S. Geiger
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Preprint
(2026)
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Zaid Jangda, Tom Bultreys, Zeyun Jiang, Sajjad Foroughi, Hannah P. Menke, Andreas Busch, Sebastian Geiger, Kamaljit Singh
Underground hydrogen storage in porous formations is a promising solution for large-scale energy storage. Understanding hydrogen flow and trapping at the pore-scale is crucial for assessing storage capacity and recovery efficiency. While pore-scale flow visualisation experiments provide realistic insights, they are resource intensive and technically challenging. Pore-network models offer a computationally efficient tool for simulating multiphase flow in porous media and can serve as a valuable complement to pore-scale experiments. However, their accuracy remains a key uncertainty and must be evaluated for future application. This study evaluates the performance of a quasi-static pore-network model by comparing its predictions against three-dimensional pore-scale hydrogen flow visualisation experiments in a homogeneous Bentheimer sandstone and a layered Clashach sandstone. The model was calibrated to match experimental end-state saturations, and its performance was evaluated through comparisons of spatial saturation profiles and pore occupancy. The novelty of this study lies in the direct comparison of hydrogen displacement between pore-scale experimental observations and pore-network model simulations, providing an assessment of model performance under varying degrees of rock heterogeneity relevant to underground hydrogen storage. The pore-network model shows good agreement with experimental observations for the homogeneous rock, particularly during drainage, and is subsequently used to analyse additional scenarios, including cyclic hydrogen injection and withdrawal, and wettability variations. These simulations provide insights into capillary pressure behaviour and residual saturation trends. In contrast, for the heterogeneous and layered Clashach sandstone, the model fails to capture the trapping and fluid redistribution observed experimentally during imbibition, revealing limitations in modelling fine-scale heterogeneity.
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Underground hydrogen storage in porous formations is a promising solution for large-scale energy storage. Understanding hydrogen flow and trapping at the pore-scale is crucial for assessing storage capacity and recovery efficiency. While pore-scale flow visualisation experiments provide realistic insights, they are resource intensive and technically challenging. Pore-network models offer a computationally efficient tool for simulating multiphase flow in porous media and can serve as a valuable complement to pore-scale experiments. However, their accuracy remains a key uncertainty and must be evaluated for future application. This study evaluates the performance of a quasi-static pore-network model by comparing its predictions against three-dimensional pore-scale hydrogen flow visualisation experiments in a homogeneous Bentheimer sandstone and a layered Clashach sandstone. The model was calibrated to match experimental end-state saturations, and its performance was evaluated through comparisons of spatial saturation profiles and pore occupancy. The novelty of this study lies in the direct comparison of hydrogen displacement between pore-scale experimental observations and pore-network model simulations, providing an assessment of model performance under varying degrees of rock heterogeneity relevant to underground hydrogen storage. The pore-network model shows good agreement with experimental observations for the homogeneous rock, particularly during drainage, and is subsequently used to analyse additional scenarios, including cyclic hydrogen injection and withdrawal, and wettability variations. These simulations provide insights into capillary pressure behaviour and residual saturation trends. In contrast, for the heterogeneous and layered Clashach sandstone, the model fails to capture the trapping and fluid redistribution observed experimentally during imbibition, revealing limitations in modelling fine-scale heterogeneity.
Pore-scale analysis of hydrogen-water displacement in sandstones
A comparison of pore-network modelling and flow visualisation experiments
Journal article
(2026)
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Zaid Jangda, Tom Bultreys, Zeyun Jiang, Sajjad Foroughi, Hannah Menke, Andreas Busch, Sebastian Geiger, Kamaljit Singh
Hydrogen–water displacement in porous rocks involves capillary-dominated multiphase-flow processes at the pore scale that are critical for understanding fluid distribution, trapping, and recovery behaviour. Three-dimensional pore-scale flow visualisation experiments provide direct insight into these processes but are resource intensive and technically challenging. Pore-network models offer a computationally efficient alternative for simulating capillary-dominated multiphase flow, but their accuracy depends on how well-simplified displacement rules represent real pore-scale behaviour. This work presents a direct pore-by-pore comparison between experimentally observed displacement events and predictions from a quasi-static pore-network model. The comparison enables evaluation of the model’s simplifying assumptions and its ability to reproduce pore-scale displacement behaviour across contrasting rock types, including a homogeneous Bentheimer sandstone and a layered Clashach sandstone. The model was calibrated to match experimental end-state saturations, and its performance was evaluated using spatial saturation distributions and pore-occupancy statistics. The pore-network model shows good agreement with experimental observations for the homogeneous rock, particularly during drainage. It is subsequently used to analyse additional scenarios, including cyclic hydrogen injection and withdrawal and wettability variations, providing insight into capillary pressure behaviour and residual saturation trends. In contrast, for the heterogeneous rock, the model does not fully capture the trapping and fluid redistribution observed experimentally, indicating limitations in representing fine-scale heterogeneity. Overall, the results identify the conditions under which the quasi-static pore-network model can reliably represent hydrogen–water displacement and where its simplifying assumptions become limiting, providing guidance for its application in pore-scale multiphase-flow research.
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Hydrogen–water displacement in porous rocks involves capillary-dominated multiphase-flow processes at the pore scale that are critical for understanding fluid distribution, trapping, and recovery behaviour. Three-dimensional pore-scale flow visualisation experiments provide direct insight into these processes but are resource intensive and technically challenging. Pore-network models offer a computationally efficient alternative for simulating capillary-dominated multiphase flow, but their accuracy depends on how well-simplified displacement rules represent real pore-scale behaviour. This work presents a direct pore-by-pore comparison between experimentally observed displacement events and predictions from a quasi-static pore-network model. The comparison enables evaluation of the model’s simplifying assumptions and its ability to reproduce pore-scale displacement behaviour across contrasting rock types, including a homogeneous Bentheimer sandstone and a layered Clashach sandstone. The model was calibrated to match experimental end-state saturations, and its performance was evaluated using spatial saturation distributions and pore-occupancy statistics. The pore-network model shows good agreement with experimental observations for the homogeneous rock, particularly during drainage. It is subsequently used to analyse additional scenarios, including cyclic hydrogen injection and withdrawal and wettability variations, providing insight into capillary pressure behaviour and residual saturation trends. In contrast, for the heterogeneous rock, the model does not fully capture the trapping and fluid redistribution observed experimentally, indicating limitations in representing fine-scale heterogeneity. Overall, the results identify the conditions under which the quasi-static pore-network model can reliably represent hydrogen–water displacement and where its simplifying assumptions become limiting, providing guidance for its application in pore-scale multiphase-flow research.
Journal article
(2026)
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Hariharan Ramachandran, Iain de Jonge-Anderson, Ikhwanul Hafizi Musa, Uisdean Nicholson, Chee Phuat Tan, S. Geiger, Florian Doster
Simulating the fluid flow along fault zones at different scales is essential for predicting the CO2 leakage and containment during injection and storage. However, this can be challenging, especially in the early stages of a storage project when knowledge of the reservoir and caprock is limited and the cost of obtaining the relevant data is high. This study develops a tool for fast screening of fault leakage at the site screening stage. The tool uses a vertically integrated reservoir model coupled with a newly developed upscaled fault leakage function based on source/sink relations. The fault is conceptualized as an increased vertical permeability through the caprock due to the presence of a fracture network in the damage zone and a reduced horizontal permeability in the reservoir due to fault throw and presence of a low-permeability fault core. The proposed tool is validated against numerical simulations demonstrating strong agreement in predicting leakage rates under varying reservoir conditions. The model's capabilities are further tested through simulation cases, including a field-scale application in the Malay Basin. These cases revealed key insights into the roles of fault permeability and fault capillary entry pressure in controlling leakage and highlighted the importance of accurately characterizing these properties to mitigate risks. The computationally efficient model presented in this study is a valuable tool for quantifying uncertainties in key fault parameters, and other constitutive relations that affect the behavior of the storage reservoir and potential fault leakage.
