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Permeability Prediction in One of Iraqi Carbonate Reservoir Using Hydraulic Flow Units and Neural Networks

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
Tue Jul 01 2014
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Detection of Cd69 Marker by Flow Cytometry in Iraqi Patients with Coeliac Disease.

Background: Coeliac disease is a chronic, immunologically determined form of enteropathy affecting the small intestine in genetically predisposed children and adults. It is precipitated by the ingestion of gluten-containing foods. It is also referred to as celiac sprue, gluten-sensitive enteropathy, or nontropical sprue. CD69 is a lymphoid activation antigen whose rapid expression makes it suitable for the detection of T-ce

J Fac Med Baghdad

2014; Vol.56, No .2

Received Feb .2014

Accepted Apr. 2014

 
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Publication Date
Sun Dec 09 2018
Journal Name
Baghdad Science Journal
Pose Invariant Palm Vein Identification System using Convolutional Neural Network

Palm vein recognition is a one of the most efficient biometric technologies, each individual can be identified through its veins unique characteristics, palm vein acquisition techniques is either contact based or contactless based, as the individual's hand contact or not the peg of the palm imaging device, the needs a contactless palm vein system in modern applications rise tow problems, the pose variations (rotation, scaling and translation transformations) since the imaging device cannot aligned correctly with the surface of the palm, and a delay of matching process especially for large systems, trying to solve these problems. This paper proposed a pose invariant identification system for contactless palm vein which include three main

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Tue Jun 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Using Artificial Neural Network to Predict Rate of Penetration from Dynamic Elastic Properties in Nasiriya Oil Field

   The time spent in drilling ahead is usually a significant portion of total well cost. Drilling is an expensive operation including the cost of equipment and material used during the penetration of rock plus crew efforts in order to finish the well without serious problems. Knowing the rate of penetration should help in speculation of the cost and lead to optimize drilling outgoings. Ten wells in the Nasiriya oil field have been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software based on the las files and log record provided. The average rate of penetration and average dynamic elastic propert

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Engineering Science And Technology (jestec)
Water Quality Assessment And Total Dissolved Solids Prediction For Tigris River In Baghdad City Using Mathematical Models

Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

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Publication Date
Sun Nov 01 2009
Journal Name
Tencon 2009 - 2009 Ieee Region 10 Conference
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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

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
Wed May 10 2023
Journal Name
Journal Of Engineering
EFFECT OF CHANGE IN THE COEFFICIENT OF PERMEABILITY ON CONSOLIDATION CHARACTERISTICS OF CLAYS

The settlement rate and pore water pressure dissipation rate are mainly controlled by the permeability of soil. Both laboratory and field tests show that the permeability is varied during the loading and consolidation process. It is known that consolidation process is accompanied by decrease in void ratio which leads to decrease in the coefficient of permeability. The importance of the decrease of the coefficient of permeability on the time rate of settlement and pore water pressure needs to be investigated.
This paper takes into account the change in coefficient of permeability during consolidation and studies its effect on consolidation characteristics of a clay layer. The finite element method is used in the analysis and the packag

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Publication Date
Wed Dec 01 2021
Journal Name
Civil And Environmental Engineering
Prediction of the Delay in the Portfolio Construction Using Naïve Bayesian Classification Algorithms
Abstract<p>Projects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postpo</p> ... Show More
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Publication Date
Wed Aug 31 2022
Journal Name
Iraqi Journal Of Science
Aquifer depth determination of low permeability layers using geo-resistivity data: A case study of Enyigba mine area and environs, South Eastern Nigeria

      Many geophysical methods have been applied to locate groundwater in Nigeria’s rural and urban villages. Locating groundwater in low permeability formations like shales and siltstones is even more challenging due to the difficulty of mapping fracture zones within these formations. The fracture zones serve as potential aquifers in low permeability formations and have been the object of groundwater search in shales, siltstones and other low permeability formations. The electrical resistivity method has proven helpful in fracture mapping within low permeability formations due to the existing resistivity contrast usually observed between the fractured and non-fractured sections in the Shales and Siltstones. Three vertical electri

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