CO2-N2 Mixtures Research Articles

Optimizing oil recovery with CO2 microbubbles: A study of gas composition

Microbubbles represent a feasible method for enhancing oil recovery (EOR). To further investigate microbubble displacement and interaction mechanisms between gas and oil, in this study, EOR experiments were conducted on normal (NB) and microbubble (MB) CO2 and CO2–N2 mixtures using NMR. The CO2 flooding process and the mechanism of microbubble CO2-oil interaction were examined, the contributions of small and large pores to oil recovery and CO2 storage were quantified. Importantly, economic benefits were analyzed under different injection conditions for the first time. The results show CO2 injection formed a stable displacement front and the maximum oil recovery was obtained from MB CO2. The oil swelling and “jamin effect” increased MB CO2 sweep area and the efficiency of small pore utilization was 20.9 % higher than NB CO2. Compared to CO2 injection, the oil recovery gradually decreased with increasing N2 concentration due to the reduced sweep area. The maximum CO2 storage efficiency achieved under MB CO2 injection was 35.92 %. Economic analysis revealed that MB CO2-EOR could provide significant economic benefits of approximately US $492.5 per ton of CO2 injected. This study provides data for the commercial application of microbubble technology.

Experimental Study on the Reaction of Magnesium in Carbon Dioxide and Nitrogen Atmosphere

This manuscript presents an experimental study focusing on the combustion of magnesium in an atmosphere depleted of oxygen. The study explores various mixtures of carbon dioxide and nitrogen, examining their impact on the combustion performance. The experimental design involved evaluating how the carbon content influences combustion parameters. Temperature profiles were analyzed to elucidate different stages of the combustion process. Furthermore, the effects of pressure (2 and 3 ata) and the composition of CO2-N2 mixtures (10%, 19.5%, 35%, 48%, 72%, and 80% CO2 content) on magnesium combustion, including ignition time, maximum temperature, and post-combustion temperatures, were investigated. The results revealed a substantial impact on the ignition delay and combustion time, with the ignition delay decreasing with higher chamber pressure. The combustion process, especially with regard to the ignition time and heat of combustion, was notably affected by CO2 concentration. The morphology of the combustion residue from the magnesium microparticles was characterized using scanning electron microscopy combined with energy-dispersive X-ray spectroscopy (SEM-EDX). The reaction of Mg with CO2 represents a promising energy source, quickly releasing a substantial amount of heat with a very low quantity of Mg. The estimated value of the heat of combustion for magnesium in N2-CO2 atmosphere is 78.4 kJ mol−1.

Small-scale experimental study of microevolutionary processes and dynamics of CO2-N2 mixtures before BLEVE

CCS technology involves carbon capture, where the captured CO2 contains N2 impurities and there is a risk of Boiling Liquid Expanding Vapor Explosion (BLEVE) in the high-pressure CO2-N2 mixtures vessel. Therefore, in this paper, we experimentally investigated the jet structure and boiling nucleation microevolution process after the sudden release of high-pressure CO2-N2 mixtures in a pressure vessel and discussed the effects of rupture disc diameter, and N2 molar ratio on the dynamic pressure before the startup of BLEVE. The results show that under-expanded jets are experimentally observed due to the Joule-Thompson effect. The boiling and nucleation microevolution is divided into six main stages, in the second of which the boiling expansion of the liquid and the "backfilling" of the gas leads to a dynamic pressure peak greater than the initial pressure, and BLEVE starts to occur. In the experiments, the dynamic pressure peaks were larger at 8 mm rupture disc diameter and 8 mol% N2, BLEVE did not occur at 15 mm, and N2 content below 5 mol% had less effect on the dynamic pressure behavior. This study provides a preliminary investigation of the pre-BLEVE behavior of CO2-N2 mixtures and provides theoretical support for risk prevention.

