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Accurate Petrophysical Interpretation of Carbonate using the Elemental Capture Spectroscopy (ECS)
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Elemental capture spectroscopy (ECS) is an important tool in the petroleum industry for determining the composition and properties of rock formations in a reservoir. Knowledge of the types and abundance of different minerals in the reservoir is crucial for accurate petrophysical interpretation, reservoir engineering practices, and stratigraphic correlation. ECS measures the elemental content of the rock, which directly impacts several physical properties that are essential for reservoir characterization, such as porosity, fluid saturation, permeability, and matrix density. The ability to accurately determine these properties leads to better reservoir mapping, improved production, and more effective resource management. Accurately determining the mineralogy and porosity of carbonate rocks and other materials is the aim of this paper. Calcite, dolomite, quartz, clay (illite), anhydrite, and pyrite, in addition to water as a fluid, are taken into account in the computation. The formation's lithology and porosity can be ascertained from this data. When compared to the core descriptions in the geological report, the results demonstrated a distinct zone of unique lithology with good prediction accuracy.

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Publication Date
Wed Oct 25 2023
Journal Name
2023 Ieee 8th International Conference On Engineering Technologies And Applied Sciences (icetas)
Vibration Characteristics of Perforated Plate using Experimental and Numerical Approaches
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Vibration analysis plays a vital role in understanding and analyzing the behavior of the structure. Where, it can be utilized from this analysis in the design process of the structures in different engineering applications, check the quality and safety of the structure under different working conditions. This work presents experimental measurements and numerical solutions to an out of plane vibration of a rectangular plate with a circular hole. Free edges rectangular plates with different circular holes diameters were studied. The effects of hole location on the plate natural frequencies were also investigated. A finite element modeling (using ANSYS Software) has been used to analyze the vibration characteristics of the plates. A good agree

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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Applied Sciences
Improvement of Mechanical Welding Properties by using Induced Harmonic Vibration
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Publication Date
Wed Oct 28 2020
Journal Name
Egyptian Journal Of Chemistry
Inhibition of Aluminum Alloy 7025 in Acid Solution Using Sulphamethoxazole
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Corrosion behavior of aluminum alloy 7025 was investigated in hydrochloric acid (pH=1) containing 0.6 mol.dm-3 NaCl in the existence and absence of diverse concentrations of sulphamethoxazole as environmentally friendly corrosion inhibitor over the temperature range (298-313)K. Electrochemical polarization method using potentiostatic technique was employed. The inhibition efficiency has been raised with increased sulphamethoxazole concentration but lessened at temperature increases. The highest efficiency value was 96.5 at 298 K and 2 x10-4 mol.dm-3 concentration of sulphamethoxazole. The sulphamethoxazole adsorption was agreed with Langmuir adsorption isotherm. Some thermodynamic parameter (△Gads) and activation energy (Ea) were determin

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Publication Date
Sun Jan 08 2017
Journal Name
International Journal Of Information Technology And Computer Science
Adaptive Modeling of Urban Dynamics during Armada Event using CDRs
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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Improving Wear Properties of 392 Al Alloy Using Centrifugal Casting
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The microstructure and wear properties of 392 Al alloy with different Mg contents were studied using centrifugal casting. All melted alloys were heated to 800 ºC and poured into the preheated centrifugal casting mold (200-250 ºC) at different mould rotational speeds (1500, 1900 and 2300 r.p.m).  It is clear from the results obtained that wear rate was dependent on the Mg content, applied load and mould rotational speed. Furthermore, wear test showed that the minimum wear rate was found in the inner layer of produced rings at mould rotational speed of 1900 r.p.m and Mg content of 5%.

 

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Publication Date
Wed Oct 05 2022
Journal Name
Asian Journal Of Water, Environment And Pollution
Biosorption of Pollutants in Diyala River by Using Irrigated Vegetables
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In the absence of environmental regulation, food stays to be contaminated with heavy metals, which is becoming a big worry for human health. The present research focusses on the environmental and health effects of irrigating a number of crops grown in the soils surrounding the Al-Rustamia old plant using treated wastewater generated by the plant. The physicochemical properties, alkalinity, and electrical conductivity of the samples were evaluated, and vegetable samples were tested for Cd, Pb, Ni, and Zn, levels, and even the transfer factor (TF) from soils to crops and crop and multi-targeted risk, daily intake (DIM) of metals, and health risk index (HRI) was calculated. The findings found that the average contents of Zn, Pb, Ni, and Cd in

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Two Stage Evaporative Cooling of Residential Building Using Geothermal Energy
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The weather of Iraq has longer summer season compared with other countries. The ambient temperature during this season reaches over 50 OC which makes the evaporative cooling system suitable for this climate. In present work, the two-stage evaporative cooling system is studied. The first stage is indirect evaporative cooling (IEC) represented by two heat exchangers with the groundwater flow rate (5 L/min). The second stage is direct evaporative cooling (DEC) which represents three pads with groundwater flow rates of (4.5 L/min). The experimental work was conducted in July, August, September, and October in Baghdad. Results showed that overall evaporative efficiency of the system (two coils with three pads each

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
An Overview of Audio-Visual Source Separation Using Deep Learning
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    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
Bioremediation of Petroleum Hydrocarbons Contaminated Soil using Bio piles System
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This study was focused on biotreatment of soil which polluted by petroleum compounds (Diesel) which caused serious environmental problems. One of the most effective and promising ways to treat diesel-contaminated soil is bioremediation. It is a choice that offers the potential to destroy harmful pollutants using biological activity.

Four bacterial strains were isolated from diesel contaminated soil samples. The isolates were identified by the Vitek 2 system, as Sphingomonas paucimobilis, Pentoae species, Staphylococcus aureus, and Enterobacter cloacae. The potential of biological surfactant production was tested using the Sigma 703D stand-alone tensiometer showed

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

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