Carbon dioxide (CO2) sequestration in deep saline aquifers and formations

Rosenbauer, Robert J.; Thomas, Burt

doi:10.1533/9781845699581.1.57

Cited by 17 publications

(9 citation statements)

References 130 publications

(110 reference statements)

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“…Hence, the research field of carbon capture and storage (CCS) techniques emerged . Several process concepts were developed over the last decades, for example, wet scrubbing with amine solutions and geological storage of CO 2 under pressure in deep saline aquifers, as a potential major geological storage reservoir. , Other carbon capture and utilization (CCU) techniques are C–H carboxylation reactions, where CO 2 is chemically bond during liquid-phase reactions . All these applications highly depend on CO 2 solubility in multicomponent liquid mixtures.…”

Section: Introductionmentioning

confidence: 99%

Modeling the CO₂ Solubility in Aqueous Electrolyte Solutions Using ePC-SAFT

2020

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Carbon dioxide (CO 2 ) solubility in aqueous electrolyte solutions is of special interest for carbon capture and storage and for biochemical processes, particularly at moderate to high temperatures, pressures, and electrolyte concentrations. Unfortunately, experimental determination at such conditions is rather laborious. Therefore, the ionbased model ePC-SAFT was used in this work to model the CO 2 solubility in such systems over a broad range of conditions. The mixtures under investigation were the basis system CO 2 + water and higher systems containing either NaCl, KCl, MgCl 2 , CaCl 2 , NaNO 3 , KNO 3 , Mg(NO 3 ) 2 , or NaHCO 3 . In the pH range considered in this work (pH < 7), CO 2 dissociation reactions were found to be negligible; thus, only physical interactions were considered. Assuming induced association for CO 2 , binary interaction parameters between CO 2 −water and CO 2 − ion species were determined by fitting to literature data. For this purpose, different literature data sets were compared, and only the most reliable data were used to estimate the binary parameters. ePC-SAFT was found to be able to accurately model the CO 2 solubility in water as well as in aqueous systems containing electrolytes over a broad range of temperatures, pressures, and salt concentrations.

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Section: Introductionmentioning

confidence: 99%

Modeling the CO₂ Solubility in Aqueous Electrolyte Solutions Using ePC-SAFT

2020

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“…The contribution from, and the relative importance of, the aforementioned trapping mechanisms change over time as CO2 advances and reacts with reservoir fluids and minerals (Benson and Cole, 2008). Capillary trapping has emerged as one of the dominant mechanisms for long-term carbon storage (Taku Ide et al, 2007, Rosenbauer andThomas, 2010) with a substantial amount of entrapped CO2 reported in core-scale experiments (Iglauer et al, 2011. In this thesis, CO2 trapped by dissolution and capillary forces are evaluated.…”

Section: Co2 Storage and Trapping Mechanismsmentioning

confidence: 99%

Experimental Study of Foam Generation, Sweep Efficiency and Flow in a Fracture Network

et al. 2014

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Foam is consistently generated in situ in rough-walled, calcite fracture networks during experiments using surfactant-alternating-gas (SAG) and coinjection of gas and surfactant solution over a range of gas fractional flows. Boundary conditions are systematically changed including gas fractional flow, total flow rate, and liquid rates. Local sweep efficiency was evaluated through visualization of the propagation of the fluid front and compared for pure gas injection, SAG, and coinjection. Foam as a mobility control agent resulted in significantly improved sweep and delayed gas breakthrough. Gas mobility reduction factors varied from about 200 to more than 1000 consistent with observations of improved sweep. Shear-thinning foam-flow behavior was observed during coinjection over a range of gas fractional flow.

