مجله پژوهش نفت
پیاپی 134 (فروردین و اردیبهشت 1403)

The emulsion of salt water in crude oil causes reduction of crude oil quality, catalyst poisoning in downstream industries, and equipment corrosion in various parts of crude oil transportation, refining and storage systems. The most common industrial method for separating saline water from crude oil is the application of chemical compounds. Procuring the required chemical compounds will cost a lot. In addition, the performance of chemical demulsifiers is highly dependent on the type and structure of crude oil. The complexity of crude oil’s structure makes it difficult to develop performance models for demulsifiers. In order to reduce the number of important parameters of crude oil in modeling, the ratio of asphaltene to the total of resin and aromatic was used as the discriminating factor of crude oil emulsion process. Considering the complexity of the considered model, a support vector machine was used to predict the performance of commercial demulsifiers. The most important challenge in support vector machines is tuning hyperparameters. To tune the hyperparameters in this study, the risk criterion was used in predicting efficiencies higher than 85% and increasing the correlation coefficient. In order to collect modeling data, four samples of crude oil along with two samples of common commercial demulsifiers were prepared in the Production units of the southwestern fields of the country, and the performance of commercial demulsifiers at different operating conditions was checked using the bottle test method. The performance of the proposed algorithm for tuning hyperparameters was compared with the Bayesian optimization algorithm. The results show that adjusting the support vector machine hyperparameter with the risk criterion helps to design a model with better accuracy for predicting the performance of commercial demulsifiers. Considering the importance of modeling the performance of demulsifiers in petroleum industry, the evaluation of the model was investigated with a new emulsion sample. The results show that support vector machine can provide an efficient model for predicting the performance of commercial demulsifiers.

The high heterogeneity in carbonate rocks makes it impossible to relate reservoir and production parameters to the rock properties and generalize it to the reservoir. Hence, in order to reduce diversity, different rock types have been created based on various factors such as lithological parameters, porosity, and petrophysical properties. Fluid flow parameters are not adequately addressed in these classifications, and some of these rock classifications are overly complex, rendering them challenging to utilize. Considering the features of fluid flow in classification, utilizing minimal data input can have a major impact on carbonate rock studies. In this study, the focus of investigation is on analyzing the reservoir quality of Winland throat radius rock typing, while also exploring fluid flow parameters as production and dynamic parameters. In this regard, using the petrophysical data of 779 carbonate rock samples from the Ilam, Sarvak and Fahliyan formations, the Winland rock typing was determined, and then the appropriateness of the rock typing was investigated using lithological, petrophysical, pore and dynamic parameters. Investigations showed that by correcting the boundaries of the Winland rock typing, regular connections are established with the mentioned parameters. The results showed that although the reservoir properties show improvement with the increase in the group number, the dynamic properties do not follow this trend. Overall, the middle groups are the most desirable part of the rock typing in terms of reservoir quality and production parameters. The shift of static rock typing towards dynamic rock typing and also the use of the ratio of recovery factor to irreducible water saturation are as a key parameters to check production quality which are recommended.

Improving production from multi-layer oil reservoirs in order to maximize recovery factor and reduce water production has become a major challenge in the petroleum industry. Layers with higher productivity index experience the water breakthrough earlier which causes a huge amount of other layers’ oil to remain unswept due to the higher mobility ratio of water. Since reducing the surface choke opening will also reduce oil production along with water, inflow Control Valves (ICVs) are being installed downhole within the completion string across different layers of the reservoir to provide selective depletion. Before equipping the oil well with ICVs, it is crucial to select the most fit-for-target type among a variety of them including infinite, and discrete variable ICVs. However, this selection is highly affected by their number and installation location within the completion string. In this project, after simulating the oil production well with an ICV across each layer of the multi-layer reservoir, the cross-sectional area of ICVs was optimized using Genetic Algorithm with the aim to maximize the field oil efficiency (FOE). As results indicate a pattern representing the reservoir layers’ production dependency on ICVs, a multi-stage ICV removal in the completion string was performed. The optimum type, number, and location of ICVs were selected with the aim to meet the maximum Net Present Value (NPV). Ultimately, the methodology utilized in this project was proposed as a workflow for the optimization of ICV technical parameters to improve production in multi-layer oil reservoirs.

