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Numerical Simulation of Gas Lift Optimization Using Genetic Algorithm for a Middle East Oil Field: Feasibility Study
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<p>Gas-lift technique plays an important role in sustaining oil production, especially from a mature field when the reservoirs’ natural energy becomes insufficient. However, optimally allocation of the gas injection rate in a large field through its gas-lift network system towards maximization of oil production rate is a challenging task. The conventional gas-lift optimization problems may become inefficient and incapable of modelling the gas-lift optimization in a large network system with problems associated with multi-objective, multi-constrained, and limited gas injection rate. The key objective of this study is to assess the feasibility of utilizing the Genetic Algorithm (GA) technique to optimize the allocation of the continuous gas-lift injection rate in a network system of a Middle Eastern oil field with 43 gas-lift injected wells through numerical modelling and simulation studies. Reservoir pressure and water cut sensitivity studies are performed to investigate the potential impacts of these parameters on well production performance and production life cycle of the field. Sample economics analysis are exercised to broaden the understanding of potential benefit of the implementation gas lift techniques in the field from both technical and economic viewpoint.</p><p>In addition, while application of GA is not a new idea, this paper elaborates the GA based optimization techniques for improving the oil production rate by implementing gas lift in a large Middle Eastern oil field. The optimization model is presented step by step, so it can easily be followed, and be used as a guide, especially by frontline production engineers involved in designing and development of gas-lift system towards optimally allocation of gas injection rate to individual well in a network system for a field with limited gas injection rate.</p>
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Publication Date
Mon Jan 01 2024
Journal Name
Tropical Journal Of Natural Product Research
Cytotoxic Potential of Neem (Azadirachta indica A. Juss) Oil
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An increasing interest is emerging in identifying natural products to overcome drug resistance in cancer patients. In this context, the present study was conducted to investigate the cytotoxic effects of neem plant (Azadirachta indica) oil in three different biological models (breast cancer cell lines, Allium cepa root tip, and mice vital organs). The cytotoxic potential of the neem oil was evaluated with two human cell lines (MCF7 and MDA-MB231) and an Allum cepa root tip bioassay. Histopathological analysis was conducted on the neem oil-treated and untreated control mice. The results revealed an anti-proliferative effect for neem oil on both estrogen receptor-positive (MCF7) and estrogen receptor-negative (MDA-MB231) breast cancer cell li

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Publication Date
Sun Dec 31 2023
Journal Name
Tropical Journal Of Natural Product Research
Cytotoxic Potential of Neem (Azadirachta indica A. Juss) Oil
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Publication Date
Thu Oct 14 2021
Journal Name
Iraqi Journal Of Physics
Measurement of radon and thoron concentrations of soil- gas in Al-Kufa city using RAD-7 detector
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This work represents the set of measurements of radon and thoron concentrations levels of soil-gas in Al-Kufa city in Iraq using electric Radon meter (RAD-7). Radon and thoron concentration were measured in soil-gas in 20 location for three depth of (50, 100 and 150) cm.
The results show that the emanation rate of radon and thoron gas varied from location to anther, depending on the geological formation. The Radon concentration in soil has been found to vary from (12775±400) Bq/m3 at 150 cm depth in location (sample K2) to (41.45±17) Bq/m3, for depth 150 cm in location (sample K20). The thoron concentration in soil has been found to vary from (198±8.5) Bq/m3 at 150 cm depth in location samples (K1 & K2) to undetected in the mos

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Publication Date
Sun Mar 31 2013
Journal Name
Inventi Impact: Artificial Intelligence
SIMULATION OF IDENTIFICATION AND CONTROL OF SCARA ROBOT USING MODIFIED RECURRENT NEURAL NETWORKS
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This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

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Publication Date
Mon Jul 20 2026
Journal Name
Plant Science Today
Investigation of oleaginous plant-associated fungi from oil-producing plants: Molecular identification and gas chromatography-mass spectrometry (GC-MS) profiling
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The study evaluated endophytic communities associated with five oil-bearing plants, including sesame, corn, sunflower, olives and castor, which were collected from Baghdad and Diyala (Iraq), evaluated their oil production capacity and identified metabolites from the lipid fraction. Out of 151 isolates were collected from 21 taxa. Aspergillus niger showed the highest frequency (6.62 %), while the genera Aspergillus and Fusarium were the most dominant endophytes. The highest oil yield was identified and recorded in Aspergillus terreus (24.12 %). While the lowest oil yield was observed in Sclerotinia spp. (3.96 %). Gas chromatography-mass spectrometry (GC-MS) analysis of A. terreus revealed a profile dominated by pentadecyl acrylate (2

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Publication Date
Mon Oct 01 2018
Journal Name
Iraqi Journal Of Physics
Synthesis of gold nanoparticles by laser ablation on porous silicon for sensing CO2 gas
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In this research, porous silicon (PS) prepared by anodization etching on surface of single crystalline p-type Si wafer, then Gold nanoparticle (AuNPs) prepared by pulsed laser ablation in liquid. NPs deposited on PS layer by drop casting. The morphology of PS, AuNPs and AuNPs/PS samples were examined by AFM. The crystallization of this sample was characterized by X-ray diffraction (XRD). The electrical properties and sensitivity to CO2 gas were investigated to Al/AuNPs/PS/c-Si/Al, we found that AuNPs plays crucial role to enhance this properties.

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Publication Date
Tue Sep 29 2020
Journal Name
Reaction Kinetics, Mechanisms And Catalysis
Development of two-step noncatalytic esterification of waste cooking oil for biodiesel preparation
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An innovative two-step noncatalytic esterifcation technique was proposed to synthesize alkyl esters from free fatty acids simulated in waste cooking oil, as a pretreatment process for biodiesel production, without adding any catalyst under normal conditions of pressure and temperature. The efect of methanol:oil molar ratio, reaction time, mixing rate, and reaction temperature were investigated. The results confrmed that the conversion of the reaction was increased when increasing the methanol molar ratio and decreased in prolonged reaction temperature. High conversion (94.545%) was successfully achieved at optimized conditions of 115:1, 65:1 methanol:oil molar ratio in the frst step and second step, respectively, other conditions i

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Publication Date
Mon Oct 22 2018
Journal Name
Journal Of Economics And Administrative Sciences
Using simulation to compare between parametric and nonparametric transfer function model
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In this paper, The transfer function model in the time series was estimated using different methods, including parametric Represented by the method of the Conditional Likelihood Function, as well as the use of abilities nonparametric are in two methods  local linear regression and cubic smoothing spline method, This research aims to compare those capabilities with the nonlinear transfer function model by using the style of simulation and the study of two models as output variable and one model as input variable in addition t

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Multi – Linear in Multiple Nonparametric Regression , Detection and Treatment Using Simulation
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             It is the regression analysis is the foundation stone of knowledge of statistics , which mostly depends on the ordinary least square method , but as is well known that the way the above mentioned her several conditions to operate accurately and the results can be unreliable , add to that the lack of certain conditions make it impossible to complete the work and analysis method and among those conditions are the multi-co linearity problem , and we are in the process of detected that problem between the independent variables using farrar –glauber test , in addition to the requirement linearity data and the lack of the condition last has been resorting to the

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Publication Date
Sat Sep 01 2018
Journal Name
2018 11th International Conference On Developments In Esystems Engineering (dese)
Natural Rivers Longitudinal Dispersion Coefficient Simulation Using Hybrid Soft Computing Model
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