Modeling Of CO2 Solubility Research Articles

A concise chemical kinetics algorithm for carbonated brine injection in carbonate reservoirs

A single-cell segregated solver for calculating the behavior of carbonated brine injection in carbonate rocks aiming at carbon geological storage is presented. The approach is designed to represent an element in computational fluid dynamics simulations and enhance customization to include dissolution chemistry by integrating a CO2 solubility model, speciation calculations, mineral dissolution reactions and the consequent change in reservoir properties over time. The equilibrium and dissolution reactions are calculated sequentially, where an adaptive control of the time step ensures that the dissolution rate is computed from the correct equilibrium condition. A pseudo-homogeneous medium represents the reservoir, where alterations in rock structure are computed via a formulation based on Kozeny-Carman. Finally, a stabilization algorithm based on the Bjerrum plot of H2CO3 provides numerical robustness for the speciation calculations. The results can estimate the time frame for the system to reach equilibrium and the corresponding changes in rock structure. The solubility model was validated against experimental data, while the speciation model was compared to more rigorous thermodynamics models such as electrolyte-NRTL and Pitzer, showing minor differences. The algorithm as a whole provides similar results for the pH when compared to a state-of-the-art single-cell model with an extensive chemical system for a real reservoir, proving it can be a viable option for numerical simulations.

Modeling of CO2 solubility in aqueous alkanolamine solutions with an extended UMR-PRU model

The phase and chemical equilibria in aqueous alkanolamine solutions containing CO2 is examined in this work. The alkanolamines considered are monoethanolamine (MEA), methyldiethanolamine (MDEA), as well as blends of these two amines. For the vapor-liquid equilibrium calculations, the UMR-PRU model has been extended by incorporating the extended UNIQUAC activity coefficient model to account for the long range electrostatic interactions. The parameters of the UMR-PRU model are either taken from the literature, when available, or determined in this work through fitting vapor-liquid equilibrium experimental data. Very satisfactory results are obtained in all cases examined, which are similar or better than those obtained by other models proposed in the literature, indicating that the UMR-PRU model is able to accurately describe the phase and chemical equilibria in aqueous solutions of alkanolamines and carbon dioxide.

A CO2 solubility model for silicate melts from fluid saturation to graphite or diamond saturation

A model based on a thermodynamic framework for CO2 concentrations and speciation in natural silicate melts at graphite/diamond-saturated to fluid-saturated conditions is presented. The model is simultaneously calibrated with graphite-saturated and fluid-saturated conditions allowing for consistent model predictions across the CCO buffer. The model was calibrated using water-poor (≤1 wt% H2O) silicate melts from graphite- to CO2-fluid-saturation over a range of pressure (P = 0.05–3 GPa), temperature (T = 950–1600 °C), composition (foidite-rhyolite; NBO = 0.02–0.92; wt% SiO2 ~ 39–77, TiO2 ~ 0.1–5.8, Al2O3 ~ 7.5–18, FeO ~ 0.2–24 MgO ~ 0.1–24, CaO ~ 0.3–14, Na2O~1-5, K2O ~ 0–6), and fO2 (~QFM +1.5 to ~QFM −6). The model can predict CO2 concentrations for a wide range of silicate melt compositions from ultramafic to rhyolitic compositions, i.e., melts that dissolve carbon only as carbonate anions CO32– and those that dissolve carbon both as CO32– and as molecular CO2mol as a function of pressure, temperature, and oxygen fugacity. The model also does a reasonable job in capturing CO2 solubility in hydrous silicate melts with ≤2–3 wt% H2O. New CO2 solubility experiments at pressures >3 GPa suggest that the newly developed CO2 solubility model can be satisfactorily extrapolated to ~4–5 GPa. Above 5 GPa the model poorly reproduces experimental data, likely owing to structural change in silicate melt at pressures above 5 GPa. An Excel spreadsheet and a Matlab function are provided as online supplementary materials for implementing the new CO2 solubility model presented here.

