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Artificial Neural Network Application to Permeability Prediction from Nuclear Magnetic Resonance Log
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Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is used to train the model, where the model prediction result is validated with core permeability. Seven oil well logs were used as input parameters, and the model was constructed with Techlog software. The predicted permeability with the model compared with Schlumberger-Doll-Research permeability as a cross plot, which results in the correlation coefficient of 94%, while the predicted permeability validated with the core permeability of the well, which obtains good agreement where R2 equals 80%. The model was utilized to forecast permeability in a well that did not have a nuclear magnetic resonance log, and the predicted permeability was cross-plotted against core permeability as a validation step, with a correlation coefficient of 77%. As a result, the low percentage of matching was due to data limitations, which demonstrated that as the amount of data used to train the model increased, so did the precision.

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Publication Date
Sun Jan 01 2023
Journal Name
Second International Conference On Innovations In Software Architecture And Computational Systems (isacs 2022)
Permeability estimation of Yamama formation in a Southern Iraqi oil field, case study
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Permeability is one of the essential petrophysical properties of rocks, reflecting the rock's ability to pass fluids. It is considered the basis for building any model to predict well deliverability. Yamama formation carbonate rocks are distinguished by sedimentary cycles that separate formation into reservoir units and insulating layers, a very complex porous system caused by secondary porosity due to substitute and dissolution processes. Those factors create permeability variables and vary significantly. Three ways used for permeability calculation, the firstly was the classical method, which only related the permeability to the porosity, resulting in a weak relationship. Secondly, the flow zone indicator (FZI) was divided reservoir into

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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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Publication Date
Wed Oct 04 2023
Journal Name
Environmental Progress & Sustainable Energy
Removal of <scp>E133</scp> brilliant blue dye from artificial wastewater by electrocoagulation using cans waste as electrodes
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Abstract<p>Solid‐waste management, particularly of aluminum (Al), is a challenge that is being confronted around the world. Therefore, it is valuable to explore methods that can minimize the exploitation of natural assets, such as recycling. In this study, using hazardous Al waste as the main electrodes in the electrocoagulation (EC) process for dye removal from wastewater was discussed. The EC process is considered to be one of the most efficient, promising, and cost‐effective ways of handling various toxic effluents. The effect of current density (10, 20, and 30 mA/cm<sup>2</sup>), electrolyte concentration (1 and 2 g/L), and initial concentration of Brilliant Blue dye (15 and 30 mg/L) on </p> ... Show More
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Publication Date
Sun Sep 03 2017
Journal Name
Baghdad Science Journal
Study the effect of stable magnetic field on the inhibition activity of Saccharomyces boulardii against pathogenic bacteria isolated from urinary tract infection
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An increasing trend to use probiotic and study their effects on the pathogens has been conductor where they are defined as live micro-organisms that give a health benefit to the host when ingested in sufficient quantities, including the yeast Saccharomyces boulardii In addition research show that a magnetic field (MF) has a biological effect. This study aims to investigate the effects of magnetic field on the inhibitory action of Saccharomyces boulardii against bacteria isolated from urinary tract infection, Study the sensitivity of bacterial isolates to antibiotics after diagnosis by microscopic, Cultural and biochemical examinations as well as Api20 E examinations were used gram negative bacteria , Most isolates were resistant to an

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Publication Date
Wed Jul 01 2015
Journal Name
Political Sciences Journal
Israeli vision of Iran's nuclear program Under Iranian - US rapprochement
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Israel is one of the countries most interested in Iran's nuclear program file, and the progress of negotiations between Iran and the six countries and will end it, as well as the nature of the relationship between Iran and the United States of America. Is determined by the Israeli vision of the nature of Iran's nuclear program Iran's policy toward Israel orientations, which does not recognize the existence of Israel. Israel, therefore, one of the countries pushing to prevent Iran from acquiring nuclear technology. However, those Israeli efforts did not succeed in achieving its objectives, the United States of America and European countries is well aware of the risk of stenosis on Iran, as well as the risks and the consequences of militar

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Publication Date
Wed Dec 01 2010
Journal Name
Iraqi Journal Of Physics
Partial Level Densities for Neutron Induced Pre-equilibrium Nuclear Reactions
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The state and partial level densities were calculated using the corresponding formulas that are obtained in the frame work of the exciton model with equidistant spacing model (ESM) and non-ESM (NESM). Different corrections have been considered, which are obtained from other nuclear principles or models. These corrections are Pauli Exclusion Principle, surface effect, pairing effect, back shift due to shell effect and bound state effect . They are combined together in a composite formula with the intention to reach the final formula. One-component system at energies less than 100 MeV and mass number range (50-200) is assumed in the present work. It was found that Williams, plus spin formula is the most effective approach to the composite

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Publication Date
Wed Feb 20 2019
Journal Name
Iraqi Journal Of Physics
Assessment of nuclear radiation pollution in uranium mining-impacted soil
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Activities associated with mining of uranium have generated significant quantities of waste materials containing uranium and other toxic metals. A qualitative and quantitative study was performed to assess the situation of nuclear pollution resulting from waste of drilling and exploration left on the surface layer of soil surrounding the abandoned uranium mine hole located in the southern of Najaf province in Iraq state. To measure the specific activity, twenty five surface soil samples were collected, prepared and analyzed by using gamma- ray spectrometer based on high counting efficiency NaI(Tl) scintillation detector. The results showed that the specific activities in Bq/kg are 37.31 to 1112.47 with mean of 268.16, 0.28 to 18.57 with

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Publication Date
Sun Jun 05 2011
Journal Name
Baghdad Science Journal
Magnetic Deflection Coefficient Investigation for Low Energy Particles
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In this research we solved numerically Boltzmann transport equation in order to calculate the transport parameters, such as, drift velocity, W, D/? (ratio of diffusion coefficient to the mobility) and momentum transfer collision frequency ?m, for purpose of determination of magnetic drift velocity WM and magnetic deflection coefficient ? for low energy electrons, that moves in the electric field E, crossed with magnetic field B, i.e; E×B, in the nitrogen, Argon, Helium and it's gases mixtures as a function of: E/N (ratio of electric field strength to the number density of gas), E/P300 (ratio of electric field strength to the gas pressure) and D/? which covered a different ranges for E/P300 at temperatures 300°k (Kelvin). The results show

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Publication Date
Sun Dec 21 2025
Journal Name
Journal Of Administration And Economics
Bayesian Method in Classification Regression Tree to estimate nonparametric additive model compared with Logistic Model with Application
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The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode

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Publication Date
Tue Jul 01 2025
Journal Name
Iet Conference Proceedings
Spatial quantile autoregressive model with application to poverty rates in the districts of Iraq
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This research aims to provide insight into the Spatial Autoregressive Quantile Regression model (SARQR), which is more general than the Spatial Autoregressive model (SAR) and Quantile Regression model (QR) by integrating aspects of both. Since Bayesian approaches may produce reliable estimates of parameter and overcome the problems that standard estimating techniques, hence, in this model (SARQR), they were used to estimate the parameters. Bayesian inference was carried out using Markov Chain Monte Carlo (MCMC) techniques. Several criteria were used in comparison, such as root mean squared error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R^2). The application was devoted on dataset of poverty rates acro

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