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.
In this paper, analyzing the non-dimensional Magnesium-hydrodynamics problem Using nanoparticles in Jeffrey-Hamel flow (JHF) has been studied. The fundamental equations for this issue are reduced to a three-order ordinary differential equation. The current project investigated the effect of the angles between the plates, Reynolds number, nanoparticles volume fraction parameter, and magnetic number on the velocity distribution by using analytical technique known as a perturbation iteration scheme (PIS). The effect of these parameters is similar in the converging and diverging channels except magnetic number that it is different in the divergent channel. Furthermore, the resulting solutions with good convergence and high accuracy for the d
... Show MoreKey words:Jasminumsambac, Volatile oil, Antioxidant.
The air flow pattern in a co-current pilot plant spray dryer fitted with a rotary disk atomizer was determined experimentally and modelled numerically using Computational Fluid Dynamics (CFD) (ANSYS Fluent ) software. The CFD simulation used a three dimensions system, Reynolds-Average Navier-Stokes equations (RANS), closed via the RNG k −ε turbulence model. Measurements were carried out at a rotation of the atomizer (3000 rpm) and when there is no rotation using a drying air at 25 oC and air velocity at the inlet of 5 m/s without swirl. The air flow pattern was predicted experimentally using cotton tufts and digital anemometer. The CFD simulation predicted a downward central flowing air core surrounded by a slow
... Show MoreExcessive water production is a persistent challenge in oil and gas wells, with polymer and gel solutions commonly employed for water control. This study investigates the rheological behaviour of cross-linked polyacrylamide gels and their impact on water shutoff treatment in gas wells. Rheological measurements, coreflooding experiments using Berea sandstone samples, and micromodel flow visualizations were conducted to evaluate gel performance. Results showed that during water injection, the water residual resistance factor ( Frrw ) decreases with increasing flow rates, mainly due to gel shear thinning behaviour and reduced residual gas saturation. Higher polymer concentrations in the gel enhance water permeability reduction. In contrast, un
... Show MorePreserving the Past and Building the Future: A Sustainable Urban Plan for Mosul, Iraq
The utilization of recycled brick tile powder as a replacement for conventional filler in the asphalt concrete mix has been studied in this research. This research evaluates the effectiveness of recycled brick tile powder and determines its optimum replacement level. Using recycled brick tile powder is significant from an environmental standpoint as it is a waste product from construction activities. Sixteen asphalt concrete samples were produced, and eight were soaked for a day. Samples contained 5% Bitumen, 2% to 5% brick tile powder, and conventional stone dust filler. The properties of samples were evaluated using the Marshall test. It was observed that the resistance to stiffness and deformation of asphalt concrete
... Show MoreGlobal warming has a serious impact on the survival of organisms. Very few studies have considered the effect of global warming as a mathematical model. The effect of global warming on the carrying capacity of prey and predators has not been studied before. In this article, an ecological model describing the relationship between prey and predator and the effect of global warming on the carrying capacity of prey was studied. Moreover, the wind speed was considered an influencing factor in the predation process after developing the function that describes it. From a biological perspective, the nonnegativity and uniform bounded of all solutions for the model are proven. The existence of equilibria for the model and its local stability is inves
... Show MoreIn aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we
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