The CO2-Assisted Gravity Drainage process (GAGD) has been introduced to become one of the mostinfluential process to enhance oil recovery (EOR) methods in both secondary and tertiary recovery through immiscibleand miscible mode. Its advantages came from the ability of this process to provide gravity-stable oil displacement forenhancing oil recovery. Vertical injectors for CO2 gas have been placed at the crest of the pay zone to form a gas capwhich drain the oil towards the horizontal producing oil wells located above the oil-water-contact. The advantage ofhorizontal well is to provide big drainage area and small pressure drawdown due to the long penetration. Manysimulation and physical models of CO2-AGD process have been implemented at reservoir and ambient conditions tostudy the effect of this method to improve oil recovery and to examine the most parameters that control the CO2-AGDprocess. The CO2-AGD process has been developed and tested to increase oil recovery in reservoirs with bottom waterdrive and strong water coning tendencies. In this study, a scaled prototype 3D simulation model with bottom waterdrive was used for CO2-assisted gravity drainage. The CO2-AGD process performance was studied. Also the effects ofbottom water drive on the performance of immiscible CO2 assisted gravity drainage (enhanced oil recovery and watercut) was investigated. Four different statements scenarios through CO2-AGD process were implemented. Resultsrevealed that: ultimate oil recovery factor increases considerably when implemented CO2-AGD process (from 13.5%to 84.3%). Recovery factor rises with increasing the activity of bottom water drive (from 77.5% to 84.3%). Also,GAGD process provides better reservoir pressure maintenance to keep water cut near 0% limit until gas flood frontreaches the production well if the aquifer is active, and stays near 0% limit at all prediction period for limited waterdrive.
Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
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The current research aims to determine the requirements of Trends of International Mathematics and Science Study (TIMSS 2019) and to find out the extent to which the content of science textbooks for grades (1-4) in the Sultanate of Oman includes the requirements of (TIMSS 2019). Only the Cognitive Process dimension has been considered when conducting the analysis. The study population includes all science books from the first to the fourth grade for the academic year 2021-2022. The study identified and organized the requirements in the study tool, which is a list of requirements of (TIMSS 2019). After confirming its validity and reliability, the analysis was performed, and data were collected and analyzed statistically using frequencies
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This research aims to clarify the advantages of using the regression method as analytical procedure in the tax audit to reducing the examination cost , time, effort, human and material resources, and represents an applied study in the General Commission of taxes. In order to achieve its objectives the research has used in the theoretical side the descriptive approach (analytical), and in the practical side regression method has been applied to the research sample represented by the soft drinks company that is subject to the tax settlement for the year 2014, where the value of sales has been verified by using the regression method without conductinga comprehensive examination. The most important results of the research indicate that the r
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To identify the fungi associated with water hyacinth (Eichhornia crassipes [Mart.] Solms), an aquatic weed, which presents in Tigris river from Baghdad south ward. Five regions from middle and south of Iraq (Al-Noumanya, Saeid Bin-Jubier, Al-Azizia, Al-Reyfay and Al-Hay) were selected for this study. Twelve fungal species were isolated. Alternaria alternata, Acremonium sp and Cladsporium herbarum, were the most frequently species (91.66 % ,50 % and 25 %) respectively. The fungi Alternaria alternata, Acremonium sp. and Phoma eupyrena were more aggressive to water hyacinth as (91.66%,83,33%, and 75%) in pathogenicity test.
In this study, the stable isotop 18O and 2H has been used to investigate the interaction of surface water (SW), and groundwater (GW) in Al-Taji district/ Northern Baghdad for two seasons (March and August 2022). 16 Samples were collected from water resources in the Al-Taji district (Tigris channel, Tigris River, and groundwater), in each season water samples from 8 Tigris channel, 5 drilled wells, and 3 Tigris River were taken for the analysis of the isotopes 18O and 2H. The average analysis results of 18O and 2H in the Tigris channel, Tigris River, and groundwater were found to be -3.435‰ and -18.6094‰, -2.07167‰ and -17.81‰, -4.125‰ and -34.707‰ respectively. The results, generally, show a comparable range of isotope c
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The aim of this study was the discrimination of Salmonella isolated from chicken and their feed and drinking water for the epidemiological control of salmonellosis. Totally, 289 samples, including 217 chicken cloaca swabs, 46 water, and 26 feed samples were collected from five different farms in Karbala governorate, Iraq. Conventional bacteriology tests, API 20E, Vitek 2, and serology were used for bacterial identification. Random amplified polymorphic DNA (RAPD)-polymerase chain reaction (PCR) was applied to analyze the genetic relationships among Salmonella isolates. The isolation rate of Salmonella spp. was 21.1% (61/289). While the water samples constituted the highest rate (30.4%), a rate of
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