مجله پژوهش نفت
پیاپی 130 (امرداد و شهریور 1402)

Nowadays, numerous types of research have been conducted to identify automatically fault and fracture systems based on seismic data. Seismic coherence is one of the geometric indicators that is widely used in revealing seismic discontinuities such as faults, fractures, and river channels. One of the suitable tools for identifying faults and fractures is the use of seismic data, which is done using the ant-tracking algorithm. In this paper, by examining the ant tracking algorithm, faults and micro-faults in the Salman oilfield were identified. In the study area, five reservoir formations are present in the Salman field. In addition, five exploratory wells have been drilled in this area. An ant-tracking algorithm is an efficient tool for accurately identifying reservoir fractures. In this research, with the help of ant tracking algorithm, faults and deep fractures of the Salman oil field were investigated. According to the results, a salt anticline was observed in the Salman region and at the top of the anticline, there are significant normal faults that have caused the graben structure in the region. Also, normal faults are along the northwest-southeast. The sub-faults are also normal along the main faults. The ant conjugation algorithm of conjugate fractures in the area identified them.

The method of low salinity water with nanoparticles can be considered as a hybrid method of enhanced oil recovery. The goal of this paper is to investigate the effect of salinity on nanoparticles with a green surfactant in enhanced oil recovery. It was tried to determine the appropriate mass fraction of the nanohybrid and the optimal concentration of salinity for nanofluids in the micromodel flooding test. In this research, gamma-alumina and silica metal oxide nanoparticles were used in basic fluids with different salinities. Nanoparticles improve oil recovery factor, however the most important challenge of using nanoparticles is when they are placed next to divalent ions in brine, which become very unstable. Therefore, an attempt was made to study the stability of gamma-alumina, silica and their hybrid nanoparticles (in different mass fractions) with different salinity. To increase the duration of stability of nanoparticles in water with different salinity, environmentally compatible and green surfactant called Gum Arabic was used. The experiments were designed with software and Taguchi method. After the preparation of nanofluids, their stability was investigated and the flooding test was performed on the nanofluids that had good stability. The lowest stability period was related to nanofluids whose base fluid was reported to have a salinity of 40,710 ppm. The highest recovery factor of gamma-alumina nanohybrids with a mass fraction of 10:90 in water with a salinity of 20400 ppm, with 1000 ppm of Arabic gum equal to 60.34% and the lowest recovery factor among nanofluids for silica nanoparticles with deionized water without gum Arabic was reported to be 34.5%.

In this study investigate the foaming behavior and surface tension of aqueous N-Methyldiethanolamine (MDEA) in the presence of amine functionalized UiO-66 (UiO-66-NH2) was studied. Foam volume and foam stability of solution containing of MDEA and MDEA + UiO-66-NH2 nanofluid was measured and effect of added UiO-66-NH2 to the MDEA solution on foam volume and foam stability was studied. Experiments were carried out at 313.15, 323.15 and 333.15 K and atmospheric pressures. Results show that addition of 0.1 % wt. of UiO-66-NH2 to the solution of 40% wt. of MDEA, decreases up to 25% in foam volume and up to 47 % in foam stability. Besides, effect of addition UiO-66-NH2 to the MDEA solution on surface tension was studied by LAUDA interfacial tensiometer model TD3, which uses the Du Noüy ring method and results of this study showed that addition of 0.1 % wt. of UiO-66-NH2 to the solution of 40% wt. of MDEA increases 0.8 % in surface tension of solution. A suitable model was used to investigate foam property and highlights that solutions behave linearly in decreasing foam formation and surface tension with an increasing of temperature. Foaming model was successfully developed and was fitted to experimental data and and maximum error were 0.9957 and 12%, respectively

