategies for CO₂ storage using three-dimensional ultrasonic imaging.
The facility consists of a 1:2000 downscaled physical replica of the upper caprock of the Utsira Formation at the Sleipner CO₂ storage site, submerged in water and monitored by a dense array of ultrasonic transducers. A total of 128 high-frequency (1 MHz) and low-frequency (0.15 MHz) piezoelectric transducers are configured to act as both sources and receivers, enabling highly flexible acquisition geometries. Using air as a safe laboratory proxy for CO₂, controlled injection experiments were conducted to emulate plume migration beneath the caprock. Continuous scanning of the transducer array allows the acquisition of large 3D time-lapse (“4D”) datasets within minutes.
The resulting data demonstrates clear detection of gas accumulation and migration pathways beneath the model caprock, as well as successful imaging of the aquifer topography. Time-lapse amplitude changes correlate well with independently observed plume evolution, particularly when using the low-frequency, wide-beam transducers, which provide improved illumination of complex topography.
We further investigated the impact of data sparsity by systematically decimating the ultrasonic dataset. Both systematic and random receiver reductions were tested to emulate sparse and irregular monitoring geometries. Because the true plume extent is known from direct visual observations, the quality of the resulting seismic monitoring could be quantitatively evaluated as a function of sampling density and decimation strategy. The results demonstrate clear differences in detection performance between the two sparsity patterns. These findings provide important insights for the design of cost-efficient and reliable seismic monitoring programs for CO₂ storage.
The facility provides a versatile and scalable platform for testing seismic imaging techniques, acquisition strategies, and processing workflows under controlled conditions. Future developments will include an enhanced acquisition setup, for even higher flexibility, repeatability and quality, opening up new avenues of research with advanced processing techniques.
How to cite: Hunnestad, K., Landrø, M., and Ringrose, P.: Laboratory-Scale 4D Seismic Monitoring of CO₂ Storage Under Sparse Acquisition, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11074, https://doi.org/10.5194/egusphere-egu26-11074, 2026.
Giant saline aquifers (defined here as aquifers that cover areas larger than 10.000 km²) are promising candidates to scale up geological CO2 storage. However, they present significant simulation challenges due to their vast extent, heterogeneity, and limited subsurface data. This study introduces a reliable multiscale modeling framework which is designed for these fields. The method is also applied to assess CO2 storage in the Ponta Aguda saline aquifer (Santos Basin, Brazil, 40000 km2 area) to demonstrate its applicability in real field environments.
Our multiscale strategy is formulated such that it delivers reliable quantification of the trapped and mobile mass of CO2, i.e., the plume migration under complex hysteretic transport physics. Of particular interest is to preserve reliable quantification of the plume dynamics from near wellbore region (in the order of 10m horizontal resolution) all the way to the far field zones (with 1000m horizontal resolution).
Consistency checks are applied to make sure that the results from different scales are representative of the same realization and storage conditions. Our novel multiscale strategy benefits from the local saturation and global pressure physics. More precisely, the best global pressure representation is provided on the largest scale and therefore is used to provide local boundary conditions (using methods such as Fetkovich model) to the higher resolutions (smaller sub-domains). On the other hand, saturation distribution is first resolved from the smallest sub-domains (highest resolution) and upscaled to the large-scale domains. Through these analyses, it is found that classical upscaling approaches systematically overestimate the trapped amount of CO2 on coarser models. This motivates the development of advanced reliable multiscale strategies which are efficient but also accurate while the system is being represented on coarser-resolution grids.
We present three different methods and compare them based on their accuracy of trapped amount of CO2 in the field-scale model. These are namely: Local Grid Refinement (LGR), Effective Values (EV), and Algebraic Dynamic Multilevel (ADM). The results indicate that ADM is the most stable and robust approach among all the approaches considered for real-field applications. Especially, LGR and EV are found limited in their scopes since they depend on a matching procedure (against a reference solution) for their upscaled parameters, before any new simulations. As a result, their tuned parameters cannot be transferred from one model to another. ADM, on the other hand, does not require any upscaling procedure, as the multiscale basis functions allow for consistent mapping across resolutions. The results show the importance of scale-consistent modeling approaches for accurate CO2 storage assessment and highlight the risks of relying on overly simplified coarse models in the design and optimization of carbon storage projects in giant saline aquifers.