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Simulating the fluid flow along fault zones at different scales is essential for predicting the CO2 leakage and containment during injection and storage. However, this can be challenging, especially in the early stages of a storage project when knowledge of the reservoir and caprock is limited and the cost of obtaining the relevant data is high. This study develops a tool for fast screening of fault leakage at the site screening stage. The tool uses a vertically integrated reservoir model coupled with a newly developed upscaled fault leakage function based on source/sink relations. The fault is conceptualized as an increased vertical permeability through the caprock due to the presence of a fracture network in the damage zone and a reduced horizontal permeability in the reservoir due to fault throw and presence of a low-permeability fault core. The proposed tool is validated against numerical simulations demonstrating strong agreement in predicting leakage rates under varying reservoir conditions. The model's capabilities are further tested through simulation cases, including a field-scale application in the Malay Basin. These cases revealed key insights into the roles of fault permeability and fault capillary entry pressure in controlling leakage and highlighted the importance of accurately characterizing these properties to mitigate risks. The computationally efficient model presented in this study is a valuable tool for quantifying uncertainties in key fault parameters, and other constitutive relations that affect the behavior of the storage reservoir and potential fault leakage.
Journal article
(2026)
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Mathias José Kreutz Erdtmann, Filipe Silva Lira, Sebastian Geiger, Hadi Hajibeygi
Multiscale simulation frameworks are essential to quantify the CO2 trapping and migration in large-scale saline aquifers, which entail highly-resolved fine-scale heterogeneous properties. However, classical upscaling approaches which aim to define effective properties on larger grid sizes can lead to significant and systematic overestimation of the solubility and residual trapping mechanisms. Reliable assessment of these two trapping mechanisms is crucial to ensure the integrity of the storage process and properly mitigate the leakage risks. Therefore, it is essential to develop advanced simulation technologies that are both accurate and efficient (i.e., scalable) for simulation of complex CO2 plume dynamics within large-scale heterogeneous reservoir models. To overcome this challenge, in this work three advanced strategies are developed and investigated: Effective Values (EV) for parameters, Local Grid Refinement (LGR) and Algebraic Dynamic Multilevel (ADM). The numerical investigations specially include a set of consistent models in the Ponta Aguda saline aquifer, with a total area of 40,000 km2[jls-end-space/], located offshore the Brazilian coast. The results indicate that the ADM is a promising method, delivering stable and robust results in a representative section of the field. This encourages further extensions of this method for real-field deployment. Specially, LGR and EV are found to be limited in their scopes for field simulations, since they depend on a matching pre-procedure (against a reference solution) for their upscaled parameters before any new simulations can be run. In addition, 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.
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Multiscale simulation frameworks are essential to quantify the CO2 trapping and migration in large-scale saline aquifers, which entail highly-resolved fine-scale heterogeneous properties. However, classical upscaling approaches which aim to define effective properties on larger grid sizes can lead to significant and systematic overestimation of the solubility and residual trapping mechanisms. Reliable assessment of these two trapping mechanisms is crucial to ensure the integrity of the storage process and properly mitigate the leakage risks. Therefore, it is essential to develop advanced simulation technologies that are both accurate and efficient (i.e., scalable) for simulation of complex CO2 plume dynamics within large-scale heterogeneous reservoir models. To overcome this challenge, in this work three advanced strategies are developed and investigated: Effective Values (EV) for parameters, Local Grid Refinement (LGR) and Algebraic Dynamic Multilevel (ADM). The numerical investigations specially include a set of consistent models in the Ponta Aguda saline aquifer, with a total area of 40,000 km2[jls-end-space/], located offshore the Brazilian coast. The results indicate that the ADM is a promising method, delivering stable and robust results in a representative section of the field. This encourages further extensions of this method for real-field deployment. Specially, LGR and EV are found to be limited in their scopes for field simulations, since they depend on a matching pre-procedure (against a reference solution) for their upscaled parameters before any new simulations can be run. In addition, 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.
Core-scale evaluation of CO2 reinjection feasibility in a carbonate reservoir–caprock system
The S Field case study, Sarawak Basin, Malaysia
Journal article
(2026)
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Sahriza Salwani Md Shah, David N. Dewhurst, Ausama Giwelli, Mark D. Raven, Siti Syareena M. Ali, Sebastian Geiger, Andreas Busch
This study evaluates the feasibility of reinjecting separated CO₂ into its source carbonate reservoir, the high-temperature, high-pressure S Field in the Sarawak Basin, offshore Malaysia. The reservoir gas comprises ∼30% CH₄ and ∼70% CO₂. We combine mineralogical, petrophysical and geomechanical analyses to assess reservoir integrity and caprock sealing performance under in situ conditions. The calcite-dominated gas zone exhibits high porosity (>30%), whereas the underlying aquifer zone is co-dominated by calcite and dolomite with lower porosity (20–25%) and higher strength. The primary caprock (Seal A), a 500 m-thick Miocene mudrock–siltstone unit, has porosities of 2–10% and low permeability, with illite and quartz as dominant minerals. Laboratory experiments exposed reservoir and caprock samples to CO₂-charged brines at reservoir pressure (30 MPa) and temperature (150°C) for up to six months. Post-reaction analyses revealed only minor changes in mineralogy, porosity, permeability and mechanical strength. These results indicate limited CO₂–water–rock reactivity and confirm the mechanical and geochemical stability of both reservoir and caprock. The findings support the viability of CO₂ reinjection and long-term geological storage in the S Field, providing a benchmark case for carbonate-hosted carbon capture and storage systems in SE Asia.
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This study evaluates the feasibility of reinjecting separated CO₂ into its source carbonate reservoir, the high-temperature, high-pressure S Field in the Sarawak Basin, offshore Malaysia. The reservoir gas comprises ∼30% CH₄ and ∼70% CO₂. We combine mineralogical, petrophysical and geomechanical analyses to assess reservoir integrity and caprock sealing performance under in situ conditions. The calcite-dominated gas zone exhibits high porosity (>30%), whereas the underlying aquifer zone is co-dominated by calcite and dolomite with lower porosity (20–25%) and higher strength. The primary caprock (Seal A), a 500 m-thick Miocene mudrock–siltstone unit, has porosities of 2–10% and low permeability, with illite and quartz as dominant minerals. Laboratory experiments exposed reservoir and caprock samples to CO₂-charged brines at reservoir pressure (30 MPa) and temperature (150°C) for up to six months. Post-reaction analyses revealed only minor changes in mineralogy, porosity, permeability and mechanical strength. These results indicate limited CO₂–water–rock reactivity and confirm the mechanical and geochemical stability of both reservoir and caprock. The findings support the viability of CO₂ reinjection and long-term geological storage in the S Field, providing a benchmark case for carbonate-hosted carbon capture and storage systems in SE Asia.