With the increase of offshore drilling for oil extraction, exploitation and transportation of oil and oil products, on one hand, the risk of oil spills and oily waste water in the marine environment has increased significantly, on the other side, easy, controllable and economical modern methods for oil-water separation has become necessary. Oil spills and oily waste water have a disastrous effect on the ecosystem and environment, and the separation of crude oil associate water by traditional methods also requires the use of expensive chemicals. During the past few years, the development of special wetting materials for the separation of water - hydrocarbons has attracted much attention from researchers, and many researchers have created materials with selective wettability that are hydrophobic/oleophilic or hydrophilic/oleophobic, which can be used to separate a selective phase from an oil (hydrocarbons, petroleum, fats)-water mixture. In the current research, the possibility of using nonostructure tungsten oxide as a coating on stainless steel mesh is investigated in order to check the possibility of changing the wettability of the mesh and using it to selectively separate one of the water or hydrocarbon phases from their mixture. For this purpose, both sides of the 5 micron stainless steel mesh were coated with nanostructured tungsten oxide by hydrothermal method. The measurement of the contact angle of water and oil on this mesh showed that the wet coated mesh is hydrophilic in air and becomes oil-repellent when submerged. Due to such wetting behavior, this mesh can be used to separate oil and water mixtures. A piece of stainless steel mesh was placed in an autoclave with an inner Teflon coating containing 250 mL of an aqueous solution of hydrated sodium tungstate, hydrochloric acid, and oxalic acid. The autoclave was placed in an oven at 180°C for 3 hours. After cooling to room temperature, washing with ethanol and Water and drying, it was roasted in an electrical furnace of 350°C for about an hour. The wettability of the hydrophilic and underwater oleophobic filter was also evaluated by measuring the static contact angle. The wetting behavior mechanism of the constructed filter is mainly related to the hierarchical structure of the nano-spherical coating of the surface and its relative roughness, and hence the hydrophilicity of the surface increased. The EDS analysis of the coating formed on the mesh and the FE-SEM and TEM images of the fabricated filter all indicate the formation of WO3 nanostructured coating on both sides of the stainless steel mesh.

Investigation of the effective factors on the two fluid flow of CO2 injection in the reservoir rocks is important for optimizing such a process. In this study, the geometry extracted from a 2D section of the micro CT images of a real sandstone sample is used, and simulation of the two-phase flow (CO2 and oil) with the phase field approach have been implemented with Comsol software. In particular, the effect of miscibility, wettability, and injection rate is investigated, and the results of simulation such as oil recovery  and its dependence on the wettability, surface tension, and injection rate are evaluated. The results showed that surface tension and wettability have significant effects on the two-phase displacement so that, for example, more wettability towards the injected fluid improves the efficiency of the displacement process up to a 25%. The rate of CO2 injection can have different effects at various surface tension values, so the results of this study can be helpful in choosing the appropriate wettability condition and evaluating the optimal rate for real carbon dioxide injection.

In recent years, enhanced oil recovery (EOR) methods have received more attention because of the increase in demand and decrease in oil reserves. One of these methods is water injection. Due to the structural complexities and sedimentology of most of Iran’s reservoirs, the success of EOR methods, particularly water injection, is associated with high uncertainty. Therefore, monitoring and controlling the injection process using four-dimensional seismic surveys is necessary to reduce the operational risk and increase the production rate. In this study, the feasibility of seismic operation is investigated to monitor the water injection process in two reservoir formations of Burgan (sandstone) and Yamama (carbonate) in one of the oil fields in the south of Iran in zero, one, and three-dimensional scales. For this purpose, first, a comprehensive study was performed on the existing rock physics models, and the appropriate rock physics model covering most of the effective parameters was selected. Then, the changes in seismic response caused by the three scenarios of formation water injection, seawater injection, and smart water injection were investigated in each formation. The results obtained in the zero-dimensional scale showed that the acoustic impedance changes by 4.5-7% for different scenarios in both sandstone and carbonate reservoirs. To perform one-dimensional studies, synthetic seismic data were generated using well logs and for different scenarios of rising oil-water contact. The results of one-dimensional modeling indicate that four-dimensional seismic data can record any displacement over 3 meters in oil-water contact in the Burgan reservoir and over 7 meters in Yamama. To conduct studies on a 3D scale, 3D synthetic seismic data were generated using static and dynamic models of Burgan and Yamama reservoirs. Feasibility studies using 3D seismic data also indicate the possibility of success of 4D seismic data for monitoring changes in the fluid contacts of both Burgan and Yamama formations on a reservoir scale. Therefore, 4D seismic operation in the selected field is recommended for monitoring and optimizing the production plan and suggesting suitable locations for drilling new wells.