Pre-treatment through reductive calcination for CO2 mineralization and selective battery metal extraction from laterites

The world needs an increasing supply of nickel and cobalt production as battery materials for sustainable development. However, the complexity of laterite deposits and the need to control CO2 emissions challenge the enhanced global supply from laterites. This work investigates the effects of calcination as a pre-treatment for selective battery metal extraction from both limonite laterite and saprolite laterite together with concurrent achievement of CO2 mineralization. Calcination under a reducing atmosphere of CO-N2 or CO-CO2 gas mixtures can significantly enhance the extraction of critical metals from both limonite and saprolite laterites. With calcination, the hydrated silicate minerals and ferric oxides converted to reactive olivine and ferrous oxide. The calcines thus can participate in the CO2 mineralization process to stabilize CO2 as mineral carbonates and release nickel and cobalt arising from the CO2 mineral carbonation into solution as complex ions with a ligand (such as sodium nitrilotriacetate, NTA). The optimum calcination conditions are 20 ∼ 30 % CO in CO-CO2 gas mixture at 700 °C. Beyond the optimum range results in the inadequate conversion of ferric to ferrous at too low CO concentration or over calcination of ferric to metallic iron at too high CO concentration. At the optimum conditions, the nickel & cobalt extraction and CO2 mineralization can reach 90 %, 93 %, and 39 % from laterite. Each tonne saprolite with the pre-treatment of calcination can recover 20.5 kg nickel, 0.59 kg cobalt, and simultaneously sequester 142 kg CO2 as stable mineral carbonates. The pre-treatment through slightly reductive calcination enables the robust suitability of the developed process for all layers of laterites for both critical battery metal recovery and carbon mineralization.

Smart predictive viscosity mixing of CO2–N2 using optimized dendritic neural networks to implicate for carbon capture utilization and storage

Crucial for carbon capture, utilization, and storage (CCUS) initiatives and diverse industries, heat transfer underscores the need for a precise assessment of carbon dioxide (CO2) and nitrogen (N2) viscosities in gaseous blends across various temperatures. This research pioneers an intelligent model by enhancing the dendritic neural regression (DNR) framework, employing the Seagull Optimization Algorithm with Marine Predator Algorithm (SOAMPA) for optimal predictions. Leveraging recent advancements in metaheuristic optimization techniques, the study reveals the superior performance of the novel SOAMPA approach in predictive accuracy, marking a significant breakthrough in predicting CO2-N2 mixture viscosities with implications for advancing CCUS projects and diverse industries. The optimized DNR model, empowered by the modified SOAMPA optimization technique, contributes to estimating the viscosity of N2-CO2 mixture gases. Utilizing inputs like pressure, temperature, mole fraction of N2, and model fraction of CO2, the models are trained and tested on a dataset comprising over 3030 data samples from public literature. Key contributions encompass proposing an optimized DNR approach, introducing the modified SOAMPA technique, and demonstrating its superiority over established optimization methods in conjunction with the traditional DNR model for predicting viscosity based on real experimental datasets.

Investigating CO2–N2 phase behavior for enhanced hydrate-based CO2 sequestration

Storing CO2 in underwater sand sediments as hydrates offers vast capacity and minimal leakage risk. But direct CO2 injection can clog the surrounding area, reducing the flow. One solution is injecting CO2–N2 mixtures. This study investigated the movement and transformation of this gas mixture, with a focus on the formation rates and main factors of hydrate-based CO2 storage. Results revealed two distinct gas seepage-phase transition processes. In freshwater conditions, there was an initial temperature spike followed by localized hydrate formation, which then spread outward. In memory water, multiple hydrate formations occurred simultaneously. Freshwater conditions led to more blockages due to the concentration of hydrates, while the memory conditions maintained better flow due to more evenly distributed hydrates. Gas composition analysis showed that as CO2-rich hydrates formed, the CO2 level in the flowing gas dropped, which could stop further hydrate formation. This finding indicates that mixed gas injections could prevent excessive hydrate formations and maintain flow. The saturation of hydrates varied between 10 % and 50 %, with differences attributed to the unpredictable nature of initial hydrate formation. Overall, this research will guide efforts to optimize CO2 storage as hydrates and re-evaluate the viability and safety of this storage method using CO2–N2 mixtures.