Journal article
(2026)
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Guofeng Song, Sebastian Geiger, Denis Voskov, Hemmo A. Abels, Philip J. Vardon
Geothermal energy has the potential to decarbonize heating, cooling, and power production. However, managing the efficient and sustainable exploitation of geothermal resources is challenging due to the limited data availability, which restricts our ability to characterize and quantify the multi-scale, hierarchical geological structures of the hosting reservoirs. In this study, we propose a scenario-based data assimilation framework that enables the efficient modelling of multiple complex geological scenarios and is linked to flow and heat transfer simulations for subsequent uncertainty analysis. This framework is based on an ensemble smoother with multiple data assimilation (ESMDA) and demonstrated on a channelized fluvial geothermal reservoir. By improving the open-source Rapid Reservoir Modelling (RRM) tool, we efficiently create multiple deterministic fluvial geothermal reservoir scenarios that honors facies along well paths in a probabilistic manner by randomly selecting, cropping, and stacking channelized layers from the layer template library. Petrophysical properties for each scenario are then modelled using geostatistics to generate a geologically plausible and sufficiently diverse ensemble of reservoir realizations. The multiple scenarios and corresponding ensemble realizations are then subjected to heat and fluid flow simulations using the open-source Delft Advanced Research Terra Simulator (open-DARTS) to quantify the uncertainty of production temperatures and reservoir pressures. Finally, ESMDA is employed to assimilate temperature and pressure profiles at the injection well, monitoring borehole, and production well across all members of the ensemble realizations for the different geological scenarios. We demonstrate the applicability of our framework using a synthetic, yet geologically consistent, case study of a low-enthalpy geothermal system where heat is produced from a geothermal doublet located in a channelized fluvial sandstone reservoir. The framework enables the falsification of geological scenarios with poor data assimilation performance that is unlikely to reflect the actual reservoir architecture, and supports the identification of plausible geological scenarios that are more likely to represent the subsurface geology based on the deviation of modelled and observed well temperature and pressure profiles. The workflow offers an efficient way to constrain geological uncertainties inherent to geologically complex geothermal reservoirs and improve the forecasting of production temperatures and pressure differences.
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Geothermal energy has the potential to decarbonize heating, cooling, and power production. However, managing the efficient and sustainable exploitation of geothermal resources is challenging due to the limited data availability, which restricts our ability to characterize and quantify the multi-scale, hierarchical geological structures of the hosting reservoirs. In this study, we propose a scenario-based data assimilation framework that enables the efficient modelling of multiple complex geological scenarios and is linked to flow and heat transfer simulations for subsequent uncertainty analysis. This framework is based on an ensemble smoother with multiple data assimilation (ESMDA) and demonstrated on a channelized fluvial geothermal reservoir. By improving the open-source Rapid Reservoir Modelling (RRM) tool, we efficiently create multiple deterministic fluvial geothermal reservoir scenarios that honors facies along well paths in a probabilistic manner by randomly selecting, cropping, and stacking channelized layers from the layer template library. Petrophysical properties for each scenario are then modelled using geostatistics to generate a geologically plausible and sufficiently diverse ensemble of reservoir realizations. The multiple scenarios and corresponding ensemble realizations are then subjected to heat and fluid flow simulations using the open-source Delft Advanced Research Terra Simulator (open-DARTS) to quantify the uncertainty of production temperatures and reservoir pressures. Finally, ESMDA is employed to assimilate temperature and pressure profiles at the injection well, monitoring borehole, and production well across all members of the ensemble realizations for the different geological scenarios. We demonstrate the applicability of our framework using a synthetic, yet geologically consistent, case study of a low-enthalpy geothermal system where heat is produced from a geothermal doublet located in a channelized fluvial sandstone reservoir. The framework enables the falsification of geological scenarios with poor data assimilation performance that is unlikely to reflect the actual reservoir architecture, and supports the identification of plausible geological scenarios that are more likely to represent the subsurface geology based on the deviation of modelled and observed well temperature and pressure profiles. The workflow offers an efficient way to constrain geological uncertainties inherent to geologically complex geothermal reservoirs and improve the forecasting of production temperatures and pressure differences.
Evaluation of operational strategies for underground hydrogen storage in depleted gas fields under diverse geological scenarios
Guidelines for site screening and development planning
Journal article
(2026)
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Ana Loyola, Denis Voskov, Rouhi Farajzadeh, Karin de Borst, Sebastian Geiger
Underground hydrogen storage in depleted gas fields is a potential solution for large-scale, seasonal storage of hydrogen, in support of the decarbonization of energy systems and other industrial activities. Its viability depends on the performance of the storage operations, which is influenced by the interaction between reservoir geology and operational strategies. However, general guidelines for development planning that account for geological uncertainty are still lacking. In addition, existing site screening criteria remain limited in that they do not account for how operational decisions can alter the suitability of a reservoir geology for hydrogen storage. Here, we employ a numerical model of flow and transport to evaluate a set of operational strategies in varying geological scenarios for depleted methane gas reservoirs of the Bunter Sandstone, an important formation in the North Sea. We investigate the following strategies for their impact on performance and interaction with geological features that are common in the Bunter sandstone: depletion level, injected hydrogen mass, cushion gas, well perforation, idle period, production rates, and methane reinjection. We found that depletion level, injected mass, and well perforation interact strongly with geology and are critical for site selection. The methane reinjection strategy provides pressure support that increases hydrogen production, though at the cost of purity in the long-term. Furthermore, cushion gas strategies show significant optimization potential but limited interaction with geology, whereas the duration of the idle period and target rates have low optimization potential. Based on these findings, we propose a site selection and development planning framework for underground hydrogen storage in depleted gas fields. The site selection phase introduces a novel screening criterion, the gravity–purity number, which integrates geological and operational considerations. The development phase provides criteria and guidelines for planning operational strategies, and establishes a hierarchy based on their optimization potential.
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Underground hydrogen storage in depleted gas fields is a potential solution for large-scale, seasonal storage of hydrogen, in support of the decarbonization of energy systems and other industrial activities. Its viability depends on the performance of the storage operations, which is influenced by the interaction between reservoir geology and operational strategies. However, general guidelines for development planning that account for geological uncertainty are still lacking. In addition, existing site screening criteria remain limited in that they do not account for how operational decisions can alter the suitability of a reservoir geology for hydrogen storage. Here, we employ a numerical model of flow and transport to evaluate a set of operational strategies in varying geological scenarios for depleted methane gas reservoirs of the Bunter Sandstone, an important formation in the North Sea. We investigate the following strategies for their impact on performance and interaction with geological features that are common in the Bunter sandstone: depletion level, injected hydrogen mass, cushion gas, well perforation, idle period, production rates, and methane reinjection. We found that depletion level, injected mass, and well perforation interact strongly with geology and are critical for site selection. The methane reinjection strategy provides pressure support that increases hydrogen production, though at the cost of purity in the long-term. Furthermore, cushion gas strategies show significant optimization potential but limited interaction with geology, whereas the duration of the idle period and target rates have low optimization potential. Based on these findings, we propose a site selection and development planning framework for underground hydrogen storage in depleted gas fields. The site selection phase introduces a novel screening criterion, the gravity–purity number, which integrates geological and operational considerations. The development phase provides criteria and guidelines for planning operational strategies, and establishes a hierarchy based on their optimization potential.
Journal article
(2025)
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Xinyu Dong, Gary J. Hampson, Carl Jacquemyn, Matthew D. Jackson, Dmytro Petrovskyy, Sebastian Geiger, Yanghua Wang
Carbonate reservoirs host significant hydrocarbon, groundwater, geothermal and CO2- and H2-storage resources. However, their complex depositional, tectonic and diagenetic histories make it challenging to efficiently characterize and predict their flow behavior. Here, we use a novel, rapid and efficient screening methodology that integrates experimental design, the construction of three-dimensional (3D) reservoir models via sketch-based methods and single-phase flow diagnostics to investigate the impact of geological heterogeneity on flow patterns and displacement in an ultra-deep (>7 km) carbonate reservoir in the north-central Tarim Basin, northwest China. Eight heterogeneities are investigated: (1) strike-slip fault zone width; (2) complexity of flower structure configuration; (3) continuity of fault core lithology; fault zone rock properties related to (4) karstification and (5) late, post-karstification cementation; (6) the occurrence of fault-perpendicular fracture corridors; (7) connectivity of fracture corridors to fault zones and (8) variability in host rock porosity and permeability. Fault zone width has the most significant impact on reservoir properties, with wider fault zones increasing effective horizontal permeability along fault zone strike. Fracture corridor occurrence and connectivity to the fault zone are the principal heterogeneities controlling effective permeability perpendicular to fault zone strike. Fault zone rock properties reflecting karstification and late cementation also significantly impact effective permeability in all directions. Other heterogeneities have little effect on effective permeability and well performance. However, simulated wells in negative flower structures and the main fault zone have higher productivities on average than simulated wells in positive flower structures and the host rock, similar to published production data from the ultra-deep reservoir. This study demonstrates the value of the screening methodology for assessing the effects of uncertainty in the interpretation of geological heterogeneities in complex carbonate reservoirs, in order to narrow the focus of future, more comprehensive reservoir simulations. The screening methodology is directly transferable to low-carbon energy applications in settings with sparse data.