Dissolution and reaction in a CO2-brine-clay mineral particle system under geological CO2 sequestration from subcritical to supercritical conditions

To support effective geological CO2 sequestration design and operation, dissolution and reaction in CO2-brine-clay mineral particle systems (sepiolite and montmorillonite) were studied under subcritical to supercritical CO2 conditions (10 bar to 150 bar at 45 °C and 65 °C). The order of ion dissolution from the framework of sepiolite in the brine was slightly different under each experimental condition, whereas the order of dissolved ion concentration from the montmorillonite was not varied. The solubility of CO2 was lower in the CO2-brine-clay mineral particle system than in a CO2-brine system. Precipitation of amorphous silica as a secondary mineral formation was observed after the reaction of both sepiolite and montmorillonite. The CO2 solubility model, considering ion concentration and aqueous silica, reasonably predicted the CO2 solubility from subcritical to supercritical conditions. The kinetic rate constant of the dissolution reaction of sepiolite was correlated with the initial pH of the brine. After reaction with high-pressure CO2-saturated brine, the micro-crystallinity of sepiolite did not change, whereas the basal (001) plane of montmorillonite showed deformation in micro-crystallinity after the dissolution reaction. By contrast, reaction with the CO2-saturated brine led to a decrease in the surface area of sepiolite and an increase in the surface area of montmorillonite.

Applying SVM framework for modeling of CO2 solubility in oil during CO2 flooding

CO2 solubility is one of the most important parameters that affects CO2 flooding, because gas dissolution into crude oil results in oil swelling, viscosity reduction, IFT reduction, oil mobilization, and oil recovery improvement. Therefore, a better understanding of CO2 solubility mechanisms and its influence on physical properties of crude oil are essential to any effective CO2 flooding process. In this study, Least-Square Support Vector Machine (LSSVM) as a newly established soft computing algorithm is applied for developing a new correlative model for CO2 solubility in both dead and live oil systems. CO2 solubility in dead oil is basically affected by the oil saturation pressure (Ps), oil specific gravity (γ), oil molecular weight (MW), and reservoir temperature (T). Moreover, the impact of bubble point pressure is considered in constructing the LSSVM model for the live oil. A number of statistical quality measures are utilized to assess and demonstrate the superior capability of the newly developed LSSVM model in comparison with the previous empirically derived correlations. The average absolute relative deviation (AARD) and coefficient of determination (R2) of 2.2783% and 0.9933 for the dead oil system, and 1.7432% and 0.9958 for the live oil system, respectively, verify the acceptable accuracy and efficient performance of the proposed LSSVM model over a wide range of dataset used in this study within the range of the used databank. However, the impact of CO2 liquefaction pressure is ignored, the LSSVM model gives the best result. In conclusion, it is worth mentioning that the proposed LSSVM model can serve as an accurate correlative tool for fast and effective estimation of CO2 solubility in both dead and live crude oils.

Modeling of CO2 solubility in crude oil during carbon dioxide enhanced oil recovery using gene expression programming

CO2 flooding into the petroleum reservoirs has gained much universal attentions owing to the benefits originated from the reduction of greenhouse gas emission and enhanced oil recovery (EOR). Among the all parameters applied for determining the feasibility of a particular CO2 EOR project especially in the miscible mode, solubility of CO2 has a vital function in the design and simulation of the CO2 injection. CO2 solubility has a prominent contribution to reduction of oil viscosity, IFT reduction, and a rise in swelling of crude oil which leads to the oil mobility increases, and improvement in oil recovery. In the present study, gene expression programming (GEP) as a recently developed and powerful soft-computing technique was utilized for establishing new symbolic CO2 solubility correlations in both dead and live oil systems. Moreover, the prediction capability of the artificial neural network (ANN) was also examined. For this reason, a database of wide-ranging operational conditions was undertaken from the open literature. The parameters involved in both ANN and GEP-based schemes are temperature, saturation pressure, oil molecular weight, and oil specific gravity in dead oil model. In addition to these parameters, the impact of bubble point pressure has been introduced in live oil system. At the next step, these datasets were separated into the two subsets of training group to construct the model and testing group to check the model capability. For assessing the efficiency of the suggested tool, several statistical calculations and graphical illustrations were utilized. Extensive error analysis applied for the newly suggested GEP-based correlations represents satisfactory agreement with highly accurate results of AARD=0.0378, and R2=0.9860 in dead oil, and AARD=0.0376, and R2=0.9844 in live oil. In accordance to the results of this study, the best performance of the extended GEP-based tool in this study was demonstrated compared to the studied literature correlations. The results of trend analysis prove that the proposed model has the best match with the measured datapoints as compared with previously published correlations in both dead and live oil systems. The developed ANN model gives slightly better results than GEP-based correlation in live oil; however, in dead oil the GEP-based strategy is more accurate than the ANN technique. At last, it is found out the GEP-based model can serve as reliable and robust method for rapid and efficient estimation of CO2 solubility in dead and live oil systems.

