Iranian Journal of Oil and Gas Science and Technology

Abstract Among the all parameters affecting the performance of a downhole de-oiling hydrocyclone, the investigation of internal flow field deserves more attempts especially in the petroleum industry. In this study, the effects of inlet flow rate, inlet oil volume fraction, and oil droplet diameter on the separation efficiency and pressure drop ratio have been investigated along the hydrocyclone body. All the simulations were performed using computational fluid dynamics (CFD) techniques, in which the Eulerian multiphase model and the Reynolds stress turbulent model were employed for the prediction of multiphase and turbulent flow parameters through the hydrocyclone. The velocity component profiles, separation efficiency, pressure drop, and volume fraction are also other parameters which have been considered in this work. The results of the simulations illustrate good agreement with the reported experimental data. Furthermore, the simulations indicate that the separation efficiency almost increases twofold, when the droplet diameter increases from 25 to 50 micron. The effect of inlet flow rate on the separation efficiency is so significant that an increase in inlet flow rate from 5 to 25 l/min causes a sharp increase in the separation efficiency and raises it 2.5 times the initial value. However, the inlet oil volume fraction showed a minor effect on the hydrodynamic flow behavior in the hydrocyclone body compared to the other investigated parameters.

Abstract Recently different approaches have been developed in the field of sensor fault diagnostics based on Auto-Associative Neural Network (AANN). In this paper we present a novel algorithm called Self reconstructing Auto-Associative Neural Network (S-AANN) which is able to detect and isolate single faulty sensor via reconstruction. We have also extended the algorithm to be applicable in multiple fault conditions. The algorithm uses a calibration model based on AANN. AANN can reconstruct the faulty sensor using non-faulty sensors due to correlation between the process variables, and mean of the difference between reconstructed and original data determines which sensors are faulty. The algorithms are tested on a Dimerization process. The simulation results show that the S-AANN can isolate multiple faulty sensors with low computational time that make the algorithm appropriate candidate for online applications.

Abstract In this paper, the effect of cationic and anionic ion sizes on the charge storage capability of graphene nanosheets is investigated. The electrochemical properties of the produced electrode are studied using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) techniques in 3M NaCl, NaOH, and KOH electrolytes. Scanning electron microscopy (SEM) is used to characterize the microstructure and nature of the prepared electrode. The SEM images and X-ray diffraction (XRD) patterns confirm the layered structure (12 nm thickness) of the used graphene with an interlayer distance of 3.36 Å. The electrochemical results and the ratio of  confirm good charge storage and charge delivering capability of the prepared electrode in the 3M NaCl electrolyte. Charge/discharge cycling tests show a good reversibility and confirm that the solution resistance will increase after 500 cycles. In this paper, the effect of cationic and anionic ion sizes on the charge storage capability of graphene nanosheets, is investigated. Electrochemical properties of produced electrode are studied using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) techniques, in 3M NaCl, NaOH and KOH electrolytes. Scanning electron microscopy (SEM) is used to characterize the microstructure and nature of prepared electrode. SEM images and XRD patterns confirm the layered structure (12 nm thickness) of the used graphene with an interlayer distance of 3.36 (Å). The electrochemical results and the ratio of q*_O/q*_T confirm a good charge storage and charge delivering capability of prepared electrode in 3M NaCl electrolyte. Charge/discharge cycling test shows a good reversibility and confirms that solution resistance will increase after 500 cycles.

Abstract Production strategy from a hydrocarbon reservoir plays an important role in optimal field development in the sense of maximizing oil recovery and economic profits. To this end, self-adapting optimization algorithms are necessary due to the great number of variables and the excessive time required for exhaustive simulation runs. Thus, this paper utilizes genetic algorithm (GA), and the objective function is defined as net present value (NPV). After developing a suitable program code and coupling it with a commercial simulator, the accuracy of the code was ensured using a synthetic reservoir. Afterward, the program was applied to an Iranian southwest oil reservoir in order to attain the optimum scenario for primary and secondary production. Different hybrid water/gas injection scenarios were studied, and the type of wells, the number of wells, well coordination/location, and the flow rate (production/injection) of each well were optimized. The results from these scenarios were compared, and simultaneous water and gas (SWAG) injection was found to have the highest overall profit representing an NPV of about 28.1 billion dollars. The application of automated optimization procedures gives rise to the possibility of including additional decision variables with less time consumption, and thus pushing the scopes of optimization projects even further.