Two-color four-wave mixing contribution to an electrostrictive laser-induced grating signal in CO2-N2 mixtures and gas diagnostics: publisher's note.

This publisher's note corrects content in Appl. Opt.62, 8115 (2023)APOPAI0003-693510.1364/AO.497467.

Two-color four-wave mixing contribution to an electrostrictive laser-induced grating signal in CO2-N2 mixtures and gas diagnostics.

Multiparameter determination in the gas phase using the versatile laser-induced grating (LIG) technique is a challenging task due to interdependence of observables on multiple thermodynamic parameters. In C O 2-N 2 mixtures, simultaneous determination of species concentration and gas temperature can be achieved by using an additional C O 2 concentration-dependent contribution to the LIG signal, which appears if 1064 nm pump pulses are employed. This contribution can be attributed to a direct, quasi-resonant two-color four-wave mixing (TCFWM) of the pump and probe radiations in C O 2. A detailed study of the laser power and beam polarization, as well as mixture composition, pressure, and temperature dependencies of the TCFWM intensity relative to that of the LIG signal, allowed for the formulation of analytical relations enabling simultaneous mixture composition and temperature determination.

On CO2 conversion in discharges in CO2–N2 mixtures

Recent results on the efficiency of CO2 conversion in discharges in CO2–N2 mixtures are discussed. Conditions are considered when the dominating conversion mechanism is dissociation of CO2 molecules in collisions with nitrogen molecules in several electronically excited states. Its efficiency is determined by the values of dissociation yields in these collisions. Knowledge of dissociation yields for various N2 excited states is rather poor. In this paper, the effects of variation of these yields on the conversion efficiency are evaluated. Comparison of the obtained estimates with available experimental data allows ascertaining the yield values.

Residual trapping of CO2, N2, and a CO2-N2 mixture in Indiana limestone using robust NMR coreflooding: Implications for CO2 geological storage

Carbon capture and sequestration (CCS) in geological formations is a prominent solution for reducing anthropogenic carbon emissions and mitigating climate change. The capillary trapping of CO2 is a primary trapping mechanism governed by the pressure difference between the wetting and nonwetting phases in a porous rock, making the latter a key input parameter for dynamic simulation models. During the CCS operational process, however, the CO2 is prone to contamination by impurities from various sources such as surfaces (e.g., pipelines and tanks) and the subsurface (e.g., existing natural gas). Such contamination can strongly influence the overall CO2 wettability, storage capacity, and containment security. Hence, the present study uses the nuclear magnetic resonance (NMR) core flooding technique to investigate and compare the residual saturations of pure CO2, pure N2, and a 50:50 CO2/N2 mixture in an Indiana limestone. The longitudinal and transverse relaxation times (T1 and T2) are measured to examine the displacement process of the pore network, and the trapping mechanism is evaluated at the pore scale as a determinant of the field-scale flow behavior. The NMR T1-T2 and 2D maps are used to observe the fluid configurations in the pore network, and the T1/T2 ratios are used to evaluate the microscopic wettability of the limestone grains by the pore-space fluids following each drainage/imbibition process step. The results indicate substantial residual gas trapping in the rock for the CO2-brine, N2-brine, and CO2/N2-brine systems, corresponding to gas saturations of 25%, 27%, and 26%, respectively. In the CO2-brine system, the intermolecular interplay between the CO2-enriched brine and limestone grains results in a higher T1/T2 ratio and significantly reduces the hydrophilicity of the limestone. Furthermore, the NMR T2 distribution reveals the occurrence of preferential water displacement into the large pores (r > 1 µm) and from the intermediate pores (0.03 µm < r < 1 µm), whereas water remains immobile in the smaller pores (r < 0.03 µm). The insignificant difference in residual trapping saturation between pure CO2 and the CO2-N2 mixture indicates the potential to allow for impurities in the CO2 phase in CCS without reducing the residual trapping capacity. Thus, the present work provides comprehensive information on the impact of gas injection on residual gas trapping in subsurface geological formations at the pore scale, thereby aiding in the development of CCS and other potential applications in enhanced oil recovery (EOR).

