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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
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Applying some hybrid models for modeling bivariate time series assuming different distributions for random error with a practical application
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Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

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Publication Date
Sat Jun 02 2018
Journal Name
Agroforestry Systems
Biomass and buffer management practice effects on soil hydraulic properties compared to grain crops for claypan landscapes
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Publication Date
Wed Sep 16 2020
Journal Name
Route Educational & Social Journal
Effect of applying the QR-Code system for acquisition chemistry and creative thinking in of first class female student at intermediate schools.
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This research aims at identifying the system of applying the QRcode system for acquisition of chemistry by first class female students studying at intermediate schools knowledge and its effect on creative thinking. The research sample consisted of (63) female students in one of the intermediate schools in Baghdad/Iraq using two equivalents experimental and control groups. The scientific context used was based on the chemistry text book related to the periodic table, (Metals) for the first group of students and Alkaline metals,Nonmetals, Metalloides) for the second group. The research methodology employed consisted of the followings :Measuring students acquisition using (35) issues. The results were verified for their face validity and obtai

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Publication Date
Sat Jan 01 2022
Journal Name
Materials Today: Proceedings
Hydraulic behaviour and improving of water quality of the Chibayish Marshes
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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Risk management in industrial economic units by using Pareto Chart
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In the light of the globalization Which surrounds the business environment and whose impact has been reflected on industrial economic units  the whole world has become a single market that affects its variables on all units and is affected by the economic contribution of each economic unit as much as its share. The problem of this research is that the use of Pareto analysis enables industrial economic units to diagnose the risks surrounding them , so the main objective of the research was to classify risks into both internal and external types and identify any risks that require more attention.

The research was based on the hypothesis that Pareto analysis used, risks can be identified and addressed before they occur.

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Publication Date
Wed Apr 01 2020
Journal Name
Civil Engineering Journal
Model Development for the Prediction of the Resilient Modulus of Warm Mix Asphalt
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Increasing material prices coupled with the emission of hazardous gases through the production and construction of Hot Mix Asphalt (HMA) has driven a strong movement toward the adoption of sustainable construction technology. Warm Mix Asphalt (WMA) is considered relatively a new technology, which enables the production and compaction of asphalt concrete mixtures at temperatures 15-40 °C lower than that of traditional hot mix asphalt. The Resilient modulus (Mr) which can be defined as the ratio of axial pulsating stress to the corresponding recoverable strain, is used to evaluate the relative quality of materials as well as to generate input for pavement design or pavement evaluation and analysis. Based on the aforementioned preface, it is

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Publication Date
Sat Apr 01 2023
Journal Name
Alexandria Engineering Journal
Employing Sisko non-Newtonian model to investigate the thermal behavior of blood flow in a stenosis artery: Effects of heat flux, different severities of stenosis, and different radii of the artery
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Publication Date
Wed May 01 2024
Journal Name
Tropical Journal Of Pharmaceutical Research
Validation of UV-visible spectrophotometric method for niclosamide in different media
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Purpose: To validate a UV-visible spectrophotometric technique for evaluating niclosamide (NIC) concentration in different media across various values of pH. Methods: NIC was investigated using a UV-visible spectrophotometer in acidic buffer solution (ABS) of pH 1.2, deionized water (DW), and phosphate buffer solution (PBS), pH 7.4. The characterization of NIC was done with differential scanning calorimeter (DSC), powder X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The UV analysis was validated for accuracy, precision, linearity, and robustness. Results: The DSC spectra showed a single endothermic peak at 228.43 °C (corresponding to the melting point of NIC), while XRD and FTIR analysis confirmed the identit

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Publication Date
Tue Nov 29 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
A proposed form for the Combined Assurance report and its impact In achieving sustainable development in the Iraqi economic units
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Despite the importance of sustainable development and its dimensions in developing performance and supporting competitive advantage in economic units, there is a gap and lack of coordination between Combined Assurance  providers (management, internal audit, external audit) to report on sustainable development, and the research aims to propose a model for the Combined Assurance report to achieve development sustainable development in the Iraqi economic units, especially the Baghdad Municipality, enables assurance providers to coordinate efforts that lead to the achievement of Combined Assurance, The research found the proposed model for the Combined Assurance report in achieving sustainable development in the Iraqi economic units, es

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Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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