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Carbonate reservoirs host significant hydrocarbon, groundwater, geothermal and CO2- and H2-storage resources. However, their complex depositional, tectonic and diagenetic histories make it challenging to efficiently characterize and predict their flow behavior. Here, we use a novel, rapid and efficient screening methodology that integrates experimental design, the construction of three-dimensional (3D) reservoir models via sketch-based methods and single-phase flow diagnostics to investigate the impact of geological heterogeneity on flow patterns and displacement in an ultra-deep (>7 km) carbonate reservoir in the north-central Tarim Basin, northwest China. Eight heterogeneities are investigated: (1) strike-slip fault zone width; (2) complexity of flower structure configuration; (3) continuity of fault core lithology; fault zone rock properties related to (4) karstification and (5) late, post-karstification cementation; (6) the occurrence of fault-perpendicular fracture corridors; (7) connectivity of fracture corridors to fault zones and (8) variability in host rock porosity and permeability. Fault zone width has the most significant impact on reservoir properties, with wider fault zones increasing effective horizontal permeability along fault zone strike. Fracture corridor occurrence and connectivity to the fault zone are the principal heterogeneities controlling effective permeability perpendicular to fault zone strike. Fault zone rock properties reflecting karstification and late cementation also significantly impact effective permeability in all directions. Other heterogeneities have little effect on effective permeability and well performance. However, simulated wells in negative flower structures and the main fault zone have higher productivities on average than simulated wells in positive flower structures and the host rock, similar to published production data from the ultra-deep reservoir. This study demonstrates the value of the screening methodology for assessing the effects of uncertainty in the interpretation of geological heterogeneities in complex carbonate reservoirs, in order to narrow the focus of future, more comprehensive reservoir simulations. The screening methodology is directly transferable to low-carbon energy applications in settings with sparse data.
Workflows, Data and Modelling Technologies for Geothermal Heat Exploration
From Industry Standard to State-of-the-Art
Conference paper
(2025)
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L. Janku, G. Hampson, P. Bruna, H. Guðmundsdóttir, T. Fischer, G. de Vries, S. Bakrac, P. Haffinger, V. Nogales, L. Tryggvadóttir, A. Peterhaensel, H. Claridge, S. Geiger, F. Dekker, M. Bentley, T. Wynn, A. Babasafari, Matthew Jackson, A. Daniilidis, B. Lamy-Chappuis, P. Jimenez Hernandez, T. Driesner, C. Glaas, J. Vlček
High technical and economic risks stemming from the lack of detailed knowledge of the subsurface hold back large-scale investments in geothermal energy. In a survey conducted on nine use cases from diverse geological settings across Europe and with different purposes (electricity/heating and cooling) and project objectives (scientific/commercial), we identify the “common practice” and the aspiration for the “state of the art” in geothermal exploration. For each use case, the survey investigates what workflows have been adopted and what data acquired by which methods at different stages of exploration. This provided a benchmark for exploration in a range geothermal play types. The survey shows that this industry-standard base-case can be adapted to improve exploration success and efficiency by (1) applying numerical modelling in early stages of exploration to guide strategic data collection, (2) novel application of innovative technologies and (3) closer integration of software tools for static geological interpretation and dynamic heat flow simulation.
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High technical and economic risks stemming from the lack of detailed knowledge of the subsurface hold back large-scale investments in geothermal energy. In a survey conducted on nine use cases from diverse geological settings across Europe and with different purposes (electricity/heating and cooling) and project objectives (scientific/commercial), we identify the “common practice” and the aspiration for the “state of the art” in geothermal exploration. For each use case, the survey investigates what workflows have been adopted and what data acquired by which methods at different stages of exploration. This provided a benchmark for exploration in a range geothermal play types. The survey shows that this industry-standard base-case can be adapted to improve exploration success and efficiency by (1) applying numerical modelling in early stages of exploration to guide strategic data collection, (2) novel application of innovative technologies and (3) closer integration of software tools for static geological interpretation and dynamic heat flow simulation.
CO2 Storage Complex in Santos Basin, Brazil
Storage Potential and Impacts of Heterogeneity in Pressure Front
Conference paper
(2025)
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F. Silva Lira, M. Erdtmann, G. Gantois, F. Da Costa, H. Zerfass, L. Cassino, P. Walter, A. Martinius, S. Geiger, L. Menezes, S. Bortolini, A. Guirro, G. Waisman, F. Bulhoes, G. Freitas, G. Vieira, N. Lima
Brazil’s industrial emissions are 180 million tons of CO2 per year, and approximately 60% of these emissions are coming from industrial clusters located in the southeast. Tthe development of new offshore storage locations in this region is hence of strategic importance for future Carbon Capture and Storage (CCS) projects in Brazil. This study presents an evaluation of CO2 storage in the deep saline aquifers of the Jureia-Ponta Aguda formation, a gigaton-scale storage resource located in the shallow waters of Santos Basin that has the potential to support the development of at least three larger CCS hubs, each with a target injection of 1Gt of CO2. We show how Lorenz Coefficient map allows us to screen the pressure influence areas for each hub by linking reservoir heterogeneity to the spatio-temporal evolution of the pressure front, thereby identifying potential risks of pressure interference between neighboring CCS hubs.
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Brazil’s industrial emissions are 180 million tons of CO2 per year, and approximately 60% of these emissions are coming from industrial clusters located in the southeast. Tthe development of new offshore storage locations in this region is hence of strategic importance for future Carbon Capture and Storage (CCS) projects in Brazil. This study presents an evaluation of CO2 storage in the deep saline aquifers of the Jureia-Ponta Aguda formation, a gigaton-scale storage resource located in the shallow waters of Santos Basin that has the potential to support the development of at least three larger CCS hubs, each with a target injection of 1Gt of CO2. We show how Lorenz Coefficient map allows us to screen the pressure influence areas for each hub by linking reservoir heterogeneity to the spatio-temporal evolution of the pressure front, thereby identifying potential risks of pressure interference between neighboring CCS hubs.
Characterising fractures in geothermal reservoirs is crucial for understanding heat and fluid flow, as fractures control reservoir permeability. Due to data scarcity, estimating fracture network properties remains uncertain. Dynamic data, such as well tests, provides indirect insights into subsurface properties and workflows have been developed to illustrate how uncertainty in fracture data affects flow behaviour. However, they use simplified, randomly generated fracture geometries limiting their applicability to real-world scenarios. This study presents a machine learning workflow for characterizing fractured reservoirs using transient data, focusing on geothermal reservoirs. A comprehensive dataset of 5000 geologically consistent Discrete Fracture Networks (DFNs) was generated using GeoDFN and directly linked to MRST for simulations. The workflow then applies a k-medoids clustering approach, using dynamic time warping (DTW) as a distance metric, to cluster pressure responses with similar transient behaviour. We identified 18 distinct pressure behaviour. Linking clusters to fracture properties reveals that fracture intensity, aperture, and length have the most significant impact on pressure behaviour, while fracture set type was found to be the least important factor. Future work will extend this workflow to temperature transient data and apply advanced machine learning techniques for both forward and inverse modelling of fractured geothermal reservoirs.
