مجله پژوهش نفت
پیاپی 118 (امرداد و شهریور 1400)

There is a high investment risk of executing EOR (Enhanced Oil Recovery) projects due to reservoir-geology uncertainties and high cost of implementation. Hence, pilot scale EOR, in hydrocarbon field, is implemented. Moreover, selection of the pilot area, in the hydrocarbon field, is one of the key factors since the results of the pilot implementation will be extended to the entire field. In this study, reservoir simulation is applied to determine the three-dimensional reservoir quality maps of recovery factor. Subsequently, hydrocarbon field will be segmented into pilot candidate areas. Afterwards, the pilot candidate areas based on its recovery factor array are optimally clustered using hybrid hierarchical k-means clustering method. The silhouette index is utilized to obtain the number of clusters. The dominant cluster is the one with the highest number of pilot candidate areas according to clustering method. Subsequently, the proximity of each pilot candidate area to the center of dominant cluster could be used as one of the pilot area selection criteria. Moreover, Operational and economic criteria are also involved in choosing a pilot area. Finally, TOPSIS (Technique for Order Preferences by Similarity to Ideal) as multi-criteria decision-making methods are applied to calculate the pilot opportunity index in each candidate area. The pilot candidate areas could be prioritized based on the value of this index, and the first priority area may be selected for pilot implementation. Ultimately, the whole methodology is carried out for a real hydrocarbon field.

One of the common problems in porous media, such as oil reservoirs and surface facilities, is the mineral scale formation that directly affects the production rate. Controlling and mitigating scale formation have therefore been investigated intensively in both research and industrial fields for many years. Recently, due to the limitations applied by the international community for environmental protection and according to the point that laboratory investigations of any scale inhibitors under oilfield conditions is essential prior to its use in oil industries, environmentally friendly green inhibitors have attracted a great attention. In the present study, the performance of two green scale inhibitors and one commercial phosphate-based inhibitor against calcium carbonate and calcium sulfate formation were investigated using standard static tests (Jar tests) and XRD analysis to determine the performance of appropriate inhibitor. The results demonstrate that to achieve reasonable inhibition efficiency, inhibitor A is more efficient than B, although higher amount of green inhibitors is consumed in comparison with the commercial phosphonate-based ones.

Accurate measurement of gas flow is a basic need in domestic use. Diaphragm gas meters are currently used to measure domestic gas consumption, which is a very old and inaccurate technology. In recent years, the use of thermal MEMS flowmeters has been growing due to their small size, low power consumption, and good accuracy, but their limited measurement range has prevented them from being used to measure domestic gas consumption. In order to eliminate this limitation, in the present study, a bypass system similar to capillary tube flowmeters was introduced, which it has also been used in several commercial microthermal flowmeters. This system must be designed in such a way that an acceptable flow enters the bypass (microchannel). Therefore, in this study, for the first time, the effect of different geometrical parameters on the flow rate to the bypass in the flow range of domestic consumption was studied by simultaneously solving turbulent and laminar flow equations through fluid dynamics simulation. According to the results, with the higher the height of the bypass channel is, the smaller the diameter of the laminar flow element is and the less bypass-laminar flow element distance is, more gas enters the bypass. Finally, the channel height of 160 micrometers, the distance of 2 mm between bypass entrance and laminar flow element, and the square arrangement of the laminar flow element with a diameter of 1.8 mm can be appropriate. In these specifications, 100 to 220 percent more flow enters the bypass than most other configurations of the work.

Formation damage in hydrocarbon reservoirs around the wellbore is inevitable, and it can happen from the earliest stages of drilling to the latest hydrocarbon recovery stages by tertiary enhanced recovery methods. Numerical simulations of production behavior around wellbore perforation in single-phase and two-phase states have been conducted by the CFD method to investigate the effect of perforation geometry on formation damage. Moreover, formation damage due to drilling mud penetration into the perforations by dispersion mechanism has also been analyzed. The results of the simulation were validated in good accordance with the published data. Based on simulation results, although perforations enhance the drilling mud penetration damage, especially for perforation lengths up to 20 cm, they can effectively reduce perforation skin if they become adequately cleaned. Perforation density, length, and diameter have the most pronounced effect on reducing the skin factor. There is almost a linear relationship between skin factor and clean perforation diameter. Since larger diameters come with shorter lengths, perforation optimization is required according to casing material, hole size, rock mineral, and perforation technology available.

In recent years, many studies have been done on the use of surfactant to enhancement oil recovery from reservoirs; in which the performance of biosurfactant with chemical surfactant was compared. But so far no study has been conducted focusing on comparing the performance of biosurfactant with polymers as well as the effect of temperature on oil recovery. Therefore, the present study was dedicated to study the effect of temperature on the rhamnolipid biosurfactant performance using glass micromodel and to compare its performance with anionic polyacrylamide polymer. Thus, the results of the biosurfactant flooding tests were compared with saltwater and polyacrylamide flooding tests. Experiments were conducted at two temperature, 25 and 75 Celsius degrees, in two homogenous and non-homogenous micromodels. Results indicated that in the homogenous model, for two mentioned temperatures, enhanced oil recovery due to flooding with rhamnolipid biosurfactant was 48 and 62, respectively, in which there was 9 and 12.7 percent improvement in compare to saltwater. Meanwhile, the results of polymer flooding showed 61 and 70 percent enhancement, respectively. The same results were obtained in non-homogenous model. The enhanced oil recovery due to rhamnolipid biosurfactant injection in two temperatures were 41 and 51 percent, respectively, which it is higher compared to saltwater and lower compared to polymer. In general, at higher temperature, oil recovery increased in both homogenous and non-homogenous models under three floods.

