In the petroleum industry, multiphase flow dynamics within the tubing string have gained significant attention due to associated challenges. Accurately predicting pressure drops and wellbore pressures is crucial for the effective modeling of vertical lift performance (VLP). This study focuses on predicting the multiphase flow behavior in four wells located in the Faihaa oil field in southern Iraq, utilizing PIPESIM software. The process of selecting the most appropriate multiphase correlation was performed by utilizing production test data to construct a comprehensive survey data catalog. Subsequently, the results were compared with the correlations available within the PIPESIM software. The outcomes reveal that the Hagedorn and Brown (HB) correlation provides the most accurate correlation for calculating pressure in FH-1 and FH-3 while the Beggs and Brill original (BBO) correlation proves to be the optimal fit for wells FH-2 and Gomez mechanistic model for FH-4. These correlations show the lowest root mean square (RMS) values of 11.5, 7.56, 8.889, and 6.622 for the four wells, respectively, accompanied by the lowest error ratios of 0.00692%, 0.00033%, 0.00787%, and 0.0011%, respectively. Conversely, Beggs and Brill original (BBO) correlation yields less accurate results in predicting pressure drop for FH-1 compared with other correlations. Similarly, correlations, such as Orkiszewski for FH-2, Duns and Ros for FH-3, and ANSARI for FH-4, also display less accuracy level. Notably, the study also identifies that single-phase flow dominates within the tubing string until a depth of 6000 feet in most wells, beyond which slug flow emerges, introducing significant production challenges. As a result, the study recommends carefully selecting optimal operational conditions encompassing variables such as wellhead pressure, tubing dimensions, and other pertinent parameters. This approach is crucial to prevent the onset of slug flow regime and thus mitigate associated production challenges.
The aim of this research is to benefit from recycl the aircraft waste oils which is discarded in sewage network, to be used in preparation of greases for industrial purposes and to reduce the environmental pollution. In this research synthetic greases were prepared with special specifications by mixing the waste oils after treating with (silica gel as adsorbent agent, and filtration to precipitate impurities then heated to 110 C? to get rid of water) bentonite produced in Iraq which is available and cheap with existence of high density polyethylene at specific conditions of ( heating and mixing) . The best weight proportion were reached, then paraffin wax and additives were added to improve the properties of grease and give the
... Show MoreThis study investigates the improvement of Iraqi atmospheric gas oil characteristics which contains 1.402 wt. % sulfur content and 16.88 wt. % aromatic content supplied from Al-Dura Refinery by using hydrodesulfurization (HDS) process using Ti-Ni-Mo/γ-Al2O3 prepared catalyst in order to achieve low sulfur and aromatic saturation gas oil. Hydrodearomatization (HDA) occurs simultaneously with hydrodesulfurization (HDS) process. The effect of titanium on the conventional catalyst Ni-Mo/γ-Al2O3 was investigated by physical adsorption and catalytic activity test. Ti-Ni-Mo/γ-Al2O3 catalyst was prepared under vacuum impregnation condition to ensure efficient precipitation of metals within the carrier γ-Al2O3. The loading percentage of met
... Show MoreSuperconducting compound Bi2Sr2-xYxCa2Cu3O10+δ were Synthesized by method of solid state reaction, at 1033 K for 160 hours temperature of the sintering at normal atmospheric pressure where substitutions Yttrium oxide with Strontium. When Y2O3 concentration (0.0, 0.1, 0.2, 0.3, 0.4 and 0.5). All specimens of Bi2Sr2Ca2Cu3O10+δ superconducting compounds were examined. The resistivity of electrical was checked by the four point probe technique, It was found th
six specimens of the Hg0.5Pb0.5Ba2Ca2Cu3-y
This study was aimed to determine a phytotoxicity experiment with kerosene as a model of a total petroleum hydrocarbon (TPHs) as Kerosene pollutant at different concentrations (1% and 6%) with aeration rate (0 and 1 L/min) and retention time (7, 14, 21, 28 and 42 days), was carried out in a subsurface flow system (SSF) on the Barley wetland. It was noted that greatest elimination 95.7% recorded at 1% kerosene levels and aeration rate 1L / min after a period of 42 days of exposure; whereas it was 47% in the control test without plants. Furthermore, the percent of elimination efficiencies of hydrocarbons from the soil was ranged between 34.155%-95.7% for all TPHs (Kerosene) concentrations at aeration rate (0 and 1 L/min). The Barley c
... Show MoreIn recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the road in all the sections of the country. Vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the developing system is consist of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny
... Show MoreA seemingly uncorrelated regression (SUR) model is a special case of multivariate models, in which the error terms in these equations are contemporaneously related. The method estimator (GLS) is efficient because it takes into account the covariance structure of errors, but it is also very sensitive to outliers. The robust SUR estimator can dealing outliers. We propose two robust methods for calculating the estimator, which are (S-Estimations, and FastSUR). We find that it significantly improved the quality of SUR model estimates. In addition, the results gave the FastSUR method superiority over the S method in dealing with outliers contained in the data set, as it has lower (MSE and RMSE) and higher (R-Squared and R-Square Adjus
... Show MoreThe study included the extraction of volatile oil from Mentha piperita which was 1.3 % in the leaves and flowers . Volatile oil of the Mentha piperita leaves had special aromatic odour, pale yellow color, slightly pungent taste . The specific gravity and refractive index were (0.9794) and ( 1.464) respectively. The inhibition activity of the Mentha piperita Volatile oil extracts were studied on some pathogenic microorganisms like Staphylococcus aureus, Salmonella typhi, Escherichia coli, Proteus sp, and Klebsiella pneumoniae . The result showed that the volatile oil had an inhibition effect on the growth of all microorganisms, and it gave the higher inhibition effect on the growth of S. aureus in which the inhibition zone reached to 2
... Show MoreA Strength Pareto Evolutionary Algorithm 2 (SPEA 2) approach for solving the multi-objective Environmental / Economic Power Dispatch (EEPD) problem is presented in this paper. In the past fuel cost consumption minimization was the aim (a single objective function) of economic power dispatch problem. Since the clean air act amendments have been applied to reduce SO2 and NOX emissions from power plants, the utilities change their strategies in order to reduce pollution and atmospheric emission as well, adding emission minimization as other objective function made economic power dispatch (EPD) a multi-objective problem having conflicting objectives. SPEA2 is the improved version of SPEA with better fitness assignment, density estimation, an
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