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Gas Lift Optimization for Zubair Oil Field Using Genetic Algorithm-Based Numerical Simulation: Feasibility Study
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The gas-lift method is crucial for maintaining oil production, particularly from an established field when the natural energy of the reservoirs is depleted. To maximize oil production, a major field's gas injection rate must be distributed as efficiently as possible across its gas-lift network system. Common gas-lift optimization techniques may lose their effectiveness and become unable to replicate the gas-lift optimum in a large network system due to problems with multi-objective, multi-constrained & restricted gas injection rate distribution. The main objective of the research is to determine the possibility of using the genetic algorithm (GA) technique to achieve the optimum distribution for the continuous gas-lift injection flows in the structure of the network of Zubair, oil field with 10 gas-lift injected wells. This will be done through numerical simulation and modeling studies. The overall enhancement of the filed production rate is found to have increased from 15767 STB/day to 19847 STB/day. The well's reservoir pressure and water cut sensitivity studies are carried out to study the possible impacts of these elements upon the well and its efficiency through the course of the field. Our understanding of the potential benefits of utilizing gas lift techniques in a field from a technical and economical point of view is deepened by the use of examples from economic analysis. Furthermore, even though the idea of employing GA in this manner is not new, this work discusses GA-based optimization methodologies for increasing the oil production rate by using gas lifting in a Zubair oilfield. In order to assign gas injection rates to specific wells in a network throughout the field using limited gas injection rates, the model for optimization will be laid out step-by-step making it simple to understand and employ as a guide, especially for the front-line production technicians involved in the development and design of gas-lift systems.

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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Dynamic algorithm (DRBLTS) and potentially weighted (WBP) to estimate hippocampal regression parameters using a techniqueBootstrap (comparative study)
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Bootstrap is one of an important re-sampling technique which has given the attention of  researches recently. The presence of outliers in the original data set may cause serious problem to the classical bootstrap when the percentage of outliers are higher than the original one. Many methods are proposed to overcome this problem such  Dynamic Robust Bootstrap for LTS (DRBLTS) and Weighted Bootstrap with Probability (WBP). This paper try to show the accuracy of parameters estimation by comparison the results of both methods. The bias , MSE and RMSE are considered. The criterion of the accuracy is based on the RMSE value since the method that provide us RMSE value smaller than other is con

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Publication Date
Sun Jan 01 2017
Journal Name
Australian Journal Of Basic And Applied Sciences
Proposed Algorithm for Gumbel Distribution Estimation
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Gumbel distribution was dealt with great care by researchers and statisticians. There are traditional methods to estimate two parameters of Gumbel distribution known as Maximum Likelihood, the Method of Moments and recently the method of re-sampling called (Jackknife). However, these methods suffer from some mathematical difficulties in solving them analytically. Accordingly, there are other non-traditional methods, like the principle of the nearest neighbors, used in computer science especially, artificial intelligence algorithms, including the genetic algorithm, the artificial neural network algorithm, and others that may to be classified as meta-heuristic methods. Moreover, this principle of nearest neighbors has useful statistical featu

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Publication Date
Thu Sep 13 2018
Journal Name
Baghdad Science Journal
Synthesis and Fabrication of In2O3: CdO Nanoparticles for NO2 Gas Sensor
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The physical and morphological characteristics of porous silicon (PS) synthesized via gas sensor was assessed by electrochemical etching for a Si wafer in diluted HF acid in water (1:4) at different etching times and different currents. The morphology for PS wafers by AFM show that the average pore diameter varies from 48.63 to 72.54 nm with increasing etching time from 5 to 15min and from 72.54 to 51.37nm with increasing current from 10 to 30 mA. From the study, it was found that the gas sensitivity of In2O3: CdO semiconductor, against NO2 gas, directly correlated to the nanoparticles size, and its sensitivity increases with increasing operating temperature.