Carbon dioxide is one of the most important greenhouse gases that plays a major role in global warming. Gas hydrates are one of the newest technologies available to remove this gas before entering the atmosphere. In this research, the effect of the stirrer speed on the most important kinetic parameters of carbon dioxide hydrate formation, i.e. amount of gas uptake, hydrate growth rate, storage capacity, and water to hydrate conversion percentage in a constant-volume constant-temperature reactor was investigated. The experiments were carried out in the presence of double distilled water at a temperature of 278.15 K and two pressures of 2.9 MPa. Vertical and horizontal stagnant conditions and rocking cell stirrer with speeds of 2, 4 and 10 rpm were used to investigate the effect of stirrer speed on the kinetics of carbon dioxide hydrate formation. The results of the experiments showed that the use of a stirrer promotes the kinetics of carbon dioxide hydrate formation. The use of a stirrer at a speed of 10 rpm increased the amount of gas uptake compared to the vertical and horizontal conditions, respectively, by 84.4 and 78.5 percent. The storage capacity of carbon dioxide hydrate formation increased by 72.6% and 67.7%, respectively, when using a stirrer at a speed of 10 rpm compared to the vertical and horizontal conditions.

More and more rigid requirements for sulfur contents of motor fuels stimulate search for new ways of purification of hydrocarbon raw materials from sulfur compounds and modernization of existing desulfurization technologies. The main classes of gas and oil-sulfur compounds are thiols, dialkyl and cycloalkyl sulfides, alkyl aryl sulfides, as well as heteroaromatic compounds, specifically thiophene derivatives. The sulfur content of Ilam refinery′s natural gas condensate is very high (4150 ppm) and should be removed to reduce the sulfur content. Sulfur components are traditionally considered as undesirable contaminants of liquid hydrocarbon fuels. Sulfur oxidation appears a very promising route for obtaining ultralow-sulfur fuels requested worldwide by the new regulation mandates. This paper describes the oxidation of several kinds of S-containing molecules in Natural-Gas Condensate with hydrogen peroxide in a two liquid–liquid (L–L) phase system with Fe3O4@SiO2@polyionene/K2S2O8 Core-Shell-shell Magnetite Nanoparticle Catalyst under atmospheric pressure. The influence of the reaction temperature, the reaction time, the solvent, the volume ratio of the oxidant (H2O2) and the natural gas condensate were examined.

In recent years, low salinity polymer injection as an enhanced oil recovery method has drawn more attention by researchers. Combination of other methods with low salinity water injection has also been investigated in the literature. Among them is the combined low salinity water and surfactant or polymer injection which shows its efficiency in enhancing oil recovery. In this study, the combined low salinity water and polymer injection to five sandpack models and its efficiency in oil production is investigated through different flooding experiments. To this end, three and two polymer injection experiments were conducted in tertiary and secondary modes (after and before low salinity water injection), respectively. The results indicates that polymer injection in tertiary mode has better performance than the secondary mode injection experiments as in the former case the oil recovery at breakthrough is about 11% higher than the later one. In tertiary polymer injection experiments, as the concentration of polymer solution increases, the mobility of the displacing fluid decreases leading to an increase in the microscopic efficiency. During the secondary polymer injection, polymer is in contact with the high salinity formation water which increases the adsorption of polymer onto the rock surface and decreases the permeability of the porous medium. As a result, oil recovery decrease. The pH analysis of the produced water shows that during the low salinity water injection experiments, the pH increment is the active mechanism and the wettability alteration toward water-wet increases the oil recovery. Displacement of the polymer and low salinity water are also investigated by measuring the refractive index in the produced water indicating the trend of the salinity change.

In this research MgFe2O4 and MgAl2O4 spinels were synthesized by simple and fast mechanochemical method. Using high-speed ball-milling causes diminishing the ball milling time. Physiochemical analysis including XRD, TEM, FESEM, EDX-Dot mapping, BET-BJH and Magnetic Susceptibility were used to define the physicochemical properties of synthesized samples. Also, pulse chromatographic titration methodology was used to evaluate acidity of synthesized samples. The XRD results confirmed the successful synthesis of both spinels and indicated that two samples have been synthesized with large crystals. Also, the results of other analysis showed good agreement with each other. To investigate catalyst activity of synthesized spinels, the catalysts were used in the production of benzyl toluene from toluene and benzyl chloride by using microwaves. In reaction condition of 3 minutes and 300 watt microwave no conversion was observed for MgAl2O4 while in the same reaction conditions, conversion of MgFe2O4 was achieved to be 100% and even after 3 times reused of this sample no change was observed in the conversion. According to the results of catalyst performance and high magnetic susceptibility of MgFe2O4 which is an effective factor to separate the catalyst from the reaction mixture, it seems that there can be have high hopes for the economic production of this catalyst.

