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Artificial neural network and response surface methodology for modeling oil content in produced water from an Iraqi oil field
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ABSTRACT<p>The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value &lt;0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, temperature 46.4 °C, pressure 21 Mpa, and flowrate 27,000 m3/day which is nearly closed to suggested oily content 8.5 ppm. An artificial neural network (ANN) technique was employed in this study to estimate the oil content in the treatment process. An artificial neural network model was remarkably accurate at simulating the process under investigation. A low mean squared error (MSE) and relative error (RE) equal to 1.55 × 10−7 and 2.5, respectively, were obtained during the training phase, whilst the testing results demonstrated a high coefficient of determination (R2) equal to 0.99.</p>
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Publication Date
Sat Jan 01 2022
Journal Name
Ssrn Electronic Journal
Developing a Predictive Model and Multi-Objective Optimization of a Photovoltaic/Thermal System Based on Energy and Exergy Analysis Using Response Surface Methodology
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Publication Date
Fri Dec 01 2023
Journal Name
Materials Today Sustainability
Structure and performance of polyvinylchloride microfiltration membranes improved by green silicon oxide nanoparticles for oil-in-water emulsion separation
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Publication Date
Thu Jan 30 2020
Journal Name
Journal Of Engineering
The The Optimum Reservoir Performance of Nahr Umr/Ratawi Oil Field
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Reservoir study has been developed in order to get a full interesting of the Nahr Umr formation in Ratawi oil field. Oil in place has been calculated for Nahr Umr which was 2981.37 MM BBL. Several runs have been performed to get matching between measured and calculated of oil production data and well test pressure. In order to get the optimum performance of Nahr Umr many strategies have been proposed in this study where vertical and horizontal wells were involved in addition to different production rates. The reservoir was first assumed to be developed with vertical wells only using production rate of (80000–125000) STB/day. The reservoir is also proposed to produce using horizontal wells besides vertical wells with pr

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Publication Date
Mon Sep 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development of East Baghdad Oil Field By Clusters of Horizontal Wells
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There are varieties of reasons lead for drilling horizontal wells rather than verticals. Increasing the recovery of oil, especially from thin or tight reservoir permeability is the most important parameter.

East Baghdad oil field considered as a giant field with approximately more than 1billion barrel of a proved reserves accompanying recently to low production rate problems in many of the existing wells.

   It is important to say that presence of of  horizontal wells in East Baghdad field especially by converting some of already drilled wells by re-entry drilling horizontal sections may provide one of best solutions for the primary development stage in East Baghdad field which may be followed by drilling n

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Publication Date
Mon Sep 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development of East Baghdad Oil Field By Clusters of Horizontal Wells
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There are varieties of reasons lead for drilling horizontal wells rather than verticals. Increasing the recovery of oil, especially from thin or tight reservoir permeability is the most important parameter. East Baghdad oil field considered as a giant field with approximately more than 1billion barrel of a proved reserves accompanying recently to low production rate problems in many of the existing wells.    It is important to say that presence of of  horizontal wells in East Baghdad field especially by converting some of already drilled wells by re-entry drilling horizontal sections may provide one of best solutions for the primary development stage in East Baghdad field which may be followed by drilling new horizont

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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Effects of Aloe vera Gel, Sesame Oil and Camphor Oil on Pseudomonas aeruginosa Isolated from Burnt Patients
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Three isolates of  P. aeruginosa were isolated from burnt patients. The ability of these isolates for adhesion and formation of slime layer were tested, the result showed that all isolates were able to adherence on the smooth surface. The sensitivity of  P. aeruginosa isolates for antibiotics were tested , all isolates were sensitive  to Gentamycin, Piperacillin and Amikacin Ciprofloxacin, and  resist to Tetracyclin, Amoxicillin, Cephalexine , Ceftriaxone. Ciprofloxacin and Amikacin were found effective against P. aeruginosa isolates with MIC values of 3.8 μg/ ml for  Ciprofloxacin  and 0.244 μg/ ml for Amikacin The antibacterial effect of Different concentrations of Aloe

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Influence of Nanosilica on Solvent Deasphalting for Upgrading Iraqi Heavy Crude Oil
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In this study, the upgrading of Iraqi heavy crude oil was achieved utilizing the solvent deasphalting approach (SDA) and enhanced solvent deasphalting (e-SDA) by adding Nanosilica (NS). The NS was synthesized from local sand. The XRD result, referred to as the amorphous phase, has a wide peak at 2Θ= (22 - 23º) The inclusion of hydrogen-bonded silanol groups (Si–O–H) and siloxane groups (Si–O–Si) in the FTIR spectra. The SDA process was handled using n-pentane solvent at various solvent to oil ratios (SOR) (4-16/1ml/g), room and reflux temperature, and 0.5 h mixing time. In the e-SDA process, various fractions of the NS (1–7 wt.%) have been utilized with 61 nm particle size and 560.86 m²/g surface area in the presence of 12 m

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Publication Date
Tue Jun 03 2025
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Comparison of some artificial neural networks for graduate students
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Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer

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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Engineering
Spiking Neural Network in Precision Agriculture
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In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Face Recognition and Emotion Recognition from Facial Expression Using Deep Learning Neural Network
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Abstract<p>Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.</p>
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