CO2 Saturation Research Articles

A rock physics modelling approach for time‐lapse monitoring and characterization of fluid–rock interactions in hydrocarbon reservoirs

AbstractOne of the research gaps is to understand the development of seismic characteristics of gas‐saturated rock along with the change in rock properties because of chemical reactions. We suggest a method to explain the change in elastic properties brought on by CO2 injection in a rock by capturing the physico‐chemical interactions observed in the laboratory in a theory of rock physics. To explain the laboratory‐measured physical characteristics and velocity of a dynamic rock–fluid system, we include a time‐dependent component in the existing cemented‐sand model. We demonstrate theoretically the rate of change of elastic moduli of the dry frame by incorporating the measured rate of change of cement due to chemical dissolution. We adapt the theory such that it can be applied to the field data and calibrate the theory using water‐saturated well log data from the Ankleshwar field, an established oil field in the Cambay basin, western India. Theoretical time‐lapse logs of velocity and density are then produced using the theory over a range of CO2 saturations, assuming cementing material in grain contacts and geochemical interactions comparable to those observed in the laboratory rock. Then, using theoretical logs, corresponding time‐lapse synthetic seismic data are produced for different saturation. These data clearly demonstrate that, for a uniform model, velocity decreases by up to 18% as CO2 saturation increases from 0% to 20% (ignoring the chemical effect), and that, for a specific saturation, say 20%, chemical effects result in a 17% decrease in velocity from the present to the end of 60 years. However, for the patchy model, velocity decreases maximum by 14% and 16% due to varying saturation and chemical reaction. Moreover, for a particular saturation of CO2, say 20%, velocity differs by 16% for different types of models. This research contributes to making strategy for CO2‐sequestration in a designated field.

Research on CO2 sequestration in saline aquifers with different relative permeability considering CO2 phase conditions

Saline aquifers are the most feasible potential site for the storage of CO2. The behavior of CO2 in different phase states may significantly affect the flow properties and sequestration efficiency. It is important to understand and predict the effects of different CO2 phases. This study conducted relative permeability tests under two experimental conditions with CO2 in different phases. Incorporating experimental data into reservoir-scale simulations to analyze the effects of different phases of CO2 on structural, solubility, and residual sequestration mechanisms, and to predict CO2 behavior in saline aquifers. The results show that the CO2 relative permeability and residual CO2 saturation are high under supercritical conditions. It is more favorable to consider the relative permeability and hysteresis effects on the supercritical CO2 results, with a more dispersed distribution of CO2 at the bottom of the reservoir. There was a significant difference in residual sequestration, with the gaseous group showing a 14.16 % reduction in residual sequestration and a 4.27 % reduction in total sequestration compared to the supercritical group. The ratio of structural sequestration, solubility sequestration, and residual sequestration in the total sequestration in this study is about 50 %:30 %:20 %.

Evaluation of CO2 Leakage Potential through Fault Instability in CO2 Geological Sequestration by Coupled THMC Modelling

A faulted saline aquifer system was simulated in a coupled thermal-hydraulic-mechanical-chemical (THMC) framework to examine the potential breaching of the caprock seal from long-term CO2 sequestration. The pH of the brines steadily dropped from 7.5 to 4.7 due to the continuous injection of scCO2 (supercritical CO2), which was caused by the rapid dissolution of calcite in the reservoir and associated fault zones, alongside alterations in the concentrations of primary and secondary minerals within the formation. The increase in pore pressure with the continuous injection of scCO2 triggered fault reactivation at 6y with the resultant leakage of CO2 along the fault. This builds CO2 saturation inside the fault at 7y to six-fold higher than pre-slip. Continuing shear reactivation and creation of reactive surface area following the initial CO2 leakage accelerates dissolution/precipitation reactions, in turn further increasing porosity and permeability of the reservoir and fault. In particular, the permeability and porosity in the fault zone were increased by only 2% and 6%, respectively – staunched by competitive feedbacks in dissolution countered by precipitation that are individually much larger. Comparison of mineral concentrations adjacent to the fault before-and-after instability revealed that the development of shear failure also promotes the transport of reactivated minerals into the fault zone. Among them, feldspar changes most significantly in later stages, dominated by dissolution with the volume fraction decreasing by 80% and increasing the aqueous concentration of K+ by approximately an order of magnitude. However, secondary minerals counter this dissolution through precipitation with the volume fraction of kaolinite increasing by an order of magnitude compared with the original fraction. Finally, the evolution of the fault sealing coefficient (FS) demonstrates that the porosity and permeability exert a pivotal influence in controlling the self-sealing behavior in the basal of the fault, while the upper fault layer exhibits self-enhancing response. A notable observation is that changes in mineral ion concentrations in fault zones could be applied as a significant diagnostic signal to monitor fault stability and the potential for progress of self-sealing behavior.

