Development of the automated temperature control system of the main gas pipeline.

This article presents the results of a numerical experiment and an analysis of temperature fields (coolers for gas) using cooling elements in the case study gas pipeline. An analysis of the temperature fields demonstrated several principles for the formation of a temperature field, which indicates the need to maintain a relative temperature for gas pumping. The essence of the experiment was to install an unlimited number of cooling elements on the gas pipeline. The purpose of this study was to determine at what distance it is possible to install cooling elements for the optimal gas pumping regime, regarding the synthesis of the control law and the determination of the optimal location and assessment of control error depending on the location of the cooling elements. The developed technique allows for the evaluation of the developed control system's regulation error.

Insight into Nano-chemical Enhanced Oil Recovery from Carbonate Reservoirs Using Environmentally Friendly Nanomaterials.

The use of nanoparticles (NPs) in enhanced oil recovery (EOR) processes is very effective in reducing the interfacial tension (IFT) and surface tension (ST) and altering the wettability of reservoir rocks. The main purpose of this study was to use the newly synthesized nanocomposites (KCl/SiO2/Xanthan NCs) in EOR applications. Several analytical techniques including X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscope (SEM) were applied to confirm the validity of the synthesized NCs. From the synthesized NCs, nanofluids were prepared at different concentrations of 100-2000 ppm and characterized using electrical conductivity, IFT, and ST measurements. From the obtained results, it can be observed that 1000 ppm is the optimal concentration of the synthesized NCs that had the best performance in EOR applications. The nanofluid with 1000 ppm KCl/SiO2/Xanthan NCs enabled reducing the IFT and ST from 33 and 70 to 29 and 40 mN/m, respectively. However, the contact angle was highly decreased under the influence of the same nanofluid to 41° and the oil recovery improved by an extra 17.05% OOIP. To sum up, KCl/SiO2/Xanthan NCs proved highly effective in altering the wettability of rocks from oil-wet to water-wet and increasing the cumulative oil production.

Development of a Nanobiodegradable Drilling Fluid Using Prosopis farcta Plant and Pomegranate Peel Powders with Metal Oxide Nanoparticles.

One of the inevitable problems encountered during the petroleum well drilling process is "lost circulation" in which part of the drilling fluid is lost into the formation. A combination of nanoparticles with their unique properties and cost-effective biodegradable materials can play an effective role in treating fluid loss. In this study, our aim was to formulate drilling fluids modified with nanoparticles, pomegranate peel powder, and Prosopis farcta plant powder. The drilling fluids were identified and recognized using scanning electron microscopy, X-ray diffraction, and Fourier transform infrared spectroscopy techniques. Furthermore, experimental tests were conducted in order to investigate the performance of the newly formulated drilling fluid in improving fluid loss characteristics. The obtaining results have shown that adding 0.3 wt % of pomegranate peel powder to the reference (base) drilling fluid reduces the filter loss volume to 7.9 mL compared to the reference fluid (11.6 mL). As the optimal concentration of TiO2 was mixed with 0.3 wt % of pomegranate peel powder then added to the reference fluid, the filter loss volume was reduced to 8.6 mL.

Synergistic Efficiency of Zinc Oxide/Montmorillonite Nanocomposites and a New Derived Saponin in Liquid/Liquid/Solid Interface-Included Systems: Application in Nanotechnology-Assisted Enhanced Oil Recovery.

Oil production faces challenges such as limited oil production from carbonate reservoirs, high oil production costs, and environmental issues. Chemical flooding as an enhanced oil recovery (EOR) method (CEOR) can increase oil production by the use of chemical additives such as surfactants into the reservoirs. Surfactants can increase oil recovery by interfacial tension (IFT) reduction and alteration of the rock wettability from oil-wet to water-wet. The synthesis of chemicals such as synthetic surfactants is usually costly and harmful to the environment. To solve these problems, many researchers have oriented on the use of natural surfactants instead of synthetic ones within the CEOR process. A new approach to increase the efficiency of CEOR is the synergizing of the chemical additives with nanoparticles as a hybrid fluid, which is known as the nanotechnology-assisted EOR method. In this research, a natural surfactant derived from Cyclamen persicum (CP) plant was extracted, and its performance was optimized with the zinc oxide/montmorillonite (ZnO/MMT) nanocomposite in a synergistic usage. At the optimum concentration of the surfactant, the measurements of the IFT and the contact angle show 57.78 and 61.58% optimizations, respectively. Also, in the presence of NaCl, the performance of CP is improved. IFT and contact angle measurements were also conducted for ZnO/MMT nanofluids and CP-ZnO/MMT as hybrid nanofluids. Results indicate that ZnO/MMT nanocomposites can alter the wettability of the carbonate rock to the water-wet state. Also, the CP-ZnO/MMT hybrid nanofluid shows a good potential in both IFT reduction and altering wettability from oil-wet to water-wet. Finally, to investigate the effects of solutions on increasing oil recovery factor (RF), the optimum concentrations of the surfactant, nanocomposite, and hybrid solutions were selected for dynamic core flooding experiments, and improvements showed oil RF increases of 8.2, 6, and 13%, respectively.