How to cite: Kreutz Erdtmann, M., Lira, F., Geiger, S., and Hajibeygi, H.: Accurate and efficient multiscale simulation of CO2 storage in Giant Saline Aquifers, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13358, https://doi.org/10.5194/egusphere-egu26-13358, 2026.
Posters on site: Thu, 7 May, 16:15–18:00 | Hall X4
Underground hydrogen storage in salt caverns is a promising option for large-scale energy storage; however, its long-term integrity is governed by the time-dependent creep deformation of rock salt. While dislocation creep is commonly assumed to dominate cavern-scale behavior, increasing experimental evidence indicates that pressure solution creep can play a critical role under low-stress and low-temperature conditions. Nevertheless, its contribution at the field scale and under realistic operational scenarios remains insufficiently quantified. This study presents a three-dimensional numerical investigation of pressure solution creep and its impact on the mechanical behavior of salt caverns used for underground hydrogen storage. A three-dimensional modeling framework incorporating elastic deformation, dislocation creep, and pressure solution creep is implemented in the open-source finite-element simulator SafeInCave using Python. The constitutive model is calibrated against laboratory creep data from the literature over a wide range of stresses and temperatures, ensuring accurate reproduction of both linear (diffusion-controlled) and non-linear (dislocation-controlled) creep regimes. A comprehensive set of numerical experiments is conducted, covering caverns with regular and irregular geometries, varying depths, temperature conditions, and interlayer configurations, under both constant and cyclic gas pressure loading. The results reveal a clear spatial and temporal partitioning of deformation mechanisms. Dislocation creep dominates near cavern walls and in deeper, warmer formations, where deviatoric stresses and temperatures are high. In contrast, pressure solution creep becomes increasingly significant over time in shallow and colder formations, particularly in regions away from the cavern wall where von Mises stresses are low. Neglecting pressure solution creep leads to a systematic underestimation of long-term displacement and cavern convergence, especially under cyclic loading conditions relevant to hydrogen injection and withdrawal. Overall, the study demonstrates that pressure solution creep can govern long-term deformation in shallow or low-temperature salt formations and strongly influences stress redistribution and cavern convergence. Consequently, the explicit inclusion of pressure solution creep is essential for the reliable prediction of cavern performance, integrity assessment, and the safe design of underground hydrogen storage operations.
How to cite: Amini, M. S., T. Honório, H., Vuik, C., and Hajibeygi, H.: Impact of pressure solution creep on the performance of salt caverns for underground hydrogen storage, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2989, https://doi.org/10.5194/egusphere-egu26-2989, 2026.
Hydrogen plays a major role as a low-carbon energy solution for global energy transition, but its low volumetric energy density makes underground hydrogen storage (UHS) in geological formations the only viable solution for meeting large-scale demand. Passive continental margins host thick Cenozoic successions and are located adjacent to many coastal demand centres, yet their UHS potential is hard to assess where subsurface data are limited. Here, using an open-source landscape evolution code, pyBadlands, we examine how Cenozoic sea-level changes influence passive-margin stratigraphic architecture, focusing on the greenhouse–icehouse transition at around 34 million years ago. Our models of the Hunter margin offshore New South Wales (Australia), an area transitioning from fossil fuel dependence to renewable energy, reveal two main depositional styles. Greenhouse intervals dominated by longer sea-level cycles favour the development of thicker (up to 50 m), laterally progradational packages, aligning with high-capacity reservoirs. In contrast, icehouse intervals marked by higher-frequency oscillations generate more vertically stacked, thinner stratigraphic units, which are more suitable for composite multi-layer sealing systems. The Eocene–Oligocene transition emerges as a potential key boundary separating these different depositional regimes. These contrasting architectures indicate that passive margin successions hosting both greenhouse thick reservoir packages and overlying icehouse multi-layer seal intervals can represent highly prospective configurations for UHS, thus providing storage capacity and containment integrity. However, favourable reservoir–seal architecture alone does not ensure UHS feasibility due to hydrogen’s high mobility, which can lead to vertical migration and leakage. Therefore, we applied a vertical mobility model to a representative offshore exploration well in the same region. Our results reveal a pronounced contrast in vertical velocity between potential reservoir and seal units, with the most favourable configurations observed in the deepest Cenozoic intervals: thick sandstone packages display high hydrogen mobility (~68 m/day), supporting high injection rates, whereas the immediately overlying laminated shale interval exhibits reduced vertical velocity (~0.02 m/day), ensuring effective containment capacity. These results demonstrate how paleoclimate-driven stratigraphic variability controls the distribution and performance of candidate hydrogen storage sites. By combining landscape evolution modelling with vertical mobility analysis, this work offers a predictive framework for assessing subsurface storage potential in data-limited passive margin settings, ultimately supporting more informed site selection and enhanced risk characterisation for UHS deployment along passive margins.
