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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 formation based on the four straight lines. The permeability was calculated by two methods for comparison and choosing the best.  The modified FZI method gives better results because the predicted permeability by this method demonstrates a coefficient of correlation (R2) higher than that of the conventional approach, where the value of R2 is 0.9645 of  modified FZI method while 0.892 of the conventional approach. When plotting RQI versus  on a log-log scale, all core samples with similar FZI values will lie on a straight line with a unit slope. Other core samples that have different FZI values will lie on other parallel lines. All lines in (RQI and ) plot of modified FZI method have unit slop and more parallel than these of the conventional approach. The plot of probability cumulative of FZIm is used to determine number of hydraulic flow unit for Nahr Umr formation. The plot of core-derived probability FZI for both modified and conventional method which indicates 4 Hus for Nahr Umr formation based on the four straight lines, these four straight lines of modified FZI method was more distinguished than these of the conventional approach.

 

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Publication Date
Thu Oct 31 2024
Journal Name
Iraqi Geological Journal
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 use

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Publication Date
Sun Dec 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Using Time Series Methods To Modify The Seasonal Variations in the Consumer Price Index
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     As is  known that the consumer price index (CPI) is one of the most important  price indices because of its direct effect on the welfare of the individual and his living.

       We have been address the problem of Strongly  seasonal  commodities in calculating  (CPI) and identifying some of the solution.

   We have  used an actual data  for a set of commodities (including strongly seasonal commodities) to calculate the index price by using (Annual Basket With Carry Forward Prices method) . Although this method can be successfully used in the context of seasonal&nbs

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Publication Date
Tue Dec 03 2013
Journal Name
Baghdad Science Journal
Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
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Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

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Publication Date
Mon Jan 01 2024
Journal Name
Fusion: Practice And Applications
Optimizing Task Scheduling and Resource Allocation in Computing Environments using Metaheuristic Methods
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Optimizing system performance in dynamic and heterogeneous environments and the efficient management of computational tasks are crucial. This paper therefore looks at task scheduling and resource allocation algorithms in some depth. The work evaluates five algorithms: Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Firefly Algorithm (FA) and Simulated Annealing (SA) across various workloads achieved by varying the task-to-node ratio. The paper identifies Finish Time and Deadline as two key performance metrics for gauging the efficacy of an algorithm, and a comprehensive investigation of the behaviors of these algorithms across different workloads was carried out. Results from the experiment

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Change detection of remotely sensed image using NDVI subtractive and classification methods.
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Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Moisture Susceptibility of Hot Mix Asphalt Mixtures Modified by Nano Silica and Subjected to Aging Process
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Moisture damage is described as a reduction in stiffness and strength durability in asphalt mixtures due to moisture. This study investigated the influence of adding nano silica (NS) to the Asphalt on the moisture susceptibility of hot-mix-asphalt (HMA) mixtures under different aging conditions. NS was mixed with asphalt binder at concentrations of 2%, 4%, and 6% by weight of the binder. To detect the microstructure changes of modified Asphalt and estimate the dispersion of NS within the Asphalt, the field emission scanning electron microscope (FE-SEM) was used. To examine the performance of Asphalt mixed with NS at different aging stages (short-term and long-term aging), asphalt mixture tests such as Marshall stability,

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Publication Date
Wed Dec 14 2022
Journal Name
Civil Engineering Journal
Rutting Prediction of Hot Mix Asphalt Mixtures Modified by Nano silica and Subjected to Aging Process
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High-volume traffic with ultra-heavy axle loads combined with extremely hot weather conditions increases the propagation of rutting in flexible pavement road networks. Several studies suggested using nanomaterials in asphalt modification to delay the deterioration of asphalt pavement. The current work aims to improve the resistance of hot mix asphalt (HMA) to rutting by incorporating Nano Silica (NS) in specific concentrations. NS was blended into asphalt mixtures in concentrations of 2, 4, and 6% by weight of the binder. The behavior of asphalt mixtures subjected to aging was investigated at different stages (short-term and long-term aging). The performance characteristics of the asphalt mixtures were evaluated using the Marshall s

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Estimation of Water and Energy Saving by Rainwater Harvesting: Sulaimani City as a Case Study
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Rainwater harvesting could be a possible solution to decrease the consequences of water scarcity and energy deficiency in Iraq and the Kurdistan Region of Iraq (KRI). This study aims to calculate the water and energy (electricity) saved by rainwater harvesting for rooftops and green areas in Sulaimani city, KR, Iraq. Various data were acquired from different formal entities in Sulaimani city. Moreover, Google Earth and ArcMap 10.4 software were used for digitizing and calculating the total rooftop and green areas. The results showed that for the used runoff coefficients (0.8 and 0.95), the harvested rainwater volumes were 2901563 and 12197131 m³ during the study period (2005 – 2006) and (2019-2020). Moreover, by compa

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Publication Date
Mon Sep 01 2025
Journal Name
Journal Of Engineering
Petrophysical Evaluation by Integrating AI and HFU Methods. A Case Study of the Mishrif Reservoir in Southern Iraq
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Reservoir quality assessment is important for detecting hydrocarbon-bearing zones and guiding future enhancement strategies. This study presents a detailed petrophysical evaluation of the Mishrif Formation in the Buzurgan Oilfield, which was selected due to its strategic value through its significant remaining reserves which making it an ideal candidate for advanced evaluation techniques. This study aims for shale content, porosity, permeability, water saturation, net to gross, and lithology determination. Well log and core data were used together to establish accurate property estimations. Permeability prediction through conventional methods, like core permeability-porosity correlations, was highly dispersive due to the heterogenei

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