Pub Date : 2025-10-01Epub Date: 2025-10-11DOI: 10.1016/j.ijggc.2025.104488
Saeid Barzegar, Hamed M. Kermani, Hamidreza M. Nick
Well integrity during and after the abandonment of CO2-injected wells is a critical concern in subsurface carbon storage. Cement sheaths used for sealing must maintain long-term durability under chemically aggressive conditions, particularly in the presence of CO2-rich fluids. The present study simulates a multi-component reactive diffusion in cementitious materials with a focus on understanding the self-healing behavior of cement in contact with CO2. This model considers the primary phases of hydrated G Class, a high sulfate-resistant grade typically used for subsurface wellbores, that contains Calcium Silicate Hydrate, Portlandite, Hydrotalcite, Monosulfoaluminate, C3FH6, and Ettringite. The model predicts the mineralogical alterations and the propagation of the dissolved CO2 front under varying temperature and pressure conditions. The results indicate how the multi-component reactive transport leads to an efficient healing of the cement sheath by reducing porosity at the carbonation front and how both temperature and pressure conditions notably influence the healing zone. Furthermore, the analysis demonstrates how temperature, pressure, and porosity changes impact the diffusive CO2 propagation. Importantly, considering the interaction between chemical reactions and changes in the properties of the porous media, an empirical relationship is proposed to estimate the long-term durability and performance of G-class cement used in abandonment applications.
{"title":"Insights into cement healing under long-term carbonation","authors":"Saeid Barzegar, Hamed M. Kermani, Hamidreza M. Nick","doi":"10.1016/j.ijggc.2025.104488","DOIUrl":"10.1016/j.ijggc.2025.104488","url":null,"abstract":"<div><div>Well integrity during and after the abandonment of CO<sub>2</sub>-injected wells is a critical concern in subsurface carbon storage. Cement sheaths used for sealing must maintain long-term durability under chemically aggressive conditions, particularly in the presence of CO<sub>2</sub>-rich fluids. The present study simulates a multi-component reactive diffusion in cementitious materials with a focus on understanding the self-healing behavior of cement in contact with CO<sub>2</sub>. This model considers the primary phases of hydrated G Class, a high sulfate-resistant grade typically used for subsurface wellbores, that contains Calcium Silicate Hydrate, Portlandite, Hydrotalcite, Monosulfoaluminate, C<sub>3</sub>FH<sub>6</sub>, and Ettringite. The model predicts the mineralogical alterations and the propagation of the dissolved CO<sub>2</sub> front under varying temperature and pressure conditions. The results indicate how the multi-component reactive transport leads to an efficient healing of the cement sheath by reducing porosity at the carbonation front and how both temperature and pressure conditions notably influence the healing zone. Furthermore, the analysis demonstrates how temperature, pressure, and porosity changes impact the diffusive CO<sub>2</sub> propagation. Importantly, considering the interaction between chemical reactions and changes in the properties of the porous media, an empirical relationship is proposed to estimate the long-term durability and performance of G-class cement used in abandonment applications.</div></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"147 ","pages":"Article 104488"},"PeriodicalIF":5.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145325750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01Epub Date: 2025-09-30DOI: 10.1016/j.ijggc.2025.104482
Jiachao Ge , Zain Rasheed , Yamin Wang , Saira , Furqan Hussain
Determining CO2-water drainage relative permeability generally requires laboratory experiments, followed by numerical history matching. However, achieving low water saturations in the laboratory is challenging. Consequently, the relative permeability values at these low saturations—though essential for field-scale modelling—must be extrapolated, introducing significant uncertainty.
Previous studies used continuous mathematical functions—such as Corey or LET—to define relative permeability curves across the full saturation range. In such functions, changes to curve parameters affected both high and low saturation values, masking the specific uncertainty present at low saturations. In this study, we reanalyzed published data revealing a wide range of plausible relative permeability values at low water saturation, all of which yield equally good history matches—indicating substantial hidden uncertainty in this region.