How to cite: Cherene, R., Zahirovic, S., Salles, T., McManus, P., Ding, X., Bradshaw, M., and H Stephenson, M.: From Paleoclimate to Energy Storage: Predictive Stratigraphic and Mobility Modelling and Implications for Underground Hydrogen Storage, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5903, https://doi.org/10.5194/egusphere-egu26-5903, 2026.
During injection and production for oil and gas geological storage, the cement sheath is frequently subjected to high-magnitude, high-frequency cyclic compressive loads. These cyclic loads can induce progressive, irreversible damage in the cement sheath in the form of brittle microcracking and plastic deformation, while the casing and surrounding formation typically exhibit predominantly elastic recovery during the unloading phase. However, existing fatigue life prediction models often fail to capture the dynamic stress-strain constitutive behavior of cement sheath under cyclic loading. In this study, intelligent inversion methods (i.e. Artificial Neural Networks) were employed to directly capture highly nonlinear and complex correlations among variables from measured experimental data, offering greater flexibility and adaptability in deriving material constitutive models. Five constitutive prediction models for the complex hysteresis loops of hardened oil-well cement slurries under cyclic loading are developed using deep learning (DL) statistical theory and physics-informed constraint methods. Firstly, to effectively describe the nonlinear morphological evolution of the hysteresis loops in cyclic curves, the experimental dataset is subdivided into 416 sub-datasets according to different cycle periods. Three different hybrid DL architectures—LSTM, CNN-LSTM, and TCN-LSTM—are constructed, and their learning accuracy and effectiveness are evaluated. Then, combined with physics-informed (physics-constrained) supervised approaches, ablation studies are conducted to compare and assess the use of a single-step prediction model with physics-based constraints. Finally, the optimal model is extended to the full-process prediction of the entire cyclic loading paths. The research approach presented in this paper differs from previous methods that input the entire cyclic curve data into an ANN model all at once. Instead, it establishes a novel methodology characterized by single-step rolling learning, enhanced accuracy through physics-informed constraints, and continuous full-process prediction, demonstrating excellent predictive performance (R² > 0.98).
How to cite: Yang, H., He, Z., Yang, Y., and Guo, W.: A Cyclic Constitutive Model for Oil-Well Cement Slurries Based on Hybrid Deep Learning Architectures and Physics-Informed Constraints, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6281, https://doi.org/10.5194/egusphere-egu26-6281, 2026.
Geological CO2 storage is a key component of climate mitigation strategies, yet its large-scale deployment is hampered by the risks of rock failure and fault reactivation, which may compromise storage integrity. Mitigating these risks requires robust assessment of injection-induced pressure buildup and associated geomechanical risks, particularly in heterogeneous reservoirs and under uncertain geological and operational conditions.
In this work, we propose a fast software tool to estimate the amount of CO2 that can be safely stored without jeopardizing fault stability, using physics-based analytical pressure solutions coupled with geomechanical failure criteria. Pressure buildup is evaluated across a range of injection scenarios and well configurations, allowing assessment of how well spacing, injection rate, and reservoir properties influence regional pressure propagation. Emphasis is placed on computationally efficient approaches that are suitable for screening studies at regional scale.
To account for subsurface uncertainty, a Monte Carlo framework is applied to quantify variability in stress state, fault orientation, and mechanical properties, and to derive critical pressure thresholds and fault-specific probabilities of failure. This probabilistic perspective supports risk-informed evaluation of pressure-constrained storage capacity and highlights parameters that most strongly control fault reactivation potential.
The tool provides scalable decision-oriented workflows for CO2 storage by combining pressure and geomechanical analysis with practical design considerations. It helps define safe injection strategies, assess reservoir geometry and boundary effects, and guide early-stage decision making, site screening, and operational planning, reducing geomechanical risks as projects move toward regional-scale deployment.
How to cite: Sheikhansari, R. and De Simone, S.: Probabilistic Assessment of Pressure-Constrained Regional Potential for Geological Carbon Storage, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6708, https://doi.org/10.5194/egusphere-egu26-6708, 2026.