One of the most intense and expensive problems during drilling operations is the loss of circulation, which should be addressed and mitigated immediately. Lost circulation could result in several consequences, including wellbore instability, poor hole cleaning, stuck pipe, well control issues and formation damage. Cross-linkable polymer gels play an important role in plugging loss zones. Coating the cross-linker on the nanomaterials extends the length of the cross-linker and forms a stronger network between the polymers. The nanocomposite gel consists of a crosslinked gel by nano-crosslinkers. In this study, the effect of parameters such as the type of crosslinker, temperature and salinity on the performance of the gel, as well as re-crosslinking efficiency at high shear rates and the stability of the gel with time, was investigated and evaluated. Using dynamic stability tests, the maximum amount of pressure that gels can withstand to prevent further drilling fluid loss in highly permeable or fractured formations, was examined. Also, empirical modeling was done by using response surface methodology. The obtained model predicts the viscosity of nanocomposite gel with an accuracy of 86% within the range of input parameters. According to the experimental results, the presence of nano crosslinker in the gel causes the self-healing ability of the formed gel at high shear rates. The nanocomposite gel has a better performance than the hybrid gel at high temperatures and also in the presence of destructive ions, which is due to the high efficiency of the nano-crosslinker in in creating the gel network. In addition, the presence of nano-crosslinker in the gel increases the maximum sealing pressure of gels in plugging highly permeable and fractured formations. Due to the complete rupture of nanocomposite gel in hydrochloric acid, the possibility of formation damage is reduced.

As the oil is extracted from reservoir starts, the pressure of the reservoir decreases. Hence, the well needs to use methods of increased harvesting. The method of increasing harvesting through the injection of CO2 gas is a well-known technology, and this method has been economically justified. For this goal, to maximize recovery, sometimes the combination of two methods of water and gas injection, known as the WAG method, is used. Furthermore, in the mixed state, CO2 causes the viscosity of crude oil to decrease. Reduction in viscosity facilitated the flow of oil into production wells. Additionally, the tank pressure rose due to unmixed CO2. The quantity of oil extracted rises as a result of the interaction of these variables. In this research study, the effect of additives was studied and investigated in different conditions, and parameters include type of additive, additive concentration, process pressure, and temperature, and the effects of these parameters on kinetics and the solubility of CO2 were investigated. The inhibitory effect of tetrabutylammonium hydroxide was very effective in preventing the formation of CO2 gas hydrate compared to the pure system. For this purpose, Design Expert software was used to design the experiment. In addition, the presence of TMAH salt extends the induction time of hydrate formation, and the system with the highest concentration of this addition has the most optimal increase in induction time, according to the statistical analysis of the parameters impacting the induction time of hydrate formation.

Gas storage is a vital component of the global energy system and plays a crucial role in ensuring energy security. As demand for natural gas increases, the need for efficient and effective gas storage facilities becomes increasingly important. One solution for this need identified by researchers and engineers is to find an optimal model for site selection, which it combines expert opinions and geographic information systems. Thus, the aim of this study is to identify gas storage sites in the Bushehr province by using a combination of geographic information systems and an expert panel to identify the most optimal location for gas storage. The research methodology in this study is analytical-descriptive, and it has a practical nature. To identify the indicators, theoretical studies have been used, ultimately determining four dimensions: natural (9 variables), physical (5 variables), environmental (5 variables), and infrastructure (9 variables), for which each criterion›s spatial layer was prepared. Of the 25 identified criteria, 9 have a negative effect, and they are normalized using an increasing linear fuzzy method, and the other 16 indices are normalized using a decreasing linear fuzzy method. According to the experts› opinions, salt domes and underground water tables, with a weight of 0.097, are identified as the most important criteria. Given that the inconsistency rate in the model is 0.05 and less than 0.1, the validity of the experts› comparisons is also confirmed. After applying the criteria weights and combining them using five fuzzy operators, the Gamma method identifies the best location, and two places, including the Jashak salt dome and the Sarbesi salt dome, are identified as the most suitable locations for gas storage.

Identifying and analyzing small components within the oil industry plays a vital role in the extraction, processing, and exploration of crude oil. This study aimed to accurately determine the presence of elements and rare metals in asphaltenes. To achieve this objective, the study employs Energy-Dispersive X-ray spectroscopy (EDX) and Laser-Induced Breakdown Spectroscopy (LIBS) techniques to precisely analyze the elemental composition of asphaltene samples. Furthermore, EDX analysis revealed significant quantities of Carbon (C), Oxygen (O), Nitrogen (N), and Sulfur (S) in asphaltenes. Moreover, the LIBS analysis identified 38 atomic and molecular transmission lines from various elements. Molecular structures such as CN and C2, as well as atoms including Iron (Fe), Hydrogen (H), Sodium (Na), Copper (Cu), Calcium (Ca), Aluminum (Al), Cadmium (Cd), Molybdenum (Mo), Vanadium (V), Potassium (K), Lead (Pb), Magnesium (Mg), and Strontium (Sr), were identified through the examination of observed emission lines.  This research highlights the use of two elemental analysis techniques, showing that oil sediments contain valuable and strategic elemental compounds that can be considered for extracting and processing petroleum products.