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9BYSGIcBVTCNdQwC2TXQ
Development of Artificial Neural Networks and Multiple Regression Analysis for Estimating of Formation Permeability
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Publication Date
Mon Dec 30 2024
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Formation evaluation for Mauddud Formation in Bai Hassan oilfield, Northern Iraq
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   Formation evaluation is a critical process in the petroleum industry that involves assessing the petrophysical properties and hydrocarbon potential of subsurface rock formations. This study focuses on evaluating the Mauddad Formation in the Bai Hassan oil field by analyzing data obtained from well logs and core samples. Four wells were specifically chosen for this study (BH-102, BH-16, BH-86, and BH-93). The main objectives of this study were to identify the lithology of the Mauddud Formation and estimate key petrophysical properties such as shale volume, porosity, water saturation, and permeability. The Mauddud Formation primarily consists of limestone and dolomite, with some anhydrites present. It is classified as a clean for

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Publication Date
Tue Dec 12 2017
Journal Name
Al-khwarizmi Engineering Journal
Model Reference Adaptive Control based on a Self-Recurrent Wavelet Neural Network Utilizing Micro Artificial Immune Systems
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Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Educational And Psychological Researches
The content of intermediate stage biology books for multiple intelligences
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The aim of current study is to analyze the content of intermediate stage biology books based on multiple intelligences. To do this, the researcher used the descriptive analytical approach. To analyze the three books of the intermediate stage, the author adopted content analysis tool and area unit. They were exposed to group of experts in methods of teaching biology, and measurement and evaluation. The findings of the study have shown a significant difference between what was expected and the observation of the multiple intelligences for the three biology books excluded the (social, musical, and kinetic intelligence), and there is no significant difference between the analysis' result of the biology books and the expectations of b

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Publication Date
Sat Oct 02 2021
Journal Name
International Journal Of Nonlinear Analysis And Applications
Using the wavelet analysis to estimate the nonparametric regression model in the presence of associated errors
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Abstract The wavelet shrink estimator is an attractive technique when estimating the nonparametric regression functions, but it is very sensitive in the case of a correlation in errors. In this research, a polynomial model of low degree was used for the purpose of addressing the boundary problem in the wavelet reduction in addition to using flexible threshold values in the case of Correlation in errors as it deals with those transactions at each level separately, unlike the comprehensive threshold values that deal with all levels simultaneously, as (Visushrink) methods, (False Discovery Rate) method, (Improvement Thresholding) and (Sureshrink method), as the study was conducted on real monthly data represented in the rates of theft crimes f

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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
Sat Sep 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
A comparison Of Some Semiparametric Estimators For consumption function Regression
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    This article aims to explore the importance of estimating the a semiparametric regression function ,where we suggest a new estimator beside the other combined estimators and then we make a comparison among them by using simulation technique . Through the simulation results we find  that the suggest estimator is the best with the first and second models ,wherealse for the third model we find Burman and Chaudhuri (B&C) is best.

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Publication Date
Sun Aug 25 2019
Journal Name
Journal Of University Of Babylon For Engineering Sciences
Observation of Consolidation and Permeability Parameters of Soil Stabilized By Cutback Asphalt
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For design purposes, it`s necessary to know the compression rate of soil layers which might be happened when it`s subjected to effective stresses. Also, it`s essential to know the rate of flow through soil mass specially for the design of marine structures or earth embankment. These two important behavior could be predicted from the coefficient of consolidation (Cv) and the coefficient of permeability (k). This study shows the effect of cutback asphalt stabilization on Cv and k and other compressibility factors, the investigation was done for silty clay samples, specimens were prepared by mixing the soil with different percentage of asphalt from (0-10)% and subjected to one-dimensional consolidation test of 50mm diameter and 20mm height wer

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Publication Date
Tue Jul 01 2008
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
THE STUDY OF MINERALOGICAL AND MICROFACIES ANALYSIS SHIRANISH FORMATION WELL (KH-6) ANSAB AREA IN SOUTHERN IRAQ
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The study of Shiranish Formation rocks in southern part of Iraq at Ansab area well (KH-6)
were carried out. The formation is tongued with tayarat formation, which bounded from top
and bottom, the upper tongue at thickness 49m. and tongued at depth (476-525m.) the lower
tongue at thickness 4m. tongued at (541-537m.).
The rocks of this formation were divided into three sedimentary microfacies:
1- Dolomitized formininferal Wackestone facies.
2- Dolomitized formininferal Mudstone facies.
3- Dolostone facies.
34 slides were investigated depending on mineralogical, compositional and biological
processes and compared diagenesis which reflect open marine shelf at lower part of formation
(F.Z.2) (S.M.F.8), but at the

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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Permeability Prediction for Nahr-Umr Reservoir / Subba field by Using FZI Method
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 The permeability determination in the reservoirs that are anisotropic and heterogeneous is a complicated problem due to the limited number of wells that contain core samples and well test data. This paper presents hydraulic flow units and flow zone indicator for predicting permeability of rock mass from core for Nahr-Umr reservoir/ Subba field. The Permeability measurement is better found in the laboratory work on the cored rock that taken from the formation. Nahr-Umr Formation is the main lower cretaceous sandstone reservoir in southern of Iraq. This formation is made up mainly of sandstone. Nahr-Umr formation was deposited on a gradually rising basin floor. The digenesis of Nahr-Umr sediments is very important du

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of classical method and optimization methods for estimating parameters in nonlinear ordinary differential equation
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  This study is concerned with the estimation of constant  and time-varying parameters in non-linear ordinary differential equations, which do not have analytical solutions. The estimation is done in a multi-stage method where constant and time-varying parameters are estimated in a straight sequential way from several stages. In the first stage, the model of the differential equations is converted to a regression model that includes the state variables with their derivatives and then the estimation of the state variables and their derivatives in a penalized splines method and compensating the estimations in the regression model. In the second stage, the pseudo- least squares method was used to es

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