An improved model for CO2 solubility in aqueous electrolyte solution containing Na+, K+, Mg2 +, Ca2 +, Cl− and SO42 − under conditions of CO2 capture and sequestration

Based on the Pitzer electrolyte theory for activity coefficient and an accurate equation of state for vapor fugacity, an improved activity-fugacity model is developed to calculate CO2 solubility in aqueous KCl, MgCl2, CaCl2, Na2SO4, K2SO4 and MgSO4 solutions, respectively. The valid range of temperature, pressure and ion strength is up to 450K, 500bar and 5molkg−1. Average absolute deviation of CO2 solubility is about 5% compared to a large number of experimental data available, within or close to experimental uncertainties. By combining the interaction parameters of CO2 and ions developed here with those of CO2 and Na+ and Cl− from an earlier study of Mao et al. (2013), this model can be used to accurately predict CO2 solubility in aqueous mixed-salt solution containing Na+, K+, Mg2+, Ca2+, Cl− and SO2–4under conditions of CO2 capture and sequestration (generally less than 423K and 500bar). Computer code of the application program can be obtained from the corresponding author (maoshide@163.com).

Modeling of CO2 Solubility in Aqueous Potassium Lysinate Solutions at Post-Combustion CO2 Capture Conditions

Aqueous potassium lysinate (LysK) has been proposed as an alternative to aqueous alkanolamines for CO2 capture due to fast kinetics and large absorption capacity. However, thermodynamic modeling for aqueous LysK system has not been available yet. In this work, a modified Kent-Eisenberg model with correlated equilibrium constants was developed to interpret the vapor-liquid equilibrium (VLE) data at postcombustion capture conditions. The predictions from the developed model are in good agreement with the experimental results with AAD within 19 %.

Experimental data, thermodynamic and neural network modeling of CO2 solubility in aqueous sodium salt of l-phenylalanine

In this study, experimental CO2 solubility in aqueous sodium salt of l-phenylalanine (Na-Phe) was investigated at concentrations (w=0.10, 0.20, and 0.25) mass fractions. The solubility was measured in a high-pressure solubility cell at temperatures 303.15, 313.15 and 333.15K, over a CO2 pressure range of (2–25) bar. The effect of temperature, equilibrium CO2 pressure and Na-Phe concentration on CO2 loading were examined. Two different models namely modified Kent-Eisenberg and artificial neural network (ANN) were used to correlate the CO2 solubility data. Carbamate hydrolysis and amine deprotonation equilibrium constants were estimated as a function of temperature, pressure and solvent concentration from modified Kent-Eisenberg model. Also, the comparison of prediction results obtained from both modeling techniques was carried out. It was found that ANN model performed better than modified Kent-Eisenberg model.

Modeling of CO2 solubility in MEA, DEA, TEA, and MDEA aqueous solutions using AdaBoost-Decision Tree and Artificial Neural Network

This communication deals with investigating the available experimental data for CO2 capture by MEA, DEA, TEA, and MDEA aqueous solutions. For this purpose, first, the published data on CO2 solubility in the aforementioned amine solutions have been gathered. Second, the modeling has been carried out by employing AdaBoost algorithm coupled with Decision Tree Regressor (AdaBoost-DT) and Artificial Neural Network (ANN). Furthermore, a new model is developed for predicting the CO2 loading capacity of MDEA solution based on the Least Square Support Vector Machine (LSSVM). Finally, the modeling capabilities of the AdaBoost-DT, ANN, and LSSVM models for the application of interest are evaluated using some statistical parameters. In terms of R2, ARD, AARD, and RMSE values, it was found that the presented AdaBoost-DT models provide the best predictions for all the studied systems. Furthermore, the error analysis revealed that the LSSVM outperforms the ANN in predicting CO2 loading capacity of amine solutions.

