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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
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Human Pose Estimation Algorithm Using Optimized Symmetric Spatial Transformation Network
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Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

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Publication Date
Mon May 01 2017
Journal Name
Australian Journal Of Basic And Applied Sciences
Sprite Region Allocation Using Fast Static Sprite Area Detection Algorithm
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Background: Sprite coding is a very effective technique for clarifying the background video object. The sprite generation is an open issue because of the foreground objects which prevent the precision of camera motion estimation and blurs the created sprite. Objective: In this paper, a quick and basic static method for sprite area detection in video data is presented. Two statistical methods are applied; the mean and standard deviation of every pixel (over all group of video frame) to determine whether the pixel is a piece of the selected static sprite range or not. A binary map array is built for demonstrating the allocated sprite (as 1) while the non-sprite (as 0) pixels valued. Likewise, holes and gaps filling strategy was utilized to re

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Publication Date
Thu May 05 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Classification SINGLE-LEAD ECG by using conventional neural network algorithm
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Publication Date
Sun Jan 01 2023
Journal Name
Desalination And Water Treatment
Optimization of chemical oxygen demand removal from petroleum refinery wastewater by electrocoagulation using tubular electrochemical reactor with a novel design
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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Artificial Neural Network (ANN) for Prediction of Viscosity Reduction of Heavy Crude Oil using Different Organic Solvents
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The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio

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Publication Date
Mon Jan 01 2024
Journal Name
Results In Nonlinear Analysis
Numerical solutions for the time fractional Black-Scholes model governing European option by using double integral transform decomposition method
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Publication Date
Sun Dec 03 2017
Journal Name
Baghdad Science Journal
Measurement of Indoor Radon Gas Concentration in same Region of Baghdad Governorate Using CR-39 Nuclear Track Detector
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In this research the activity of radon gas in air in Baghad governorate,Iraq, using “alpha-emitters track registration (CR-39) track detector were measured. This measurement was done for selected areas from Baghdad Governorate, The results obtained shows that the highest average concentrations for Rn-222 is (179.077 Bq/m^3) which was recorded within Al-Shaaib city and less average concentrations was (15.79 Bq/m^3) in the nearby residential area of Baghdad International Airport and the overall average concentrations is (86.508 Bq/m^3) for these regions. Then the radon concentration was measured annual effective dose calculated from radon concentration and found in range from 0.4031 mSv/y to 4.5179 mSv /y with an average value of 2.1824 m

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Publication Date
Sun Jun 30 2019
Journal Name
Journal Of Engineering
Numerical Study of Fluid Flow and Heat Transfer Characteristics in Solid and Perforated Finned Heat Sinks Utilizing a Piezoelectric Fan
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Numerical study is adapted to combine between piezoelectric fan as a turbulent air flow generator and perforated finned heat sinks. A single piezoelectric fan with different tip amplitudes placed eccentrically at the duct entrance. The problem of solid and perforated finned heat sinks is solved and analyzed numerically by using Ansys 17.2 fluent, and solving three dimensional energy and Navier–Stokes equations that set with RNG based k−ε scalable wall function turbulent model. Finite volume algorithm is used to solve both phases of solid and fluid. Calculations are done for three values of piezoelectric fan amplitudes 25 mm, 30 mm, and 40 mm, respectively. Results of this numerical study are compared with previous b

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Publication Date
Sat Dec 24 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
A Comparative Study for the Accuracy of Three Molecular Docking Programs Using HIV-1 Protease Inhibitors as a Model
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Flexible molecular docking is a computational method of structure-based drug design to evaluate binding interactions between receptor and ligand and identify the ligand conformation within the receptor pocket. Currently, various molecular docking programs are extensively applied; therefore, realizing accuracy and performance of the various docking programs could have a significant value. In this comparative study, the performance and accuracy of three widely used non-commercial docking software (AutoDock Vina, 1-Click Docking, and UCSF DOCK) was evaluated through investigations of the predicted binding affinity and binding conformation of the same set of small molecules (HIV-1 protease inhibitors) and a protein target HIV-1 protease enzy

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Runge-kutta Numerical Method for Solving Nonlinear Influenza Model
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Abstract<p>The main object of this study is to solve a system of nonlinear ordinary differential equations (ODE) of the first order governing the epidemic model using numerical methods. The application under study is a mathematical epidemic model which is the influenza model at Australia in 1919. Runge-kutta methods of order 4 and of order 45 for solving this initial value problem(IVP) problem have been used. Finally, the results obtained have been discussed tabularly and graphically.</p>
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