Separators play a very important and key role in oil and gas production fields. For this reason, their optimal design is very important. The design method with semi-empirical equations is a common method for determining the dimensions of separators. However, due to the simplifying assumptions used in them, it can only be used to obtain an approximate estimate of the dimensions of the separators. In this study, the accuracy of semi-empirical relationships was investigated using a gas-liquid separator pilot unit and the experimental results and the results obtained from CFD simulation as necessary data for the design and construction of a neural network optimized by Genetic algorithm. A model was proposed to determine the correction factor of semi-experimental relationships under different operating conditions. The pilot unit of the separator test consists of a laboratory-scale two-phase horizontal separator, pumps, compressors and a static mixer to form a two-phase flow and a liquid filter to trap liquid droplets from the exhaust gas flow from the separator. The separation efficiency is determined by weighing the dispersed liquid droplets. The maximum diameter of the liquid droplets in the exhaust gas flow is determined by imaging. The CFD model developed with laboratory data had a relative error of less than 8 percent, and the root mean square error of the neural network optimized by the genetic algorithm for the actual and predicted values of the correction factor was 1%. One of the most important achievements of this research is to provide the necessary basis for the optimal design of surface separators.

In the oil industry, artificial intelligence is used to identify relationships, optimize, estimate and classify porosity. One of the most important steps in evaluating the petrophysical parameters of the reservoir is to identify the porosity properties. The main purpose of this study is to compare the accuracy and generalizability of three multilayer feed neural networks (MLFNs), radius base function networks (RBFNs) and probabilistic neural networks (PNNs) to estimate porosity using seismic properties. In this regard, geological data of 7 wells were evaluated from an offshore oil field in Hindijan in the northwest of the Persian Gulf basin. Acoustic impedance was estimated using model-based inversion method, and then the mentioned neural networks were designed using optimal seismic properties and evaluated by stepwise regression method. Finally, it became clear that the MLFN model did not work well for estimating porosity. PNN has the best performance accuracy in porosity interpolation, but RBFNꞌs generalizability is better.

Multiple pipeline network is known as the safest and the most cost-effective method to transport local needs for a variety of fossil fuels. In order to achieve this goal, petroleum products in the form of batches with a certain volume must be transported consecutively within the pipelines. The issue of planning the transportation of petroleum product batches within a multiple pipeline network is significant to fulfill the periodic demands of the refined petroleum products distribution system. The multiple pipeline network as a constrained system includes various types of restrictions in the field of production, transportation, and storage of petroleum products. In this paper, we presented automated planning in the form of a constrained optimization problem applying model predictive control strategy based on the nonlinear state-space model. And then we implemented the receding horizon control strategy to delineate daily schedule during a month in the presence of breakdown disturbance such an online planning process that optimization was performed by a weekly prediction horizon at the end of each day and the optimal solution for the first day was applied to the multiple pipeline network as the next day plan. The results of the proposed method show that the optimized plan satisfies the transportation goals regarding the existing constraints and breakdown disturbances.

The magnetotelluric method uses natural and time-varying electric and magnetic fields on the earth’s surface to detect the earth’s electrical structures, such as hydrocarbons exploration. In the inversion process, the matrix inverse calculation method has a considerable effect on the inversion speed as well as the quality of obtained models. Lanczos Bidiagonalization (LB) method has been reported to be a fast and efficient approach for solving the inversion problems. In LB algorithm, the full set of equations is replaced by a dimensionally reduced system of equations. In addition, we employed Active Constraint Balancing (ACB) approach for determining the optimum regularization parameter. The results of the synthetic data inversion show that both methods require equal computer memory, but LB method is faster and more reliable than Conjugate Gradient (CG) method. The proposed approach was also applied to inverse real MT data collected from the Kashan area, which is the most interesting area for oil and gas exploration in the Central Iran Basin. The obtained model shows the Qom Formation, which is the most important reservoir rock and hydrocarbon source rock in central Iran, and other geological structures of the region, such as the Navab anticline and faults.

In this study, the capability of local bacteria, isolated from oily sludge in Kermanshah refinery oil tanks, and cultivation environment conditions effects on fuel oil upgrading were investigated. In order to isolate and purify microorganisms, liquid and solid culture media were used, and the amount of microbial population increased during different stages. The isolated bacteria include the Pseudomonas aeruginosa and Rhodococus erythropolis. In these experiments, the selected variables including pH, temperature, time parameters, fuel oil concentration and microorganism concentration were used at different levels based on the conditions. Density and total sulfur reduction were used as responses parameters. Also, the effect of chemical surfactant on the responses was studied. Based on the achieved results, the best conditions for sulfur removal and converting heavy cut to ligher one, were obtained at pH = 6.5, temperature of 40 °C, fuel oil concentration 0f 4 % (V/V) microorganisms’ concentration of 2 % (V/V) and 3 days, together with the addition of chemical surfactant. The SARA analysis results shown that total sulfur and density in untreated fuel oil were 25400 ppm and 0.9428 kg/L, respectively, and in optimal treated one, they were 9400 ppm and 0.9096 kg/L, which it demonstrated that the conversion rate of fuel oil to gas oil was equal to 29.3% and reduction of total sulfur by more than 60%.