To mitigate this, we performed laboratory experiments with extended injection of water-saturated CO₂ to 78 pore volumes (PV), achieving 34 % water saturations, much lower than commonly reported. Following this, desaturation was performed at constant pressure using a porous plate to further reduce water saturation to 0.225, enabling direct measurement of maximum CO₂ relative permeability. Results indicate that extending CO2 injection reduces uncertainty in relative permeability at lower saturations, though experimental limitations persist below 0.34 water saturation. Including porous plate data significantly improves reliability by applying higher capillary pressures representative of field conditions.
This work highlights the necessity of advanced experimental designs to extend the reliability of CO₂-water relative permeability measurements to lower water saturations. These findings are crucial for enhancing predictive accuracy in field-scale CO₂ sequestration modelling.
{"title":"Laboratory and literature insights into uncertainty in CO2-water relative permeability at low water saturations","authors":"Jiachao Ge , Zain Rasheed , Yamin Wang , Saira , Furqan Hussain","doi":"10.1016/j.ijggc.2025.104482","DOIUrl":"10.1016/j.ijggc.2025.104482","url":null,"abstract":"<div><div>Determining CO<sub>2</sub>-water drainage relative permeability generally requires laboratory experiments, followed by numerical history matching. However, achieving low water saturations in the laboratory is challenging. Consequently, the relative permeability values at these low saturations—though essential for field-scale modelling—must be extrapolated, introducing significant uncertainty.</div><div>Previous studies used continuous mathematical functions—such as Corey or LET—to define relative permeability curves across the full saturation range. In such functions, changes to curve parameters affected both high and low saturation values, masking the specific uncertainty present at low saturations. In this study, we reanalyzed published data revealing a wide range of plausible relative permeability values at low water saturation, all of which yield equally good history matches—indicating substantial hidden uncertainty in this region.</div><div>To mitigate this, we performed laboratory experiments with extended injection of water-saturated CO₂ to 78 pore volumes (PV), achieving 34 % water saturations, much lower than commonly reported. Following this, desaturation was performed at constant pressure using a porous plate to further reduce water saturation to 0.225, enabling direct measurement of maximum CO₂ relative permeability. Results indicate that extending CO<sub>2</sub> injection reduces uncertainty in relative permeability at lower saturations, though experimental limitations persist below 0.34 water saturation. Including porous plate data significantly improves reliability by applying higher capillary pressures representative of field conditions.</div><div>This work highlights the necessity of advanced experimental designs to extend the reliability of CO₂-water relative permeability measurements to lower water saturations. These findings are crucial for enhancing predictive accuracy in field-scale CO₂ sequestration modelling.</div></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"147 ","pages":"Article 104482"},"PeriodicalIF":5.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study presents a techno-economic evaluation of liquefied CO2 transport via trucking, covering the full transport chain from liquefaction, buffer storage and trucking to reconditioning. The analysis spans a wide range of transport demands (25–1000 t/d) and distances (25–500 km), aiming to quantify the conditions under which trucking is a cost-effective alternative to pipeline transport. A detailed cost model was developed for each transport stage, including component-level capital and operating costs. Results indicate that trucking transport is economically favorable for long distances and low transport volumes, with its cost advantage ending beyond 400 t/d. As distance increases, trucking remains competitive at higher flow rates up to this threshold. Liquefaction is the dominant cost contributor at shorter distances, whereas the trucking part becomes the largest cost factor over longer distances. Buffer storage and reconditioning consistently contribute less to the total cost. Operational expenditure (OPEX) consistently exceeds capital expenditure (CAPEX), with energy consumption and liquefaction O&M costs together representing on average around 60% of OPEX (ranging from ∼80% for the 50 km case to ∼43% for the 500 km case). The Sensitivity analysis identifies trailer load capacity and electricity price as the most influential cost drivers, while fixed infrastructure costs have relatively minor impacts. Overall, this work provides a robust framework and practical insights for selecting cost-efficient CO2 transport methods and supports future planning of CCUS systems. Beyond its quantitative findings, this study introduces a transparent, step-by-step methodology for CO2 trucking cost assessment, filling a notable gap in existing literature.
