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Prediction of Hydraulic Flow Units for Jeribe Reservoir in Jambour Oil Field Applying Flow Zone Indicator Method
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The Jeribe reservoir in the Jambour Oil Field is a complex and heterogeneous carbonate reservoir characterized by a wide range of permeability variations. Due to limited availability of core plugs in most wells, it becomes crucial to establish correlations between cored wells and apply them to uncored wells for predicting permeability. In recent years, the Flow Zone Indicator (FZI) approach has gained significant applicability for predicting hydraulic flow units (HFUs) and identifying rock types within the reservoir units.    This paper aims to develop a permeability model based on the principles of the Flow Zone Indicator. Analysis of core permeability versus core porosity plot and Reservoir Quality Index (RQI) - Normalized porosity log-log plot reveals the presence of three distinct Hydraulic Flow Units and corresponding rock types within the Jeribe reservoir. These rock types can be identified if known. The reservoir can be divided into three groups of rock types, namely good, moderate, and bad quality. The bad rock type represents a restricted section within the reservoir, while the upper and lower parts predominantly consist of moderate-quality rock types. Conversely, the central section of the reservoir exhibits a good-quality rock type.    By utilizing the Flow Zone Indicator principles, this study provides valuable insights into the hydraulic flow behavior and rock types present in the Jeribe reservoir. The proposed permeability model derived from this method can aid in predicting permeability values for uncored wells, contributing to a better understanding of the reservoir's heterogeneity and facilitating reservoir characterization and management decisions.

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Publication Date
Mon Jan 01 2018
Journal Name
Matec Web Of Conferences
Evaluation water quality of Diyala River in Iraq using Bhargava method
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Diyala River is a tributary of Tigris River, it is one of the important rivers in Iraq. It covers a total distance of 445 km (275 miles). 32600 km2is the area that drains by Diyala River between Iraqi-Iranian borders. This research aims to evaluate the water quality index WQI of Diyala River, where three stations were chosen along the river. These stations are D12 at Jalawlaa City at the beginning of Diyala River, the second station is D15 at Baaquba City at the mid distance of the river, and the third station is D17 which is the last station before the confluence of Diyala River with Tigris River at Baghdad city. Bhargava method was used in order to evaluate the water quality index for both irrigation and drink

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Publication Date
Sun Sep 02 2018
Journal Name
Arab Journal Of Basic And Applied Sciences
Development of the Banach contraction method for the solution of nonlinear thin film flows of non-Newtonian fluids
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Publication Date
Sat Jan 27 2024
Journal Name
History Of Medicine
Developing and Validating a Spectrophotometric Method for Estimating Antifungal (Nystatin) in its Pure Form Pharmaceutical Formulation Using Tetrachloro-1,4 benzoquinone
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The UV−VIS absorption spectroscopy technique was used to study the formation of a new complex of charge transfer (CT) between bioactive organic molecules as (Nystatin) containing both a π-electrons from a conjugated system and lone-pair of electrons (amine) with Tetrachloro-1,4 benzoquinone (TCBQ) as a π-acceptor in which the transferred electron goes into its vacant anti-bonding molecular orbitals. The Tyrian purple-colored complex formed was quantitatively measured at 544 nm. This complex shows obeying Beer's law within the concentration range of (10-90) μg.ml-1The stoichiometry of the formed complex between the (Nys.) and (TCBQ) was found 1:2 as evaluated by continuous variation (Job's method) and mole ratio method The value of mola

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Publication Date
Wed Feb 22 2017
Journal Name
Geological Society, London, Special Publications
Role of facies diversity and cyclicity on the reservoir quality of the mid-Cretaceous Mishrif Formation in the southern Mesopotamian Basin, Iraq
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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
The role of the green human resources management practices in a achieving requirements of environmental citizenship- Field research at the General Company for Vegetable Oils.
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The research aims to determine the role of the practices of green human resources management in achieving requirements of environmental citizenship in the workplace, the General Company for Vegetable Oils was chosen for the application of field-side of research which represent one of the important industrial companies in Iraq, which suffers from poor Green human resources management applications, which reflected negatively on the development Environmental citizenship among Employees. The questionnaire use as a tool to collect data and information as well as field presence of the researcher, The research sample included (30) managers of departments and Division ,and through using statistical program (SPSS) the data has been analys

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Strategic Analysis of the Reasons for the Delay of the Investment Projects of the North Oil Company / Case Study
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The research aims to find a contemporary model in analyzing the reasons behind the delay of the investment plan projects suffered by the North Oil Company. This model is able to understand the environment surrounding the implementation of projects in the light of the changes facing the company at the present time, which in turn requires the need to identify the most important strengths and weaknesses Internal and external opportunities and threats using the SWOT matrix and identify the appropriate strategic alternative based on clear policy, strategies and programs to address weaknesses and look to the future prospects as the company can be stronger and more flexible environmental changes surrounding the reality of implementation

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Publication Date
Fri Dec 23 2011
Journal Name
International Journal Of The Physical Sciences
Fast prediction of power transfer stability index based on radial basis function neural network
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Publication Date
Thu Apr 04 2024
Journal Name
Journal Of Electrical Systems
AI-Driven Prediction of Average Per Capita GDP: Exploring Linear and Nonlinear Statistical Techniques
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Average per capita GDP income is an important economic indicator. Economists use this term to determine the amount of progress or decline in the country's economy. It is also used to determine the order of countries and compare them with each other. Average per capita GDP income was first studied using the Time Series (Box Jenkins method), and the second is linear and non-linear regression; these methods are the most important and most commonly used statistical methods for forecasting because they are flexible and accurate in practice. The comparison is made to determine the best method between the two methods mentioned above using specific statistical criteria. The research found that the best approach is to build a model for predi

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
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Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Prediction of DNA Binding Sites Bound to Specific Transcription Factors by the SVM Algorithm
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In gene regulation, transcription factors (TFs) play a key function. It transmits genetic information from DNA to messenger RNA during the process of DNA transcription. During this step, the transcription factor binds to a segment of the DNA sequence known as Transcription Factor Binding Sites (TFBS). The goal of this study is to build a model that predicts whether or not a DNA binding site attaches to a certain transcription factor (TF). TFs are regulatory molecules that bind to particular sequence motifs in the gene to induce or restrict targeted gene transcription. Two classification methods will be used, which are support vector machine (SVM) and kernel logistic regression (KLR). Moreover, the KLR algorithm depends on another regress

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