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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
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Polyaniline Nano Films Synthesis in One Step via Chemical Oxidative Polymerization
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Polyaniline films were successfully synthesized in this study using an oxidative polymerization method at temperatures ranging from 0 to 4 ° C. Polyaniline films were deposited using a single step of chemical oxidative polymerization rather than electrochemical polymerization. The polyaniline was examined using FTIR, XRD, SEM, AFM, and Four Point Probe. This result demonstrates that polyaniline synthesized using this method has a uniform morphology, small size (17 to 40) nm, high crystallinity, and high conductivity (9.42 s/cm).

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Publication Date
Fri Jul 01 2016
Journal Name
Arabian Journal Of Geosciences
Polymetallic sulfide ores hosted in Late Permian carbonate at the Alanish locality, northern Iraq: petrography and mineral chemistry
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Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Engineering
Iraqi Sentiment and Emotion Analysis Using Deep Learning
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Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Physics: Conference Series
Using Spatial Analysis Methods to Evaluate the Soil Contamination of Baghdad City, Iraq
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Abstract<p>The current study aims to identify soil pollutants from heavy metals The study utilized 40 topsoil (5 cm) samples, which adapted and divided into seven regions lies in Baghdad governorate, included (Al-Husainya,(Hs) Al-Doura (Do), Sharie Al-Matar (SM), Al-Waziria (Wz), Nharawan (Nh), Abu Ghraib (Abu) and Al-Mahmoodyia (Mh)). Spatial distribution maps of Nickel (Ni), Manganese (Mn), Lead (Pb) and Zinc (Zn) were created for Baghdad city using Geographic Information Systems (GIS). The concentrations of four heavy metals in the soil of different area of Baghdad were measured and observed using XRF instrument. The result found highest values of Pb and Zn at the middle of the Baghdad in (Wz</p> ... Show More
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Publication Date
Sat Mar 01 2025
Journal Name
Results In Engineering
Advancing asphalt binder performance through nanomaterial and polymer modification: Experimental and statistical insights
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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Geological Journal
Estimation of Petrophysical Properties for Zubair Reservoir in Abu-Amood Oil Field
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The petrophysical analysis is significant to determine the parameters controlling the production wells and the reservoir quality. In this study, Using Interactive petrophysics software to analyze the petrophysical parameters of five wells penetrated the Zubair reservoir in the Abu-Amood field to evaluate a reservoir and search for hydrocarbon zones. The available logs data such as density, sonic, gamma ray, SP, neutron, and resistivity logs for wells AAm-1, AAm-2, AAm-3, AAm-4, and AAm-5 were used to determine the reservoir properties in Zubair reservoir. The density-neutron and neutron-sonic cross plots, which appear as lines with porosity scale ticks, are used to distinguish between the three main lithologies of sandstone, limesto

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Publication Date
Sat Dec 31 2016
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Experimental Work to Study the Behavior of Proppant Inside the Hydraulic Fractures and the Plugging Time
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Experiments were conducted to study the behavior of the solid particles (proppant) inside the hydraulic fracture during the formation stimulation, and study the effect of the proppant concentration on the hydraulic fracturing process, which lead to bridge and screen-out conditions inside the fractures across the fracture width that restricts fracturing fluid to flow into the hydraulic fracture. The research also studies the effect of the ratio between the fracture size and the average particles diameter “proppant", on fracture bridging. In this study two ratios were considered β= 2 and 3 ,where β=Dt / Dp where: Dt= hydraulic fracture size (width) and Dp=Average particles diameter.

This work pr

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Publication Date
Sun Jun 13 2021
Journal Name
Turkish Journal Of Computer And Mathematics Education
Private Drinking Stations In Al-Dora And Ways To Unify Them In One Station To Prevent Pollution
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The Current Research Seeks To Identify The Possibility Of Unifying The Private Drinking Stations In The Session In A Single Station In Order To Prevent Pollution. In Order To Achieve The Goal Of The Current Research, The Researcher Followed The Descriptive Survey Approach. The Researcher Identified The Research Community As Working In Institutions Related To Drinking Water Filtering In The Governorate Of Baghdad, And In Order To Collect Data And Information Necessary To Answer The Study's Question (Is It Possible To Supply Private Drinking Stations With One Station?) Researcher Designed A Questionnaire Consisting Of (10) Paragraphs Measuring Aspects Of This Topic, And Applied It To A Sample Of Employees And Workers Amounted To (200) People,

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Publication Date
Thu Mar 31 2022
Journal Name
Pakistan Journal Of Medical And Health Sciences
Effect of Moral Distress on Decision Making among Nurses in Intensive Care Units
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Background: Moral distress, as one of the most important issues in the nursing profession, can negatively affect the healthcare system Objectives: To examine the effect of moral distress on decision making. Methodology: A descriptive cross-sectional study a non-probability sampling method was used and a total sample collected was (126) ICU nurses Result: Moral distress among ICUs nurses were moderate and decision making was good Conclusion: Although nurses in ICUs perceive good decision making but suffered from moderate MD which affected their decision making. MD is still an important issue that nurses may face in ICUs Conclusion: Although nurses in ICUs perceive good decision making but suffered from moderate MD which affected the

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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