{"title":"Techno-economic assessment of liquefied CO2 transport via trucking","authors":"Mostafa Ashkavand , Marcel Scheffler , Wolfram Heineken , Mithran Daniel Solomon , Torsten Birth-Reichert","doi":"10.1016/j.ijggc.2025.104491","DOIUrl":"10.1016/j.ijggc.2025.104491","url":null,"abstract":"<div><div>This study presents a techno-economic evaluation of liquefied CO<sub>2</sub> transport via trucking, covering the full transport chain from liquefaction, buffer storage and trucking to reconditioning. The analysis spans a wide range of transport demands (25–1000 t/d) and distances (25–500 km), aiming to quantify the conditions under which trucking is a cost-effective alternative to pipeline transport. A detailed cost model was developed for each transport stage, including component-level capital and operating costs. Results indicate that trucking transport is economically favorable for long distances and low transport volumes, with its cost advantage ending beyond 400 t/d. As distance increases, trucking remains competitive at higher flow rates up to this threshold. Liquefaction is the dominant cost contributor at shorter distances, whereas the trucking part becomes the largest cost factor over longer distances. Buffer storage and reconditioning consistently contribute less to the total cost. Operational expenditure (OPEX) consistently exceeds capital expenditure (CAPEX), with energy consumption and liquefaction O&M costs together representing on average around 60% of OPEX (ranging from ∼80% for the 50 km case to ∼43% for the 500 km case). The Sensitivity analysis identifies trailer load capacity and electricity price as the most influential cost drivers, while fixed infrastructure costs have relatively minor impacts. Overall, this work provides a robust framework and practical insights for selecting cost-efficient CO<sub>2</sub> transport methods and supports future planning of CCUS systems. Beyond its quantitative findings, this study introduces a transparent, step-by-step methodology for CO<sub>2</sub> trucking cost assessment, filling a notable gap in existing literature.</div></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"147 ","pages":"Article 104491"},"PeriodicalIF":5.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145325749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01Epub Date: 2025-10-15DOI: 10.1016/j.ijggc.2025.104498
Debanjan Chandra , Auke Barnhoorn
CO2 injection into porous sandstone reservoirs offers a promising pathway to curb anthropogenic carbon emissions, but poses risks of leakage and induced seismicity from stress perturbations and fault reactivation without meticulous monitoring. Here, we present a time-lapse monitoring approach based on laboratory measurements of ultrasonic Vp, Vs and corresponding peak amplitudes in critically stressed, partially saturated North Sea sandstones (porosity 9–23%). Our experiments show that Vp and Vs exhibit higher sensitivity (4–15%) to stress changes compared to fluid saturation changes (0.8–1%), whereas amplitudes are more responsive (30–500%) to saturation, showing staggered change when brine is displaced by CO2. Under pure stress perturbation, amplitude variations are smaller (10–50%). During elastic deformation, the Vp/Vs ratio decreases while the ratio of their corresponding amplitudes increases, underscoring the need for both P- and S-wave measurements. Velocity and amplitude changes are more pronounced in high-porosity rocks. In a critically stressed state (beyond yield/before failure), the rise in pore fluid density from CO2 injection boosts shear wave amplitudes, offsetting attenuation from inelastic deformation. Knowing the pre-injection stress state enables these velocity and amplitude trends to serve as robust indicators of reservoir conditions during and after CO2 injection. This cost-effective approach can be adapted to reservoir-scale monitoring and extends beyond CCS, supporting enhanced detection of stress and fluid-induced changes in subsurface formations.