Zeta Potential of Supercritical CO2‐Water‐Sandstone Systems and Its Correlation With Wettability and Residual Subsurface Trapping of CO2

AbstractAlthough CO2 geological storage (CGS) is thought to be one of the most promising technologies to sequester the anthropogenic CO2 to mitigate the climate change, implementation of the method is still challenging due to lack of fundamental understanding of controls of wettability, which is responsible for residual trapping of the gas and its flow dynamics. One of the key parameters that controls the wetting state is the zeta potential, ζ, at rock‐water and CO2‐water interfaces. ζ in systems comprising rocks, carbonated aqueous solutions and immiscible supercritical CO2 have not been measured prior to this study, where we detail the experimental protocol that enables measuring ζ in such systems, and report novel experimental data on the multi‐phase ζ. We also demonstrate for the first time that ζ of supercritical CO2‐water interface is negative with a magnitude greater that 14 mV. Moreover, our experimental results suggest that presence of multi‐valent cations in tested solutions causes a shift of wettability toward intermediate‐wet state. We introduce a new parameter that combines multi‐phase ζ and relative permeability endpoints to characterize the wetting state and residual supercritical CO2 saturation. Based on these results, we demonstrate that ζ measurements could serve as a powerful experimental method for predicting CGS efficiency and/or for designing injection of aqueous solutions with bespoke composition prior to implementing CGS to improve the residual CO2 trapping in sandstone formations.

1-D electrical inversion sensitivity applied to CO2 geological storage monitoring

Discussions on the effects of anthropogenic emissions of greenhouse gas and their consequences on climate change have gained public notoriety in recent decades. The capture of carbon dioxide (CO2) from industrial sources and its subsequent storage in geological reservoirs has the potential to play an important role in reducing the harmful effects of the atmosphere CO2 emissions in the medium and long term. Based on their physical properties for applying geophysical techniques, studying and evaluating the behavior of rocks in the presence of CO2 has shown high relevance. This study deals with monitoring geological reservoirs in the presence of CO2 through the electrical resistivity method to estimate the electrical properties of the rocks involved, such as CO2 saturation and electrical resistivity of the medium. Simulations were performed on a four-layer synthetic model. The results validated the applicability of the electrical method in monitoring CO2 injection and leakage.

Fluid effect on elastic properties of carbonate and implication for CO2 geological sequestration monitoring

Laboratory measurement of the elastic properties of carbonates saturated with different fluids is crucial for characterizing reservoirs and monitoring CO2 sequestration. However, it is challenging to distinguish the effects of different fluids. We measured eight carbonate samples under varying pressure and fluids saturation conditions, and conducted quantitative analysis. The measurements showed that water saturation can increase P-wave velocity (Vp), while oil and CO2 saturation may lead to an increase, decrease or no change in Vp. Meanwhile, all fluids saturation reduces the S-wave velocity (Vs). The velocities of dolomite samples are higher and less pressure-sensitive than that of limestone samples. Four attributes are adopted to distinguish the fluids effect, including elastic moduli, impedance, Vp/Vs ratio, and a newly designed fluid discrimination factor F, which is proposed by multiplying P-wave modulus and square value of density change. Among the attributes, the F factor performed the best as it achieved evident and consistent results for all the samples. Rock physics models were used to simulate the elastic behaviors with the differential effective medium model predicting Vs the best. The Gassmann’s equation correctly indicated the positive or negative changes of rock velocity after fluid saturation even though its prediction did not exactly match the data. This study highlights the impact of various pore fluids on the carbonate elastic properties through laboratory measurement and theoretical modeling, and introduces a novel fluid identification factor, providing insights for reservoir seismic characterization and CO2 sequestration monitoring.

