Microfluidic chips in the last two decades have had significant advances in the analysis of INTERFACIAL TENSION phenomenon due to their many advantages. To analyze INTERFACIAL TENSION phenomena, droplet flow in microchannels can be used. In this study, water-n-hexane INTERFACIAL TENSION in the presence of surface-active agents was measured, using microfluidic tensiometry. For this purpose, a glass microfluidic flow-focusing junction was fabricated for generating n-hexane droplets within an aqueous phase. The dependence of droplet size on the concentration of surfactants has been investigated. A theoretical equation was developed, considering force balance on the droplet generation in the microfluidic device, giving a relation between the INTERFACIAL TENSION and the generated droplet sizes. By standardizing the microfluidic chips with the aid of a system, whose INTERFACIAL TENSION is known (hexane normal and tween 20 in distilled water), INTERFACIAL TENSION can be measured with measuring the size of produced droplets for other systems that can form droplets in the microchannel. In this study, the microfluidic device and the relation were employed to measure the INTERFACIAL TENSION in the presence of either of sodium dodecyl sulphate (SDS) or Cetyl trimethylammonium bromide (CTAB) surfactants. It was found that the measured INTERFACIAL TENSIONs deviate less than 10% compared to those measured with a commercially available ring method.

In this study, surface TENSION modeling is developed using intermolecular thermodynamic potential function including the two-parameter Lennard-Jones model in a semi-analytical form and the three-parameter well-square model in a full-analytical form in a wide range of temperatures in the bulk scale. The comparison of the results for hydrocarbon fluids (light to heavy) and non-hydrocarbon fluids shows that the prediction of surface TENSION through the square-well model, due to its high flexibility and mathematical simplicity compared to the Lennard-Jones model, provides significant agreement with experimental data.

A key variable for determining carbon dioxide (CO2) storage capacity in sub-surface reservoirs is the INTERFACIAL TENSION (IFT) between formation water (brine) and injected gas. Establishing efficient and precise models for estimating CO2 – brine IFT from measurements of independent variables is essential. This is the case because laboratory techniques for determining IFT are time-consuming, costly and require complex interpretation methods. For the datasets used in the current study, correlation coefficients between the input variables and measured IFT suggest that CO2 density and pressure are the most influential variables, whereas brine density is the least influential. Six artificial neural network configurations are developed and evaluated to determine their relative accuracy in predicting CO2– brine IFT. Three models involve multilayer perceptron (MLP) tuned with Levenberg-Marquardt, Bayesian regularization and scaled conjugate gradient back-propagation algorithms, respectively. Three models involve the radial basis function (RBF) trained with particle swarm optimization, differential evolution, and farmland fertility optimization algorithms, respectively. The six models all generate CO2– brine IFT predictions with high accuracy (RMSE <0. 7 mN/m). However, the RBF models consistently provide slightly higher IFT prediction accuracies (RMSE <0. 54 mN/m) than the MLP models.

As a physiochemical property, asphaltenes are known to be one the most surface active compounds in crude oil. Due to such property, their behavior is most probably influenced by fluid-fluid interactions at the contact surface (interface). Potentially and naturally, in most cases, water is in contact with crude oil and is co-produced with it as well. Considering that asphaltene molecules are polar compounds similar to water molecules, asphaltenes are INTERFACIALly affected by water while they are absorbed to the interface. Such effects could be investigated by INTERFACIAL TENSION (IFT) changes when de-ionized water is used and dead-crude oil does not contain other surface active impurities like metallic compounds. In this study, extensive IFT experiments were conducted between three different oil samples and distilled water in a wide range of pressure from 2000 to 0 psia. The reversibility of asphaltene absorbance to the interface was also investigated by reversing the pressure path from 0 to 2000 psia. The results show that oil/water IFT changes with pressure, but upward/downward oscillations were detected. Such an oscillating behavior of IFT trends was related to asphaltenes surface activity as the oil samples used did not contain other impurities. Oscillations were reduced as resin to asphaltene ratio was increased, suggesting the non-absorbable behavior of the asphaltenes stabilized by resins. A microscopic surface experiment on one of the samples showed that at a certain concentration and particle size, a rigid film of absorbed asphaltenes was created at the interface instantaneously. The high rigidity of such a film gives rise to a hypothesis, which states that water affects asphaltene surface behavior possibly through strong hydrogen bonding (H-bond). Reversing the pressure path revealed that asphaltene surface absorbance is partially irreversible. The experiments were conducted three times, and each data set was presented along with an average of three sets for each sample.

Surface active agents (surfactants) as the most important chemicals to enhance oil recovery (EOR) can reduce INTERFACIAL TENSION between the injected aqueous solution and the oil in a reservoir. They change wettability of the porous media to release and move the remaining oil trapped in the pores and throats towards the well. According to the important roles of the surfactants، it is necessary to predict their performance for EOR process. In this research، two data-based mathematical models were developed to estimate INTERFACIAL TENSION of the oil، salty water and anionic surfactant system using 598 experimental data. To obtain the correlations between the independent variables and the objective function، genetic programing has been applied. Squared correlation coefficient (R2) of the models is 0. 946 and 0. 9387; moreover، root-mean-square deviation (RMSD) of the models is 3. 4439 mN/m and 3. 3261 mN/m respectively. Simplicity and acceptable estimation are particular features of the models.

