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Optimizing Gas Lift for Improved Oil Recovery in a Middle East Field: A Genetic Algorithm Approach
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This paper presents a study of the application of gas lift (GL) to improve oil production in a Middle East field. The field has been experiencing a rapid decline in production due to a drop in reservoir pressure. GL is a widely used artificial lift technique that can be used to increase oil production by reducing the hydrostatic pressure in the wellbore. The study used a full field model to simulate the effects of GL on production. The model was run under different production scenarios, including different water cut and reservoir pressure values. The results showed that GL can significantly increase oil production under all scenarios. The study also found that most wells in the field will soon be closed due to high water cuts. However, the application of GL can keep these wells economically viable. The economic evaluation of the study showed that the optimum GL design is feasible and can significantly improve oil production. This suggests that GL is a promising technology for improving oil production in fields that are experiencing a decline in production. The study also provides a new approach to GL optimization using a genetic algorithm, which can be used to find the optimal GL design for a given field.

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network
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       In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.

         

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Direction Finding Using GHA Neural Networks
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 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

 

 

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Improving the Direction of Arrival Estimation Using the Parasitic Subspace Generated by Active-Parasitic Antenna (APA) Arrays
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The improvement in Direction of Arrival (DOA) estimation when the received signals impinge on Active-Parasitic Antenna (APA) arrays will be studied in this work. An APA array consists of several active antennas; others are parasitic antennas. The responses to the received signals are measured at the loaded terminals of the active element. The terminals of the parasitic element are shorted. The effect of the received signals on the parasites, i.e., the induced short-circuit current, is mutually coupled to the active elements. Eigen decomposition of the covariance matrix of the measurements of the APA array generates a third subspace in addition to the traditional signal and noise subspaces generated by the all-active ante

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Fault Location of Doukan-Erbil 132kv Double Transmission Lines Using Artificial Neural Network ANN
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Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p

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Publication Date
Thu Jun 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
The Effects of Operating Variables on Efficancy of Water Disinfection by Sodium Hypochlorite Using Al-Wathba Wastewater
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The aim of this investigation was to study the impact of various reaction parameters on wastewater taken from Al-Wathba water treatment plant on Tigris River in south of Baghdad, Iraq with sodium hypochlorite solution. The parameters studied were sodium hypochlorite dose, contact time, initial fecal coliform bacteria concentration, temperature, and pH. In a batch reactor, different concentrations of sodium hypochlorite solution were used to disinfect 1L of water. The amount of hypochlorite ions in disinfected water was measured using an Iodimetry test for different reaction times, whereas the Most Probable Number (MPN) test was used to determine the concentration of coliform bacteria. Total Plate Count (TPC) was utilized in this study to

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
Effect of the Iranian Seperation Dikes on the Water Salinity Patterns Within Al Huweizah Marsh
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Al Huweizah Marsh is considered as the largest marsh at the southern part of Iraq. About one third of the marsh is located within the Iranian territory. Iran began to construct earth dikes along the Iraqi-Iranian international borders to separate the Iranian part of the marsh. The electrical conductivity, EC, value was adopted to be the indicator for the water salinity within the marsh. A steady two-dimensional water quality routing model was implemented by using the RMA2 and RMA4 softwares within the SMS computer package to estimate the distribution of the
EC values within the marsh seasonally during the wet, moderate and dry water years. The EC distribution Patterns were estimated considering the expected two cases of the marsh futu

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Publication Date
Wed Dec 15 2021
Journal Name
Journal Of Baghdad College Of Dentistry
Assessment of Coating Zirconium Implant Material with Nanoparticles of Faujasite
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Aim: To evaluate the wettability and microhardness of Zirconium (ZrO2) dental material when coated with different concentrations of Faujasite. Materials and methods: 30 circular disks produced from ZrO2, then each group is classified into 10 control groups, 10 coated groups with 3% Faujasite, and 10 coated groups with 7% faujasite by electro-spun tool to study variable properties in hardness and water contact angle of implant materials. Results: This study stated the high hardness in 7% of faujasite concentration for ZrO2, in addition, the contact angle decreased gradually until reach 0 ᵒ in 7% concentration of faujasite with ZrO2 Conclusion: Water contact angle (WCA) declined till disappeared in (7% wt.) of faujasite coated with the Z

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Publication Date
Fri Dec 01 2023
Journal Name
Baghdad Science Journal
Microbial Quality of Paddy fields at Alfurat Alawsat Area, Iraq and the Effect of Milling Process on the Rice Contamination Level
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Fifty-Four paddy samples, 45 soil samples, and nine irrigation water samples of some paddy fields at Alfurat Alawsat Area, Iraq were collected to investigate the microbial quality including total count bacteria (TCB), molds and yeast, total coliform (TC), and E. coli bacteria. Paddy samples were processed at the laboratory level to produce rice at 32 and 36 whiteness, and the microbial quality of the produced rice was conducted too. The results showed that all irrigation water samples were overpassed the FDA limit for E. coli. All paddy samples were exceeded the good limit of TCB, but no sample exceeded the acceptable limit. Most paddy samples were exceeded the FDA limit for molds and yeast, and few paddy samples exc

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Publication Date
Fri Mar 31 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Effect of Nanoparticles and Surfactant on Phase Inversion of Two Phases
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In the present study, a pressure drop technique was used to identify the phase inversion point of oil-in-water to water-in-oil flows through a horizontal pipe and to study the effect of additives (nanoparticles, cationic surfactant and blend  nanoparticles-surfactant) on the critical dispersed volume fraction (phase inversion point). The measurements were carried  for mixture velocity ranges from 0.8 m/sec to 2.3 m/sec. The results showed that at low mixture velocity 0.8 and 1 m/sec there is no effect of additives and velocity on phase inversion point, while at high mixture velocities the phase inversion point for nanoparticles and blend (nanoparticles/surfactant) systems was delayed (postponed) to a higher value of the dispers

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Influence of Design Efficiency of Water Supply Network Inside Building on its Optimum Usage: Review
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The water supply network inside the building is of high importance due to direct contact with the user that must be optimally designed to meet the water needs of users.  This work aims to review previous research and scientific theories that deal with the design of water networks inside buildings, from calculating the amount of consumption and the optimal distribution of the network, as well as ways to rationalize the use of water by the consumer.  The process of pumping domestic water starts from water treatment plants to be fed to the public distribution networks, then reaching a distribution network inside the building till it is  provided to the user.  The design of the water supply network inside the building is

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