{"title":"Ultrasonic response of a brine-saturated reservoir rock during coupled stress and fluid perturbation during liquid-CO2 injection","authors":"Debanjan Chandra , Auke Barnhoorn","doi":"10.1016/j.ijggc.2025.104498","DOIUrl":"10.1016/j.ijggc.2025.104498","url":null,"abstract":"<div><div>CO<sub>2</sub> injection into porous sandstone reservoirs offers a promising pathway to curb anthropogenic carbon emissions, but poses risks of leakage and induced seismicity from stress perturbations and fault reactivation without meticulous monitoring. Here, we present a time-lapse monitoring approach based on laboratory measurements of ultrasonic Vp, Vs and corresponding peak amplitudes in critically stressed, partially saturated North Sea sandstones (porosity 9–23%). Our experiments show that Vp and Vs exhibit higher sensitivity (4–15%) to stress changes compared to fluid saturation changes (0.8–1%), whereas amplitudes are more responsive (30–500%) to saturation, showing staggered change when brine is displaced by CO<sub>2</sub>. Under pure stress perturbation, amplitude variations are smaller (10–50%). During elastic deformation, the Vp/Vs ratio decreases while the ratio of their corresponding amplitudes increases, underscoring the need for both P- and S-wave measurements. Velocity and amplitude changes are more pronounced in high-porosity rocks. In a critically stressed state (beyond yield/before failure), the rise in pore fluid density from CO<sub>2</sub> injection boosts shear wave amplitudes, offsetting attenuation from inelastic deformation. Knowing the pre-injection stress state enables these velocity and amplitude trends to serve as robust indicators of reservoir conditions during and after CO<sub>2</sub> injection. This cost-effective approach can be adapted to reservoir-scale monitoring and extends beyond CCS, supporting enhanced detection of stress and fluid-induced changes in subsurface formations.</div></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"147 ","pages":"Article 104498"},"PeriodicalIF":5.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145325751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01Epub Date: 2025-10-16DOI: 10.1016/j.ijggc.2025.104500
Ward Peeters, Randi Neerup, Philip L. Fosbøl
Amine-based carbon capture is one of the most widely used technologies for mitigating industrial CO₂ emissions. However, solvent degradation significantly compromises process efficiency and economic viability. This review critically examines both thermal and oxidative degradation mechanisms, emphasizing how operational conditions, such as flue gas composition, CO₂ loading, temperature, and pressure, influence degradation. The catalytic role of dissolved metals in oxidative degradation and the interconnection with corrosion is an important aspect of solvent degradation. Beyond chemical mechanisms, practical mitigation strategies including the use of inhibitors, solvent reclamation methods, and solvent selection criteria are discussed in detail. The limitations of current degradation monitoring techniques are also evaluated, emphasizing the need for real-time analytical solutions.
This review fills in a critical gap in the literature. While previous review papers provide a strong foundation on solvent degradation, this review goes a step further by focusing on the industrial implications and practical mitigation strategies. In addition to summarizing key degradation pathways, special attention is given to the role of metals in accelerating oxidative degradation through autocatalytic effects. This work also highlights how these mechanisms impact long-term solvent stability and operational efficiency. By covering both chemical insights and real-world challenges, this review aims to bridge the gap between laboratory findings and industrial application.