Validation of non-equilibrium kinetics in CO2–N2 plasmas

This work explores the effect of N2 addition on CO2 dissociation and on the vibrational kinetics of CO2 and CO under various non-equilibrium plasma conditions. A self-consistent kinetic model, previously validated for pure CO2 and CO2–O2 discharges, is further extended by adding the kinetics of N2. The vibrational kinetics considered include levels up to v = 10 for CO, v= 59 for N2 and up to v 1= 2 and v 2= v 3= 5, respectively for the symmetric stretch, bending and asymmetric stretch modes of CO2, and account for electron-impact excitation and de-excitation (e–V), vibration-to-translation (V–T) and vibration-to-vibration energy exchange (V–V) processes. The kinetic scheme is validated by comparing the model predictions with recent experimental data measured in a DC glow discharge operating in pure CO2 and in CO2–N2 mixtures, at pressures in the range 0.6–4 Torr (80.00–533.33 Pa) and a current of 50 mA. The experimental results show a higher vibrational temperature of the different modes of CO2 and CO and an increased dissociation fraction of CO2, that can reach values as high as 70%, when N2 is added to the plasma. On the one hand, the simulations suggest that the former effect is the result of the CO2–N2 and CO–N2 V–V transfers and the reduction of quenching due to the decrease of atomic oxygen concentration; on the other hand, the dilution of CO2 and dissociation products, CO and O2, reduces the importance of back reactions and contributes to the higher CO2 dissociation fraction with increased N2 content in the mixture, while the N2(B3Πg) electronically excited state further enhances the CO2 dissociation.

Modeling Viscosity of CO2-N2 Gaseous Mixtures Using Robust Tree-Based Techniques: Extra Tree, Random Forest, GBoost, and LightGBM.

Carbon dioxide (CO2) has an essential role in most enhanced oil recovery (EOR) methods in the oil industry. Oil swelling and viscosity reduction are the dominant mechanisms in an immiscible CO2-EOR process. Besides numerous CO2 applications in EOR, most oil reservoirs do not have access to natural CO2, and capturing it from flue gas and other sources is costly. Flue gases are available in huge quantities at a significantly lower price and can be considered economically viable agents for EOR operations. In this work, four powerful machine learning algorithms, namely, extra tree (ET), random forest (RF), gradient boosting (GBoost), and light gradient boosted machine (LightGBM) were utilized to accurately estimate the viscosity of CO2-N2 mixtures. To this aim, a databank was employed, containing 3036 data points over wide ranges of pressures and temperatures. Temperature, pressure, and CO2 mole fraction were applied as input parameters, and the viscosity of the CO2-N2 mixture was the output. The RF smart model had the highest precision with the lowest average absolute percent relative error (AAPRE) of 1.58%, root mean square error (RMSE) of 2.221, and determination coefficient (R 2) of 0.9993. The trend analysis showed that the RF model could precisely predict the real physical behavior of the CO2-N2 viscosity variation. Finally, the outlier detection was performed using the leverage approach to demonstrate the validity of the utilized databank and the applicability area of the developed RF model. Accordingly, nearly 96% of the data points seemed to be dependable and valid, and the rest of them were located in the suspected and out-of-leverage data zones.