Abstract In this study, nanocomposite coatings based on polyurethane cerium nitrate montmorillonite (MMT) were prepared, applied on carbon steel substrates, and investigated. The nanocomposite coatings were successfully prepared by the effective dispersing of nanoparticles in polyurethane resin by mechanical and sonication processes. The state of dispersion, dissolution, and incorporation were characterized by optical microscopy, sedimentation tests, and transmission electron microscopy. The structure and properties of the nanocomposite coatings were investigated by X-ray diffraction and anticorrosive properties of the nanocomposites were studied by Tafel polarization measurements. The experimental results showed that the PU/MMT/Cerium nitrate nanocomposite coatings were superior to the neat PU in corrosion protection. In addition, it was observed that the corrosion protection of the nanocomposite coatings was improved as the clay and cerium nitrate loadings were increased to 4 wt.% to 2 wt.% respectively.

Abstract Corrosion results in hazardous and expensive damage to pipelines, vehicles, water and wastewater systems, and even home appliances. One of the most extensively practical methods for protecting metals and alloys against corrosion is to use organic inhibitors. The inhibition capability of 2-Mercaptobenzothiazole (2-MBT) against the corrosion of carbon steel in a 2 M NaCl solution was examined by Tafel polarization. By using 2-Mercaptobenzothiazole both the cathodic and anodic reactions are delayed through chemical and physical adsorption and blocking the active corrosion sites. Based on the polarization curves, it was indicated that by increasing the inhibitor concentration, the inhibition efficiency increases up to 70% at room temperature, and it improves at higher temperatures. The adsorption of 2-Mercaptobenzothiazole was based on the Langmuir adsorption isotherm. The enthalpies of activation were determined to be around +50 kJ.mol^-1. The endothermic nature of the steel dissolution procedure is reflected by the positive symbols of the enthalpies (ΔH) of activation process. The determined  values range from -32.69 to -35.81 kJ.mol^-1, which shows both electrostatic adsorption and the chemisorption of the adsorption mechanism. The calculated entropy of adsorption was 78 J.mol^-1_.K^-1 indicating the increment in the solvent entropy and a more positive water desorption entropy.

Abstract When a natural gas pipeline ruptures, the adjacent upstream and downstream automatic control valves (ACV) should close quickly to prevent leakage or explosion. The differential pressure set point (DPS) at each valve location is the main criteria for value setting in ACV actions. If the DPS is not properly adjusted, the ACV may mistakenly close or it may not take any actions at a proper time. In this study, the effect of characteristic parameters such as pipeline operational pressure (POP) and pipeline pressure drop rate (ROD) due to rupture or a major leak was experimentally investigated on DPS. 25 different conditions with the double set of the mentioned typical characteristic parameters were chosen. In each condition, the differential pressure (DP) was measured over a period of 180 s by statistically analyzing the experimental results, so 25 maximum DP values (DPSs) were obtained. The DPS rises by an increase in ROD or a decrease in POP. Because of using nitrogen gas instead of natural gas for safety reasons and the uncertainties, the DPS results can be practically applied by adding a safety factor of 15%. Finally, the diagram of DPS with respect to ROD and that of non-dimensional DPS (DOP) versus non-dimensional ROD (RTP) were provided for different POP’s.

Abstract In the present study, the permeabilities of CO₂ and CH₄ in terms of ideal and actual CO₂/CH₄ selectivity were investigated through the synthesized membranes of poly (ether-block-amide) (Pebax 1657) accompanied with poly (ethylene glycol) (PEG 400) and NH₂-MIL125 nanoparticles. NH₂-MIL125 nanofillers were added to the blend of PEG 400 and Pebax 1657 at various weight fractions to fabricate polymeric nanocomposite membranes. Several analyses such as the crystalline structure of the synthesized membranes, field emission scanning electron microscopy (FESEM) and X-ray diffraction analysis (XRD) were utilized to investigate the cross-sectional and surface morphology of the membranes; the formation of the chemical bonds was identified by Fourier transform infrared (FTIR). This study presents the permeation of both pure and mixed gases ofmethane and carbon dioxide through Pebax 1657, Pebax/PEG blend, and the Pebax/PEG/NH₂-MIL125 nanocomposite membranes in a pressure range of 2-8 bar and at ambient temperature. The findings demonstrated that the synthesized nanocomposite membranes had a positive effect on the separation performance in comparison with the membranes made of neat polymer and polymer blends.

