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Distribution of New Horizontal Wells by the Use of Artificial Neural Network Algorithm
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Abstract<p>It is an established fact that substantial amounts of oil usually remain in a reservoir after primary and secondary processes. Therefore; there is an ongoing effort to sweep that remaining oil. Field optimization includes many techniques. Horizontal wells are one of the most motivating factors for field optimization. The selection of new horizontal wells must be accompanied with the right selection of the well locations. However, modeling horizontal well locations by a trial and error method is a time consuming method. Therefore; a method of Artificial Neural Network (ANN) has been employed which helps to predict the optimum performance via proposed new wells locations by incorporating reservoir properties and production data of previous wells.</p><p>This study used the Artificial Neural Network (ANN) that has been programmed in a manner to predict the cumulative oil produced for a certain grid by providing the corresponding properties of the grid. The network has been validated with real data collected from a number of drilled hypothetical wells. Furthermore; the validated network used to simulate the field parts that have not been drilled yet, to predict the corresponding cumulative oil for each grid. Field-scale simulation has been carried out and new horizontal wells have been allocated using the validated prepared data by the Artificial Neural Network Algorithm and an approved Iraqi reservoir model. Finally, different optimization scenarios have been investigated on the overall field recovery performance.</p>
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Publication Date
Sun Jun 06 2010
Journal Name
Baghdad Science Journal
New Method for the Determination of DL-Histidine by FIA and Chemiluminometric Detection
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This paper present a simple and sensitive method for the determination of DL-Histidine using FIA-Chemiluminometric measurement resulted from oxidation of luminol molecule by hydrogen peroxide in alkaline medium in the presence of DL-Histidine. Using 70?l. sample linear plot with a coefficient of determination 95.79% for (5-60) mmol.L-1 while for a quadratic relation C.O.D = 96.44% for (5-80) mmol.L-1 and found that guadratic plot in more representative. Limit of detection was 31.93 ?g DL-Histidine (S/N = 3), repeatability of measurement was less that 5% (n=6). Positive and negative ion interferances was removed by using minicolume containing ion exchange resin located after injection valve position.

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
The Effect of Magnetic Field with Nanofluid on Heat Transfer in a Horizontal Pipe
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This work presents an experimental study of heat transfer and flow of distilled water and metal oxide nanofluid Fe3O4-distilled water at concentrations of (φ = 0.3, 0.6, 0.9 %) by volume in a horizontal pipe with constant magnetic field. All the tests are carried out with Reynolds number range (2900-9820) and uniform heat flux (11262-19562 W/m2). The results show that, the nanofluid concentration and magnetic intensity increase, the Nusselt number increases. The maximum enhancement in Nusselt number with magnetic nanofluid is (5.4 %, 26.4 %, 42.7 %) for volume concentration (0.3, 0.6, 0.9 %) respectively. The enhancement is maximized with magnetic intensity (0.1, 0.2, 0.3 tesla) respectively to (43.9, 44

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Publication Date
Mon Aug 05 2019
Journal Name
Gen. Lett. Math
Building a three-dimensional maritime transport model to find the best solution by using the heuristic algorithm
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The aim of this research is to construct a three-dimensional maritime transport model to transport nonhomogeneous goods (k) and different transport modes (v) from their sources (i) to their destinations (j), while limiting the optimum quantities v ijk x to be transported at the lowest possible cost v ijk c and time v ijk t using the heuristic algorithm, Transport problems have been widely studied in computer science and process research and are one of the main problems of transport problems that are usually used to reduce the cost or times of transport of goods with a number of sources and a number of destinations and by means of transport to meet the conditions of supply and demand. Transport models are a key tool in logistics an

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Publication Date
Thu Apr 01 2021
Journal Name
Complexity
Bayesian Regularized Neural Network Model Development for Predicting Daily Rainfall from Sea Level Pressure Data: Investigation on Solving Complex Hydrology Problem
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Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

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Publication Date
Wed May 31 2023
Journal Name
Iraqi Geological Journal
Studying the Effect of Permeability Prediction on Reservoir History Matching by Using Artificial Intelligence and Flow Zone Indicator Methods
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The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Sun Jan 01 2023
Journal Name
Ssrn Electronic Journal
Increasing Safety in Highways Transit Systems by Using Ethical Artificial Intelligence AI
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“Smart city” projects have become fully developed and are actively using video analytics. Our study looks at how video analytics from surveillance cameras can help manage urban areas, making the environment safer and residents happier. Every year hundreds of people fall on subway and railway lines. The causes of these accidents include crowding, fights, sudden health problems such as dizziness or heart attacks, as well as those who intentionally jump in front of trains. These accidents may not cause deaths, but they cause delays for tens of thousands of passengers. Sometimes passers-by have time to react to the event and try to prevent it, or contact station personnel, but computers can react faster in such situations by using ethical

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Publication Date
Tue Jun 01 2021
Journal Name
Journal Of Physics And Chemistry Of Solids
Sensitization of TiO2 nanotube arrays photoelectrode via homogeneous distribution of CdSe nanoparticles by electrodeposition techniques
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Engineering
Performance enhancement of Echo Cancellation Using a Combination of Partial Update ( PU) Methods and New Variable Length LMS (NVLLMS) Algorithm
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In this paper, several combination algorithms between Partial Update LMS (PU LMS) methods and previously proposed algorithm (New Variable Length LMS (NVLLMS)) have been developed. Then, the new sets of proposed algorithms were applied to an Acoustic Echo Cancellation system (AEC) in order to decrease the filter coefficients, decrease the convergence time, and enhance its performance in terms of Mean Square Error (MSE) and Echo Return Loss Enhancement (ERLE). These proposed algorithms will use the Echo Return Loss Enhancement (ERLE) to control the operation of filter's coefficient length variation. In addition, the time-varying step size is used.The total number of coefficients required was reduced by about 18% , 10% , 6%

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Publication Date
Mon Oct 05 2015
Journal Name
Diyala Journal For Pure Science
Determination of zinc ions in drinking water distribution systems (PVC pipes) by spectrophotometric method
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In this work, a method for the simultaneous spectrophotometric determination of zinc which was precipitated into deionized water that is in a commercial distribution systems PVC pipe, is proposed using UV-VIS Spectrophotometer. The method based on the reaction between the analytes Zn2+ and 2-carboxy-2-hyroxy-5-sulfoformazylbenze (Zincon) at an absorption maximum of 620nm at pH 9-10. This ligand is selective reagent. Since the complex is colored (blue), its stoichiometry can be established using visible spectrometry to measure the absorbance of solutions of known composition. The stoichiometry of the complex was determined by Job’s method and molar ratio method and found to be 1:2 (M: L). A series of synthetic solution containing different

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