Gasification and kinetic study on metallurgical cokes in CO2-N2-H2O and CO2-N2 atmosphere

ABSTRACT A high-temperature gas-solid reaction device was used to simulate the gasification of coke in a hydrogen-rich blast furnace, with the gasification reaction of water/anhydrous bulk cokes studied. CO2 and H2O effects on coke gasification kinetics were analyzed in CO2-N2-H2O and CO2-N2 with the experimental temperature of 1173–1523 K, the CO2 content of 15–60%, and the H2O content of 15%. Compared with those of CO2-N2, the gasification reaction rate and carbon conversion rate of cokes in the CO2-N2-H2O mixture were significantly higher. Carbon conversion rates of the CO2-N2-H2O mixture at different temperatures were about 30% higher than those of CO2-N2 on average, and the gasification reaction rate was about 50% higher on average. There were two temperature regions for gasifying cokes in CO2-N2-H2O and CO2-N2 mixtures. At 1,273 K, the gasification reaction is transformed into diffusion control, which is from chemical reaction control. The aggravation of coke gasification by H2O generated after hydrogen reduction of iron ores was mainly reflected at the lower temperature. Besides, the kinetic model analysis showed that random pore model was optimal in describing the gasification reaction of cokes in CO2-N2-H2O and CO2-N2, and the addition of H2O improved the gasification reaction’s activation energy.

Permeability of Hydrate-Bearing Sediment Formed from CO2-N2 Mixture

CO2-N2-mixture injection can be used for the exploitation and reformation of natural gas hydrate reservoirs. The permeability evolution of sediments in the presence of CO2-N2 hydrate is very important. In current permeability tests, hydrate-bearing sediment formed from CO2-N2 gas mixture is rarely involved. In this work, hydrate-bearing sediment was formed from CO2-N2 mixtures, and a constant flow method was employed to measure the permeability of the hydrate-bearing sediments. The effects of CO2 mole fraction and hydrate saturation on the permeability were investigated. The results show that gas composition is the key factor affecting hydrate formation. Hydrate saturation increases with increasing CO2 mole fraction in the gas mixture. The presence of hydrate formed from a CO2-N2 mixture leads to a sharp permeability reduction. The higher the fraction of CO2 in the injected gas mixture, the lower the sediment’s permeability. Our measured permeability data were also compared with and fitted to prediction models. The pore-filling model underestimates the permeability of hydrate-bearing sediments formed from a CO2-N2 gas mixture. The fitted hydrate saturation index in the Masuda model is 15.35, slightly higher than the general values, which means that the formed hydrates tend to occupy the pore center, and even block the pore throat.

Enhanced Carbon Storage Process from Flue Gas Streams Using Rice Husk Silica Nanoparticles: An Approach in Shallow Coal Bed Methane Reservoirs

Carbon capture and storage (CCS) is considered a key process to reach net-zero emission by the 2050 aim of limiting global warming. Coal bed methane (CBM) is considered potential geological reservoirs for underground CCS due to the CO2–CH4 exchange feasibility by adsorptive phenomena. Global implementation has been focused only on deep reservoirs to provide methane recovery. Thus, this work proposes a modified CCS process based on silica nanoparticle inclusion for shallow CBM reservoirs (<300 m). The nanomaterials were evaluated at high pressure in two main stages including i) CO2 sorption on a single CO2 stream and ii) CO2 selectivity on a flue gas stream (N2–CO2 mixture). This work includes silica nanomaterial synthesized from rice husk as agro-waste sources with better technical-economic feasibility framed in a circular economy to reduce costs and maximize the use of available resources. Rice husk silica (RSi) nanoparticles were doped with 1.0, 3.0, and 5.0 wt % of urea (Si–U), diethylamine (Si-DE), triethylamine (Si-TE), and ethylenediamine (Si-EM) to enhance the CO2 sorption. First, CO2 sorption was evaluated at 30 °C and between 0.084 and 3 MPa using a CO2 stream to determine the best-doped amount of each N-source. Then, the best nanoparticles were used to impregnate CBM at 10 and 20 wt %, and the subsequent CO2 storage on the flue gas stream (70% v/v N2 and 30% v/v CO2) was done. The results showed that CO2 sorption on RSi increases with the N-group coating in the order RSi-DE < RSi-TE < RSi-U < RSi-EM. Also, the best-doped amount for each N-source was 3 wt %. For CBM impregnation, the nanofluid containing 20 wt % of RSi-EM3 presented the best yield increasing the CO2 sorption from 0.05 to 0.75 mmol g–1, meaning an increase of more than 1000% in the sorption capacity.