UHS represents viable option for enabling large-scale and long-term energy storage in Net Zero energy systems. However, UHS involves several uncertainties, particularly from a geomechanical perspective. To ensure safe operation in porous reservoirs, storage integrity must be maintained under cyclic injection and production. This study investigates the effects of hydrogen exposure and pore pressure cycling on the geomechanical and flow properties of two sandstones: Bentheimer sandstone, which is 99% quartz, and Corsehill sandstone, which is clay rich. Core plugs were exposed to hydrogen at 70 °C and 18 MPa for 50 days, while nitrogen-exposed and unexposed samples were used as controls to isolate hydrogen-specific effects. Triaxial and flow tests were conducted before and after each pore pressure cycle under in-situ stresses and temperatures representative of North Sea reservoir conditions.
Results show a reduction in stiffness, measured as Young’s modulus, of about 6% in Corsehill sandstone after five pore pressure cycles, whereas Bentheimer sandstone showed no significant change. The reduction in Young’s modulus was slightly higher in hydrogen exposed Corsehill samples compared to nitrogen exposed and unexposed control samples. This difference may reflect sample variability, as Corsehill sandstone exhibits a degree of heterogeneity. The reduction in Young’s modulus of Corsehill sandstone may result from several factors, including fracture development, grain grinding, and mineral dissolution facilitated by deionized water. Clay-focused XRD analysis confirmed the absence of swelling clay minerals in Corsehill sandstone. Batch geochemical and core flood experiments revealed mineral dissolution, which likely contributed to the observed mechanical degradation. The finer and more angular grains of Corsehill sandstone increase the reactive surface area in contact with deionized water, enhancing dissolution under cyclic effective stress. Flow tests showed negligible changes in permeability for both sandstones after pore pressure cycling, indicating that the observed mechanical changes did not significantly affect flow properties. This implies that permeability trends alone are not sufficient to assess integrity during cyclic operation, and that rock-specific mechanical criteria are required.
How to cite: Saricam, I. H., Soustelle, V., Abedi, S., Ataei Fath Abad, S., Hassanpouryouzband, A., and Edlmann, K.: Comparative Geomechanical and Flow Behaviour of Bentheimer and Corsehill Sandstones Under Underground Hydrogen Storage (UHS) Conditions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7625, https://doi.org/10.5194/egusphere-egu26-7625, 2026.
The accelerating rise in global temperature and the growing risk of crossing critical climate thresholds have transformed gigatonne-scale geological CO2 storage from a long-term mitigation option to an immediate necessity. Robust assessment of formation injectivity is central to storage site screening and project design, as it directly constrains injection pressure management, achievable injection rates, and the scalability and security of long-term storage. However, existing injectivity evaluation approaches often face a fundamental trade-off between physical fidelity and computational efficiency, limiting their applicability to large-scale, multi-site deployment. Here, we present a physics-informed, machine learning-based framework for the precise quantification of geological CO2 injectivity. A three-dimensional two-phase multicomponent numerical model was developed to explicitly simulate CO2 injection, plume migration, and in-situ phase behavior in deep saline aquifers. Based on this model, 200 high-fidelity simulations were conducted by systematically varying key geological parameters, including formation area, thickness, porosity, permeability, heterogeneity, pressure, and temperature. The resulting dataset was employed to train an artificial neural network (ANN) surrogate model with Bayesian hyperparameter optimization, enabling rapid prediction of injectivity while preserving the governing trapping mechanisms. Feature importance was quantified using Shapley values derived from cooperative game theory, allowing each geological parameter to be assigned a contribution-based weight within the injectivity evaluation system. The results indicate that permeability, reservoir thickness, and heterogeneity exert dominant controls on injectivity, with normalized weights of 0.444, 0.269, and 0.108, respectively. In contrast, porosity, formation pressure, area, and temperature show comparatively weaker influences, with weights of 0.062, 0.048, 0.036, and 0.033. A weighted scoring framework was subsequently constructed to classify formation injectivity into four levels ranging from poor to good. The proposed methodology was applied to three representative CO2 storage candidates (Site A, B and C) in the Ordos Basin, China. For the site classified as having good injectivity (Site A), the ANN-based surrogate predicts a minimum injectivity index of 95,671 t·yr-1·MPa-1, corresponding to a maximum sustainable injection rate of 589,333 t·yr-1. By integrating physics-based modeling, explainable machine learning, and site-scale decision metrics, this study provides a scalable framework for screening and designing gigatonne-scale geological CO2 storage projects. Beyond CO2 sequestration, the methodology is readily transferable to other subsurface fluid and energy storage systems - such as underground hydrogen storage, nuclear waste disposal and compressed air energy storage - where injectivity and formation performance are critical to operational feasibility and long-term safety.