Measurement and modeling of CO2 solubility in [bmim]Cl – [bmim][Tf2N] mixed-ionic liquids for design of versatile reaction solvents

In this work, mixtures of 1-butyl-3-methylimidazolium chloride ([bmim]Cl) and 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([bmim][Tf2N]) were chosen to study because [bmim]Cl is suitable for processing biomass and [bmim][Tf2N] is suitable for increasing carbon dioxide (CO2) solubility in the ionic liquid phase. Solubilities of CO2 in mixed ionic liquid systems ([bmim]Cl and [bmim][Tf2N]) were measured at (353–393) K and at pressures up to 15MPa with a magnetic suspension balance technique. Mixed ionic liquids were prepared at mole ratios, [bmim]Cl: [bmim][Tf2N] of 0.75: 0.25, 0.50: 0.50 and 0.25: 0.75. CO2 solubility in mixed ionic liquids changed regularly from that in single [bmim]Cl to that in single [bmim][Tf2N]. By assuming mixed ionic liquids as a mixture of two ionic liquids, the ε*-modified Sanchez-Lacombe equation of state could predict CO2 solubility data with pure component parameters of single ionic liquids and interaction parameters for [bmim]Cl-CO2, [bmim][Tf2N]-CO2 and [bmim]Cl-[bmim][Tf2N] to within an average relative deviation of 2.4%.

Modeling of CO2 solubility in aqueous N-methyldiethanolamine solution using electrolyte modified HKM plus association equation of state

In this work, a new type of electrolyte cubic plus association equation of state as emHKM-CPA EoS has been developed and was used to modeling the CO2 solubility in aqueous alkanolamine such as N-methyldiethanolamine (MDEA) and diethanolamine (DEA) solutions. This EoS consists of the several terms as the cubic HKM part for dispersion contribution, electrolyte part and association term. The Mean Spherical Approximation (MSA) term together with Born term are used for electrostatic long-range interaction and charging processes, respectively, and for association the Wertheim equation was applied. Using the present EoS, the solubility of CO2 in aqueous MDEA solutions is modeled so that the 470 experimental solubility data were used at the different solution compositions, temperatures, pressures and acid gas loadings. At first, the pure components parameters were obtained through regression of the pure components vapor pressure and saturated liquid density experimental data. Consequently, the binary interaction parameters were calculated using the binary vapor-liquid equilibrium data. Finally, the ternary H2O-CO2-MDEA and H2O-CO2-DEA systems were modeled using a reactive bubble point pressure calculation method. Moreover, the present EoS is applied for LLE calculation of heptane-MEA system. The results showed that the calculated values were in good agreement with the experimental data. For the H2O-CO2-MDEA and H2O-CO2-DEA systems, the percentage of Absolute Average Deviation (AAD%) were 12.14 and 9.17, respectively, that shows emHKM- CPA is an efficient EoS which can be successfully applied to representation of the solubility of CO2 in aqueous alkanolamine solutions in wide ranges of temperature, pressure, acid gas loading, and amine concentration.

Modeling of CO2 Solubility in Tertiary Amine Solvents Using pKa

Tertiary amines are widely used to capture CO2 from the gases of high-pressure processes because these compounds have high CO2 solubilities at high pressures of 0.5–1 MPa and low CO2 absorption heats compared to primary and secondary amines. CO2 solubility model for tertiary amine solvents was developed using pKa. This study used selected aqueous solutions of tertiary alkanolamines, tertiary cyclic amines, and tertiary diamines as solvents for modeling. Chemical equilibrium constants were correlated with a linear function of pKa. The generalized parameters provide a method to predict CO2 solubility in a tertiary amine solution from the pKa of the amine.