Numerical Simulation of Carbon Dioxide–Nitrogen Mixture Dissolution in Water-Saturated Porous Media: Considering Cross-Diffusion Effects

The possibility of impure carbon dioxide (CO2) sequestration can reduce the cost of these projects and facilitate their widespread adoption. Despite this, there are a limited number of studies that address impure CO2 sequestration aspects. In this study, we examine the convection–diffusion process of the CO2–nitrogen (N2) mixture dissolution in water-saturated porous media through numerical simulations. Cross-diffusion values, as the missing parameters in previous studies, are considered here to see the impact of N2 impurity on dissolution trapping in more realistic conditions. Homogeneous porous media are used to examine this impact without side effects from the heterogeneity, and then simulations are extended to heterogeneous porous media, which are a good representative of the real fields. Heterogeneity in the permeability field is generated with sequential Gaussian simulation. Using the averaged dissolved CO2 and dissolution fluxes for each case, we could determine the onset of different dissolution regimes and behaviors of dissolution fluxes in CO2–N2 mixture dissolution processes. The results show that there is a notable difference between the pure cases and impure cases. Additionally, a failure to recognize the changes in the diffusion matrix and cross-diffusion effects can result in significant errors in the dissolution process. At lower temperatures, the N2 impurity decreases the amount and flux of CO2 dissolution; however, at higher temperatures, sequestrating the CO2–N2 mixture would be a more reasonable choice due to enhancing the dissolution behavior and lowering the project costs. The results of the heterogeneous cases indicate that heterogeneity, in most cases, reduces the averaged dissolved CO2, and dissolution flux and impedes the onset of convection. We believe that the results of this study set a basis for future studies regarding the CO2–N2 mixture sequestration in saline aquifers.

Reduction disintegration behavior of vanadium titanomagnetite pellets in H2–CO–CO2–N2 mixtures

In this paper, the low–temperature disintegration behavior of vanadium titanomagnetite (VTM) pellets in H 2 –CO–CO 2 –N 2 mixtures was investigated. Thermodynamic calculations indicated that pseudobrookite (Fe 2 TiO 5 ) was reduced in the order Fe 2 TiO 5 → Fe 2 TiO 4 → FeTiO 3 → FeTi 2 O 5 , and the reduction potentials of H 2 and CO were mainly depended on the temperature. The experiments were carried out at temperatures of 400–700 °C with H 2 /(H 2 + CO) of 0–1. The experimental results revealed that disintegration mainly occurred over the temperature range of 500–600 °C, because hematite/pseudobrookite was reduced to magnetite/titanomagnetite resulted in the lattice expansion. A maximum RDI −3.15mm of 45.30% was obtained at 550 °C with a H 2 /(H 2 + CO) ratio of 0.26, and the corresponding reduction degree was 13.31%. Moreover, cracks were observed with a H 2 /(H 2 + CO) ratio of 0.20. A certain interaction between H 2 and CO reduction exists, owing to their different diffusion coefficients and reduction potentials. The reduction by individual CO gases tended to follow the topochemical reaction mode, whereas the non-topochemical reaction mode was dominant with H 2 –CO mixtures. • Thermodynamically, the reduction of pseudobrookite (Fe2TiO5) by H2 and CO is studied. • The disintegration behavior under different conditions is investigated. • The effect of different parameters on disintegration is obtained, and the reason is revealed. • The reaction modes named topochemical and non–topochemical under different gas mixtures are discussed.