How to cite: Pan, Z., Li, X., Ren, C., and Zhang, K.: Machine learning-powered precise quantification of geological CO2 injectivity, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8512, https://doi.org/10.5194/egusphere-egu26-8512, 2026.
Carbon capture and storage (CCS) projects raise fundamental questions beyond technical performance, including how injected CO₂ behaves in the subsurface over long-time scales, how reliable model predictions are, and how experimental observations and simulations can be meaningfully combined. Addressing these questions requires not only process-based physical understanding, but also transparent modeling workflows, experimental validation, and effective collaboration across disciplines and institutions.
In this contribution, we use the ongoing CO₂ Long-term Periodic Injection Experiment (CL-Experiment) at the Mont Terri Rock Laboratory in Switzerland as a central case study to illustrate how such integrated understanding can be developed. The core of the work is a numerical benchmark modeling study of CO₂ injection into the Opalinus Clay formation, using a two-dimensional axisymmetric representation of the injection system to investigate hydraulic propagation and coupled geochemical processes over a 20-year period. The simulations assume a fully water-saturated domain and single-phase injection at 3 MPa, using artificial porewater containing dissolved CO₂ corresponding to a partial pressure of 2 MPa. As part of a benchmark study, international teams use different numerical codes. Evaluation of the results enables a transparent assessment of model assumptions, sensitivities, and limitations, as well as model verification.
To gain insights into CO₂–water–rock interactions, laboratory experiments were conducted using crushed Opalinus Clay from the in-situ sandy facies field site in an open system under controlled CO₂ conditions. Differences and consistencies between laboratory observations and numerical simulations are explicitly examined, highlighting key parameters and controlling processes that influence both model behavior and experimental responses.
This study integrates numerical benchmarking, laboratory experiments, and interdisciplinary collaboration as a learning process to improve understanding of CO₂ storage in clay formations. Continuum-scale modeling shows that the CO₂ plume remains confined within approximately 1 m of the injection zone over 20 years (based on a cutoff concentration of 10 mmol/L), while CO₂-induced carbonate dissolution causes localized porosity increases within about 5 cm of the injection zone. At the laboratory scale, modeling indicates that carbonate reactions are the dominant factor on the pH evolution. However, strong spatial mineralogical heterogeneity observed in the in-situ samples limits the applicability of homogeneous batch-scale representations. For the international benchmark exercise, effective coordination relied on a hierarchical benchmarking strategy in which model complexity was increased stepwise by progressively introducing key variables and parameters. Together, the results of this study demonstrate the strength of coordinated benchmarking initiatives, and continuous exchange across disciplines, tools, and teams.
How to cite: Chen, S., Corvisier, J., Ma, J., Ziefle, G., Ostertag-Henning, C., Kumar, V., Koç, Ü., Blanco Martin, L., and Massmann, J.: CO₂ Injection in Opalinus Clay at the Mont Terri CL-Experiment: Insights from Laboratory Experiments and Hydraulic-Geochemical Coupled Modeling , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9014, https://doi.org/10.5194/egusphere-egu26-9014, 2026.
Subsurface microbial communities constitute a major part of the global biosphere and they play a crucial role in the cycling of several gases related to Underground Hydrogen Storage (UHS), such as carbon dioxide, methane, hydrogen sulfide and, certainly, hydrogen (Beaver & Neufeld, 2024; Cascone et al., 2025; Kieft, 2016; Magnabosco et al., 2018; McMahon & Parnell, 2014). The key reactions in these processes involve the transfer of electrons between chemical species, i.e. the coupling the oxidation of electron donors to the reduction of electron acceptors, and are catalysed by a specialized subgroup of enzymes: oxidoreductases (Hay Mele et al., 2023). Organisms can then capture the free Gibbs energy released in these reactions and use it to sustain themselves (Lane & Martin, 2012). By elucidating which oxidoreductases a given microbial species or community contains, we can infer the potential for these reactions to occur in the environment of interest. Despite recent efforts, there are few comprehensive and comparative studies targeting the presence of oxidoreductases in the subsurface and their implications for UHS, which is critical to understand the risks these operations may face (Dopffel et al., 2021; Escudero & Amils, 2023; Ranchou-Peyruse, 2024; Templeton & Caro, 2023; Thaysen et al., 2023). In this work, we expand on a previous bioinformatics pipeline to predict the presence of oxidoreductases employing publicly available datasets of subsurface microbial communities as a case study with relevance to UHS (Climent Gargallo et al., 2025). Preliminary results point to potential sinks for the stored hydrogen and sources for the corrosive and toxic hydrogen sulfide, as well as methane and other related gases, which could greatly impact the operation conditions of the UHS pipeline.