Kinetic Study on Nannochloropsis Oculata's Lipid Extraction Using Supercritical CO2 and n-Hexane for Biodiesel Production.

Biodiesel as a renewable fuel has attracted increasing attention in recent years. Microalgae biomass is becoming an attractive raw material for producing biodiesel using supercritical CO2 (SC-CO2) as a safe and environmentally friendly technique with high efficiency for lipid extraction. In this study, the lipid of Nannochloropsis oculata was extracted under different conditions of SC-CO2 to assess the kinetics of supercritical fluid extraction. The effective parameters on lipid extraction, including temperature, pressure, and the existence of n-hexane as a co-solvent, were investigated. The results show that an increase in temperature at low or high pressures causes the kinetic constant of lipid extraction to decrease or increase, respectively. Also, an increase in pressure causes the kinetic constant of lipid extraction to increase at low or high temperatures. The most yield and the most kinetic constant value during extraction with pure CO2 are about 0.262 [g extracted lipid/g microalgal biomass] and 0.062 min-1, respectively, at the highest pressure and temperature (i.e., 550 bar and 75 °C). Using SC-CO2 laced with n-hexane increases both the final yield and the rate of lipid extraction. Also, it improves the quality of the biodiesel fuel through the extraction of unsaturated fatty acids with a concentration of almost two times more than saturated fatty acids. Additionally, results reveal that the effect of adding n-hexane to CO2 in lipid extraction would be more efficient by increasing the temperature and lowering the pressure.

Effects of MgO, γ-Al2O3, and TiO2 Nanoparticles at Low Concentrations on Interfacial Tension (IFT), Rock Wettability, and Oil Recovery by Spontaneous Imbibition in the Process of Smart Nanofluid Injection into Carbonate Reservoirs.

Recently, some nanoparticles have been used to upgrade injected water into oil reservoirs to enhance oil recovery. These nanoadditives can be used in a variety of injectable waters, including smart/engineered water with special salinities. In this study, the performance of smart water containing different concentrations of magnesium sulfate (MgSO4) and calcium chloride (CaCl2) and 500 ppm of titanium dioxide (TiO2), γ-alumina (γ-Al2O3), and magnesium oxide (MgO) nanoparticles in interfacial tension (IFT) and contact angle reduction and oil production under imbibition of the chemical fluids was investigated. Based on the results, the IFT decreased more when ions and nanoparticles were present in the system. An optimum IFT of 4.684 mN/m was recorded for the nanofluid containing 2000 ppm of MgSO4 + 500 ppm of MgO. The results of contact angle tests demonstrated improved saline water capabilities in the presence of nanoparticles and showed that a very effective reduction was accessible and highly hydrophilic wettability was obtained when using smart water with stable nanoparticles as a minimum contact angle of 18.33° was obtained by the optimal fluid containing nano-γ-Al2O3. Finally, an ultimate oil production of 64.1-68.7% was obtained in six experiments with smart water and stable nanoparticles.

Experimental Measurement and Thermodynamic Modeling of the Wax Disappearance Temperature (WDT) for a Quaternary System of Normal Paraffins.

Normal paraffin (N-alkane)-based wax is well known as a severe problem in petroleum production, transportation, and processing. Implementing suitable solutions for wax-related problems requires vast technical knowledge and investigation of the wax disappearance temperature (WDT) of multicomponent systems in petroleum-dominated systems. In this study, the WDTs of a quaternary system comprising different mixtures of n-undecane + n-tetradecane + n-hexadecane + n-octadecane were measured using a visual-based diagnosis apparatus under atmospheric pressure. On the other hand, the WDTs of the studied systems are predicted by applying a solid solution model without any adjustable parameter. Two approaches namely γ-φ and γ-γ are assessed. In the (γ-φ) approach, perturbed-chain statistical associating fluid theory (PC-SAFT) is applied for liquid phase modeling, while the solid phase is described using different activity coefficient models. In the (γ-γ) approach, nonidealities of both the liquid and solid phases are investigated using different combinations of activity coefficient models such as ideal solution, regular solution theory, predictive Wilson, predictive UNIQUAC, and UNIFAC. Comparison of experimental data and thermodynamic modeling results indicates that applying the predictive UNIQUAC model for describing the nonideality of the solid phase and the regular solution model for the liquid phase is the best combination for the aforementioned system with the average absolute deviation (AAD) of 0.8 K.