Abstract < p>One of the most important factors through the miscible gas injection process is to determine the Minimum Miscibility Pressure. According to the definition, the minimum miscibility pressure is the minimum pressure at which, at a constant temperature, the oil and gas injected can dissolve together to form a single phase. This pressure is typically abbreviated as MMP. Among the available methods for determining the minimum miscibility pressure, laboratory methods including slim tube test and ascending bubble apparatus test are more widely utilized. Although the mentioned tests have high measurement accuracy, they are very time consuming and expensive. Therefore, the determination of the minimum miscibility pressure is usually done using computational and simulation approaches that also have high accuracy. Conducting PVT tests and determining their MMP using slim tube method was previously performed. In this study, the minimum miscibility pressure of reservoirs was determined by applying three methods of simulation with PVTi software, simulation with Eclipse 300 software and using Empirical Correlations. By comparing the obtained results and the laboratory results, it was revealed that the simulation by Eclipse 300 is regarded as the fastest and most accurate approach.

Abstract In this paper, graphene oxide decorated with cerium oxide (CeO₂) nanoparticles was prepared and used as anticorrosive pigments in epoxy nanocomposite coatings. The synthesized nanoparticle was characterized by FTIR, XRD, SEM, and EDX analyses. Graphene oxide decorated with CeO₂ nanoparticles was dispersed in epoxy resin by sonication. The optimum nanoparticle content of the epoxy resin was studied by differential scanning calorimetry. The anticorrosive properties of these coatings were investigated using electrochemical impedance spectroscopy method and polarization in corrosive solution. Impedance parameters showed a decrease in the coating resistance over immersion time. The results indicated that the epoxy coatings containing nanoparticles could significantly increase the corrosion resistance of composite coatings compared to those of pure epoxy, and the highest value was obtained for 1% nanocomposite coatings after 270 days of immersion. Pull-off adhesion test showed that the highest value of adhesion was related to the coating containing 1% nanoparticles.

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Abstract The organic geochemical characterization of crude oil samples from the oil fields of the Niger delta was carried out using gas chromatography–-mass spectrometry (GC–-MS) to genetically characterize the oil samples in terms of their biomarker composition. Geochemical characteristics such as depositional environments, kerogen type, and source of organic matter were analyzed using aliphatic biomarkers as a supporting tool. Five samples were randomly collected from Tebidaba, Clough Creek and Azuzuama fields in Bayelsa State, Nigeria. The saturated hydrocarbons were analyzed using GC–MS. The n-alkanes, isoprenoids, biomarkers hopanes, and steranes fingerprints were extracted from chromatogram for m/z 57, 191, 217 values respectively. The results revealed that the five studied samples were characterized by C₂₉ sterane predominance and the presence of oleanane, depicting organic matter with vascular land plant material inputs and a deltaic contribution. Ternary plots showed that the oils were deposited in an estuarine environment. The pristane (Pr) /nC₁₇ versus phytane (Ph)/nC₁₈ showed that TEB 08 and WELL 2 are in the anoxic environment inferring kerogen II and a mixture of types I and II respectively. TEB 12, CCST, and AZU ST has kerogen type III deposited in an oxic environment.

Abstract Modelling involves the use of statistical techniques or analogy data to infill the inter-well volume producing images of the subsurface. Integration of available data sets from “KO” field were used to identify hydrocarbon prospects and by means of interpolation, populate the facies and petrophysical distribution across the field to define the reservoir properties for regions with missing logging data[KO1] . 3D seismic data, check-shot data, and a series of well logs of four wells were analyzed, and the analysis of the well logs was performed using the well data. The synthetic seismogram produced from the well ties [M.N.2] [KO3] was used to map horizon slices across the reservoir regions. Four horizons and fifteen faults, including one growth fault, four major faults, and other minor faults, all in the time domain were mapped. Attribute analyses were carried out, and a 3D static model comprised of the data from the isochore maps, faults, horizons, seismic attributes, and the various logs generated was built. A stochastic method was also employed in populating the facies and petrophysical models. Two hydrocarbon-bearing sands (reservoirs S1 and S2) with depth values ranging from –1729 to 1929 m were mapped. The petrophysical analysis gave porosity values ranging from 0.18 to 0.24 across the reservoirs, and the permeability values ranged from 2790 to 5651 mD. The water saturation (S_w) of the reservoirs had an average value of 50% in reservoir S1 and 47% in reservoir S2. The depth structure maps generated showed an anticlinal structure in the center of the surfaces, and the mapped faults with the four wells were located in the anticlinal structure. The reserve estimate for the stock tank oil initially in place (STOIIP) of the reservoirs was about 70 mmbbl, and the gas initially in place (GIIP) of the reservoirs ranged from 26714 to 63294 mmcf. The result of the petrophysical analysis revealed the presence of hydrocarbon at favorable quantities in the wells, while the model showed the distribution of these petrophysical parameters across the reservoirs.