References
- Beaver, R. C., & Neufeld, J. D. (2024). Microbial ecology of the deep terrestrial subsurface. The ISME Journal.
- Cascone, M., et al. (2025). Hydrogenotrophic metabolisms in the subsurface and their implications for underground hydrogen storage and natural hydrogen prospecting. EarthArXiv.
- Climent Gargallo, et al. (2025). Closing the circuit: Mapping the fate of electrons in the environment. Goldschmidt 2025.
- Dopffel, N., et al. (2021). Microbial side effects of underground hydrogen storage – Knowledge gaps, risks and opportunities for successful implementation. International Journal of Hydrogen Energy.
- Escudero, C., & Amils, R. (2023). Dark biosphere: Just at the very tip of the iceberg. Environmental Microbiology.
- Hay Mele, B., et al. (2023). Oxidoreductases and metal cofactors in the functioning of the earth. Essays in Biochemistry.
- Kieft, T. L. (2016). Microbiology of the Deep Continental Biosphere. Springer International Publishing.
- Lane, N., & Martin, W. F. (2012). The Origin of Membrane Bioenergetics. Cell.
- Magnabosco, C., et al. (2018). The biomass and biodiversity of the continental subsurface. Nature Geoscience.
- McMahon, S., & Parnell, J. (2014). Weighing the deep continental biosphere. FEMS Microbiology Ecology.
- Ranchou-Peyruse, A. (2024). Artificial subsurface lithoautotrophic microbial ecosystems and gas storage in deep subsurface. FEMS Microbiology Ecology.
- Templeton, A. S., & Caro, T. A. (2023). The Rock-Hosted Biosphere. Annual Review of Earth and Planetary Sciences.
- Thaysen, E. M., et al. (2023). Microbial risk assessment for underground hydrogen storage in porous rocks. Fuel.
How to cite: Climent Gargallo, G. and Edlmann, K.: Exploring the biochemical potential of the subsurface for UHS risk assessments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13282, https://doi.org/10.5194/egusphere-egu26-13282, 2026.
High-Temperature Aquifer Thermal Energy Storage (HT-ATES) is increasingly considered as a key technology to enhance the flexibility of heat supply systems and to support the decarbonization of District Heating Networks (DHN). In this study, we present a physics-based numerical modeling framework for the consistent assessment of HT-ATES performance across scales, from reservoir physics to energy system modeling.
Coupled thermal-hydraulic numerical models are developed to simulate the storage of high-temperature fluids in a stratified geothermal reservoir. This layered configuration captures key subsurface heterogeneity and enables the systematic evaluation of zone-specific contribution to fluid migration, heat transfer, and associated heat losses. The models consistently account for temperature- and pressure-dependent fluid density and viscosity, allowing density-driven effects and their interaction with forced convection to be resolved.
The numerical analysis captures the spatial and temporal evolution of the thermal perturbation induced by the cyclic HT-ATES operation. Beyond conventional thermal performance metrics, the approach additionally quantifies the hydraulic performance of the HT-ATES system via computing the productivity and injectivity indices, thus enabling the assessment of heat recovery and well performance within a unified framework. The geometry of the thermally influenced rock volume and the developing surface area between the thermal front and undisturbed rock are shown to critically affect heat losses. The hydraulic performance is primarily controlled by the reservoir transmissibility, while variations in fluid properties introduce an additional transient component to the system response.
Building on the reservoir-scale model, the HT-ATES system is exemplarily integrated into a multicomponent energy network, in which a geothermal plant provides the base load and gas boilers supply peak demand. To enhance the energy flexibility in the system, the seasonally operated HT-ATES system is combined with a short-term Thermal Energy Storage (TES) tank. In this hybrid storage configuration, the HT-ATES charges the TES tank, which in turn manages short-term fluctuations in peak heat demand. A coupled simulation framework links the reservoir-scale HT-ATES model with the network-scale thermal-hydraulic models of the DHN and the TES. The dynamic interaction between subsurface storage and heat demand is resolved through the exchange of transient mass fluxes and fluid temperature. Simulation results demonstrate that the integrated HT-ATES/TES storage system can flexibly respond to fluctuating heat demand, covering the greatest portion of the annual peak load and thus significantly reducing reliance on gas boilers.