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Characterising fractures in geothermal reservoirs is crucial for understanding heat and fluid flow, as fractures control reservoir permeability. Due to data scarcity, estimating fracture network properties remains uncertain. Dynamic data, such as well tests, provides indirect insights into subsurface properties and workflows have been developed to illustrate how uncertainty in fracture data affects flow behaviour. However, they use simplified, randomly generated fracture geometries limiting their applicability to real-world scenarios. This study presents a machine learning workflow for characterizing fractured reservoirs using transient data, focusing on geothermal reservoirs. A comprehensive dataset of 5000 geologically consistent Discrete Fracture Networks (DFNs) was generated using GeoDFN and directly linked to MRST for simulations. The workflow then applies a k-medoids clustering approach, using dynamic time warping (DTW) as a distance metric, to cluster pressure responses with similar transient behaviour. We identified 18 distinct pressure behaviour. Linking clusters to fracture properties reveals that fracture intensity, aperture, and length have the most significant impact on pressure behaviour, while fracture set type was found to be the least important factor. Future work will extend this workflow to temperature transient data and apply advanced machine learning techniques for both forward and inverse modelling of fractured geothermal reservoirs.
Towards Conceptual-Model Based Exploration and Appraisal of Geothermal Resources
The FindHeat Project
Conference paper
(2025)
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S. Geiger, A. Daniilidis, T. Driesner, B. Lamy-Chappuis, A. Grayver, L. Janku, J. Vlček, T. Fischer, P. Hernandez, A. Garcia Craviotto, P. Doulgeris, P. Haffinger, P. Bruna, S. Bakrac, A. Babasafari, A. Peterhaensel, M. Bentley, T. Wynn, H. Guðmundsdóttir, L. Tryggvadóttir, Carole Glaas, C. Baujard, A. Genter, G. de Vries, F. Dekker, H. Claridge, V. Nogales Herrera, G. Hampson, M. Jackson, C. Jacquemyn
To enable reliable exploration strategies for geothermal energy that have inherently lower economic and technical risks and hence increase public support, the multi-national, multi-disciplinary, and publicly funded FindHeat project is developing a novel, conceptual model-based geothermal exploration workflow. This workflow specifically focuses on faster turnaround times for exploration and appraisal of geothermal resources, making better use of legacy data and non-invasive geophysical techniques, and constraining uncertainties with respect to the size of the heat source and the range of possible heat production rates. Comprehensive social science research complements the technical work to set the foundation for new communication strategies that allow geothermal operators to earn the public trust that improved geothermal exploration and appraisal will lead to a more efficient and sustainable exploitation of geothermal energy. The workflow is being tested and validated at eight geologically diverse geothermal plays situated in Iceland, France, UK, Spain, and Netherlands, which allows us to demonstrate its economic and technical benefits as well as its societal impact.
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To enable reliable exploration strategies for geothermal energy that have inherently lower economic and technical risks and hence increase public support, the multi-national, multi-disciplinary, and publicly funded FindHeat project is developing a novel, conceptual model-based geothermal exploration workflow. This workflow specifically focuses on faster turnaround times for exploration and appraisal of geothermal resources, making better use of legacy data and non-invasive geophysical techniques, and constraining uncertainties with respect to the size of the heat source and the range of possible heat production rates. Comprehensive social science research complements the technical work to set the foundation for new communication strategies that allow geothermal operators to earn the public trust that improved geothermal exploration and appraisal will lead to a more efficient and sustainable exploitation of geothermal energy. The workflow is being tested and validated at eight geologically diverse geothermal plays situated in Iceland, France, UK, Spain, and Netherlands, which allows us to demonstrate its economic and technical benefits as well as its societal impact.
Impact of sedimentological heterogeneity on subsurface storage in net-transgressive, shallow-marine sandstones
Cliff House Sandstone, New Mexico, USA
Journal article
(2025)
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Xiaowen Wu, Gary J. Hampson, Carl Jacquemyn, Shakhawat Hossain, Matthew Jackson, Dmytro Petrovskyy, Sebastian Geiger
Net-transgressive, shallow-marine sandstone reservoirs overlain by thick mudstone seals are prime candidates for storage of CO2, H2 and thermal energy. Although these reservoirs have high net-to-gross ratios, analogous outcrops demonstrate a wide range of sedimentological heterogeneities that are sampled only sparsely or at low resolution in subsurface data. We use a combination of outcrop data, sketch-based reservoir modelling and flow diagnostics to assess the impact of sedimentological heterogeneities on subsurface storage.
The Cliff House Sandstone outcrop example comprises wave-dominated shoreface sandstones arranged in aggradationally-to-retrogradationally stacked parasequences, which overlie and pass up depositional dip into mudstone-dominated coastal plain, lagoonal and tidal flat deposits that encase channelized tidal and tidally influenced fluvial sandbodies. Reservoir models of this outcrop example demonstrate that effective horizontal permeability, flow patterns and displacement, and stratigraphic trapping potential are controlled by: (1) the packaging of shoreface sandstones into laterally extensive parasequences bounded by offshore mudstones; (2) the spatial distribution, connectivity and permeability of channelized sandbodies; and (3) the localized connections between channelized sandbodies and shoreface sandstones. The last two parameters are likely to be poorly constrained in subsurface seismic and well data, and their potential effects require evaluation in reservoir modelling studies. ...
The Cliff House Sandstone outcrop example comprises wave-dominated shoreface sandstones arranged in aggradationally-to-retrogradationally stacked parasequences, which overlie and pass up depositional dip into mudstone-dominated coastal plain, lagoonal and tidal flat deposits that encase channelized tidal and tidally influenced fluvial sandbodies. Reservoir models of this outcrop example demonstrate that effective horizontal permeability, flow patterns and displacement, and stratigraphic trapping potential are controlled by: (1) the packaging of shoreface sandstones into laterally extensive parasequences bounded by offshore mudstones; (2) the spatial distribution, connectivity and permeability of channelized sandbodies; and (3) the localized connections between channelized sandbodies and shoreface sandstones. The last two parameters are likely to be poorly constrained in subsurface seismic and well data, and their potential effects require evaluation in reservoir modelling studies. ...
Net-transgressive, shallow-marine sandstone reservoirs overlain by thick mudstone seals are prime candidates for storage of CO2, H2 and thermal energy. Although these reservoirs have high net-to-gross ratios, analogous outcrops demonstrate a wide range of sedimentological heterogeneities that are sampled only sparsely or at low resolution in subsurface data. We use a combination of outcrop data, sketch-based reservoir modelling and flow diagnostics to assess the impact of sedimentological heterogeneities on subsurface storage.
The Cliff House Sandstone outcrop example comprises wave-dominated shoreface sandstones arranged in aggradationally-to-retrogradationally stacked parasequences, which overlie and pass up depositional dip into mudstone-dominated coastal plain, lagoonal and tidal flat deposits that encase channelized tidal and tidally influenced fluvial sandbodies. Reservoir models of this outcrop example demonstrate that effective horizontal permeability, flow patterns and displacement, and stratigraphic trapping potential are controlled by: (1) the packaging of shoreface sandstones into laterally extensive parasequences bounded by offshore mudstones; (2) the spatial distribution, connectivity and permeability of channelized sandbodies; and (3) the localized connections between channelized sandbodies and shoreface sandstones. The last two parameters are likely to be poorly constrained in subsurface seismic and well data, and their potential effects require evaluation in reservoir modelling studies.
The Cliff House Sandstone outcrop example comprises wave-dominated shoreface sandstones arranged in aggradationally-to-retrogradationally stacked parasequences, which overlie and pass up depositional dip into mudstone-dominated coastal plain, lagoonal and tidal flat deposits that encase channelized tidal and tidally influenced fluvial sandbodies. Reservoir models of this outcrop example demonstrate that effective horizontal permeability, flow patterns and displacement, and stratigraphic trapping potential are controlled by: (1) the packaging of shoreface sandstones into laterally extensive parasequences bounded by offshore mudstones; (2) the spatial distribution, connectivity and permeability of channelized sandbodies; and (3) the localized connections between channelized sandbodies and shoreface sandstones. The last two parameters are likely to be poorly constrained in subsurface seismic and well data, and their potential effects require evaluation in reservoir modelling studies.