 



Modelling involves the use of statistical techniques or analogy data to infill the inter-well volume producing images of the subsurface. Integration of available data sets from “KO” field were used to identify hydrocarbon prospects and by means of interpolation, populate the facies and petrophysical distribution across the field to define the reservoir properties for regions with missing logging data[KO1] . 3D seismic data, check-shot data, and a series of well logs of four wells were analyzed, and the analysis of the well logs was performed using the well data. The synthetic seismogram produced from the well ties [M.N.2] [KO3] was used to map horizon slices across the reservoir regions. Four horizons and fifteen faults, including one growth fault, four major faults, and other minor faults, all in the time domain were mapped. Attribute analyses were carried out, and a 3D static model comprised of the data from the isochore maps, faults, horizons, seismic attributes, and the various logs generated was built. A stochastic method was also employed in populating the facies and petrophysical models. Two hydrocarbon-bearing sands (reservoirs S1 and S2) with depth values ranging from –1729 to 1929 m were mapped. The petrophysical analysis gave porosity values ranging from 0.18 to 0.24 across the reservoirs, and the permeability values ranged from 2790 to 5651 mD. The water saturation (S_w) of the reservoirs had an average value of 50% in reservoir S1 and 47% in reservoir S2. The depth structure maps generated showed an anticlinal structure in the center of the surfaces, and the mapped faults with the four wells were located in the anticlinal structure. The reserve estimate for the stock tank oil initially in place (STOIIP) of the reservoirs was about 70 mmbbl, and the gas initially in place (GIIP) of the reservoirs ranged from 26714 to 63294 mmcf. The result of the petrophysical analysis revealed the presence of hydrocarbon at favorable quantities in the wells, while the model showed the distribution of these petrophysical parameters across the reservoirs.



 [KO1]Sentence has been rephrased.




 [M.N.2]This verb does not make sense in this context and has made the sentence unclear.




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Abstract Water can contain microorganisms and cause deposition and corrosion in cooling tower systems. Therefore, the water treatment of cooling towers is essential. Various biocides are used to remove bacteria and disinfect the water of cooling towers, and the most commonly used are sodium hypochlorite and chlorine compounds. This work examined two chlorinated water, namely hypochlorous acid and sodium hypochlorite, in two pilot and industrial cooling towers. The results of the experiments on the pilot tower showed that the performance of hypochlorous acid in the disinfection and removal of bacteria and microorganisms was excellent. The total bacterial count decreased from 10000 to less than 800 (cfu/mL) compared to sodium hypochlorite. The experiments were performed on the industrial cooling tower of an acetic acid unit for six months, in which pH, free chlorine, total bacterial count (TBC), and sulfate-reducing bacteria (SRB) were measured. The very high disinfection power of hypochlorous acid compared to sodium hypochlorite and its relatively lower pH level led to a significant reduction in the use of chemicals in the cooling tower. The experiments and TBC and SRB tests showed outstanding performance in using hypochlorous acid.

Abstract This study investigated the effect of ethylene-vinyl acetate (EVA) as an inhibitor on wax appearance temperature (WAT) of crude oil in the Iranian oil field using the differential scanning calorimetry (DSC) method. The effect of EVA on the morphology of crude oil wax crystals was examined by a system equipped with an ocular microscope. The EVA inhibitor has an outstanding performance in reducing the wax appearance temperature of crude oil and prevents the crystallization process and the connection of the growing wax crystals to form a network structure by adsorbing on them. Adding 800 ppm of the EVA inhibitor caused the most significant decrease in the WAT of crude oil at a rate of 26.13 °C and formed smaller crystals and weaker structures at this concentration. Therefore, 800 ppm of the EVA inhibitor was selected as the optimal value.

Abstract Challenges of rock absolute permeability prediction of tiny samples are remarkable when laboratory apparatus is not applicable and there is no pore network modeling. The prediction using the characterization of micro-computed tomography images has been studied in this paper. Twenty series of 2D micro-computed tomography rock binary images have been collected, and each was considered a 3D binary image. Their geometric measures in 2D and 3D for measuring image properties have been considered using Minkowski functionals and available functions, developing a regression model; absolute permeabilities have also been evaluated. Some 2D and 3D geometric properties are considered. The area, the perimeter, and the 2D Euler number are 2D binary image properties. The volume, surface area, mean breadth, integral of the mean curvature, and the 3D Euler number are 3D binary image properties. The porosity and number of objects have also been considered parameters of a regression model. Twenty-four parameters were evaluated, and some were chosen to perform linear regression. An equation was proposed based on the extensive study to predict rock permeability. This equation has two sets of parameter coefficients: one set predicts high-permeability rocks (above two Darcy), and the other used for low- and medium-permeability rocks (less than two Darcy) can be employed for carbonated rock. The average absolute relative error for conducted cases is 0.06.