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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
Thu Dec 01 2022
Journal Name
Iop Conference Series: Earth And Environmental Science
Study of water productivity of wheat and moisture distribution under the influence of center pivot irrigation and different tillage systems for desert soils
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A field experiment was conducted to grow the wheat crop during the fall season 2020 in Karbala province, north of Ain Al-Tamr District in two locations of different textures and parent materials. The first site (calcareous soil) with a sandy loam texture, is located at (44° 40′ 37′) east longitude and (32° 41′ 34′) north latitude, at an altitude of 32 m above sea level, and an area of 20 hectares. As for the second location (gypsum soil) with a loam texture, it is located at a longitude (45° 41′ 39′) east and a latitude (33° 43′ 34′ north) and at an altitude of 33 m above sea level and an area of 20 hectares. To find out the effect of different tillage systems on water productivity and wheat yield under center pivot irri

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Publication Date
Tue Dec 23 2025
Journal Name
Journal Of Studies And Researches Of Sport Education
The effectiveness of the use of yoga exercises and its impact on the reactions of the two Alvesologih nervous and respiratory systems in the correction of antenna pistol shooting accuracy
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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Al-mansoor College
An Improvement to Face Detection Algorithm for Non-Frontal Faces
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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Online Sumarians Cuneiform Detection Based on Symbol Structural Vector Algorithm
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The cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
A Novel Gravity ‎Optimization Algorithm for Extractive Arabic Text Summarization
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An automatic text summarization system mimics how humans summarize by picking the most ‎significant sentences in a source text. However, the complexities of the Arabic language have become ‎challenging to obtain information quickly and effectively. The main disadvantage of the ‎traditional approaches is that they are strictly constrained (especially for the Arabic language) by the ‎accuracy of sentence feature ‎functions, weighting schemes, ‎and similarity calculations. On the other hand, the meta-heuristic search approaches have a feature tha

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
A Parallel Adaptive Genetic Algorithm for Job Shop Scheduling Problem
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Publication Date
Sun Dec 01 2013
Journal Name
2013 Ieee International Rf And Microwave Conference (rfm)
Differential Evolution algorithm for linear frequency modulation radar signal denoising
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Signal denoising is directly related to sample estimation of received signals, either by estimating the equation parameters for the target reflections or the surrounding noise and clutter accompanying the data of interest. Radar signals recorded using analogue or digital devices are not immune to noise. Random or white noise with no coherency is mainly produced in the form of random electrons, and caused by heat, environment, and stray circuitry loses. These factors influence the output signal voltage, thus creating detectable noise. Differential Evolution (DE) is an effectual, competent, and robust optimisation method used to solve different problems in the engineering and scientific domains, such as in signal processing. This paper looks

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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Minimum Spanning Tree Algorithm for Skin Cancer Image Object Detection
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This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that

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Publication Date
Thu May 01 2008
Journal Name
2008 International Conference On Computer And Communication Engineering
A binary Particle Swarm Optimization for attacking knapsacks Cipher Algorithm
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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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