Experimental Investigation of Foam Flooding Using Anionic and Nonionic Surfactants: A Screening Scenario to Assess the Effects of Salinity and pH on Foam Stability and Foam Height.

Gravity override and viscous fingering are inevitable in gas flooding for improving hydrocarbon production from petroleum reservoirs. Foam is used to regulate gas mobility and consequently improve sweep efficiency. In the enhanced oil recovery process, when the foam is introduced into the reservoir and exposed to the initial saline water saturation and pH condition, selection of the stable foam is crucial. Salinity and pH tolerance of generated foams are a unique concern in high salinity and pH variable reservoirs. NaOH and HCl are used for adjusting the pH, and NaCl and CaCl2 are utilized to change salinity. Through analyzing these two factors along with surfactant concentration, we have instituted a screening scenario to optimize the effects of salinity, pH, surfactant type, and concentration to generate the most stable state of the generated foams. An anionic (sodium dodecyl sulfate) and a nonionic (lauric alcohol ethoxylate-7) surfactants were utilized to investigate the effects of the surfactant type. The results were applied in a 40 cm synthetic porous media fully saturated with distilled water to illustrate their effects on water recovery at ambient conditions. This most stable foam along with eight different stabilities and foamabilities and air alone was injected into the sand pack. The results show that in optimum surfactant concentration, the stability of LA-7 was not highly changed with salinity alteration. Also, we probed that serious effects on foam stability are due to divalent salt and CaCl2. Finally, we found the most water recovery that was obtained by the three most stable foams by the formula of 1 cmc SDS + 0.5 M NaCl, 1 cmc SDS + 0.01 M CaCl2, and LA-7@ pH ∼ 6 from porous media flooding. Total water recovery for the most stable foam increased by an amount of 65% compared to the state of air alone. A good correlation between foam stability and foamability at higher foam stabilities was observed.

AdaBoost Metalearning Methodology for Modeling the Incipient Dissociation Conditions of Clathrate Hydrates.

This paper proposes the AdaBoost metalearning methodology to combine the outcomes of tree-based models of classification and the regression tree (CART) algorithm for estimating the equilibrium dissociation temperature of clathrate hydrates. In addition to the AdaBoost-CART models, models based on the adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) approaches were also developed. Training and testing of the models were done utilizing a gathered database of more than 3500 experimental data on incipient dissociation conditions of CO2 and other hydrate systems. With the average absolute relative deviation percent (AARD%) between 0.03 and 0.07, 0.04 and 1.09, and 0.09 and 1.01, which were obtained by the presented AdaBoost-CART, ANFIS, and ANN models, respectively, the targets were reproduced with satisfactory accuracy. However, for all of the studied clathrate hydrate systems, the proposed AdaBoost-CART models provide more reliable results. Indeed, the obtained AARD% values for tree-based models are lower than those of other models.

Simulation and Optimization of the Acid Gas Absorption Process by an Aqueous Diethanolamine Solution in a Natural Gas Sweetening Unit.

The presence of carbon dioxide in natural gases can lower the quality of natural gas and can cause CO2 freezing problems. Therefore, using reliable techniques for the reduction and elimination of carbon dioxide from natural gases is necessary. The aqueous diethanol amine (DEA) solution's ability to simultaneously absorb H2S and CO2 from sour natural gases makes it possible to use this solution in the natural gas sweetening process. The goal of this work was to determine the maximum amount of the removed CO2 by an aqueous DEA solution in one of the gas sweetening plants of the National Iranian South Oilfields Company (NISOC). For this purpose, based on the obtained designed experiment results using the L9 orthogonal array Taguchi method, the experiments were conducted and three levels of amine concentrations (25, 28, and 30 wt %), temperatures (40, 50, and 60 °C), and circulation rates of lean amine (220, 240, and 260 m3 h-1) were considered as the key operational parameters on CO2 removal. To evaluate the ability of the HYSYS simulation software and the Kent-Eisenberg thermodynamic model to predict CO2 absorption by an aqueous DEA solution in the gas sweetening process, the field data were compared with the results of the simulation. It was observed that the maximum removal of CO2 is achieved at a lean amine concentration of 30 wt %, a temperature of 40 °C, and a circulation rate of 260 m3 h-1. Also, the experimental results indicate that the effects of the selected process variables on CO2 absorption are not linear and the most effective parameter on carbon dioxide removal is the concentration of amine in an aqueous solution and the temperature of the lean amine has the least effect. Besides, the obtained simulation results are in the range of the unit design basis but have some deviations from field data. The findings of this study can help in better understanding of the selection of the effective variables in the natural gas sweetening process and obtaining their appropriate values to achieve the highest efficiency.