From outcrop observations to dynamic simulations
An efficient workflow for generating ensembles of geologically plausible fracture networks and assessing their impact on flow and transport
Journal article
(2025)
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Elahe Kamel Targhi, Pierre-Olivier Bruna, Alexandros Daniilidis, Guillaume Rongier, Sebastian Geiger
Fractures are ubiquitous in geological formations and can often have an impact on subsurface applications such as geothermal energy, groundwater management or CO2 storage. Quantifying the relationship between the uncertainties inherent to fracture networks and the corresponding flow behaviour for these applications remains an open challenge. Simulation studies that are based on outcrop analogues of fracture networks have yielded many new insights about heat and mass transfer in fractured geological formations but are restricted to a limited number of fracture network realizations, simplified assumptions about fracture network properties or deterministic models, making it difficult to analyse a wide range of uncertainties. This study introduces a flexible workflow that generates ensembles of geologically plausible fracture networks that can be based on statistical data from outcrop analogues. The fracture networks are generated using a computationally efficient approach that combines mechanical and statistical methods. The ensembles are then seamlessly linked to multi-purpose flow and transport simulations where the fractures are represented explicitly in a porous and permeable rock matrix. This approach can enable new uncertainty quantification methods, supported by machine-learning-based emulators, to analyse how fracture network properties, such as fracture intensity, fracture aperture or fracture orientation, influence heat and mass transfer in fractured geological formations. The workflow is illustrated using two classic example applications pertinent to fracture network modelling – one based on outcrop data to assess thermal behaviour in geothermal systems, and one synthetic study to analyse the transition from matrix-dominated to fracture-dominated flow – and released as open-source code.
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Fractures are ubiquitous in geological formations and can often have an impact on subsurface applications such as geothermal energy, groundwater management or CO2 storage. Quantifying the relationship between the uncertainties inherent to fracture networks and the corresponding flow behaviour for these applications remains an open challenge. Simulation studies that are based on outcrop analogues of fracture networks have yielded many new insights about heat and mass transfer in fractured geological formations but are restricted to a limited number of fracture network realizations, simplified assumptions about fracture network properties or deterministic models, making it difficult to analyse a wide range of uncertainties. This study introduces a flexible workflow that generates ensembles of geologically plausible fracture networks that can be based on statistical data from outcrop analogues. The fracture networks are generated using a computationally efficient approach that combines mechanical and statistical methods. The ensembles are then seamlessly linked to multi-purpose flow and transport simulations where the fractures are represented explicitly in a porous and permeable rock matrix. This approach can enable new uncertainty quantification methods, supported by machine-learning-based emulators, to analyse how fracture network properties, such as fracture intensity, fracture aperture or fracture orientation, influence heat and mass transfer in fractured geological formations. The workflow is illustrated using two classic example applications pertinent to fracture network modelling – one based on outcrop data to assess thermal behaviour in geothermal systems, and one synthetic study to analyse the transition from matrix-dominated to fracture-dominated flow – and released as open-source code.
Conference paper
(2025)
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Q. Zhang, S. Geiger, J. Storms, H. Hajibeygi, M. Jackson, G. Hampson, C. Jacquemyn, S. Krevor, A. Martinius
The North Sea’s potential as a Green Energy Hub depends on large-scale CO2 storage in shallow-marine sandstones, but the effects of geologic heterogeneity, such as permeability barriers and capillary entry pressure contrasts, remain underexplored. This study uses multiphase flow simulations on geologically realistic, surface-based reservoir models informed by outcrop analogue data from wave-dominated shoreface sandstones. We investigate how sedimentological heterogeneity influences CO2 plume migration, pressure evolution, and storage capacity.
Preliminary results show that capillary barriers tied to facies architecture and early cementation, conditioned to clinoform geometries, significantly control plume movement. These barriers promote lateral spreading and residual trapping, representing a potential upper limit on long-term CO2 storage when stable. Clinoform-related heterogeneity also induces flow compartmentalization, limiting pressure dissipation and enhancing anisotropy, which may reduce injectivity and cause spatially variable pressure buildup.
Comparisons with waterflood simulations reveal contrasting dynamics: water advances more uniformly, while CO2 migration is more sensitive to fine-scale architecture due to its lower interfacial tension and capillary entry pressures. These findings underscore the need to incorporate realistic sedimentological heterogeneity in dynamic models to avoid misestimating injectivity, pressure behavior, and storage security. This approach offers a robust framework for early-stage screening and risk assessment in complex storage settings. ...
Preliminary results show that capillary barriers tied to facies architecture and early cementation, conditioned to clinoform geometries, significantly control plume movement. These barriers promote lateral spreading and residual trapping, representing a potential upper limit on long-term CO2 storage when stable. Clinoform-related heterogeneity also induces flow compartmentalization, limiting pressure dissipation and enhancing anisotropy, which may reduce injectivity and cause spatially variable pressure buildup.
Comparisons with waterflood simulations reveal contrasting dynamics: water advances more uniformly, while CO2 migration is more sensitive to fine-scale architecture due to its lower interfacial tension and capillary entry pressures. These findings underscore the need to incorporate realistic sedimentological heterogeneity in dynamic models to avoid misestimating injectivity, pressure behavior, and storage security. This approach offers a robust framework for early-stage screening and risk assessment in complex storage settings. ...
The North Sea’s potential as a Green Energy Hub depends on large-scale CO2 storage in shallow-marine sandstones, but the effects of geologic heterogeneity, such as permeability barriers and capillary entry pressure contrasts, remain underexplored. This study uses multiphase flow simulations on geologically realistic, surface-based reservoir models informed by outcrop analogue data from wave-dominated shoreface sandstones. We investigate how sedimentological heterogeneity influences CO2 plume migration, pressure evolution, and storage capacity.
Preliminary results show that capillary barriers tied to facies architecture and early cementation, conditioned to clinoform geometries, significantly control plume movement. These barriers promote lateral spreading and residual trapping, representing a potential upper limit on long-term CO2 storage when stable. Clinoform-related heterogeneity also induces flow compartmentalization, limiting pressure dissipation and enhancing anisotropy, which may reduce injectivity and cause spatially variable pressure buildup.
Comparisons with waterflood simulations reveal contrasting dynamics: water advances more uniformly, while CO2 migration is more sensitive to fine-scale architecture due to its lower interfacial tension and capillary entry pressures. These findings underscore the need to incorporate realistic sedimentological heterogeneity in dynamic models to avoid misestimating injectivity, pressure behavior, and storage security. This approach offers a robust framework for early-stage screening and risk assessment in complex storage settings.
Preliminary results show that capillary barriers tied to facies architecture and early cementation, conditioned to clinoform geometries, significantly control plume movement. These barriers promote lateral spreading and residual trapping, representing a potential upper limit on long-term CO2 storage when stable. Clinoform-related heterogeneity also induces flow compartmentalization, limiting pressure dissipation and enhancing anisotropy, which may reduce injectivity and cause spatially variable pressure buildup.
Comparisons with waterflood simulations reveal contrasting dynamics: water advances more uniformly, while CO2 migration is more sensitive to fine-scale architecture due to its lower interfacial tension and capillary entry pressures. These findings underscore the need to incorporate realistic sedimentological heterogeneity in dynamic models to avoid misestimating injectivity, pressure behavior, and storage security. This approach offers a robust framework for early-stage screening and risk assessment in complex storage settings.
