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Rock facies classification and its effect on the estimation of original oil in place based on petrophysical properties data
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The most significant function in oil exploration is determining the reservoir facies, which are based mostly on the primary features of rocks. Porosity, water saturation, and shale volume as well as sonic log and Bulk density are the types of input data utilized in Interactive Petrophysics software to compute rock facies. These data are used to create 15 clusters and four groups of rock facies. Furthermore, the accurate matching between core and well-log data is established by the neural network technique. In the current study, to evaluate the applicability of the cluster analysis approach, the result of rock facies from 29 wells derived from cluster analysis were utilized to redistribute the petrophysical properties for six units of Mishrif Formation; MA, MB11, MB12, MB21, MC1, and MC2. The precise facies modelling is constructed by using Petrel software while applying different appropriate scale-up methods. Consequently, the petrophysical properties such as porosity, water saturation and permeability are distributed within each unit depending on facies modelling. The Net to a gross parameter which has a significant impact on determining original oil in place (OIIP) also calculated and distributed using facies modelling. The facies modelling is performed to obtain an accurate estimation of OIIP. Finally, the results of the facies investigation have a significant effect on petrophysical properties and therefore affect the estimation of OIIP by 2\% for the whole Mishrif Formation.

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
SDN-RA: An Optimized Reschedule Algorithm of SDN Load Balancer for Data Center Networks Based on QoS
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Abstract<p>With the development of cloud computing during the latest years, data center networks have become a great topic in both industrial and academic societies. Nevertheless, traditional methods based on manual and hardware devices are burdensome, expensive, and cannot completely utilize the ability of physical network infrastructure. Thus, Software-Defined Networking (SDN) has been hyped as one of the best encouraging solutions for future Internet performance. SDN notable by two features; the separation of control plane from the data plane, and providing the network development by programmable capabilities instead of hardware solutions. Current paper introduces an SDN-based optimized Resch</p> ... Show More
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Publication Date
Tue Jan 06 2004
Journal Name
Iraqi Journal Of Science
Cluster and factor analyses R and Q mode technique of geochemical and petrological data of the Shalair Metamorphic Rock Group, Shalair Valley area, Northeastern Iraq
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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Visible-Light-driven Photocatalytic Properties of Copper(I) Oxide (Cu2O) and Its Graphene-based Nanocomposites
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In this study, an improved process was proposed for the synthesis of structure-controlled Cu2O nanoparticles, using a simplified wet chemical method at room temperature. A chemical solution route was established to synthesize Cu2O crystals with various sizes and morphologies. The structure, morphology, and optical properties of Cu2O nanoparticles were analyzed by X-ray diffraction, SEM (scanning electron microscope), and UV-Vis spectroscopy. By adjusting the aqueous mixture solutions of NaOH and NH2OH•HCl, the synthesis of Cu2O crystals with different morphology and size could be realized. Strangely, it was found that the change in the ratio of de-ionized water and NaOH aqueous solution led to the synthesis of Cu2O crystals of differen

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Publication Date
Tue Jan 01 2019
Journal Name
البحوث التربوية والنفسية
An educational design based on the models of the constructivist theory of chemistry and its impact on the life skills of second-year middle school female students
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Publication Date
Sun Feb 26 2012
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Study the Effect of Annealing Temperature on the Structural, Optical and Electrical Properties of ZnS Thin Films
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The structural, optical and electrical properties of ZnS films prepared by vacuum evaporation technique on glass substrate at room temperature and treated at different annealing temperatures (323, 373, 423)K of thickness (0.5)µm have been studied. The structure of these films is determined by X-ray diffraction (XRD). The X-ray diffraction studies show that the structure is polycrystalline with cubic structure, and there are strong peaks at the direction (111). The optical properties investigated which include the absorbance and transmittance spectra, energy band gab, absorption coefficient, and other optical constants. The results showed that films have direct optical transition. The optical band gab was found to be in the range t

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Publication Date
Sat Jun 15 2019
Journal Name
Journal Of The College Of Basic Education
The Effect Of Phoenix Dactylifera L. Pinnae Reinforcement On The Mechanical And Thermal Properties Of Polymer Composite
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Phoenix dactylifera l. pinnae (the green leaves of dates palm) were used as natural reinforcing (strengthening) fibers to improve the mechanical properties of polyester as a matrix material, the fibers of the green leaves of dates palm were used in two lengths, 10 and 20mm with five rates of 0, 2.5, 5, 10, and 20% , where the reinforcing with the leaves fibers increases the hardness strength from 76.5 to be about 86.55 , the Impact value raised from about 0.313 to 0.461 , in addition to that the flexural strength from 2.66 to be about 55 , and the thermal conductivity increases from 2.54 𝑤∕𝑚.℃ to 5.41 𝑤∕𝑚.℃. The results of the present search explains that the composite samples reinforced at rate 20% and 10mm fiber length

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Publication Date
Thu Jan 15 2015
Journal Name
مجلة كلية التربية-المؤتمر العلمي التخصصي لكلية التربية
Investigation the Effect of Irradiation by Gamma-Ray on the Structural and Optical Properties of (CIGS) Films
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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Effect of Grain and Calcinations Kaolin Additives on Some Mechanical and Physical properties on Low Density Polyethylene Composites
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In this work, a composite material was prepared from Low-density polyethylene (LDPE) with different weight percent of grain and calcinations kaolin at temperature of (850oC) using single screw extruder and a mixing machine operated at a temperature between (190-200oC). Some of mechanical and physical properties such as tensile strength, tensile strength at break, Young modulus, and elongation at break, shore hardness and water absorption were determined at different weight fraction of filler (0, 2, 7, 10 and 15%). It was found that the addition of filler increases the modulus of elasticity, elongation at break, shore hardness and impact strength; on other hand, it decreases the tensile strength and tensile strength

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Publication Date
Thu Feb 29 2024
Journal Name
Iraqi Journal Of Science
Monitoring the Expansion of Unplanned Urbanization and its Impact on Climate Change based on Google Earth Engine Service, a Case Study of Baghdad / Iraq
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     The earth's surface comprises different kinds of land cover, water resources, and soil, which create environmental factors for varied animals, plants, and humans. Knowing the significant effects of land cover is crucial for long-term development, climate change modeling, and preserving ecosystems. In this research, the Google Earth Engine platform and freely available Landsat imagery were used to investigate the impact of the expansion and degradation in urbanized areas, watersheds, and vegetative cover on the land surface temperature in Baghdad from 2004 to 2021. Land cover indices such as the Normalized Difference Vegetation Index, Normalized Difference Water Index, and Normalized Difference Built-up Index (NDVI, NDWI, an

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Publication Date
Tue Jan 01 2019
Journal Name
Advances On Computational Intelligence In Energy
A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption
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Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

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