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“…Additionally, the interplay of CO 2 and reservoir brine solubility has a profound impact on long-term storage security, as well as the intricate physical and chemical interactions among minerals and fluids within the reservoir. 18 In order to accurately assess these impacts and ensure efficient carbon storage, it is imperative to possess a dependable model for forecasting the solubility of CO 2 in reservoir brines within the context of geological carbon storage conditions. Given the crucial relevance of CO 2 solubility in both pure water and brine, numerous extensive studies have been conducted to acquire valuable insights into CO 2 dissolution in aqueous solutions.…”

Section: Introductionmentioning

confidence: 99%

Toward Estimating CO₂ Solubility in Pure Water and Brine Using Cascade Forward Neural Network and Generalized Regression Neural Network: Application to CO₂ Dissolution Trapping in Saline Aquifers

Zou,

Zhu,

et al. 2024

ACS Omega

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Predicting carbon dioxide (CO2) solubility in water and brine is crucial for understanding carbon capture and storage (CCS) processes. Accurate solubility predictions inform the feasibility and effectiveness of CO2 dissolution trapping, a key mechanism in carbon sequestration in saline aquifers. In this work, a comprehensive data set comprising 1278 experimental solubility data points for CO2–brine systems was assembled, encompassing diverse operating conditions. These data encompassed brines containing six different salts: NaCl, KCl, NaHCO3, CaCl2, MgCl2, and Na2SO4. Also, this databank encompassed temperature spanning from 273.15 to 453.15 K and a pressure range spanning 0.06–100 MPa. To model this solubility databank, cascade forward neural network (CFNN) and generalized regression neural network (GRNN) were employed. Furthermore, three optimization algorithms, namely, Bayesian Regularization (BR), Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton, and Levenberg–Marquardt (LM), were applied to enhance the performance of the CFNN models. The CFNN-LM model showcased average absolute percent relative error (AAPRE) values of 5.37% for the overall data set, 5.26% for the training subset, and 5.85% for the testing subset. Overall, the CFNN-LM model stands out as the most accurate among the models crafted in this study, boasting the highest overall R 2 value of 0.9949 among the other models. Based on sensitivity analysis, pressure exerts the most significant influence and stands as the sole parameter with a positive impact on CO2 solubility in brine. Conversely, temperature and the concentration of all six salts considered in the model exhibited a negative impact. All salts exert a negative impact on CO2 solubility due to their salting-out effect, with varying degrees of influence. The salting-out effects of the salts can be ranked as follows: from the most pronounced to the least: MgCl2 > CaCl2 > NaCl > KCl > NaHCO3 > Na2SO4. By employing the leverage approach, only a few instances of potential suspected and out-of-leverage data were found. The relatively low count of identified potential suspected and out-of-leverage data, given the expansive solubility database, underscores the reliability and accuracy of both the data set and the CFNN-LM model’s performance in this survey.

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Carbon dioxide (CO2) sequestration in deep saline aquifers and formations

Cited by 17 publications

References 130 publications

Modeling the CO₂ Solubility in Aqueous Electrolyte Solutions Using ePC-SAFT

Modeling the CO₂ Solubility in Aqueous Electrolyte Solutions Using ePC-SAFT

Experimental Study of Foam Generation, Sweep Efficiency and Flow in a Fracture Network

Toward Estimating CO₂ Solubility in Pure Water and Brine Using Cascade Forward Neural Network and Generalized Regression Neural Network: Application to CO₂ Dissolution Trapping in Saline Aquifers

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Carbon dioxide (CO2) sequestration in deep saline aquifers and formations

Cited by 17 publications

References 130 publications

Modeling the CO2 Solubility in Aqueous Electrolyte Solutions Using ePC-SAFT

Modeling the CO2 Solubility in Aqueous Electrolyte Solutions Using ePC-SAFT

Experimental Study of Foam Generation, Sweep Efficiency and Flow in a Fracture Network

Toward Estimating CO2 Solubility in Pure Water and Brine Using Cascade Forward Neural Network and Generalized Regression Neural Network: Application to CO2 Dissolution Trapping in Saline Aquifers

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Product

Resources

About

Modeling the CO₂ Solubility in Aqueous Electrolyte Solutions Using ePC-SAFT

Modeling the CO₂ Solubility in Aqueous Electrolyte Solutions Using ePC-SAFT

Toward Estimating CO₂ Solubility in Pure Water and Brine Using Cascade Forward Neural Network and Generalized Regression Neural Network: Application to CO₂ Dissolution Trapping in Saline Aquifers