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Permeability Prediction in One of Iraqi Carbonate Reservoir Using Statistical, Hydraulic Flow Units, and ANN Methods
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   Permeability is an essential parameter in reservoir characterization because it is determined hydrocarbon flow patterns and volume, for this reason, the need for accurate and inexpensive methods for predicting permeability is important. Predictive models of permeability become more attractive as a result.

   A Mishrif reservoir in Iraq's southeast has been chosen, and the study is based on data from four wells that penetrate the Mishrif formation. This study discusses some methods for predicting permeability. The conventional method of developing a link between permeability and porosity is one of the strategies. The second technique uses flow units and a flow zone indicator (FZI) to predict the permeability of a rock mass using data from cores and well logs. The approach is used to predict the permeability of some uncored wells/intervals. The flow zone indicator is an efficient metric for calculating hydraulic flow units since it is based on the geological properties of the material and varied geometries pore of rock mass (HFU) and Artificial Neural Network (ANN) analysis is another way for predicting permeability. The result shows the FZI method, gave acceptable results compared with the obtained from core analysis than the other methods.

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Publication Date
Wed Oct 05 2016
Journal Name
Al-academy
Relationship of psychological time with elements of movie's expression Example) movies, which their events takes, place in one day / as)
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This research deals with and which was entitled: relationship between psychological time and elements of filming expression (one-day event filmsas an example). It is about the relationship of psychological time (internal) with the elements of filming expression and how the time affected when using these elements in terms of its deceleration or acceleration. In particular, this research focus on elements that slow down time or stops it when using these elements. As one day time is short and heavy at the time of spectators in terms of the large number of film events which makes the viewer runs out of breath to understand the nature of those events and then identify the causes and consequences, as they occur in a short time (one day time) a

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Publication Date
Sat Aug 01 2015
Journal Name
International Journal Of Computer Science And Mobile Computing
Image Compression based on Non-Linear Polynomial Prediction Model
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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
Vertical Stress Prediction for Zubair Oil Field/ Case Study
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Predicting vertical stress was indeed useful for controlling geomechanical issues since it allowed for the computation of pore pressure for the formation and the classification of fault regimes. This study provides an in-depth observation of vertical stress prediction utilizing numerous approaches using the Techlog 2015 software. Gardner's method results in incorrect vertical stress values with a problem that this method doesn't start from the surface and instead relies only on sound log data. Whereas the Amoco, Wendt non-acoustic, Traugott, average technique simply needed density log as input and used a straight line as the observed density, this was incorrect for vertical computing stress. The results of these methods

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Attention-Deficit Hyperactivity Disorder Prediction by Artificial Intelligence Techniques
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Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Electrical And Electronics Engineering
HF Wave Propagation Prediction Based On Passive Oblique Ionosonde
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High frequency (HF) communications have an important role in long distances wireless communications. This frequency band is more important than VHF and UHF, as HF frequencies can cut longer distance with a single hopping. It has a low operation cost because it offers over-the-horizon communications without repeaters, therefore it can be used as a backup for satellite communications in emergency conditions. One of the main problems in HF communications is the prediction of the propagation direction and the frequency of optimum transmission (FOT) that must be used at a certain time. This paper introduces a new technique based on Oblique Ionosonde Station (OIS) to overcome this problem with a low cost and an easier way. This technique uses the

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Publication Date
Mon Mar 01 2021
Journal Name
Journal Of Physics: Conference Series
Synthesis and study the liquid crystalline properties of new compounds containing 5-methyl-2,4-dihydro-3H-pyrazol-3-one
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Abstract<p>The new compounds of pyrazolines were synthesized from the reaction of different acid hydrazide with ethylacetoacetate and ethanol under reflux. These compounds were obtained from many sequence reactions. The 4-acetyl-5-methyl-2,4-dihydro-3H-pyrazol-3-one compounds synthesized from the reaction of 5-methyl-2,4-dihydro-3H-pyrazol-3-one with acetyl chloride in calcium hydroxide and 1,4-dioxane. Finaly, Schiff bases were prepared via condensation reaction of products of mono- and tri ketone derivatives[IV]<sub>a, b</sub> with phenyl hydrazines as presented in (Scheme 1, 2). The synthesized compounds were identification by using FTIR, NMR and Mass spectroscopy (of some of them).</p> ... Show More
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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Applied Engineering Science
Rutting prediction of hot mix asphalt mixtures reinforced by ceramic fibers
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One of the most severe problems with flexible asphalt pavements is permanent deformation in the form of rutting. Accordingly, the practice of adding fiber elements to asphalt mix to improve performance under dynamic loading has grown significantly in order to prevent rutting distress and ensure a safe and long-lasting road surface. This paper explores the effects of a combination of ceramic fiber (CF), a low-cost, easily available mineral fiber, and thermal insulator fiber reinforced to enhance the Marshall properties and increase the rutting resistance of asphalt mixes at high temperatures. Asphalt mixtures with 0%, 0.75%, 1.5%, and 2.25% CF content were prepared, and Marshall stability and wheel tracking tests were employed to stu

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Publication Date
Mon Dec 02 2024
Journal Name
Engineering, Technology &amp; Applied Science Research
An Artificial Neural Network Prediction Model of GFRP Residual Tensile Strength
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This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

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Publication Date
Sun Sep 11 2022
Journal Name
Journal Of Petroleum Research And Studies
Distribution of Petrophysical Properties Based on Conceptual Facies Model, Mishrif Reservoir/South of Iraq
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A 3D geological model is an essential step to reveal reservoir heterogeneity and reservoir properties distribution. In the present study, a three-dimensional geological model for the Mishrif reservoir was built based on data obtained from seven wells and core data. The methodology includes building a 3D grid and populating it with petrophysical properties such as (facies, porosity, water saturation, and net to gross ratio). The structural model was built based on a base contour map obtained from 2D seismic interpretation along with well tops from seven wells. A simple grid method was used to build the structural framework with 234x278x91 grid cells in the X, Y, and Z directions, respectively, with lengths equal to 150 meters. The to

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Publication Date
Wed Dec 14 2022
Journal Name
Civil Engineering Journal
Rutting Prediction of Hot Mix Asphalt Mixtures Modified by Nano silica and Subjected to Aging Process
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High-volume traffic with ultra-heavy axle loads combined with extremely hot weather conditions increases the propagation of rutting in flexible pavement road networks. Several studies suggested using nanomaterials in asphalt modification to delay the deterioration of asphalt pavement. The current work aims to improve the resistance of hot mix asphalt (HMA) to rutting by incorporating Nano Silica (NS) in specific concentrations. NS was blended into asphalt mixtures in concentrations of 2, 4, and 6% by weight of the binder. The behavior of asphalt mixtures subjected to aging was investigated at different stages (short-term and long-term aging). The performance characteristics of the asphalt mixtures were evaluated using the Marshall s

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