{"title":"Solvent degradation & influences on amine-based carbon capture operations","authors":"Ward Peeters, Randi Neerup, Philip L. Fosbøl","doi":"10.1016/j.ijggc.2025.104500","DOIUrl":"10.1016/j.ijggc.2025.104500","url":null,"abstract":"<div><div>Amine-based carbon capture is one of the most widely used technologies for mitigating industrial CO₂ emissions. However, solvent degradation significantly compromises process efficiency and economic viability. This review critically examines both thermal and oxidative degradation mechanisms, emphasizing how operational conditions, such as flue gas composition, CO₂ loading, temperature, and pressure, influence degradation. The catalytic role of dissolved metals in oxidative degradation and the interconnection with corrosion is an important aspect of solvent degradation. Beyond chemical mechanisms, practical mitigation strategies including the use of inhibitors, solvent reclamation methods, and solvent selection criteria are discussed in detail. The limitations of current degradation monitoring techniques are also evaluated, emphasizing the need for real-time analytical solutions.</div><div>This review fills in a critical gap in the literature. While previous review papers provide a strong foundation on solvent degradation, this review goes a step further by focusing on the industrial implications and practical mitigation strategies. In addition to summarizing key degradation pathways, special attention is given to the role of metals in accelerating oxidative degradation through autocatalytic effects. This work also highlights how these mechanisms impact long-term solvent stability and operational efficiency. By covering both chemical insights and real-world challenges, this review aims to bridge the gap between laboratory findings and industrial application.</div></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"147 ","pages":"Article 104500"},"PeriodicalIF":5.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145321355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Given the severe climate crisis and the urgent need to limit the adverse effects of global warming, drastic changes are required across various industries. Among them, the iron and steel sector is a major contributor to greenhouse gas emissions, accounting for approximately 7 % of global CO2 emissions. This study proposes the integration of innovative carbon capture technologies, such as DISPLACE and CASOH, into a conventional BF-BOF (Blast Furnace-Basic Oxygen Furnace) steelmaking process. A comprehensive techno-economic analysis was conducted, supported by simulations performed in Aspen Plus, to optimize the integration of these technologies. The study suggests a redesigned gas distribution system within the BF-BOF steel plant, incorporating oxy-fired units to facilitate post-combustion carbon capture and minimize the plant emissions. The analysis reveals that, employing CASOH for pre-combustion CO2 capture to decarbonize a mixture of BFG (Blast Furnace Gas) and BOFG (Basic Oxygen Furnace Gas), combined with DISPLACE for decarbonizing flue gases from hot stoves, sinter plant, and reheating ovens, 72 % reduction in CO2 emissions and a SPECCA around 0 GJ/tCO2 can be achieved. This is attainable within a renewable electricity scenario, at a cost of 138 € per ton of CO2 avoided. Lower CO2 avoidance values can also be achieved by treating less exhaust gases with reduction in both SPECCA and costs.
{"title":"Integration of CASOH and DISPLACE technologies in a steel plant for the mitigation of CO2 emissions – A techno-economic analysis","authors":"Nicola Zecca , Santiago Zapata Boada , Vincenzo Spallina , Giampaolo Manzolini","doi":"10.1016/j.ijggc.2025.104478","DOIUrl":"10.1016/j.ijggc.2025.104478","url":null,"abstract":"<div><div>Given the severe climate crisis and the urgent need to limit the adverse effects of global warming, drastic changes are required across various industries. Among them, the iron and steel sector is a major contributor to greenhouse gas emissions, accounting for approximately 7 % of global CO<sub>2</sub> emissions. This study proposes the integration of innovative carbon capture technologies, such as DISPLACE and CASOH, into a conventional BF-BOF (Blast Furnace-Basic Oxygen Furnace) steelmaking process. A comprehensive techno-economic analysis was conducted, supported by simulations performed in Aspen Plus, to optimize the integration of these technologies. The study suggests a redesigned gas distribution system within the BF-BOF steel plant, incorporating oxy-fired units to facilitate post-combustion carbon capture and minimize the plant emissions. The analysis reveals that, employing CASOH for pre-combustion CO<sub>2</sub> capture to decarbonize a mixture of BFG (Blast Furnace Gas) and BOFG (Basic Oxygen Furnace Gas), combined with DISPLACE for decarbonizing flue gases from hot stoves, sinter plant, and reheating ovens, 72 % reduction in CO<sub>2</sub> emissions and a SPECCA around 0 GJ/t<sub>CO2</sub> can be achieved. This is attainable within a renewable electricity scenario, at a cost of 138 € per ton of CO<sub>2</sub> avoided. Lower CO<sub>2</sub> avoidance values can also be achieved by treating less exhaust gases with reduction in both SPECCA and costs.</div></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"147 ","pages":"Article 104478"},"PeriodicalIF":5.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01Epub Date: 2025-09-25DOI: 10.1016/j.ijggc.2025.104480
J.A. Ademilola, Jack C. Pashin
Assessing the geomechanical integrity of seals and storage reservoirs is important prior to carbon dioxide (CO2) storage because it can determine the safety of storage, containment and stability of a proposed storage, and helps minimize the possibility of CO2 leakage. This study has integrated simultaneous seismic inversion, multi-attribute transform, and a probabilistic neural network, and uses geophysical well logs to evaluate geomechanical parameters for reservoir and seal integrity assessment of Cenozoic strata. Results indicate that candidate reservoir and seal units identified from wells in the study area possesses greater failure strength than the in-situ stresses and are geomechanically stable. However, there is possibility of tensile failure occurring when the injection get to the mature stage and the effective minimum stress crosses the zero effective normal stress line. Each candidate reservoir storage unit has higher rock strength than its overlying shale layer. The thickness of the caprock units is adequately high to provide effective seal and the thickness of the reservoirs are sufficient to support optimal CO2 storage resources in the study area. The friction angle of Pliocene–Pleistocene strata is adequately high especially in the eastern part of the study area to minimize the risk of fault reactivation and associated deformation. Additional work can be performed to simulate the response of seals, reservoirs, and geomechanical deformation at variable rates and durations of injection.