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Publication Date
Mon Feb 01 2021
Journal Name
Materials Science Forum
The Feasibility of Using Micro Silica Sand Powder as Partial Replacement of Cement in Production of Roller Compacted Concrete
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Roller compacted concrete (RCC) is a special type of concrete with zero or even negative slump consistency. In this work, it had aimed to produce an RCC mix suitable for roads paving with minimum cost and better engineering properties so, different RCC mixes had prepared i.e. (M1, M2, M3, and M4) using specified percentages of micro natural silica sand powder (SSP) as partial replacement of (0%, 5%, 10%, and 20%) by weight of sulfate resistant Portland cement. Additionally, M-sand, crushed stone, filler, and water had been used. The results had obtained after 28 days of water curing. The control mix (M1) had satisfied the required f ‘c with accepted results for the other tests. M2 mix with SSP of 5% had

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Publication Date
Sun Feb 02 2025
Journal Name
Engineering, Technology & Applied Science Research
A Numerical Study of Concrete Composite Circular Columns encased with GFRP I-Section using the Finite Element Method
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This paper presents ABAQUS simulations of fully encased composite columns, aiming to examine the behavior of a composite column system under different load conditions, namely concentric, eccentric with 25 mm eccentricity, and flexural loading. The numerical results are validated with the experimental results obtained for columns subjected to static loads. A new loading condition with a 50 mm eccentricity is simulated to obtain additional data points for constructing the interaction diagram of load-moment curves, in an attempt to investigate the load-moment behavior for a reference column with a steel I-section and a column with a GFRP I-section. The result comparison shows that the experimental data align closely with the simulation

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Publication Date
Fri Mar 18 2016
Journal Name
International Journal Of Basic And Applied Sciences
Analytic and numerical solution for duffing equations
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<p>Daftardar Gejji and Hossein Jafari have proposed a new iterative method for solving many of the linear and nonlinear equations namely (DJM). This method proved already the effectiveness in solved many of the ordinary differential equations, partial differential equations and integral equations. The main aim from this paper is to propose the Daftardar-Jafari method (DJM) to solve the Duffing equations and to find the exact solution and numerical solutions. The proposed (DJM) is very effective and reliable, and the solution is obtained in the series form with easily computed components. The software used for the calculations in this study was MATHEMATICA<sup>®</sup> 9.0.</p>

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
An Evolutionary Algorithm for Solving Academic Courses Timetable Scheduling Problem
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Scheduling Timetables for courses in the big departments in the universities is a very hard problem and is often be solved by many previous works although results are partially optimal. This work implements the principle of an evolutionary algorithm by using genetic theories to solve the timetabling problem to get a random and full optimal timetable with the ability to generate a multi-solution timetable for each stage in the collage. The major idea is to generate course timetables automatically while discovering the area of constraints to get an optimal and flexible schedule with no redundancy through the change of a viable course timetable. The main contribution in this work is indicated by increasing the flexibility of generating opti

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Publication Date
Mon Mar 07 2022
Journal Name
Journal Of Educational And Psychological Researches
Reflective Mercifulness and its Implications for Social Cohesion / field study in Baghdad Governorate
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Mercifulness is a trait of civilization, humanity, and a moral value in society, because it has an impact on social life and its role in spreading interdependence, joint liability, and solidarity among people. Mercifulness means spreading mercy, synergy, sympathy, and cooperation. Generally, a society that enjoys strong ties tends to have a kind of stability and development, as well as, is able to face the economic, political, and security crises. Conversely, a weak society leads to weak social cohesion and weak community infrastructure that is more vulnerable to social, economic, and political instability. Thus, this is the aim of the research that has used a social survey method applied to a sample of respondents who have reached (300)

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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
Social Medical Care for the Deformed Children: A Field Study in Baghdad City
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The Child is the first sedum for the human society performing, and we deal in our
research to explain the nature of the mutual relations in between the form and the medicine
social caring foundation. So the motherhood and the childhood nowadays become the most
dedicated in the researchers works, whom interesting in the social affairs, and that whom
work in the medicine field as scientists.
So the child is the future man and must be in wright body construction that need to great
care and interest to make him wright mind through capability of performing anything support
to him.
In our research we deal with the main factors in which lead to infect the child by the
creative malfunction, like the environmental and m

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Publication Date
Fri Nov 28 2025
Journal Name
Arabian Journal For Science And Engineering
Role of Artificial Intelligence in Enhancing Efficiency and Sustainability in Middle Eastern Oil and Gas: A Review
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This review examines how artificial intelligence (AI) including machine learning (ML), deep learning (DL), and the Internet of Things (IoT) is transforming operations across exploration, production, and refining in the Middle Eastern oil and gas sector. Using a systematic literature review approach, the study analyzes AI adoption in upstream, midstream, and downstream activities, with a focus on predictive maintenance, emission monitoring, and digital transformation. It identifies both opportunities and challenges in applying AI to achieve environmental and economic goals. Although adoption levels vary across the region, countries such as Saudi Arabia, the UAE, and Qatar are leading initiatives that align with global sustainability targets.

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