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Prediction of Well Logs Data and Estimation of Petrophysical Parameters of Mishrif Formation, Nasiriya Field, South of Iraq Using Artificial Neural Network (ANN)
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    Petrophysical properties including volume of shale, porosity and water saturation are significance parameters for petroleum companies in evaluating the reservoirs and determining the hydrocarbon zones. These can be achieved through conventional petrophysical calculations from the well logs data such as gamma ray, sonic, neutron, density and deep resistivity. The well logging operations of the targeted limestone Mishrif reservoirs in Ns-X Well, Nasiriya Oilfield, south of Iraq could not be done due to some problems related to the well condition. The gamma ray log was the only recorded log through the cased borehole. Therefore, evaluating the reservoirs and estimating the perforation zones has not performed and the drilled well was abandoned. This paper presents a solution to estimate the missing open-hole logs of Mishrif Formation including sonic, neutron, density and deep resistivity using supervised Artificial Neural Network (ANN) in Petrel software (2016.2). Furthermore, the original gamma-ray log along with the predicted logs data from ANN models were processed, and the petrophysical properties including volume of shale, effective porosity and water saturation were calculated to determine the hydrocarbon zones. The ANN Mishrif Formation models recorded coefficient of determination (R2) of 0.65, 0.77, 0.82, and 0.04 between the predicted and the tested logs data with total correlations of 0.67, 0.91, 0.84 and 0.57 for sonic, neutron, density, and resistivity logs respectively. The best possible hydrocarbon-bearing zone ranges from the depth of about 1980-2030 m in the mB1unit. The ANN provides a good accuracy and data matching in clean and non-heterogeneous formations compared to those with higher heterogeneity that contain more than one type of lithology. The Ns-X Well can, therefore, be linked to the development plans of the Nasiriya Field instead of neglect it.

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Publication Date
Fri Aug 13 2021
Journal Name
Neural Computing And Applications
Integration of extreme gradient boosting feature selection approach with machine learning models: application of weather relative humidity prediction
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An improved neurogenetic model for recognition of 3D kinetic data of human extracted from the Vicon Robot system
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These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that.  The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce

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Publication Date
Tue Dec 15 2020
Journal Name
Al-academy
Formal Formation and its Semantic Projections in the Design Interior Spaces of the Daily newspapers Buildings: آراء عبد الكريم حسين
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The research deals with the topic of (formal formation and its semantic projections in the design interior spaces of daily newspapers buildings) including the research problem summarized by the following question: (does the formal formation do a semantic role in the design of the interior spaces?). The research objective has been evident in discovering strong and weak points in the formal formations and their semantic projections in the design of the interior spaces for the daily newspapers buildings, reaching at the best design foundations, and shedding light on the cognitive and scientific importance of the research, and the objective, temporal and spatial limits in addition to identifying the terms. The theoretical framework includes

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Publication Date
Tue Nov 01 2016
Journal Name
Iosr Journal Of Computer Engineering
Implementation of new Secure Mechanism for Data Deduplication in Hybrid Cloud
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Cloud computing provides huge amount of area for storage of the data, but with an increase of number of users and size of their data, cloud storage environment faces earnest problem such as saving storage space, managing this large data, security and privacy of data. To save space in cloud storage one of the important methods is data deduplication, it is one of the compression technique that allows only one copy of the data to be saved and eliminate the extra copies. To offer security and privacy of the sensitive data while supporting the deduplication, In this work attacks that exploit the hybrid cloud deduplication have been identified, allowing an attacker to gain access to the files of other users based on very small hash signatures of

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Publication Date
Sat Aug 01 2015
Journal Name
2015 Ieee Conference On Computational Intelligence In Bioinformatics And Computational Biology (cibcb)
Granular computing approach for the design of medical data classification systems
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Publication Date
Wed Jun 01 2022
Journal Name
Bulletin Of Electrical Engineering And Informatics
Proposed model for data protection in information systems of government institutions
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Information systems and data exchange between government institutions are growing rapidly around the world, and with it, the threats to information within government departments are growing. In recent years, research into the development and construction of secure information systems in government institutions seems to be very effective. Based on information system principles, this study proposes a model for providing and evaluating security for all of the departments of government institutions. The requirements of any information system begin with the organization's surroundings and objectives. Most prior techniques did not take into account the organizational component on which the information system runs, despite the relevance of

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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
IMPLEMENTATION OF THE SKIP LIST DATA STRUCTURE WITH IT'S UPDATE OPERATIONS
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A skip list data structure is really just a simulation of a binary search tree. Skip lists algorithm are simpler, faster and use less space. this data structure conceptually uses parallel sorted linked lists. Searching in a skip list is more difficult than searching in a regular sorted linked list. Because a skip list is a two dimensional data structure, it is implemented using a two dimensional network of nodes with four pointers. the implementation of the search, insert and delete operation taking a time of upto . The skip list could be modified to implement the order statistic operations of RANKand SEARCH BY RANK while maintaining the same expected time. Keywords:skip list , parallel linked list , randomized algorithm , rank.

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Publication Date
Mon Oct 09 2023
Journal Name
2023 Ieee 34th International Symposium On Software Reliability Engineering Workshops (issrew)
Semantics-Based, Automated Preparation of Exploratory Data Analysis for Complex Systems
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Publication Date
Tue Oct 15 2019
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Combining Convolutional Neural Networks and Slantlet Transform For An Effective Image Retrieval Scheme
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In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

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Publication Date
Thu Jan 01 2009
Journal Name
Computer And Information Science 2009
The Stochastic Network Calculus Methodology
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Home Computer and Information Science 2009 Chapter The Stochastic Network Calculus Methodology Deah J. Kadhim, Saba Q. Jobbar, Wei Liu & Wenqing Cheng Chapter 568 Accesses 1 Citations Part of the Studies in Computational Intelligence book series (SCI,volume 208) Abstract The stochastic network calculus is an evolving new methodology for backlog and delay analysis of networks that can account for statistical multiplexing gain. This paper advances the stochastic network calculus by deriving a network service curve, which expresses the service given to a flow by the network as a whole in terms of a probabilistic bound. The presented network service curve permits the calculation of statistical end-to-end delay and backlog bounds for broad

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