{"title":"Integrated multi-attribute transform and seismic driven machine learning technique for geomechanical assessment of Cenozoic reservoirs and seal integrity for carbon storage in the Central Gulf of Mexico","authors":"J.A. Ademilola, Jack C. Pashin","doi":"10.1016/j.ijggc.2025.104480","DOIUrl":"10.1016/j.ijggc.2025.104480","url":null,"abstract":"<div><div>Assessing the geomechanical integrity of seals and storage reservoirs is important prior to carbon dioxide (CO<sub>2</sub>) storage because it can determine the safety of storage, containment and stability of a proposed storage, and helps minimize the possibility of CO<sub>2</sub> leakage. This study has integrated simultaneous seismic inversion, multi-attribute transform, and a probabilistic neural network, and uses geophysical well logs to evaluate geomechanical parameters for reservoir and seal integrity assessment of Cenozoic strata. Results indicate that candidate reservoir and seal units identified from wells in the study area possesses greater failure strength than the in-situ stresses and are geomechanically stable. However, there is possibility of tensile failure occurring when the injection get to the mature stage and the effective minimum stress crosses the zero effective normal stress line. Each candidate reservoir storage unit has higher rock strength than its overlying shale layer. The thickness of the caprock units is adequately high to provide effective seal and the thickness of the reservoirs are sufficient to support optimal CO<sub>2</sub> storage resources in the study area. The friction angle of Pliocene–Pleistocene strata is adequately high especially in the eastern part of the study area to minimize the risk of fault reactivation and associated deformation. Additional work can be performed to simulate the response of seals, reservoirs, and geomechanical deformation at variable rates and durations of injection.</div></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"147 ","pages":"Article 104480"},"PeriodicalIF":5.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145156260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01Epub Date: 2025-10-10DOI: 10.1016/j.ijggc.2025.104487
Seunghwan Baek , Leon Hibbard , Nate Mitchell , Delphine Appriou , Robert Dilmore , Md․Lal Mamud
For geologic systems where carbon dioxide (CO2) is injected underground, existing wells represent potential pathways for fluid migration. This study introduces a novel deep learning model to quantify the likelihood and potential magnitude of fluid migration through wellbores at sites with intermediate aquifers or thief zones between the injection units and underground drinking water sources. Synthetic datasets, generated using reservoir simulations, captured a wide range of subsurface conditions, well attributes, operational parameters, and fluid migration scenarios. Among the regression models developed to predict brine and CO2 leakage rates and CO2 saturations along leaky wellbores, convolutional neural network (CNN) outperformed both Light Gradient Boosting Machine and deep neural network. Additionally, a CNN-based classification model was created to predict whether brine and CO₂ would leak along a wellbore, further improving performance over regression alone. The best models were integrated into the National Risk Assessment Partnership Open-source Integrated Assessment Model for rapid, stochastic assessment of storage system containment and leakage risks. A case study demonstrated the model’s ability to simulate fluid migration through existing wells with multiple intermediate aquifers. This computationally efficient wellbore model offers value in support of site performance evaluation and risk-informed decision making by stakeholders.
