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Permeability Prediction in One of Iraqi Carbonate Reservoir Using Hydraulic Flow Units and Neural Networks
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Permeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.

   This paper will try to develop the permeability predictive model for one of  Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).

   Histogram analysis, probability analysis and Log-Log plot of Reservoir Quality Index (RQI) versus normalized porosity (øz) are presented to identify optimal hydraulic flow units. Four HFUs were distinguished in this study area with good correlation coefficient for each HFU (R2=0.99), therefore permeability can be predicted from porosity accurately if rock type is known.

   Conventional core analysis and well log data were obtained in well 1 and 2 in one of carbonate Iraqi oil field. The relationship between core and well log data was determined by Artificial Neural Network (ANN) in cored wells to develop the predictive model and then was used to develop the flow units prediction to un-cored wells. Finally permeability can be calculated in each HFU using effective porosity and mean FZI in these HFUs. Validation of the models evaluated in a separate cored well (Blind-Test) which exists in the same formation. The results showed that permeability prediction from ANN and HFU matched well with the measured permeability from core data with R2 =0.94 and ARE= 1.04%.

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Publication Date
Wed May 17 2023
Journal Name
International Journal Of Computational Intelligence Systems
Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique
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Abstract<p>Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th</p> ... Show More
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Publication Date
Thu Nov 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Challenges of applying IFRS 16 to the Iraqi environment and its role in improving Financial indicators of economic units Applied to the General Company of Iraqi Airways
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Abstract

The leases, are regarded as one of the most controversial accounting issues in recent years, since they  represents one of the important sources of funding, which may be exploited by the tenant as off- Balance sheet Financing , which negatively affects the quality of financial reporting. The Financial Accounting Standards Board (FASB) and the International Accounting Standards Board (IASB) have "significant" interest in accounting for leases . FASB issued Statement of Financial Accounting Standards 13 on lease contracts in 1976 and IASB issued IAS 17 in 1980, which was amended in 1997 and IFRS 16, issued in January 2016, which will be effective on January 1, 2019 , to solve

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Publication Date
Sat Apr 01 2023
Journal Name
Fluid Phase Equilibria
Prediction of solubility of vitamins in the mixed solvents using equation of state
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Publication Date
Wed Oct 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fully Automated Magnetic Resonance Detection and Segmentation of Brain using Convolutional Neural Network
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     The brain's magnetic resonance imaging (MRI) is tasked with finding the pixels or voxels that establish where the brain is in a medical image The Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents. Next, the lines are separated into characters. In the Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents case of fonts with a fixed MRI width, the gaps are analyzed and split. Otherwise, a limited region above the baseline is analyzed, separated, and classified. The words with the lowest recognition score are split into further characters x until the result improves. If this does not improve the recognition s

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Publication Date
Tue Jan 10 2023
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
Enhancement the Educational Technology by Using 5G Networks
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With the spread of global markets for modern technical education and the diversity of programs for the requirements of the local and global market for information and communication technology, the universities began to race among themselves to earn their academic reputation. In addition, they want to enhance their technological development by developing IMT systems with integrated technology as the security and fastest response with the speed of providing the required service and sure information and linking it The network and using social networking programs with wireless networks which in turn is a driver of the emerging economies of technical education. All of these facilities opened the way to expand the number of students and s

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Publication Date
Wed Jan 01 2020
Journal Name
Solid State Technology
Image Fusion Using A Convolutional Neural Network
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Image Fusion Using A Convolutional Neural Network

Publication Date
Sun Jun 01 2008
Journal Name
2008 Ieee International Joint Conference On Neural Networks (ieee World Congress On Computational Intelligence)
Linear block code decoder using neural network
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Publication Date
Fri Apr 01 2022
Journal Name
Civil Engineering Journal
Prediction of Urban Spatial Changes Pattern Using Markov Chain
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Urban land uses of all kinds are the constituent elements of the urban spatial structure. Because of the influence of economic and social factors, cities in general are characterized by the dynamic state of their elements over time. Urban functions occur in a certain way with different spatial patterns. Hence, urban planners and the relevant urban management teams should understand the future spatial pattern of these changes by resorting to quantitative models in spatial planning. This is to ensure that future predictions are made with a high level of accuracy so that appropriate strategies can be used to address the problems arising from such changes. The Markov chain method is one of the quantitative models used in spatial planning to ana

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Publication Date
Tue Sep 03 2019
Journal Name
Eastern-european Journal Of Enterprise Technologies
Prediction of spot welding parameters using fuzzy logic controlling
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Publication Date
Fri Jun 01 2018
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Performance assessment of biological treatment of sequencing batch reactor using artificial neural network technique.
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Artificial Neural Network (ANN) model's application is widely increased for wastewater treatment plant (WWTP) variables prediction and forecasting which can enable the operators to take appropriate action and maintaining the norms. It is much easier modeling tool for dealing with complex nature WWTP modeling comparing with other traditional mathematical models. ANN technique significance has been considered at present study for the prediction of sequencing batch reactor (SBR) performance based on effluent's (BOD5/COD) ratio after collecting the required historical daily SBR data for two years operation (2015-2016) from Baghdad Mayoralty and Al-Rustamiya WWTP office, Iraq. The prediction was gotten by the application of a feed-forwa

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