Seasonal dynamics and regional distribution patterns of CO2 and CH4 in the north-eastern Baltic Sea

Abstract. Significant research has been carried out in the last decade to describe the CO2 system dynamics in the Baltic Sea. However, there is a lack of knowledge in this field in the NE Baltic Sea, which is the main focus of the present study. We analysed the physical forcing and hydrographic background in the study year (2018) and tried to elucidate the observed patterns of surface water CO2 partial pressure (pCO2) and methane concentrations (cCH4). Surface water pCO2 and cCH4 were continuously measured during six monitoring cruises onboard R/V Salme, covering the Northern Baltic Proper (NBP), the Gulf of Finland (GoF), and the Gulf of Riga (GoR) and all seasons in 2018. The general seasonal pCO2 pattern showed oversaturation in autumn–winter (average relative CO2 saturation 1.2) and undersaturation in spring–summer (average relative CO2 saturation 0.5), but it locally reached the saturation level during the cruises in April, May, and August in the GoR and in August in the GoF. The cCH4 was oversaturated during the entire study period, and the seasonal course was not well exposed on the background of high variability. Surface water pCO2 and cCH4 distributions showed larger spatial variability in the GoR and GoF than in the NBP for all six cruises. We linked the observed local maxima to river bulges, coastal upwelling events, fronts, and occasions when vertical mixing reached the seabed in shallow areas. Seasonal averaging over the CO2 flux suggests a weak sink for atmospheric CO2 for all basins, but high variability and the long periods between cruises (temporal gaps in observation) preclude a clear statement.

Optimization of Offshore Saline Aquifer CO2 Storage in Smeaheia Using Surrogate Reservoir Models

Machine learning-based Surrogate Reservoir Models (SRMs) can replace/augment multi-physics numerical simulations by replicating the reservoir simulation results with reduced computational effort while maintaining accuracy compared with numerical simulations. This research will demonstrate SRMs’ potential in long-term simulations and optimization of geological carbon storage in a real-world geological setting and address challenges in big data curation and model training. The present study focuses on CO2 storage in the Smeaheia saline aquifer. Two SRMs were created using Deep Neural Networks (DNNs) to predict CO2 saturation and pressure over all grid blocks for 50 years. 18 million samples and 31 features, including reservoir static and dynamic properties, build the input data. Models comprise 3–5 hidden layers with 128–512 units apiece. SRMs showed a runtime improvement of 300 times and an accuracy of 99% compared to the 3D numerical simulator. The genetic algorithm was then employed to determine the optimal rate and duration of CO2 injection, which maximizes the volume of injected CO2 while ensuring storage operations’ safety through constraints. The optimization continued for the reproduction of 100 generations, each containing 100 individuals, without any hyperparameter tuning. Finally, the optimization results confirm the significant potential of Smeaheia for storing 170 Mt CO2.

Effect of permeability anisotropy on the CO2 saturation distribution and phase change during a leakage event in a saline aquifer

Effect of permeability anisotropy on the CO2 saturation distribution and phase change during a leakage event in a saline aquifer

Role of capillary pressure on carbon dioxide sequestration: mathematical analysis

ABSTRACT Geological disposal of CO2 after capturing the gas from large emitting sources is one of the safest and most prominent methods to eliminate CO2 from the atmosphere and mitigate climate change. The heterogeneities in porosity, permeability and capillary pressure in various underground formations impact gas distribution, affecting their storage capacity. Therefore, a numerical model is developed to study the plume migration under various physical heterogeneities by upscaling the variation in capillary pressure. Accordingly, homogeneous, heterogeneous and layered formations have been considered. The influence of capillary pressure and field-scale heterogeneities, such as porosity and permeability, is incorporated using the Leverett J function. The impact of variations in capillary pressure on gas migration is calibrated in different formations for ten years of injection. The analysis project that plume evolution in different formations highly deviates and a plume length of 3410 m is obtained for layered formation. A sensitivity analysis was conducted to understand the influence of interfacial tension in formations with differing heterogeneity. The change in interfacial tension impacts the average saturation of CO2, ranging from 0.287 to 0.155 in heterogeneous aquifers. The plume migration decreases in layered and increases in homogenous and heterogeneous media with decreased interfacial tension.