This integrated approach enables the evaluation of HT-ATES as an active energy system component for seasonal heat shifting, peak-load management, and reduction of fossil-fuel-based heat generation. The presented methodology provides a transferable framework for linking detailed reservoir physics models with energy system models, supporting the design and assessment of multicomponent energy systems and advancing strategies toward flexible, decarbonized heat supply schemes.
How to cite: Tzoufka, K., Blöcher, G., Cacace, M., and Zosseder, K.: Bridging reservoir physics and energy system operation: A cross-scale numerical framework for high-temperature aquifer heat storage, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19414, https://doi.org/10.5194/egusphere-egu26-19414, 2026.
Geological heterogeneity in subsurface reservoirs, such as spatial variability in permeability and porosity, strongly controls hydrogen plume migration and reservoir pressure evolution during underground hydrogen storage (UHS) operated under cyclic injection and withdrawal. These heterogeneities introduce significant uncertainty in system response, complicating predictability, risk assessment, and site design. In our study, with proper distributed statistical sampling of heterogeneous permeability and porosity map on a synthetic two-dimensional saline aquifer benchmark, two-phase flow numerical simulation results reveal that cyclic hydrogen recovery performance is primarily controlled by mean reservoir permeability rather than porosity, with high-permeability formations consistently achieving the highest recovery factors regardless of porosity, while mean porosity plays a secondary, weakly controlling role.
Additional step was taking for the cyclic performance evaluation under geological uncertainties. A hybrid deep-learning surrogate framework that combines convolutional and recurrent neural network components to efficiently forecast cyclic UHS behavior under geological uncertainty. Spatial heterogeneity is captured using a U-Net-type convolutional architecture, which concisely encodes and decodes static reservoir features while preserving multiscale spatial structure. Temporal dynamics are modeled using a recurrent neural network framework adapted from ConvLSTM network (Zhao et al., 2024), enabling accurate learning of pressure and gas saturation evolution across successive injection–withdrawal cycles. This recurrent structure effectively captures cycle-dependent memory effects and dynamic transitions between operational phases. To enforce physical consistency, mass-conservation constraints are embedded directly into the training loss, preventing physically implausible predictions and improving generalization.
The developed surrogate model accurately reproduces hydrogen plume migration and reservoir pressure fluctuations observed in high-fidelity simulations. Reliable interpolation within the training cycles and extrapolation to future, unseen cycles, was validated by demostrating the performance on the synthetic aquifer benchmark. The result shows the physics-constrained model consistently outperforms a purely data-driven counterpart in predicting cyclic pressure and saturation dynamics. This approach enables the upscaling of multiphysics simulation insights into computationally efficient forecasting tools, supporting near-real-time scenario evaluation and decision-making for large-scale underground hydrogen storage under uncertainty.
How to cite: Xu, Z., Misaghi Bonabi, A., Zhao, M., Gerritsma, M., Hajibeygi, H., Alcalde, J., and Vilarrasa, V.: Learning Hydrogen Flow Behavior in Heterogeneous Saline Aquifers under Cyclic Operation with Physics-Constrained CNN-RNN Framework, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21098, https://doi.org/10.5194/egusphere-egu26-21098, 2026.
Carbon geological sequestration is central to China’s energy transition through carbon capture, utilization, and storage (CCUS). While saline aquifers are commonly regarded as primary targets for large-scale CO₂ storage, the storage potential of gas shales remains poorly constrained due to their complex and heterogeneous pore systems. The Upper Silurian Longmaxi Formation in the Sichuan Basin represents one of China’s most significant shale targets. This study integrates pore-scale characterization and basin-scale modelling to explicitly link intrinsic shale properties with regional CO₂ storage estimates, addressing a key limitation in current CCUS assessments that treat shale as a reservoir unit for CO2 storage.