The need to enhance oil recovery from depleted reservoirs has led to the development of various techniques, including the use of nanofluids, surfactants, and polymers in established oil fields. However, the development of injection fluids is hindered by cost, harsh reservoir conditions, and stability challenges. In this study, we introduced a novel Polymeric Surfactant (PS) with unique polar components. The resulting PS solution maintained a consistent viscosity even under changing reservoir conditions, including high temperatures (70°C). Additionally, we assessed the ability of the surfactant to change the wettability of oil-wet sandstone surfaces by measuring changes in the contact angle after treatment with the PS solution. Experimental results showed a significant reduction in the contact angle, shifting from an initial 150° to 53.4°, indicating a transition from an oil-wet to a partially water-wet state. The promising potential of PS for enhanced oil recovery was demonstrated by achieving an additional 21.11% oil recovery from the initial in-place oil content. These positive results highlight the encouraging prospects of using the PS polymer to advance enhanced oil recovery efforts. As mature wells present increasingly challenging conditions for oil extraction, solutions like PS offer promise for the future of enhanced oil recovery strategies. The need to enhance oil recovery from depleted reservoirs has led to the development of various techniques, including the use of nanofluids, surfactants, and polymers in established oil fields. However, the development of injection fluids is hindered by cost, harsh reservoir conditions, and stability challenges. In this study, we introduced a novel Polymeric Surfactant (PS) with unique polar components. The resulting PS solution maintained a consistent viscosity even under changing reservoir conditions, including high temperatures (70°C). Additionally, we assessed the ability of the surfactant to change the wettability of oil-wet sandstone surfaces by measuring changes in the contact angle after treatment with the PS solution. Experimental results showed a significant reduction in the contact angle, shifting from an initial 150° to 53.4°, indicating a transition from an oil-wet to a partially water-wet state. The promising potential of PS for enhanced oil recovery was demonstrated by achieving an additional 21.11% oil recovery from the initial in-place oil content. These positive results highlight the encouraging prospects of using the PS polymer to advance enhanced oil recovery efforts. As mature wells present increasingly challenging conditions for oil extraction, solutions like PS offer promise for the future of enhanced oil recovery strategies.

Accurate INTERFACIAL TENSION (IFT) determination between crude oil and brines is crucial in enhanced oil recovery (EOR) processes. However, the available IFT models only apply to systems containing pure hydrocarbons and saline waters. The current study aims to design comprehensive predictive tools for the IFT between asphaltenic crude oils and various brines. Hence, 339 relevant experimental data covering an extensive range of operating conditions were gathered from the literature, and the most effective input variables were determined through Spearman’s rank coefficient. Then, the experimental data were utilized to train the smart soft-computing approaches, i.e., radial basis function (RBF), multilayer perceptron (MLP), and Gaussian process regression (GPR). Although all novel predictive tools presented excellent results, the one designed based on the GPR method was recognized as the most reliable model with an average absolute relative error (AARE) of 0.67% and an R2 value of 99.63% in the testing stage. Additionally, it estimated most of the IFT data with relative errors below 0.10%. On the other hand, the validity of the gathered databank was confirmed through the leverage method. The influences of pressure, temperature, salinity, and structural characteristics of salts on the IFT were discussed in detail, and the proposed models favorably described the physical trends. Eventually, a sensitivity analysis was carried out based on the GPR model to clarify the order of significance of factors in controlling the crude oil-brine IFT.

Ultrasound assisted oxidative desulfurization (UAOD) is a new process for the sulfur removal from different middle distillate cuts. In the UAOD process, at first, the sulfur-containing compounds are oxidized using a suitable oxidation system under ultrasound irradiation. Then, the oxidized sulfur-containing compounds are separated by solvent extraction. In the present study, the effect of INTERFACIAL TENSION between aqueous and hydrocarbon phases on the sulfur removal of diesel fuel has been investigated for the first time. The selected oxidation system was hydrogen peroxide/formic acid system. In this regards, three different surfactants including anionic, cationic, and nonionic surfactants have been evaluated. The results revealed that the application of sodium dodecyl sulfate (SDS) as an anionic surfactant and cetyltrimethylammonium bromide (CTAB) as a cationic surfactant leads to the sulfur removal of 82. 65 and 83. 10% after oxidation followed by solvent extraction respectively. The sulfur removal in the absence of surfactants was 81. 61% in the same oxidation and extraction conditions. The application of span 60 as a nonionic surfactant leads to a decrease in sulfur removal to 78. 65% in the same oxidation and extraction conditions. However, the application of span 60 leads to about 3% increase in the sulfur removal in comparison with the case without surfactant after the oxidation step. Therefore, the addition of surfactants can lead to a positive effect on the oxidation step due to decreasing the INTERFACIAL TENSION between aqueous and hydrocarbon phases and a negative effect on the extraction step of the UAOD process.