Optimal monitoring design for uncertainty quantification during geologic CO[formula omitted] sequestration: A machine learning approach

An effective monitoring design is crucial to ensure the safe and permanent geologic storage of CO2. Optimal monitoring design involve an optimal placement of monitoring wells, and optimal monitoring measurement data (pressure, CO2 saturation, temperature, etc.). We developed a filtering-based data assimilation approach to design an optimal monitoring strategy for well placement and monitoring data design. To efficiently solve the optimization problem and reduce computational costs, Artificial Neural Networks are used to develop computationally efficient reduced-order models based on full-physics numerical simulations of CO2 injection in saline aquifers. We demonstrate our approach in two scenarios of CO2 leakage through legacy or abandoned wellbores where an optimal monitoring strategy are devised to reduce the uncertainty in cumulative CO2 leakage in the geologic CO2 sequestration (GCS) site. The optimal monitoring design resulted in an uncertainty reduction in the cumulative leakage of CO2 of approximately 73% and 62% in each case, respectively. The proposed approach is efficient in developing monitoring designs under geologic uncertainty and enables safe geologic carbon sequestration operations.

Coupling between the photoactivity and CO2 adsorption on rapidly thermal hydrogenated vs. conventionally annealed copper oxides deposited on TiO2 nanotubes

AbstractHighly ordered spaced titanium dioxide nanotubes were fabricated via electrochemical anodization and modified with titania nanoparticles and copper oxides. Such materials were rapidly annealed in hydrogen atmosphere or conventionally in a tube furnace in air, in which the temperature slowly increases. Applied synthesis procedure can be considered as simple, cost-effective, and environmentally friendly as it allows for reduction in used materials and enhances sustainable engineering. Manipulating the chemical composition of materials by different thermal treatments resulted in various photoelectrochemical activities and density of CO2 adsorption sites. Rapidly annealed nanotubes decorated by copper oxides exhibit excellent electrochemical properties where one electrode combines both: solar to electricity conversion (photocurrent under visible light 30 µA/cm2) and CO2 adsorption systems (18 times higher current after CO2 saturation). Rapidly thermal hydrogenated TiO2 nanotubes with copper oxides had 17 times higher photocurrent and wider absorption band (380–780 nm) than conventionally annealed ones. Furthermore, the crystal planes such as Cu (111), Cu (220), Cu2O (110), CuO (002) and Cu0, Cu+, Cu2+ oxidation states, and oxygen vacancies were recognized for hydrogenated sample. It should be highlighted that thermal annealing conditions significantly affects ability of copper oxide to CO2 adsorption and CO2 reduction reaction for hydrogenated electrode. Graphical abstract

Preparation of red mud derived eggshell coupling adsorbent and study on carbon dioxide capture performance based on experiment and density functional theory simulation

Preparing advanced CO2 capture materials is crucial for mitigating carbon emissions and alleviating global warming. Calcium-based adsorbents have attracted much attention due to their excellent environmental performance and high theoretical CO2 adsorption capacity. However, its poor cycling stability limits its widespread application. In this study, a red mud derived eggshell coupled CO2 adsorbent (RM/CaO) was prepared using solid waste RM and eggshell. The structure, CO2 capture performance, and micro-mechanism of the adsorbent were evaluated through macro micro-experiments combined with quantum mechanics simulations, to improve the adsorption performance of calcium-based adsorbents and achieve waste resource utilisation—an active, open area of research. The 1-1RM/CaO adsorbent had a specific surface area of 10.62 m2/g and a spatial structure with fused cross-linking layers. Its CO2 saturation adsorption capacity was 0.481 g/g; 171.43 % that of pure CaO. High level cycling stability can still be maintained after 15 cycles of CO2 adsorption desorption. Quantum mechanics simulations revealed that the CO2 adsorption energy on the RM/CaO (200) crystal plane can be enhanced to −8.25 eV. This indicates that the interaction between RM/CaO atoms is stronger, which is enhances the CO2 adsorption. This study optimized environmental and economic benefits by utilizing waste resources, deepened understanding of the interaction mechanism between CO2 adsorbents, and provided theoretical guidance for designing as well as optimizing future adsorbents.

