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.
Due to the great losses caused by weeds to the crop, it is necessary to continue testing new herbicides that may be more efficient than the herbicides used that can reduce competition between weeds and crops, Therefore, a field experiment was carried out in the experimental field of the Department of Field Crops, College of Agricultural Engineering Sciences, University of Baghdad (Al-Jadriya) during the winter season of 2021-22 in order to evaluate the efficiency of the herbicide H-199 and compare it with some herbicides used in controlling companion weed to three cultivars of wheat and its effect in the yield and its components. The experiment was applied according to the randomized complete block design with split-plot arrangement
... Show MoreNeighShrink is an efficient image denoising algorithm based on the discrete wavelet
transform (DWT). Its disadvantage is to use a suboptimal universal threshold and identical
neighbouring window size in all wavelet subbands. Dengwen and Wengang proposed an
improved method, which can determine an optimal threshold and neighbouring window size
for every subband by the Stein’s unbiased risk estimate (SURE). Its denoising performance is
considerably superior to NeighShrink and also outperforms SURE-LET, which is an up-todate
denoising algorithm based on the SURE. In this paper different wavelet transform
families are used with this improved method, the results show that Haar wavelet has the
lowest performance among
The Child is the first sedum for the human society performing, and we deal in our
research to explain the nature of the mutual relations in between the form and the medicine
social caring foundation. So the motherhood and the childhood nowadays become the most
dedicated in the researchers works, whom interesting in the social affairs, and that whom
work in the medicine field as scientists.
So the child is the future man and must be in wright body construction that need to great
care and interest to make him wright mind through capability of performing anything support
to him.
In our research we deal with the main factors in which lead to infect the child by the
creative malfunction, like the environmental and m
Samples of gasoline engine oil (SAE 5W20) that had been exposed to various oxidation times were inspected with a UV-Visible (UV-Vis) spectrophotometer to select the best wavelengths and wavelength ranges for distinguishing oxidation times. Engine oil samples were subjected to different thermal oxidation periods of 0, 24, 48, 72, 96, 120, and 144 hours, resulting in a range of total base number (TBN) levels. Each wavelength (190.5 – 849.5 nm) and selected wavelength ranges were evaluated to determine the wavelength or wavelength ranges that could best distinguish among all oxidation times. The best wavelengths and wavelength ranges were analyzed with linear regression to determine the best wavelength or range to predict oxidation t
... Show MoreThis research studies the comparison of deep neural network models and performance evaluation to predict the gold prices of time series, where the gold prices contain high fluctuations and non-linear patterns that are difficult to capture using traditional models, which makes predicting them a significant challenge. Therefore, the focus was on using deep learning models represented by (LSTM), (Bi-LSTM), (GRU) and (Bi-GRU). The results showed the superiority of the (Bi-GRU) model according to comparison criteria (MSE), (RMSE), (MAE), and (R∧2) compared to other models because it was able to understand the time patterns better by processing the data in both directions and provided superior performance, which indicates its effectiveness, eff
... Show MoreA series of overbased magnesium fatty acids such as caprylate, caprate, laurate, myristate, palmitate, stearate and oleate) were synthesized by the reaction of the fatty acids with active – 60 magnesium oxide and carbon dioxide (CO2) gas at 60 oC in the presence of ammonia solution as catalyst, toluene / ethanol solvent mixture (9:1vol/vol) was added.
The prepared detergent additives were characterized by FTIR, 1HNMR and evaluated by blending each additive in various concentrations with medium lubricant oil fraction (60 stock) supplied by Iraqi Midland Refineries Company. The total base number (TBN, mg of KOH/g) was determined, and the results of TBN were treated by using two-way analysis of variance (ANOVA) test. It was found that
The work reported in this study focusing on the abrasive wear behavior for three types of pipes used in oil industries (Carbone steel, Alloy steel and Stainless steel) using a wear apparatus for dry and wet tests, manufactured according to ASTM G65. Silica sand with
hardness (1000-1100) HV was used as abrasive material. The abrasive wear of these pipes has been measured experimentally by measuring the wear rate for each case under different sliding speeds, applied loads, and sand conditions (dry or wet). All tests have been conducted using sand of particle size (200-425) µm, ambient temperature of 34.5 °C and humidity 22% (Lab conditions).
The results show that the material loss due to abrasive wear increased monotonically with
Groundwater modelling is particularly challenging in arid regions where limited water recharge is available. A fault zone will add a significant challenge to the modelling process. The Western Desert in Iraq has been chosen to implement the modelling concept and calculate the model sensitivity to the changes in aquifer hydraulic properties and calibration by researching 102 observations and irrigation wells. MODFLOW-NWT, which is a Newtonian formulation for MODFLOW-2005 approaches, have been used in this study. Further, the simulation run has been implemented using the Upstream-Weighting package (UPW) to treat the dry cells. The results show sensitivity to the change of the Kx value for the major groundwater discharge flow. Only abo
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