VLE Modeling of Aqueous Solutions of Unloaded and Loaded Hydroxides of Lithium, Sodium and Potassium

This work focuses on equilibrium modeling of CO2 solubility in aqueous solutions of unloaded (as hydroxides) and loaded (as carbonates) hydroxides containing Li+, Na+ and K+ counter ions. Due to the ionic nature of the LiOH/NaOH/KOH-CO2-H2O solutions, the electrolyte-Non-Random-Two-Liquid (e-NRTL) model, described by Chen and Evans [1], is applied to correct the non-idealities in the liquid phase. The special feature of the equilibrium model employed in this work is the simultaneously regression of Vapor-Liquid Equilibrium (PCO2, Ptotal) and apparent Henry's law constant data selected from literature and Ptotal data for LiOH measured in this work. This approach will give better prediction for the molecular CO2 activity coefficients and the liquid phase activities calculated by use of the resulting e-NRTL model will be consistent with the apparent Henry's law constant. The equilibrium model developed in this work is based on and represented 112 data points for Li+ with 2.7% total AARD, 432 selected data points for Na+ with total 7.2% AARD and 354 selected data points for K+ with total 9.9% AARD. The total pressure data over aqueous LiOH solutions were measured for a range of concentrations (0.25 – 8.5wt. %) and temperatures (40 – 90°C) using an ebulliometer.

Modeling of CO2 solubility in single and mixed electrolyte solutions using statistical associating fluid theory

Statistical associating fluid theory (SAFT) is used to model CO2 solubilities in single and mixed electrolyte solutions. The proposed SAFT model implements an improved mean spherical approximation in the primitive model to represent the electrostatic interactions between ions, using a parameter K to correct the excess energies (“KMSA” for short). With the KMSA formalism, the proposed model is able to describe accurately mean ionic activity coefficients and liquid densities of electrolyte solutions including Na+, K+, Ca2+, Mg2+, Cl−, Br− and SO42− from 298.15K to 473.15K using mostly temperature independent parameters, with sole exception being the volume of anions. CO2 is modeled as a non-associating molecule, and temperature-dependent CO2–H2O and CO2–ion cross interactions are used to obtain CO2 solubilities in H2O and in single ion electrolyte solutions. Without any additional fitting parameters, CO2 solubilities in mixed electrolyte solutions and synthetic brines are predicted, in good agreement with experimental measurements.

Experimental measurement and thermodynamic modeling of CO2 solubility in aqueous solutions of morpholine

In the present work, new experimental data of CO2 solubility in aqueous solutions of 2, 3 and 4.5M (17.5, 26.1 and 39.16wt.%) morpholine (MOR) at two different temperatures (313.15 and 333.15K) is obtained by static method. The Deshmukh–Mather thermodynamic model is performed to calculate CO2 solubility in aqueous MOR solutions. The short-range interaction parameters between ion–ion and ion–molecule species in the activity coefficient model are considered to be function of temperature and are adjusted to experimental data. The model shows good results for the solubility calculations. The overall average absolute relative percent deviation (AAD%) for all the data points of CO2 partial pressure is 9.86%.

CO2 solubility in kimberlite melts

Carbon dioxide is the most abundant volatile in kimberlite melts and its solubility exerts a prime influence on the melt structure, buoyancy, transport rate and hence eruption dynamics. The actual primary composition of kimberlite magma is the matter of some debate but the solubility of CO2 in kimberlitic melts is also poorly constrained due to difficulties in quenching these compositions to a glass that retains the equilibrium CO2 content. In this study we used a range of synthetic, melt compositions with broadly kimberlitic to carbonatitic characteristics which can, under certain conditions, be quenched fast enough to produce a glass. These materials are used to determine the CO2 solubility as a function of chemical composition and pressure (0.05–1.5GPa). Our results suggest that the solubility of CO2 decreases steadily with increasing amount of network forming cations from ~30wt.% CO2 at 12wt.% SiO2 down to ~3wt.% CO2 at 40wt.% SiO2. For low silica melts, CO2 solubility correlates non-linearly with pressure showing a sudden increase from 0.1 to 100MPa and a smooth increase for pressure >100MPa. This peculiar pressure–solubility relationship in low silica melts implies that CO2 degassing must mostly occur within the last 3km of ascent to the surface having potential links with the highly explosive nature of kimberlite magmas and some of the geo-morphological features of their root zone. We present an empirical CO2 solubility model covering a large range of melt composition from 11 to 55wt.% SiO2 spanning the transition from carbonatitic to kimberlitic at pressures from 1500 to 50MPa.