Machine Learning-Driven Quantification of CO2 Plume Dynamics at Illinois Basin Decatur Project Sites Using Microseismic Data

This study utilizes machine learning to quantify CO2 plume extents by analyzing microseismic data from the Illinois Basin Decatur Project (IBDP). Leveraging a unique dataset of well logs, microseismic records, and CO2 injection metrics, this work aims to predict the temporal evolution of subsurface CO2 saturation plumes. The findings illustrate that machine learning can predict plume dynamics, revealing vertical clustering of microseismic events over distinct time periods within certain proximities to the injection well, consistent with an invasion percolation model. The buoyant CO2 plume partially trapped within sandstone intervals periodically breaches localized barriers or baffles, which act as leaky seals and impede vertical migration until buoyancy overcomes gravity and capillary forces, leading to breakthroughs along vertical zones of weakness. Between different unsupervised clustering techniques, K-Means and DBSCAN were applied and analyzed in detail, where K-means outperformed DBSCAN in this specific study by indicating the combination of the highest Silhouette Score and the lowest Davies–Bouldin Index. The predictive capability of machine learning models in quantifying CO2 saturation plume extension is significant for real-time monitoring and management of CO2 sequestration sites. The models exhibit high accuracy, validated against physical models and injection data from the IBDP, reinforcing the viability of CO2 geological sequestration as a climate change mitigation strategy and enhancing advanced tools for safe management of these operations.

Seasonal changes of dissolved CO2 and its linkage with optical characteristics of DOM in groundwater in agricultural areas

Groundwater contains significant quantities of dissolved CO2, which are crucial contributors to the global carbon cycle. Dissolved organic matter (DOM) functions as a principal carbon and energy source for microbial communities within groundwater ecosystems, yet the relationship between dissolved CO2 and optical characteristics of DOM remains ambiguous. Here, we delineate the variations in seasonal and vertical distribution of dissolved CO2 concentrations and DOM optical characteristics, and assess their interconnections in the groundwater of an agricultural region. The results showed that the average concentration of dissolved CO2 in groundwater was 11,300 ± 5,788 ppm, with the highest levels observed in summer and the lowest in winter. Additionally, shallow wells exhibited higher concentrations of dissolved CO2 compared to deep wells. The mass balance calculation suggested that 40,092 t of CO2 are released annually due to the degassing of supersaturated CO2 from groundwater extraction. Three-dimensional fluorescence with parallel factor analysis (EEM-PARAFAC) identified five components of DOM in groundwater: Components C1, C2, C3 and C4 are humic-like substances, and C5 is a tryptophan-like substance associated with protein structures. The analysis of compositional features and fluorescence indices revealed that DOM is predominantly derived from microbial sources, with mixed contributions from terrestrial sources in groundwater. Principal component analysis (PCA) showed that first two axes accounted for 74.7 % of the variance in the seasonal variation of DOM optical characteristics and dissolved CO2 concentration, which reveals that DOM decomposition contributes to CO2 saturation in groundwater. However, a larger proportion of CO2 may be derived from leaching in the vadose zone during the rainy season or irrigation periods in shallow aquifer. This study enhanced the understanding of carbon dynamics within agricultural groundwater.

Techno-economic assessment of large-scale sedimentary basin stored–CO2 geothermal power generation

One approach to reducing atmospheric carbon dioxide (CO2) emissions is to adopt carbon capture utilization and storage (CCUS) strategies. This is particularly crucial for countries to achieve their net-zero goal. In this study, we investigate the techno-economic viability of a proposed CCUS process that utilizes geologically stored CO2, associated with hydrogen (H2) production from fossil fuels, as a working fluid to extract geothermal energy from deep, large-scale, sedimentary storage formations. The process ensures permanent geological storage of all injected CO2 while generating adaptable geothermal power through supercritical CO2 turbine expansion, thus, bolstering revenue and reducing the final cost of blue hydrogen production. We simulate subsurface-wellbore fluid flow and heat transport for a representative 4-way closed anticlinal Arabian reservoir and optimize system power output, including a comprehensive and integrated economic analysis. We find that CO2 captured from an equivalent blue H2 production of ∼4.1 Mt./year can be injected at an annual rate of 0.92–1 million metric tons (Mt) per well, resulting in a cumulative sequestration of ∼1.15 gigatons (Gt) of CO2 over 11.5 years. To mitigate the risks of reaching the formation parting pressure at the crest of the anticline and ensuring sufficient CO2 saturation at the production wells, phased drilling schedules and pressure-controlled injection and production are essential. With horizontal production wells, our simulations generate an average geothermal net electricity of 164 MW. The base-case economic analysis reveals a Levelized Cost of Electricity (LCOE) of 77 $/MWh and a Net Present Value (NPV) of 480 million USD over 50 years. In contrast, vertical production wells double LCOE, and the project remains unprofitable throughout its life (negative NPV). Our economic sensitivity analysis further emphasizes how the capacity factor, electricity selling price, and drilling costs govern LCOE and NPV. On the other hand, discount rates and Opex fraction are influential yet uncertain parameters affecting the system's techno-economic outlook. Therefore, our study provides valuable insights into the benefits of geothermal energy production from over 1 Gt of stored CO2 and the associated economic landscape.