Hydrogen Flow and Trapping in Sandstone Rocks
Comparing Pore-Scale Experiments with Pore Network Modelling
Understanding pore-scale hydrogen displacement and trapping is crucial for developing subsurface hydrogen storage facilities. While pore-scale flow visualization experiments provide critical insights, they are complex and re source-intensive. Quasi-static pore-network models (PNMs) offer a faster alternative for simulating multiphase flow. This study uses a widely employed PNM to simulate hydrogen flow in sandstones, comparing results with pore-scale flow visualization experiments at reservoir conditions.
Two sandstone samples were used: homogeneous Bentheimer and heterogeneous Clashach. Pore networks were extracted comprising pores and throats, and hydrogen-water flow was simulated, modelling drainage and imbibition processes. Results were analysed for fluid saturations and pore occupancies.
For the homogeneous rock, the PNM matches experimental results for both drainage and imbibition, enabling simulations of different wettability conditions and multiple injection and production cycles. For the heterogeneous rock, the PNM reasonably predicts the hydrogen flow path during drainage but fails to accurately predict imbibition. This discrepancy highlights the limitations of PNMs in predicting pore-scale flow in complex rocks.
In conclusion, while PNMs offer a computationally efficient means to simulate hydrogen flow, they cannot currently replace experimental observations for complex rocks. Further validation against experimental findings is necessary to refine these models and expand their applicability for underground hydrogen storage. ...
Two sandstone samples were used: homogeneous Bentheimer and heterogeneous Clashach. Pore networks were extracted comprising pores and throats, and hydrogen-water flow was simulated, modelling drainage and imbibition processes. Results were analysed for fluid saturations and pore occupancies.
For the homogeneous rock, the PNM matches experimental results for both drainage and imbibition, enabling simulations of different wettability conditions and multiple injection and production cycles. For the heterogeneous rock, the PNM reasonably predicts the hydrogen flow path during drainage but fails to accurately predict imbibition. This discrepancy highlights the limitations of PNMs in predicting pore-scale flow in complex rocks.
In conclusion, while PNMs offer a computationally efficient means to simulate hydrogen flow, they cannot currently replace experimental observations for complex rocks. Further validation against experimental findings is necessary to refine these models and expand their applicability for underground hydrogen storage. ...
Understanding pore-scale hydrogen displacement and trapping is crucial for developing subsurface hydrogen storage facilities. While pore-scale flow visualization experiments provide critical insights, they are complex and re source-intensive. Quasi-static pore-network models (PNMs) offer a faster alternative for simulating multiphase flow. This study uses a widely employed PNM to simulate hydrogen flow in sandstones, comparing results with pore-scale flow visualization experiments at reservoir conditions.
Two sandstone samples were used: homogeneous Bentheimer and heterogeneous Clashach. Pore networks were extracted comprising pores and throats, and hydrogen-water flow was simulated, modelling drainage and imbibition processes. Results were analysed for fluid saturations and pore occupancies.
For the homogeneous rock, the PNM matches experimental results for both drainage and imbibition, enabling simulations of different wettability conditions and multiple injection and production cycles. For the heterogeneous rock, the PNM reasonably predicts the hydrogen flow path during drainage but fails to accurately predict imbibition. This discrepancy highlights the limitations of PNMs in predicting pore-scale flow in complex rocks.
In conclusion, while PNMs offer a computationally efficient means to simulate hydrogen flow, they cannot currently replace experimental observations for complex rocks. Further validation against experimental findings is necessary to refine these models and expand their applicability for underground hydrogen storage.
Two sandstone samples were used: homogeneous Bentheimer and heterogeneous Clashach. Pore networks were extracted comprising pores and throats, and hydrogen-water flow was simulated, modelling drainage and imbibition processes. Results were analysed for fluid saturations and pore occupancies.
For the homogeneous rock, the PNM matches experimental results for both drainage and imbibition, enabling simulations of different wettability conditions and multiple injection and production cycles. For the heterogeneous rock, the PNM reasonably predicts the hydrogen flow path during drainage but fails to accurately predict imbibition. This discrepancy highlights the limitations of PNMs in predicting pore-scale flow in complex rocks.
In conclusion, while PNMs offer a computationally efficient means to simulate hydrogen flow, they cannot currently replace experimental observations for complex rocks. Further validation against experimental findings is necessary to refine these models and expand their applicability for underground hydrogen storage.
Evaluating large-scale saline aquifers
Unlocking CO 2 storage in the Santos Basin through consistent multiscale analysis
Regional-scale saline aquifers are promising candidates for geological CO2 storage but present significant modeling challenges due to their vast extent, heterogeneity, and limited subsurface data. This study introduces a multiscale modeling framework that was applied to assess CO2 storage in the Ponta Aguda saline aquifer (Santos Basin, Brazil, 40,000 km2 area). Consistency of the multiscale models is checked by combining boundaries conditions for pressure match and verification of trapping mechanisms representativity. Four different methods were evaluated regarding the trapping mechanisms accuracy in coarse models: Local Grid Refinement, Effective Values, and Algebraic Dynamic Multilevel. Compositional simulations conducted with CMG-GEM and DARSim2 demonstrate that coarse-scale models systematically overestimate CO2 trapping due to numerical artifacts, particularly in solubility and hysteresis behavior. These artifacts arise from mismatched CO2/brine volumes in large cells, leading to artificially enhanced trapping efficiency. Among the evaluated methods, Algebraic Dynamic Multilevel delivers the most reliable predictions, providing a general solution that aligns closely with fine-scale reference simulations while remaining computationally feasible. 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 large saline aquifers.
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Regional-scale saline aquifers are promising candidates for geological CO2 storage but present significant modeling challenges due to their vast extent, heterogeneity, and limited subsurface data. This study introduces a multiscale modeling framework that was applied to assess CO2 storage in the Ponta Aguda saline aquifer (Santos Basin, Brazil, 40,000 km2 area). Consistency of the multiscale models is checked by combining boundaries conditions for pressure match and verification of trapping mechanisms representativity. Four different methods were evaluated regarding the trapping mechanisms accuracy in coarse models: Local Grid Refinement, Effective Values, and Algebraic Dynamic Multilevel. Compositional simulations conducted with CMG-GEM and DARSim2 demonstrate that coarse-scale models systematically overestimate CO2 trapping due to numerical artifacts, particularly in solubility and hysteresis behavior. These artifacts arise from mismatched CO2/brine volumes in large cells, leading to artificially enhanced trapping efficiency. Among the evaluated methods, Algebraic Dynamic Multilevel delivers the most reliable predictions, providing a general solution that aligns closely with fine-scale reference simulations while remaining computationally feasible. 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 large saline aquifers.
Capillary pinning in sedimentary rocks for CO2 storage
Mechanisms, terminology and State-of-the-Art
Review
(2025)
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Qin Zhang, Sebastian Geiger, Joep E.A. Storms, Denis V. Voskov, Matthew D. Jackson, Gary J. Hampson, Carl Jacquemyn, Allard W. Martinius
Capillary pinning refers to the immobilization of CO₂ at capillary barriers when the uprising CO2 pressure is lower than the capillary entry pressure of the overlaying pore throats. Also known as local capillary trapping, it has been proposed as a fifth geologic CO₂ storage mechanism, alongside structural, solubility, residual, and mineral trapping. Despite extensive research, the fragmented terminology surrounding capillary pinning has led to confusion, making it challenging to synthesize findings effectively. Often conflated with mechanisms such as residual and hysteresis trapping, capillary pinning is commonly underestimated or completely overlooked in reservoir-scale models. Furthermore, difficulties in characterizing and upscaling small-scale geologic heterogeneities that influence capillary pinning contribute to significant uncertainties, with estimates of CO₂ trapped via this mechanism ranging from 3 % to 100 % of total CO₂ trapped via capillary actions. This review explores the fundamental mechanisms, experimental findings, and modeling approaches for assessing CO₂ capillary pinning in carbon capture and storage (CCS). It seeks to bridge the gap between the reservoir engineering community, with its extensive expertise in hydrocarbon recovery but that needs adjustments for CCS applications, and the subsurface storage community, which stands to benefit from this knowledge but often lacks access to relevant literature. Additionally, the study identifies key research opportunities to advance the understanding of capillary pinning in sedimentary rocks, ultimately enhancing the efficacy and reliability of CCS operations.
