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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
Wed Mar 01 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
The use of ARIMA, ANN and SVR models in time series hybridization with practical application
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Forecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
The use of ARIMA, LSTM and GRU models in time series hybridization with practical application
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The importance of forecasting has emerged in the economic field in order to achieve economic growth, as forecasting is one of the important topics in the analysis of time series, and accurate forecasting of time series is one of the most important challenges in which we seek to make the best decision. The aim of the research is to suggest the use of hybrid models for forecasting the daily crude oil prices as the hybrid model consists of integrating the linear component, which represents Box Jenkins models and the non-linear component, which represents one of the methods of artificial intelligence, which is long short term memory (LSTM) and the gated recurrent unit (GRU) which represents deep learning models. It was found that the proposed h

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Publication Date
Sat Jan 10 2015
Journal Name
British Journal Of Applied Science &amp; Technology
The Use of Cubic Bezier Interpolation, Biorthogonal Wavelet and Quadtree Coding to Compress Color Images
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In this paper, an efficient method for compressing color image is presented. It allows progressive transmission and zooming of the image without need to extra storage. The proposed method is going to be accomplished using cubic Bezier surface (CBI) representation on wide area of images in order to prune the image component that shows large scale variation. Then, the produced cubic Bezier surface is subtracted from the image signal to get the residue component. Then, bi-orthogonal wavelet transform is applied to decompose the residue component. Both scalar quantization and quad tree coding steps are applied on the produced wavelet sub bands. Finally, adaptive shift coding is applied to handle the remaining statistical redundancy and attain e

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Publication Date
Sun Jun 30 2024
Journal Name
Wasit Journal For Pure Sciences
Design Polynomial IIR Digital Filters of the Integer Parameters Space Use to Compress Image Data
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Polynomial IIR digital filters play a crucial role in the process of image data compression. The main purpose of designing polynomial IIR digital filters of the integer parameters space and introduce efficient filters to compress image data using a singular value decomposition algorithm. The proposed work is designed to break down the complex topic into bite-sized pieces of image data compression through the lens of compression image data using Infinite Impulse Response Filters. The frequency response of the filters is measured using a real signal with an automated panoramic measuring system developed in the virtual instrument environment. The analysis of the output signal showed that there are no limit cycles with a maximum radius

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Crossref
Publication Date
Wed Sep 30 2015
Journal Name
College Of Islamic Sciences
The impact of the organization of markets, old and new in the holy city of Karbala
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Any city that has such a market and is organized, organized and established

Mini
And respect
Freedom of expression
Profile.
Conflict resolution and conflict resolution

Political
Which affected the growth of some markets
And religious th
The search for the return of economic and cultural activity and the emigration of some others
Cultural exchange and trade, which in turn
Al-Rifaie
We took the problem that we are experiencing
Menia, the holy city of Karbala in the market organization, has suffered from fierce attacks
Economic and heritage
e
As well as tourism and tourism, as it depends on the abundance of visitors, tourists and residents in terms of needs and motivation
Resource

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Revolution In Science And Humanity
Nonparametric Estimation of Failure Periods for Log Normal Distribution Using Bootstra
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A non-parametric kernel method with Bootstrap technology was used to estimate the confidence intervals of the system failure function of the log-normal distribution trace data. These are the times of failure of the machines of the spinning department of the weaving company in Wasit Governorate. Estimating the failure function in a parametric way represented by the method of the maximum likelihood estimator (MLE). The comparison between the parametric and non-parametric methods was done by using the average of Squares Error (MES) criterion. It has been noted the efficiency of the nonparametric methods based on Bootstrap compared to the parametric method. It was also noted that the curve estimation is more realistic and appropriate for the re

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Publication Date
Sun Mar 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Simulation of five methods for parameter estimation and functionExponential distribution reliability
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The estimation process is one of the pillars of the statistical inference process as well as the hypothesis test, and the assessment is based on the collection of information and conclusions about the teacher or the community's teachers on the basis of the result
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Publication Date
Thu Jan 16 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Comparison of some reliability estimation methods for Laplace distribution using simulations
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In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes

Publication Date
Sat Jul 01 2017
Journal Name
Al–bahith Al–a'alami
The Use of Digital Public – Relations in the Work of Iraqi Universities: A Survey Study of the Workers in the Departments of Public Relations
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the digital public relations aim at make the workers getting the necessary information about the governmental institutions where they work and the enveronment surrounding them. it also tries to let the workers get the special knowlege of tthe publich relations and their jobs like the works of planning , arranging the active communication and executive skills needed in their writing , editing , special art skills for designing , production and technological skills to deal with the computer.
the problem of the research includes some questions as :
1- what are the uses achieved by degetal public relations workers at Iraqi universities (Baghdad, Mustansiriya, and Iraqi)
2- what are the tools used to apply digital public relations

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Crossref (2)
Crossref
Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating the Survival Function and Failure Rate for the Exponentiated Expanded Power Function Distribution
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     We have presented the distribution of the exponentiated expanded power function (EEPF) with four parameters, where this distribution was created by the exponentiated expanded method created by the scientist Gupta to expand the exponential distribution by adding a new shape parameter to the cumulative function of the distribution, resulting in a new distribution, and this method is characterized by obtaining a distribution that belongs for the exponential family. We also obtained a function of survival rate and failure rate for this distribution, where some mathematical properties were derived, then we used the method of maximum likelihood (ML) and method least squares developed  (LSD)

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