Unambiguous detection of mesospheric CO2 clouds on Mars using 2.7 μm absorption band from the ACS/TGO solar occultations

Mesospheric CO2 clouds are one of two types of carbon dioxide clouds known on Mars. We present observations of mesospheric CO2 clouds made by Atmospheric Chemistry Suite (ACS) onboard the ESA-Roscosmos ExoMars Trace Gas Orbiter (TGO). We analyzed 1663 solar occultation sessions of Thermal InfraRed (TIRVIM) and Middle InfraRed (MIR) channels of ACS covering more than two Martian years that contain spectra of 2.7 μm carbon dioxide ice absorption band. That allowed us to unambiguously discriminate carbon dioxide ice aerosols from mineral dust and water ice aerosols, not relying on the information of atmospheric thermal conditions. CO2 clouds were detected in eleven solar occultation observations at altitudes from 39 km to 90 km. In five cases, there were two or three layers of CO2 clouds that were vertically separated by 5–15 km gaps. Effective radius of CO2 aerosol particles is in the range of 0.1–2.2 μm. Spectra produced by the smallest particles indicate a need for a better resolved CO2 ice refractive index. Nadir optical depth of CO2 clouds is in the range 5 × 10−4–4 × 10−2 at both 2.7 μm and 0.8 μm. Asymmetrical diurnal distribution of detections observed by ACS is potentially due to local time variations of temperature induced by thermal tides. Two out of five cases of carbon dioxide cloud detections made by the TIRVIM instrument reveal the simultaneous presence of CO2 ice and H2O ice aerosols. Temperature profiles measured by the Near InfraRed (NIR) channel of ACS are used to calculate CO2 saturation ratio S at locations of carbon dioxide clouds. Supersaturation S > 1 is detected in only 6 out of 19 cases of CO2 cloud layers; extremely low values of S < 0.1 are found in 9 out of 19 cases.

Magmatic water content in HIMU basalts from the Cook-Austral Islands: constraints on degassing processes and source composition from clinopyroxene phenocrysts

The amount of water recycled during subduction is unclear. Water/Ce estimates in HIMU (high-238U/204Pb) basalts are variable, ranging from < 100 to > 250 in glasses and melt inclusions. Because clinopyroxene (cpx) is a common early liquidus phase and the cpx/melt partitioning of water is well constrained, cpx phenocrysts provide an additional constraint on magmatic water contents. We present water and trace element concentrations in HIMU-basalt-hosted cpx phenocrysts from the Austral Islands. Calculated melt [H2O] (up to 4.3 wt.%) and H2O/Ce ratios (22–825) are higher than in olivine-hosted inclusions, as are estimated equilibration pressures. Correlation between estimated melt [H2O] and crystallization or entrapment pressure suggests significant water loss during magma ascent. Most ocean island basalts (OIBs) span a limited range in H2O (~ 1–1.5 wt.%), and low (< 100) H2O/Ce ratios are primarily observed in melts with unusually high [Ce] (up to 350 ppm). Additionally, [H2O] and H2O/Ce in some suites correlate with entrapment pressure despite having quench pressures high enough to prevent significant water loss from open- or closed-system degassing (< 100 MPa). Polybaric “sparging”, whereby low-P melts re-equilibrate with CO2-rich fluids exsolved at higher pressure, may result in water loss at pressures less than CO2 saturation. This may more accurately describe OIB degassing processes than open or closed system degassing. After correcting for degassing, primary Australs melts likely have H2O/Ce of ~ 300–600. If applicable to OIB sources in general, this limits the total water budget of the mantle, including the mantle transition zone, to < 2.4 ocean masses.