Accurately predicting subsurface flow properties holds immense significance across various domains, ranging from water resource management to the petroleum industry. In this study, recognizing the computational intensity and time constraints associated with digital rock analysis for petrophysical property calculations, we introduce a workflow that leverages deep learning to swiftly and precisely estimate these properties from micro-CT images, obviating the need for resource-intensive computational methods. Specifically, a Convolutional Neural Network (CNN) was employed to train and predict multiple physical properties of porous media using micro-CT scan images as input data. The micro-CT scan images, derived from a carbonate rock sample, were divided into 9,261 images, each with dimensions of 100x100x100, for network training. Key parameters such as porosity, throat size, pore size, connection number, and pore shape factor for each image were computed using network extraction algorithms. The designed network›s performance was evaluated, considering factors like the number of layers and learning rate. Subsequently, when tested on a separate dataset, the network exhibited impressive coefficients of determination for the mentioned parameters, namely 99% for porosity, 90.2% for Avg.throat size, 94.5% for Avg.pore size, 93.6% for Avg.connection number, and 75.3% for Avg.pore shape factor. Furthermore, the average relative error percentage for each property remained below 4%. These results signify a strong agreement between the predicted values and the actual properties, affirming the efficacy of this approach in swiftly and accurately estimating petrophysical properties from micro-CT images.

Estimating and predicting pore pressure is essential to avoid drilling hazards in areas with high pore pressure. By predicting the pore pressure, this information can be used in  the wells planning, the optimum weight of drilling mud, finding the new exploration targets and etc. The main purpose of this study is to estimate the pore pressure using well logs and seismic data and  to compare their performance. In the well logging method, the pore pressure was estimated employing the relationships presented by Eaton in 1975 in three different ways that uses the resistivity, sonic and velocity logs. Then, in 1995, utilizing  Bowers equations, the overburden pressure was calculated from density log, and then the effective stress was estimated using the velocity relationship. Finally, the pore pressure was estimated using the Terzaghi relationship. In the next step, using three-dimensional seismic data and seismic inversion products the pore pressure was estimated in a three-dimensional cube employing Eton and Bowers methods. The estimated three-dimensional cubes were then assessed with the pressure data in the existing wells. The results of this study show that the Eaton velocity method with an error of 9.7% represent the good consistency with the measured data at the well location. It also provides the most appropriate spatial distribution of pressure at the reservoir and shallower depths. Therefore, Eaton velocity method is proposed on the similar regions for the pore pressure estimations.

Nowadays, the heterogeneous catalysts play an undeniable role in chemical processes. Catalysts are generally synthesized in powder form which need to be shaped for industrial uses, which requires a separate cost. In this research, the single-step synthesis of ϒ-Al2O3 as catalyst support with spherical shape was performed by dripping the precursor solution in an oil column and the effect of synthesis conditions such as the temperature and length of oil column (paraffin), the concentration of granule hardening solution (ammonia) and heating rate of calcination temperature was evaluated. The results showed that increasing the temperature of the paraffin column decreases the surface tension and improves the movement of the injected gels, and they easily enter the ammonia layer by crossing the paraffin layer boundary. Decreasing the concentration of ammonia solution in the ion exchange step within the structure of the granules is very suitable and prevents the disintegration of the granules. The results showed that the heating rate of the calcination temperature should be set at the lowest value so that cracks and fractures do not occur on the granule surface due to the slow release of water and other solvents in the gel. Gamma aluminum oxide (alumina) granules synthesized in the conditions of paraffin column temperature of 60 °C and length of 30 cm, concentration of ammonia solution of 10% and calcination temperature of 700 °C with the heating rate of 1 °C/min had dimensions around 3 mm. Moreover, the sphericity factor of the produced granules was less than 0.05, which indicates the appropriate quality of this method for the synthsis of granular support catalyst. In addition, the characterization of the granules showed that their surface area is 78.9 m2.g-1 and they have suitable pores size and volume for use as a catalyst support.