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Evaluation of the Mishrif Formation Using an Advanced Method of Interpretation
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The Mishrif Formation is one of the most important geological formations in Iraq consisting of limestone, marl, and shale layers since it is one of the main oil producing reservoirs in the country, which contain a significant portion of Iraq's oil reserves. The formation has been extensively explored and developed by the Iraqi government and international oil companies, with many oil fields being developed within it. The accurate evaluation of the Mishrif formation is key to the successful exploitation of this field. However, its geological complexity poses significant challenges for oil production, requiring advanced techniques to accurately evaluate its petrophysical properties.

   This study used advanced well-logging analysis techniques, including mineralogical inversion with the Quanti-Elan model employed in Schlumberger's Techlog software to evaluate this formation. The lithology, clay volume, porosity, permeability, and hydrocarbon saturation data were obtained from the open hole logging of three wells in a southern Iraqi oil field. The environmental correction was applied for open-hole logging tools, and the primary mineral of the formation was determined using porosity log cross-plotting. Pickett plot technique was utilized to determine water resistivity and Archie's parameters, and the reconstruction log was generated based on volumetric and response parameters for each component. Based on thorough analysis, the clay volume of the Mishrif formation is estimated to be about 10%, which is a common value for this rock type. The porosity was computed based on the total fluid volume, ranging from 11% to 14%, and water saturation was determined using Archie's equation. The final results of the volume of each component for rock and fluid are presented using computer programming interpretation. The results of this study provide valuable insights into the petrophysical properties of the Mishrif formation and are expected to inform for better interpretation and evaluation of petrophysical properties of similar formations, which is essential for optimum field development planning as well as minimising the uncertainties.

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Publication Date
Fri Jan 01 2016
Journal Name
Bulletin Of Mathematics And Statistics Research
New Approximation Operators Using Mixed Degree Systems
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This paper is concerned with introducing and studying the first new approximation operators using mixed degree system and second new approximation operators using mixed degree system which are the core concept in this paper. In addition, the approximations of graphs using the operators first lower and first upper are accurate then the approximations obtained by using the operators second lower and second upper sincefirst accuracy less then second accuracy. For this reason, we study in detail the properties of second lower and second upper in this paper. Furthermore, we summarize the results for the properties of approximation operators second lower and second upper when the graph G is arbitrary, serial 1, serial 2, reflexive, symmetric, tra

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Publication Date
Sat Jan 01 2022
Journal Name
Turkish Journal Of Physiotherapy And Rehabilitation
classification coco dataset using machine learning algorithms
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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

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Publication Date
Thu Dec 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Hexapod Robot Static Stability Enhancement using Genetic Algorithm
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Abstract

Hexapod robot is a flexible mechanical robot with six legs. It has the ability to walk over terrain. The hexapod robot look likes the insect so it has the same gaits. These gaits are tripod, wave and ripple gaits. Hexapod robot needs to stay statically stable at all the times during each gait in order not to fall with three or more legs continuously contacts with the ground. The safety static stability walking is called (the stability margin). In this paper, the forward and inverse kinematics are derived for each hexapod’s leg in order to simulate the hexapod robot model walking using MATLAB R2010a for all gaits and the geometry in order to derive the equations of the sub-constraint workspaces for each

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Using some Natural Minerals to Remove Cadmium from Polluted Water
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Water scarcity is one of the most important problems facing humanity in various fields such as economics, industry, agriculture, and tourism. This may push people to use low-quality water like industrial-wastewater. The application of some chemical compounds to get rid of heavy metals such as cadmium is an environmentally harmful approach. It is well-known that heavy metals as cadmium may induce harmful problems when present in water and invade to soil, plants and food chain of a human being. In this case, man will be forced to use the low quality water in irrigation. Application of natural materials instead of chemicals to remove cadmium from polluted water is an environmental friendly approach. Attention was drawn in this research wor

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Publication Date
Wed Oct 01 2025
Journal Name
Chinese Journal Of Analytical Chemistry
Synthesis, characterization, antioxidant and bioactivity assessment, and thermodynamic analysis of metal ion complexes using a novel azo dye
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In this study, the new azo dye,5,5-[1,2-phenylenebis(2,1-biazenediyl)] bis[8-quinolino], was used to synthesize complexes with Co2+, Ni2+, Cu2+, Zn2+, and Cd2+ ions. The compounds were characterized using 1H and 13C nuclear magnetic resonance (NMR) spectroscopy, Fourier transform infrared (FT-IR) spectroscopy, ultraviolet-visible (UV-Vis) spectroscopy, mass spectrometry, thermo gravimetric analysis (TGA), diffevential scanning calovimltry (DSC), CHN analysis. Further, conductivity, magnetic susceptibility, and metal and chlorine content analysis using FT-IR spectroscopy revealed that the ligand chelates as a bidentate (OH) phenol group and a bidentate (C=N) ring group. The ligand exhibited tetradentate behavior, forming tetrahedral complexe

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Publication Date
Mon Dec 31 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
USE OF CLAY MINERAL IN WESTERN ALANBAR DESERT AND USING FOR CRUDE OIL FRACTIONATION (ALQAYAIRA CRUDE): USE OF CLAY MINERAL IN WESTERN ALANBAR DESERT AND USING FOR CRUDE OIL FRACTIONATION (ALQAYAIRA CRUDE)
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In this research, a number of the western al-Anbar clays (red iron clays, Attapulgite) were modified by treating them thermally with a temperature of 650oC. After that, these clays reflux with sodium hydroxide 5% for 1 hour by using microwave as a power supply. The research included fractionation alqayaira crude oil the fractionation included removing the asphaltene by precipitation from the crude using a simple paraffin solvent (normal hexane) as a non-soluble substance. After that it was filtered using the ash-free filter paper 42, the dissolved part, maltinate, was taken, drying a temperature of 75oC and weight, and to find the percentage of the two parts. Malatine was divided into three main parts (paraf

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Arabic Sentiment Analysis (ASA) Using Deep Learning Approach
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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
Spectrophotometric Determination of Copper(II) using 2,2[O-Tolidine-4,4-bis azo]bis[4,5-diphenyl imidazole](MBBAI)
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            Spectrophotometric method was developed for the determination of copper(II) ion. Synthesized (2,2[O-Tolidine-4,4-bis azo]bis[4,5-diphenyl imidazole]) (MBBAI) was used as chromogenic reagent at pH=5. Various factors affecting complex formation, such as, pH effect, reagent concentration, time effect and temperature effect, have been considered and studied. Under optimum conditions concentration ranged from (5.00-80.00) µg/mL of copper(II) obeyed Beer`s Low. Maximum absorption of the complex was 409nm with molar absorpitivity 0.127x104 L mol-1 cm-1. Limit of detection(LOD) and Limit of quantification were 1.924 and 6.42 μg/mL, respectively.

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Civil Engineering And Technology
PREDICTION OF BEARING CAPACITY, ANGLE OF INTERNAL FRICTION, COHESION, AND PLASTICITY INDEX USING ANN (CASE STUDY OF BAGHDAD, IRAQ)
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In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Civil Engineering And Technology
PREDICTION OF BEARING CAPACITY, ANGLE OF INTERNAL FRICTION, COHESION, AND PLASTICITY INDEX USING ANN (CASE STUDY OF BAGHDAD, IRAQ).
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In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

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