Optimized schemes of enhanced shale gas recovery by CO2-N2 mixtures associated with CO2 sequestration

In response to the growing demand for CO2 mitigation and unconventional natural gas, the oil and gas industry is researching for the viability to enhance shale gas recovery (ESGR) and sequester CO2 in depleted reservoirs. Previous research has shown that a CO2-N2 mixture can be employed as a desired injection fluid to concurrently address both industrial issues. Due to the infancy of ESGR operations, there is no thorough knowledge of field-level optimized strategies using CO2-N2 for the ESGR associated with CO2 sequestration. In this study, the commercial reservoir simulator GEM and CMOST by CMG were adopted to conduct ∼ 120 simulation scenarios based on the Barnett shale formation in order to comprehend the impacts of three dominating operational parameters and propose the corresponding solutions. This study reveals four major findings. Firstly, a larger N2 concentration corresponds to a better recovery factor of shale gas but a shorter breakthrough time that causes the worse CO2 storage performance. Secondly, an injection rate is initially proportional to the shale gas recovery and CO2 storage performance but beyond a threshold rate, it can inversely affect both outcomes. Thirdly, the influence of a soaking period is limited in a short term and negligible in a long term for both ESGR and CO2 sequestration. Lastly, by selecting an appropriate combination of an injection rate and a CO2-N2 ratio, the income of a project can significantly be improved by 22 % under the current carbon tax policy. This study provides shale gas operators with a guideline for implementing large-scale ESGR projects employing CO2-N2 mixtures.

Modeling of CO2 conversion in low-pressure glow discharges in CO2-N2 mixtures

An approach for evaluation of plasma parameters and conversion factor in glow discharges in CO2–N2 mixtures at low pressures is presented. In the framework of this approach, analytical expressions relating plasma characteristics (the electric field, the gas temperature) in discharges in the mixtures with those in pure CO2 have been obtained. It is shown that dissociation of CO2 molecules in collisions with electronically excited N2 molecules gives substantial contribution to the conversion rate. Obtained dependences of the plasma parameters and conversion factor on the nitrogen molar fraction agree with available experimental data.

Modeling solubility of CO2\u2013N2 gas mixtures in aqueous electrolyte systems using artificial intelligence techniques and equations of state

Determining the solubility of non-hydrocarbon gases such as carbon dioxide (CO2) and nitrogen (N2) in water and brine is one of the most controversial challenges in the oil and chemical industries. Although many researches have been conducted on solubility of gases in brine and water, very few researches investigated the solubility of power plant flue gases (CO2–N2 mixtures) in aqueous solutions. In this study, using six intelligent models, including Random Forest, Decision Tree (DT), Gradient Boosting-Decision Tree (GB-DT), Adaptive Boosting-Decision Tree (AdaBoost-DT), Adaptive Boosting-Support Vector Regression (AdaBoost-SVR), and Gradient Boosting-Support Vector Regression (GB-SVR), the solubility of CO2–N2 mixtures in water and brine solutions was predicted, and the results were compared with four equations of state (EOSs), including Peng–Robinson (PR), Soave–Redlich–Kwong (SRK), Valderrama–Patel–Teja (VPT), and Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT). The results indicate that the Random Forest model with an average absolute percent relative error (AAPRE) value of 2.8% has the best predictions. The GB-SVR and DT models also have good precision with AAPRE values of 6.43% and 7.41%, respectively. For solubility of CO2 present in gaseous mixtures in aqueous systems, the PC-SAFT model, and for solubility of N2, the VPT EOS had the best results among the EOSs. Also, the sensitivity analysis of input parameters showed that increasing the mole percent of CO2 in gaseous phase, temperature, pressure, and decreasing the ionic strength increase the solubility of CO2–N2 mixture in water and brine solutions. Another significant issue is that increasing the salinity of brine also has a subtractive effect on the solubility of CO2–N2 mixture. Finally, the Leverage method proved that the actual data are of excellent quality and the Random Forest approach is quite reliable for determining the solubility of the CO2–N2 gas mixtures in aqueous systems.