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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
Lecture Notes In Networks And Systems
Using Artificial Intelligence and Metaverse Techniques to Reduce Earning Management
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This study aims to demonstrate the role of artificial intelligence and metaverse techniques, mainly logistical Regression, in reducing earnings management in Iraqi private banks. Synthetic intelligence approaches have shown the capability to detect irregularities in financial statements and mitigate the practice of earnings management. In contrast, many privately owned banks in Iraq historically relied on manual processes involving pen and paper for recording and posting financial information in their accounting records. However, the banking sector in Iraq has undergone technological advancements, leading to the Automation of most banking operations. Conventional audit techniques have become outdated due to factors such as the accuracy of d

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Publication Date
Mon Jan 01 2024
Journal Name
International Journal Of Mathematics And Computer Science
Artificial Intelligence Techniques to Identify Individuals through Palm Image Recognition
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Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

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Publication Date
Fri Aug 16 2024
Journal Name
International Journal Of Mathematics And Computer Science
Artificial Intelligence Techniques to Identify Individuals through Palm Image Recognition
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Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

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Publication Date
Thu Mar 01 2018
Journal Name
Journal Of Engineering
Permeability Estimation by Using the Modified and Conventional FZI Methods
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There many methods for estimation of permeability. In this Paper, permeability has been estimated by two methods. The conventional and modified methods are used to calculate flow zone indicator (FZI). The hydraulic flow unit (HU) was identified by FZI technique. This technique is effective in predicting the permeability in un-cored intervals/wells. HU is related with FZI and rock quality index (RQI). All available cores from 7 wells (Su -4, Su -5, Su -7, Su -8, Su -9, Su -12, and Su -14) were used to be database for HU classification. The plot of probability cumulative of FZI is used. The plot of core-derived probability FZI for both modified and conventional method which indicates 4 Hu (A, B, C and D) for Nahr Umr forma

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Publication Date
Thu Jan 01 2009
Journal Name
Iraqi Journal Of Physics
Resonance Tunneling Through GaN/AlGaN Superlattice System
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The purpose of our work is to report a theoretical study of electrons tunneling through semiconductor superlattice (SSL). The (SSL) that we have considered is (GaN/AlGaN) system within the energy range of ε < Vo, ε = Vo and ε > Vo, where Vo is the potential barrier height. The transmission coefficient (TN) was determined using the transfer matrix method. The resonant energies are obtained from the T (E) relation. From such system, we obtained two allowed quasi-levels energy bands for ε < VO and one band for ε  VO.

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Publication Date
Wed Dec 30 2009
Journal Name
Iraqi Journal Of Physics
Resonance Tunneling Through GaN/AlGaN Superlattice System
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The purpose of our work is to report a theoretical study of electrons tunneling through semiconductor superlattice (SSL). The (SSL) that we have considered is (GaN/AlGaN) system within the energy range of ε < Vo, ε = Vo and ε > Vo, where Vo is the potential barrier height. The transmission coefficient (TN) was determined using the transfer matrix method. The resonant energies are obtained from the T (E) relation. From such system, we obtained two allowed quasi-levels energy bands for ε < VO and one band for ε  VO.

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Publication Date
Mon May 29 2017
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
APPLICATION OF TQM REQUIREMENTS AND THEIR RELATIONSHIP TO ORGANIZATIONAL PERFORMANCE FROM THE POINT OF VIEW OF THE INTERNAL CUSTOMER/ COMPARATIVE STUDY.: APPLICATION OF TQM REQUIREMENTS AND THEIR RELATIONSHIP TO ORGANIZATIONAL PERFORMANCE FROM THE POINT OF VIEW OF THE INTERNAL CUSTOMER/ COMPARATIVE STUDY.
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This study aims to Statement of the relationship between Total Quality Management philosophy and Organizational performance from the point of view of the internal customer. A comparison has been made between two companies, one of which applies the requirements of TQM well and the other does not apply these requirements as the (General Company for Electrical Industries/ Diyala) and (General Company for Electrical Industries/ Baghdad) to conduct the search, During the questionnaire prepared for this purpose and distributed to a sample of 30 employees in the General Company for Electric Industries/ Diyala and (20) employees of the General Company for Electrical Industries/ Baghdad. Their answers were analyzed using a simple correlation coef

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi Geological Journal
Integrated Core and Log Data to Determine the Reservoir Flow Unit and Rock Facies for Mishrif Formation in South Eastern Iraq
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This work represents study the rock facies and flow unit classification for the Mishrif carbonate reservoir in Buzurgan oil Field, which located n the south eastern Iraq, using wire line logs, core samples and petrophysical data (log porosity and core permeability). Hydraulic flow units were identified using flow zone indicator approach and assessed within each rock type to reach better understanding of the controlling role of pore types and geometry in reservoir quality variations. Additionally, distribution of sedimentary facies and Rock Fabric Number along with porosity and permeability was analyzed in three wells (BU-1, BU-2, and BU-3). The interactive Petrophysics - IP software is used to assess the rock fabric number, flow zon

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Publication Date
Tue Jul 01 2008
Journal Name
Arabian Journal Of Geosciences
Sub-surface geometry of Ar Rika and Ruwah faults from gravity and magnetic surveys
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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Discrete Mathematical Sciences And Cryptography
Minimum spanning tree application in Covid-19 network structure analysis in the countries of the Middle East
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Coronavirus disease (Covid-19) has threatened human life, so it has become necessary to study this disease from many aspects. This study aims to identify the nature of the effect of interdependence between these countries and the impact of each other on each other by designating these countries as heads for the proposed graph and measuring the distance between them using the ultrametric spanning tree. In this paper, a network of countries in the Middle East is described using the tools of graph theory.

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