{"title":"Deep-learning-enhanced assessment of wellbore barrier effectiveness in geologic storage systems with intermediate aquifers","authors":"Seunghwan Baek , Leon Hibbard , Nate Mitchell , Delphine Appriou , Robert Dilmore , Md․Lal Mamud","doi":"10.1016/j.ijggc.2025.104487","DOIUrl":"10.1016/j.ijggc.2025.104487","url":null,"abstract":"<div><div>For geologic systems where carbon dioxide (CO<sub>2</sub>) is injected underground, existing wells represent potential pathways for fluid migration. This study introduces a novel deep learning model to quantify the likelihood and potential magnitude of fluid migration through wellbores at sites with intermediate aquifers or thief zones between the injection units and underground drinking water sources. Synthetic datasets, generated using reservoir simulations, captured a wide range of subsurface conditions, well attributes, operational parameters, and fluid migration scenarios. Among the regression models developed to predict brine and CO<sub>2</sub> leakage rates and CO<sub>2</sub> saturations along leaky wellbores, convolutional neural network (CNN) outperformed both Light Gradient Boosting Machine and deep neural network. Additionally, a CNN-based classification model was created to predict whether brine and CO₂ would leak along a wellbore, further improving performance over regression alone. The best models were integrated into the National Risk Assessment Partnership Open-source Integrated Assessment Model for rapid, stochastic assessment of storage system containment and leakage risks. A case study demonstrated the model’s ability to simulate fluid migration through existing wells with multiple intermediate aquifers. This computationally efficient wellbore model offers value in support of site performance evaluation and risk-informed decision making by stakeholders.</div></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"147 ","pages":"Article 104487"},"PeriodicalIF":5.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01Epub Date: 2025-10-07DOI: 10.1016/j.ijggc.2025.104483
Sahar Bakhshian , Hassan Dashtian , Arya Chavoshi , Mahdi Haddad , Susan D. Hovorka , Michael H. Young , Katherine D. Romanak , Mohsen Ahmadian
The risk of CO and brine leakage to environmental receptors is one of the main concerns in geologic CO storage. Legacy wells from past oil and gas activities may be located within the area of review, necessitating continuous monitoring to ensure they are properly sealed to prevent fluid migration. Deployment of an efficient monitoring system for early detection of leakage from failed wells is imperative to mitigate environmental and financial risks. This study proposes a cost-effective near-surface monitoring package capable of real-time surveillance of plugged and abandoned (P&A) wells. Controlled pilot-scale CO and water release experiments were conducted to identify soil properties that are most sensitive to leakage in the near-surface vadose zone above P&A well stubs. Multiple release scenarios with different rates and durations were implemented, and machine learning techniques were applied to identify anomalous data patterns caused by leakage. Among measured parameters, soil electrical conductivity (EC) was the most sensitive indicator of leakage. Several machine learning models, including Logistic Regression, K-Nearest Neighbors, Support Vector Machine, Random Forest, XGBoost, and LightGBM, were evaluated for anomaly detection in EC data. Tree-based models outperformed traditional classifiers, with Random Forest achieving the lowest false alarm rate and XGBoost yielding the highest detection rate. Uncertainty quantification using Conformal Prediction showed that LightGBM had the highest confidence in anomaly prediction. Although the experiments were performed under controlled conditions, the approach demonstrates a relatively promising, low-cost monitoring technique for leakage detection for near-surface monitoring of legacy wells.