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Capillary pinning refers to the immobilization of CO₂ at capillary barriers when the uprising CO2 pressure is lower than the capillary entry pressure of the overlaying pore throats. Also known as local capillary trapping, it has been proposed as a fifth geologic CO₂ storage mechanism, alongside structural, solubility, residual, and mineral trapping. Despite extensive research, the fragmented terminology surrounding capillary pinning has led to confusion, making it challenging to synthesize findings effectively. Often conflated with mechanisms such as residual and hysteresis trapping, capillary pinning is commonly underestimated or completely overlooked in reservoir-scale models. Furthermore, difficulties in characterizing and upscaling small-scale geologic heterogeneities that influence capillary pinning contribute to significant uncertainties, with estimates of CO₂ trapped via this mechanism ranging from 3 % to 100 % of total CO₂ trapped via capillary actions. This review explores the fundamental mechanisms, experimental findings, and modeling approaches for assessing CO₂ capillary pinning in carbon capture and storage (CCS). It seeks to bridge the gap between the reservoir engineering community, with its extensive expertise in hydrocarbon recovery but that needs adjustments for CCS applications, and the subsurface storage community, which stands to benefit from this knowledge but often lacks access to relevant literature. Additionally, the study identifies key research opportunities to advance the understanding of capillary pinning in sedimentary rocks, ultimately enhancing the efficacy and reliability of CCS operations.
Conference paper
(2025)
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S. Hossain, C. Jacquemyn, D. Petrovskyy, G. Hampson, M. Jackson, S. Geiger
We describe an efficient and novel method to characterise multiscale geological heterogeneity and its effects on fluid flow using an open-source, sketch-based modelling and flow diagnostics tool (Rapid Reservoir Modelling. RRM). The method has three aims: (1) to generate a nested hierarchy of geologically accurate models of sedimentological heterogeneity at different scales; (2) to determine the representative elementary volume (REV) for each heterogeneity style, in order to calculate effective properties for larger scale models; and (3) to evaluate the impact of sedimentological heterogeneity on fluid flow and trapping in the hierarchy of geological models. The sketch-based modelling approach enables the construction of multiple geometrically accurate geological models and allows us to analyse them quickly using flow diagnostics and simulation tools. We illustrate this approach using examples from Triassic fluvial sandstones of the UK (Bunter Sandstone and Sherwood Sandstone), which host groundwater and geothermal resources and are targets for carbon capture and storage (CCS).
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We describe an efficient and novel method to characterise multiscale geological heterogeneity and its effects on fluid flow using an open-source, sketch-based modelling and flow diagnostics tool (Rapid Reservoir Modelling. RRM). The method has three aims: (1) to generate a nested hierarchy of geologically accurate models of sedimentological heterogeneity at different scales; (2) to determine the representative elementary volume (REV) for each heterogeneity style, in order to calculate effective properties for larger scale models; and (3) to evaluate the impact of sedimentological heterogeneity on fluid flow and trapping in the hierarchy of geological models. The sketch-based modelling approach enables the construction of multiple geometrically accurate geological models and allows us to analyse them quickly using flow diagnostics and simulation tools. We illustrate this approach using examples from Triassic fluvial sandstones of the UK (Bunter Sandstone and Sherwood Sandstone), which host groundwater and geothermal resources and are targets for carbon capture and storage (CCS).
Conference paper
(2025)
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S.E. Gasda, I. Al-Kafaji, Y. Guglielmi, C. Imrie, M. Naumann, F. Radu, T. Shinohara, R. Sheikhansari, S. De Simone, Å. Synnevåg, S. Tveit, W. Boon, A. Busch, A. Cartwright-Taylor, A. Cihan, F. Doster, N. Forbes Inskip, S. Geiger, S. Glubokovskikh
Achieving climate neutrality requires rapid scale-up of CO2 storage to gigatonne scale. Storage clusters—multiple injection sites sharing regional aquifers—offer economic benefits but introduce new challenges in subsurface pressure management. Elevated reservoir pressures can lead to fault slip and leakage, generating environmental and operational risks that span beyond individual license areas. Current site-focused workflows are insufficient for characterizing such cross-boundary effects.
This work introduces the research activities and key ideas of the international research project MuPSI which develops an integrated, multiscale screening and simulation approach to assess geomechanical risks in storage clusters. We present results of a new screening workflow that enables rapid evaluation of pressure interference and fault activation risk across regional aquifers. This is coupled with high-resolution modeling of fault response and new software to bridge region-, project-, and fault-scales. A new highly efficient approach for pressure-stress coupling offers greater software flexibility in geomechanical assessment of individual projects.
The approach is demonstrated using North Sea case studies, including the Horda Platform (Norway) and East Mey (UK). Outputs will support operators and regulators in improving investment decisions, permitting, and cross-license coordination. MuPSI also delivers stakeholder training and knowledge-transfer tools to accelerate adoption of robust, risk-informed storage cluster design. ...
This work introduces the research activities and key ideas of the international research project MuPSI which develops an integrated, multiscale screening and simulation approach to assess geomechanical risks in storage clusters. We present results of a new screening workflow that enables rapid evaluation of pressure interference and fault activation risk across regional aquifers. This is coupled with high-resolution modeling of fault response and new software to bridge region-, project-, and fault-scales. A new highly efficient approach for pressure-stress coupling offers greater software flexibility in geomechanical assessment of individual projects.
The approach is demonstrated using North Sea case studies, including the Horda Platform (Norway) and East Mey (UK). Outputs will support operators and regulators in improving investment decisions, permitting, and cross-license coordination. MuPSI also delivers stakeholder training and knowledge-transfer tools to accelerate adoption of robust, risk-informed storage cluster design. ...
Achieving climate neutrality requires rapid scale-up of CO2 storage to gigatonne scale. Storage clusters—multiple injection sites sharing regional aquifers—offer economic benefits but introduce new challenges in subsurface pressure management. Elevated reservoir pressures can lead to fault slip and leakage, generating environmental and operational risks that span beyond individual license areas. Current site-focused workflows are insufficient for characterizing such cross-boundary effects.
This work introduces the research activities and key ideas of the international research project MuPSI which develops an integrated, multiscale screening and simulation approach to assess geomechanical risks in storage clusters. We present results of a new screening workflow that enables rapid evaluation of pressure interference and fault activation risk across regional aquifers. This is coupled with high-resolution modeling of fault response and new software to bridge region-, project-, and fault-scales. A new highly efficient approach for pressure-stress coupling offers greater software flexibility in geomechanical assessment of individual projects.
The approach is demonstrated using North Sea case studies, including the Horda Platform (Norway) and East Mey (UK). Outputs will support operators and regulators in improving investment decisions, permitting, and cross-license coordination. MuPSI also delivers stakeholder training and knowledge-transfer tools to accelerate adoption of robust, risk-informed storage cluster design.
This work introduces the research activities and key ideas of the international research project MuPSI which develops an integrated, multiscale screening and simulation approach to assess geomechanical risks in storage clusters. We present results of a new screening workflow that enables rapid evaluation of pressure interference and fault activation risk across regional aquifers. This is coupled with high-resolution modeling of fault response and new software to bridge region-, project-, and fault-scales. A new highly efficient approach for pressure-stress coupling offers greater software flexibility in geomechanical assessment of individual projects.
The approach is demonstrated using North Sea case studies, including the Horda Platform (Norway) and East Mey (UK). Outputs will support operators and regulators in improving investment decisions, permitting, and cross-license coordination. MuPSI also delivers stakeholder training and knowledge-transfer tools to accelerate adoption of robust, risk-informed storage cluster design.