Evaluation of CO2 Absorption by Amino Acid Salt Aqueous Solution Using Hybrid Soft Computing Methods.

Amino acid salt (AAs) aqueous solutions have recently exhibited a great potential in CO2 absorption from various gas mixtures. In this work, four hybrid machine learning methods were developed to evaluate 626 CO2 and AAs equilibrium data for different aqueous solutions of AAs (potassium sarcosinate, potassium l-asparaginate, potassium l-glutaminate, sodium l-phenylalanine, sodium glycinate, and potassium lysinate) gathered from reliable references. The models are the hybrids of the least squares support vector machine and coupled simulated annealing optimization algorithm, radial basis function neural network (RBF-NN), particle swarm optimization-adaptive neuro-fuzzy inference system, and hybrid adaptive neuro-fuzzy inference system. The inputs of the models are the CO2 partial pressure, temperature, mass concentration in the aqueous solution, molecular weight of AAs, hydrogen bond donor count, hydrogen bond acceptor count, rotatable bond count, heavy atom count, and complexity, and the CO2 loading capacity of AAs aqueous solution is considered as the output of the models. The accuracies of the models' results were verified through graphical and statistical analyses. RBF-NN performance is promising and surpassed that of other models in estimating the CO2 loading capacities of AAs aqueous solutions.

Effect of Various Isolated Microbial Consortiums on the Biodegradation Process of Precipitated Asphaltenes from Crude Oil.

One of the serious problems in the oil industry is precipitation and deposition of asphaltenes in the different oil production stages including formation, wellbore, production tubing, flow lines, and separation units. This phenomenon causes a dramatic increase in the cost of oil production, processing, and transferring. Thus, it seems to be very necessary to use the removing methods for precipitated asphaltenes in different crude oil production and transferring stages. In this study, the ability of microorganisms for biodegradation of precipitated asphaltenes was investigated. For this purpose, four bacterial consortiums were isolated from oil-contaminated soil, crude oil, reservoir water, and oil sludge samples of an oil field located in the southwest of Iran. Based on the results of the designed experiments, by using response surface methodology (RSM) and central composite design, the bacterial consortiums were cultured in the flasks. Three levels of temperatures, salinity, pH, and initial asphaltene concentration as the substrate were considered as the parameters of culture medium and incubated growth mediums for 60 days. The maximum asphaltene biodegradation was 46.41% caused by the crude oil consortium including Staphylococcus saprophyticus sp. and Bacillus cereus sp. at 45 °C, salinity 160 g·L-1, pH 6.5, and 25 g·L-1 initial asphaltene concentration. Also, it was observed that the negative or positive impacts of culture media conditions such as temperature and salinity on asphaltene degradation depended on the type of the available bacterial consortium. The carbon-hydrogen-nitrogen-sulfur analysis showed that carbon, hydrogen, nitrogen, and in some cases, the sulfur in biodegraded samples are less than in control samples. Moreover, Fourier transform infrared analysis indicated that the alkyne groups were less resistant to biodegradation and were eliminated thoroughly after 2 months of incubation. In addition, alkane components were partially removed in treated asphaltene fraction. The parameters of culture medium were optimized by RSM, and besides, their effects on the performance of bacteria in the asphaltene biodegradation process were discussed. The validity of some available kinetic models to describe the behavior of the studied bacteria consortium was investigated, and it was observed that Tessier, Moser, and Contois models accurately predict the values of asphaltenes and biomass concentration at 30, 45, and 60 °C, respectively.

Rigorous prognostication and modeling of gas adsorption on activated carbon and Zeolite-5A.

Gas adsorption on various adsorbents is of highly important issue for the separation of gas mixtures in many industrial processes. In this work, estimation of pure gases (CH4, N2, CO2, H2, C2H4) adsorption on activated carbon (AC) and CO2, CH4, N2 on Zeolite-5A adsorbent were studied by developing four different computing techniques, namely MLP-ANN, ANFIS, LSSVM, and PSO-ANFIS for a broad range of experimental data found in the literature. Temperature, pressure, pore size (only for AC) and kinetic diameter of adsorbed gases are considered as the inputs and the gas adsorption as the output parameters of the developed models. We also used several statistical and graphical tools to assess the accuracy and applicability of the proposed models. The results of the study suggest the reliability and validity of all the models developed for estimating the equilibrium adsorption of gases on the adsorbents. Also, it is found that of all the models developed, the ANN model estimates experimental data of the gas adsorption on AC more accurately due to its values of R2 and AARD%, 0.9865 and 0.8948, respectively. Besides, PSO-ANFIS is the best model to prognosticate gas adsorption on zeolite 5A with R2 and AARD%, 0.9897 and 0.9551, respectively.