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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
Thu Dec 01 2016
Journal Name
Journal Of Engineering
A Laboratory Study Attempt of Flow and Energy Dissipation in Stepped Spillways
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A new laboratory study conducted on stepped spillways in order to investigate their efficiency of dissipating flow energy. All previous study on stepped spillway indicated that the flow energy dissipation decreased as increasing in discharge. Increasing in the step numbers and the spillway slope led to energy dissipation decrease. In this study, an experimental attempt to increase energy dissipation at variable discharges was performed on stepped spillway and that leads to decreasing the cost of initiating the stilling basin or may be ignoring it. Five spillways were constructed from concrete and tested to investigate and compare among them. Three were roughed by gravel with different size for each one, one of them was s

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Publication Date
Wed Jun 30 2004
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Theoretical Analysis of Concentric Flow of Spherical Capsule in Laminar Flow
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Publication Date
Tue Jan 01 2019
Journal Name
Indian Journal Of Public Health Research & Development
Spectrophotometric Determination of Nifedipine in Pharmaceutical Tablets Using Batch and Flow Injection Method Via Diazotization Coupling Reaction
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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
Preservation of Required Chlorine Concentration in Baghdad Water Supply Networks using On-Site Chlorine Injection
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The chlorine concentration variation in Baghdad water networks was studied. The
chlorine data were collected from Mayoralty of Baghdad and Ministry of Environment
(MOE) for the networks for both sides of the city Karkh and Rasafa for (2008-2009). The
study of these data indicates that there are no systematic testing program .Classified GIS
maps showed that the areas far from the treatment plants have almost always low
chlorine concentration .This indicates that the problem of the low chlorine concentration
in the far areas is due to cracks of pipe along the conveyance path ,as expected. The area's
most frequently have low concentration are Al-sadir,Al-Kadhimya, and Al-Amiria . It
was found also that the chlorine c

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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Engineering
Spiking Neural Network in Precision Agriculture
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In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Effect of IFRS 16 on the quality of financial reporting For the Iraqi economic units Applied to the General Company of Iraqi Airways
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The rental activity receives "significant" interest from accounting organizations interested in issuing accounting standards worldwide, such as the Financial Accounting Standards Board (FASB), the International Accounting Standards Board (IASB). As leases represents an important source of finance for economic units as an alternative to financing assets through purchase or borrowing. Professional organizations have focused on addressing the situation of extra-budgetary funding through which the lessee hides many leases that are classified as financing without It shows in the budget, which gives an incorrect picture of the reality of the financial situation of economic unity, IASB has issued IFRS 16, which terminates off- Balance s

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Publication Date
Sat Jan 01 2022
Journal Name
Proceedings Of International Conference On Computing And Communication Networks
Speech Age Estimation Using a Ranking Convolutional Neural Network
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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Comparison of Estimation Sonic Shear Wave Time Using Empirical Correlations and Artificial Neural Network
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Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
Estimation and Improvement of Routing Protocol Mobile Ad-Hoc Network Using Fuzzy Neural Network
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Ad-Hoc Networks are a generation of networks that are truly wireless, and can be easily constructed without any operator. There are protocols for management of these networks, in which the effectiveness and the important elements in these networks are the Quality of Service (QoS). In this work the evaluation of QoS performance of MANETs is done by comparing the results of using AODV, DSR, OLSR and TORA routing protocols using the Op-Net Modeler, then conduct an extensive set of performance experiments for these protocols with a wide variety of settings. The results show that the best protocol depends on QoS using two types of applications (+ve and –ve QoS in the FIS evaluation). QoS of the protocol varies from one prot

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Publication Date
Fri May 31 2019
Journal Name
Journal Of Engineering
Geological Model of the Tight Reservoir (Sadi Reservoir-Southern of Iraq)
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A3D geological model was constructed for Al-Sadi reservoir/ Halfaya Oil Field which is discovered in 1976 and located 35 km from Amara city, southern of Iraq towards the Iraqi/ Iranian borders.

Petrel 2014 was used to build the geological model. This model was created depending on the available information about the reservoir under study such as 2D seismic map, top and bottom of wells, geological data & well log analysis (CPI). However, the reservoir was sub-divided into 132x117x80 grid cells in the X, Y&Z directions respectively, in order to well represent the entire Al-Sadi reservoir.

Well log interpretation (CPI) and core data for the existing 6 wells were the basis of the petrophysical model (

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