The Pengye-1 well is located in the Pengshui block on the southeastern margin of the Sichuan Basin, a transitional zone between the stable platform and the Wuling fold belt. It targets organic-rich shales of the Lower Silurian Longmaxi Formation deposited in a deep-water shelf environment and, unlike overpressured reservoirs in the basin interior, is currently preserved under normal-pressure conditions due to tectonic uplift and denudation during the Yanshanian and Himalayan orogenies. To bridge the gap between regional tectonic evolution and microscopic storage capacity, a multi-scale characterization approach was adopted. At the pore scale, core samples from the Pengye-1 well were analysed using Brunauer–Emmett–Teller (BET) adsorption, scanning electron microscopy (SEM), and X-ray computed tomography (CT). Specific surface area (SSA) ranges from approximately 19 to 60 m² /g over a depth interval of 2095–2140 m. Porosity does not show the expected reduction with increasing depth, SSA and pore volume do not exhibit a simple monotonic decrease attributable solely to burial compaction. Instead, imaging reveals a depth-dependent evolution in pore morphology from relatively open and regular pores to predominantly slit-shaped pores, with locally preserved ink-bottle geometries. The substantial variability in SSA and pore volume among samples at comparable depths highlights the importance of mineralogical heterogeneity, particularly variations in clay mineral assemblages and brittle mineral phases which in controlling pore preservation and surface development. In addition, a subset of samples shows a negative correlation between pore volume and total organic carbon (TOC), in contrast to commonly reported trends, suggesting a role of TOC in pore evolution.
At the basin scale, CO₂ storage capacity was evaluated for both saline aquifers of the Xujiahe Formation and organic-rich shales of the Upper Silurian Longmaxi Formation within the Sichuan Basin, which together form an interbedded sandstone–shale system. Storage capacity was estimated using multiple volumetric approaches and further constrained by geological modelling that explicitly represents shale intra-beds within sandstone reservoirs. Reservoir-scale simulations using the Permedia® CO₂ module were conducted for the Xujiahe Formation in the central Sichuan Basin, comparing sandstone–shale interbeds with shale-dominated scenarios. The simulations indicate near-complete storage efficiency (≈99%), reflecting restricted CO₂ migration and enhanced trapping in low-porosity, tortuous shale pore networks. While saline aquifers offer higher injectivity, shale formations contribute substantially to the total basin-scale storage resource due to their extensive areal distribution and adsorption-dominated storage mechanisms.
How to cite: He, Y.: CO2 Geological Storage Potential of Longmaxi Shale: Insights from Geochemistry, Modelling, and Imaging, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21345, https://doi.org/10.5194/egusphere-egu26-21345, 2026.
Posters virtual: Tue, 5 May, 14:00–18:00 | vPoster spot 4
EGU26-19786 | ECS | Posters virtual | VPS19
Temperature-Induced Pore Structure Evolution in Shale: Implications for Underground Coal Gasification ApplicationsTue, 05 May, 14:54–14:57 (CEST) vPoster spot 4
Underground coal gasification (UCG) offers a viable approach for extracting deep-seated coal deposits with minimal surface disruption. The thermomechanical behavior of adjacent rock formations, particularly shale, which typically acts as a ceiling or floor rock, has a significant impact on the success of UCG operations. This study examines the pore structure evolution of shale samples at increased temperatures from room temperature to 800 °C, approximating the thermal range experienced during UCG procedures. The primary goal is to understand how high-temperature exposure changes the porosity and microstructure of shale, altering gas movement, confinement, and overall system stability.
Shale samples were collected from Jharia Basin, India, and were heated in a muffle furnace at gradually increasing temperatures. The pore properties were assessed by Low-Pressure Gas Adsorption (LPGA), Helium Pycnometry, and Scanning Electron Microscopy (SEM). SEM imaging showed considerable microcrack formation and intergranular pore growth at temperatures above 300 °C. LPGA data showed a shift from microporous to meso- and macroporous materials as temperature increased, implying gradual pore coalescence. The Helium Pycnometer results verified a temperature-dependent increase in apparent porosity, which corresponded well to the observed physical degradation. The findings show a non-linear rise in total porosity and considerable microstructural disintegration of shale at high temperatures, which can improve gas flow paths but may expose the confining layers' stability. These thermal changes are critical to UCG operations because they affect both gas recovery efficiency and subsurface safety. The work sheds light on the thermal behavior of shale under UCG-relevant conditions, emphasizing the importance of complete thermomechanical studies in site selection and operational planning for UCG projects.
Keywords: Underground Coal Gasification, LPGA, Permeability, temperature, Porosity.
How to cite: Sahoo, S. S.: Temperature-Induced Pore Structure Evolution in Shale: Implications for Underground Coal Gasification Applications , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19786, https://doi.org/10.5194/egusphere-egu26-19786, 2026.