Experimental measurements and modeling of CO2 solubility in sunflower, castor and rapeseed oils

In this work solubility measurements of CO2 in three vegetable oils, a high oleic sunflower oil (HOSO), a castor oil and a rapeseed oil, for mole fractions ranging from 0.32 to 0.93 in the temperature range 298–363K and up to 75MPa were performed. Moreover, the densities and viscosities of these oils are reported from 278.15 to 373.15K at atmospheric pressure. These data were used to evaluate the predictive ability of the fragment based approach. Solubility data were modeled by means of the SRK EoS and predicted employing the Carvalho and Coutinho correlation. Global average deviations inferior to 6% in CO2 mole fraction composition were achieved with the SRK EoS and maximum percentage absolute average deviations of 13% in pressure were obtained using the Carvalho and Coutinho correlation.

An improved model for calculating CO2 solubility in aqueous NaCl solutions and the application to CO2–H2O–NaCl fluid inclusions

To determine compositions, homogenization pressures and isopleths of CO2–H2O–NaCl fluid inclusions, an improved activity–fugacity model is developed to calculate CO2 solubility in aqueous NaCl solutions. The model can predict the CO2 solubility in aqueous NaCl solutions from 273.15K to 723.15K, from 1bar to 1500bar and from 0 to 4.5molkg−1 of NaCl, within or close to experimental uncertainties. Compared to a large number of reliable experimental solubility data available, the average absolute deviation is 4.62% for the CO2 solubility in aqueous NaCl solutions. In the near-critical region, the calculated CO2 solubility deviations increase to over 10%. The CO2 solubility model, together with the updated volumetric model of CO2–H2O–NaCl fluid mixtures, is applied to calculate the CO2 contents, homogenization pressures, molar volumes and volume fractions of the CO2–H2O–NaCl fluid inclusions by an iterative method based on the assumption that the volume of an inclusion keeps constant during heating and cooling. Calculation program code of the CO2 solubility in aqueous NaCl solutions can be obtained from Chemical Geology or the correspondence author (maoshide@163.com).

New experimental data and semi-empirical parameterization of H2O–CO2 solubility in mafic melts

We present here new experimental data on H2O–CO2 solubility in mafic melts with variable chemical compositions (alkali basalt, lamproite and kamafugite) that extend the existing database. We show that potassium and calcium-rich melts can dissolve ∼1wt% CO2 at 3500bar (350MPa) and 1200°C, whereas conventional models predict solubilities of 0.2–0.5wt%, under similar P–T conditions. These new data, together with those in the literature, stress the fundamental control of melt chemical composition on CO2 solubility. We present a semi-empirical H2O–CO2 solubility model for mafic melts, which employs simplified concepts of gas–melt thermodynamics coupled with a parameterization of both chemical composition and structure of the silicate melt. The model is calibrated on a selected database consisting of 289 experiments with 44 different mafic compositions. Statistical analyses of the experimental data indicate that, in mafic melts, the chemical composition and therefore the structure of the melt plays a fundamental role in CO2 solubility. CO2 solubility strongly depends on the amount of non-bridging oxygen per oxygen (NBO/O) in the melt, but the nature of the cation bonded to NBO is also critical. Alkalis (Na+K) bonded to NBO result in a strong enhancement of CO2 solubility, whereas Ca has a more moderate effect. Mg and Fe bonded to NBO have the weakest effect on CO2 solubility. Finally, we modelled the effect of water and concluded that H2O dissolution in the melt enhances CO2 solubility most likely by triggering NBO formation. In contrast with CO2 but in agreement with earlier findings, H2O solubility in mafic melts is negligibly affected by melt composition and structure: it only shows a weak correlation with NBO/O.