{"title":"Near-Surface Monitoring of Plugged and Abandoned Wells for Real-Time Leakage Detection in Geologic Carbon Storage","authors":"Sahar Bakhshian , Hassan Dashtian , Arya Chavoshi , Mahdi Haddad , Susan D. Hovorka , Michael H. Young , Katherine D. Romanak , Mohsen Ahmadian","doi":"10.1016/j.ijggc.2025.104483","DOIUrl":"10.1016/j.ijggc.2025.104483","url":null,"abstract":"<div><div>The risk of CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> and brine leakage to environmental receptors is one of the main concerns in geologic CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> storage. Legacy wells from past oil and gas activities may be located within the area of review, necessitating continuous monitoring to ensure they are properly sealed to prevent fluid migration. Deployment of an efficient monitoring system for early detection of leakage from failed wells is imperative to mitigate environmental and financial risks. This study proposes a cost-effective near-surface monitoring package capable of real-time surveillance of plugged and abandoned (P&A) wells. Controlled pilot-scale CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> and water release experiments were conducted to identify soil properties that are most sensitive to leakage in the near-surface vadose zone above P&A well stubs. Multiple release scenarios with different rates and durations were implemented, and machine learning techniques were applied to identify anomalous data patterns caused by leakage. Among measured parameters, soil electrical conductivity (EC) was the most sensitive indicator of leakage. Several machine learning models, including Logistic Regression, K-Nearest Neighbors, Support Vector Machine, Random Forest, XGBoost, and LightGBM, were evaluated for anomaly detection in EC data. Tree-based models outperformed traditional classifiers, with Random Forest achieving the lowest false alarm rate and XGBoost yielding the highest detection rate. Uncertainty quantification using Conformal Prediction showed that LightGBM had the highest confidence in anomaly prediction. Although the experiments were performed under controlled conditions, the approach demonstrates a relatively promising, low-cost monitoring technique for leakage detection for near-surface monitoring of legacy wells.</div></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"147 ","pages":"Article 104483"},"PeriodicalIF":5.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01Epub Date: 2025-10-16DOI: 10.1016/j.ijggc.2025.104493
Kevin L. McCormack , Tom Bratton , Adewale Amosu , Lianjie Huang , David Li , Jeffrey Burghardt , William Ampomah
A key consideration when planning the injection of fluids into the subsurface is the potential for induced seismicity. While avoiding major faults during injection is ideal, a detailed understanding of the fault slip potential of faults at the site enables operators to prevent large seismic events. Induced seismicity forecasting relies on combining fault surface geometries—here, we utilize ant-tracking of three-dimensional seismic images to map faults in the San Juan Basin, New Mexico—and the state of stress, which we evaluate using three distinct models. The fault slip potential is quantified using the Coulomb failure function, which measures proximity to frictional failure, based on the states of stress and fault geometries for both individual faults and a complete fault suite (n = 51). The differences observed across the three stress states are subtle, but the statistical distributions of the Coulomb failure function suggest that uncertainties vary between the models. Notably, our findings reveal that both the linear-elastic approximation and the failure criterion yield similar fault slip potentials. Consequently, the choice of method for determining the state of stress most relevant to a project depends on the specific requirements and context of the project.
{"title":"A comparative analysis of states of stress for analyzing fault slip potential","authors":"Kevin L. McCormack , Tom Bratton , Adewale Amosu , Lianjie Huang , David Li , Jeffrey Burghardt , William Ampomah","doi":"10.1016/j.ijggc.2025.104493","DOIUrl":"10.1016/j.ijggc.2025.104493","url":null,"abstract":"<div><div>A key consideration when planning the injection of fluids into the subsurface is the potential for induced seismicity. While avoiding major faults during injection is ideal, a detailed understanding of the fault slip potential of faults at the site enables operators to prevent large seismic events. Induced seismicity forecasting relies on combining fault surface geometries—here, we utilize ant-tracking of three-dimensional seismic images to map faults in the San Juan Basin, New Mexico—and the state of stress, which we evaluate using three distinct models. The fault slip potential is quantified using the Coulomb failure function, which measures proximity to frictional failure, based on the states of stress and fault geometries for both individual faults and a complete fault suite (<em>n</em> = 51). The differences observed across the three stress states are subtle, but the statistical distributions of the Coulomb failure function suggest that uncertainties vary between the models. Notably, our findings reveal that both the linear-elastic approximation and the failure criterion yield similar fault slip potentials. Consequently, the choice of method for determining the state of stress most relevant to a project depends on the specific requirements and context of the project.</div></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"147 ","pages":"Article 104493"},"PeriodicalIF":5.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145325752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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