A common field development task is the object of the present research by specifying the best location of new horizontal re-entry wells within AB unit of South Rumaila Oil Field. One of the key parameters in the success of a new well is the well location in the reservoir, especially when there are several wells are planned to be drilled from the existing wells. This paper demonstrates an application of neural network with reservoir simulation technique as decision tool. A fully trained predictive artificial feed forward neural network (FFNNW) with efficient selection of horizontal re-entry wells location in AB unit has been carried out with maintaining a reasonable accuracy. Sets of available input data were collected from the exploited grids and used in the training and testing of the used network. A comparison between the calculated and observed cumulative oil production has been carried out through the testing steps of the constructed ANN, an absolute average percentage error of the used network was reached to 4.044%, and this is consider to be an acceptable limit within engineering applications, in addition to that, a good behavior was reached with (FFNNW) and suitable re-entry wells location were identified according to the reservoir configuration (pressure and saturation distribution) output from SRF simulation model at the end of 2005.
To verify the influence of magnetic flux on the characteristics of SAE 10W-30 gasoline engine oil when the engine oil is exposed to different magnetic fluxes 0, 6, 9, and 13 Volt. The following oil characteristics were measured: viscosity at 40 and 100 °C, and total acid number (TAN) mg KOH/g. The research was carried out in a completely randomized design with three replications for each treatment under the 5% probability level to compare the means of the treatments. The results of the experiment showed that there were significant differences in the studied properties when the engine oil was exposed to the above magnetic fluxes and, inversely, especially the magnetic flux of 13 Volt, which led to a decrease in the viscosity of the oils at
... Show MoreAsphaltenes are a solubility class described as a component of crude oil with undesired characteristics. In this study, Sharqy Baghdad heavy oil upgrading was achieved utilizing the solvent deasphalting approach as asphaltenes are insoluble in paraffinic solvents; they may be removed from heavy crude oil by adding N-Hexane as a solvent to create deasphalted oil (DAO)of higher quality. This method is known as Solvent De-asphalting (SDA). Different effects have been assessed for the SDA process, such as solvent to oil ratio (4-16/1 ml/g), the extraction temperature (23 ºC) room temperature and (68 ºC) reflux temperature at (0.5 h mixing time with 400 rpm mixing speed). The best solvent deasphalting results were obtained at room temp
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De-waxing of lubricating oil distillate (400-500 ºC) by using urea was investigated in the present study. Lubricating oil distillate produced by vacuum distillation and refined by furfural extraction was taken from Al-Daura refinery. This oil distillate has a pour point of 34 ºC. Two solvents were used to dilute the oil distillate, these are methyl isobutyl ketone and methylene chloride. The operating conditions of the urea adduct formation with n-paraffins in the presence of methyl isobutyl ketone were studied in details, these are solvent to oil volume ratio within the range of 0 to 2, mixer speed 0 to 2000 rpm, urea to wax weight ratio 0 to 6.3, time of adduction 0 to 71 min and temperature 30-70 ºC). Pour point of de-waxed oil and yi
... Show MoreSamples 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
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This research aims to identify the impact of Daniel's model on the development of critical thinking. In order to achieve this objective, the following hypotheses are formulated: 1. There is no statistically significant difference at the significance level (0.05) between the average differences in the posttest scores of the experimental group taught according to Daniel's model and the control group taught according to the traditional method in the measure of critical thinking. 2. There is no statistically significant difference at the significance level (0.05) between the average differences in the preand post-tests scores of the experimental group taught according to Daniel's model in the measure of critical thinking. The current research i
... Show MoreBroadcasting across satellites has become an important media phenomenon and largely available for watchers. As the receiver can see the events at the very moment and at any spot in the world. This study aims to discover the degree of the extent of exposure of Iraqi people to the news broadcasting satellites in Arabic language, (Al Jazeera, Al Arabiya, Al Ekhbariya Satellite Channels) as one of the media that serves the public; and to discover the range of these Satellite Channels in covering the local Iraqi situation in different sides and aspects; and to know the significance of the Iraqi people in watching those news programmers; and state the motives behind the Iraqi public's dependence on these channels.
The
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Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file. In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,
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