Dynamic characteristics of high-pressure and high-density carbon dioxide leakage process

The leakage of high-pressure and high-density carbon dioxide (CO2) during storage and transportation can result in the rapid release of a substantial amount of CO2, presenting significant risks to Carbon Capture and Storage (CCS) technology. Investigating the dynamic characteristics of high-pressure and high-density CO2 leakage in storage tank, as well as understanding the variations in CO2 pressure, temperature, density, and phase during the leakage process, is crucial for the design of tank and pipeline leakage prevention. Existing research mainly focuses on leakage at the top or side of storage tank, there is a lack of attention to leakage from the bottom of storage tank. To simulate the bottom leakage processes, a depressurized experimental system with a 0.065 m3 CO2 storage tank volume was constructed. The range of CO2 parameter conditions for filling density is 811 ∼ 998 kg/m3, with initial pressure ranging from 5.72 ∼ 16.50 MPa. According to the change in the slope of the pressure drop in the storage tank, the leakage can be divided into three processes. The closer to the top of the storage tank, the liquid–gas phase transition of CO2 occurs earlier. The pressure shows two inflection points (point I and point II) representing the upper and lower limits of CO2 saturation pressure, respectively. The lower filling density results in a higher saturation pressure, while the higher initial pressure also leads to a higher saturation pressure. The current work can help to better understand pressure, temperature, density, and phase state changes of CO2 during leakage.

Water Transport Management in a Bipolar Membrane for CO2 Electrolysis Application

Bipolar membranes (BPMs) offer significant potential for electrochemical technologies, especially in CO2 electrolysis. Their unique ability to create pH gradients provides optimum chemical microenvironments at the cathode and anode for efficient, cheap and sustainable CO2 electrolysis. However, state-of-the-art BPMs are limited in their performance due to phenomena such as membrane degradation and membrane dehydration leading to low ionic conductivity, and hence their complete potential for various electrochemical technologies is yet to be realized. Previous studies have identified water transport as one of the main factors limiting the performance of BPM. A multi-physics model of BPM can serve as a useful tool to gain a comprehensive understanding of different performance limiting factors and thereafter propose solutions to overcome these limitations. The goal of the present study is to provide model based design guidelines for a BPM that facilitates efficient water transport, making it a suitable candidate for integration into a zero-gap CO2 reduction electrolyzer operating at industrial-grade performance levels.We have built a 1-D continuum model of a BPM kept in an aqueous (bi)carbonate electrolyte solution, incorporating physical phenomena such as water-dependent transport of ions and neutral species, field-enhanced homogeneous reactions (water-dissociation and acid-base reactions) along with CO2 phase transfer reaction at the BPM-aqueous electrolyte interfaces. The continuum model employs Poisson-Nernst-Planck equations to resolve local chemical species concentration. The effect of the electric field on the equilibrium dissociation constants of various charge-generating homogenous reactions is incorporated. This becomes important especially at interfaces within the domain where a sharp increase in electric field is observed. Unlike previous modeling studies, we also incorporate mass-conservation equation for water transport to resolve local water concentration inside the BPM. Local water concentration influences the transport of species in the BPM through their water-dependent activity and diffusivity. The electric potential distribution is resolved by incorporating water-dependent local permittivity of the BPM.Our model investigates both the reverse and forward bias operational modes of the BPM. In alignment with the experimental observation, in the reverse bias regime, the model identifies a distinct initial phase where current density is limited, with the majority of the current carried by protons and hydroxide ions at low overpotentials. As the potential increases, there's a rapid increase in current density, indicating a breakdown regime caused by an electric field-enhanced water dissociation reaction at the BPM interface. At even higher potentials, the polarization curve enters a third phase where the current density saturates characterized by water transport limitation. This aspect of the BPM polarization curve is uniquely captured by our model. Conversely, in the forward bias mode, as expected we do not observe any limitations due to mass transport, since water is generated at the bipolar junction. Here, the model forecasts a saturation of CO2 in the electrolyte, leading to gas bubbles forming at the BPM interface. To address the issue of water transport limitation, we conduct various parametric studies focusing on different membrane characteristics, such as individual layer thicknesses and their ion exchange capacities. The outcomes of these analyses provide crucial guidelines for optimizing these parameters and enhancing water management in BPM-based systems.