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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 Jan 31 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Structure for Modeling and Controlling Nonlinear Systems
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This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

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Publication Date
Mon Nov 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Treatability influence of municipal sewage effluent on surface water quality assessment based on Nemerow pollution index using an artificial neural network
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Abstract<p>Assessing water quality provides a scientific foundation for the development and management of water resources. The objective of the research is to evaluate the impact treated effluent from North Rustumiyia wastewater treatment plant (WWTP) on the quality of Diyala river. The model of the artificial neural network (ANN) and factor analysis (FA) based on Nemerow pollution index (NPI). To define important water quality parameters for North Al-Rustumiyia for the line(F2), the Nemerow Pollution Index was introduced. The most important parameters of assessment of water variation quality of wastewater were the parameter used in the model: biochemical oxygen demand (BOD), chemical oxygen dem</p> ... Show More
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Publication Date
Thu Feb 01 2024
Journal Name
Journal Of Engineering
The Economic Evaluation of Various Production Scenarios for Zubair Reservoir in the Kifl Field
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This work evaluates the economic feasibility of various production scenarios for the Zubair reservoir in the Kifl oil field using cash flow and net present value (NPV) calculations. The Kifl field is an exploratory field that has not yet been developed or assessed economically. The first well was drilled in 1960, and three other wells were later drilled to assess the oil accumulation, so in this research, Different production scenarios were evaluated economically. These scenarios were proposed based on the reservoir model of the Zubair formation in the field. The research methodology used QUE$TOR software to estimate capital expenditures (CapEx) and operating expenditures (OpEx) based on field-level data, production prof

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Publication Date
Mon Jan 01 2018
Journal Name
Rehabend
Prediction of impact force-time history in sandy soils
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Publication Date
Wed Sep 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Effective Bed Thermal Conductivity and Heat Transfer Coefficient in Fluidized Beds
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Experimental study of heat transfer coefficients in air-liquid-solid fluidized beds were carried out by measuring the heat rate and the overall temperature differences across the heater at different operating conditions. The experiments were carried out in Q.V.F. glass column of 0.22 m inside diameter and 2.25 m height with an axially mounted cylindrical heater of 0.0367 m diameter and 0.5 m height. The fluidizing media were water as a continuous phase and air as a dispersed phase. Low density (Ploymethyl-methacrylate, 3.17 mm size) and high density (Glass beads, 2.31 mm size) particles were used as solid phase. The bed temperature profiles were measured axially and radially in the bed for different positions. Thermocouples were connecte

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Artificial Neural Network Models to Predict the Cost and Time of Wastewater Projects
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Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was

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Publication Date
Tue Oct 01 2019
Journal Name
2019 12th International Conference On Developments In Esystems Engineering (dese)
Roadway Deterioration Prediction Using Markov Chain Modeling (Wasit Governorate/ Iraq as a Case Study)
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Publication Date
Tue May 05 2015
Journal Name
International Journal Of Research In Pharmacy And Chemistry
NEW APPROACH FOR DETERMINATION OF MEBEVERINE BY QUENCHED FLUORESCENCE OF ANALYTICALLY INTERESTED SPECIES USING CONTINUOUS FLOW INJECTION LASER DIODE FLUORIMETER ANALYSER
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The proposed method is sensitive, simple , fast for the determination of mebeverine hydrochloride in pure form or in pharmaceutical dosage . Using Homemade instrument fluorimeter continuous flow injection analyser with solid state laser (405 nm) as a source. Where it is based upon the fluorescence of fluorescein sodium salt and quenching effect of fluorescence by mebeverine in aqueous medium. The calibration graph was linear in the concentration range 0.05 to10 mMol.L-1 (r= 0.9629) with relative standard deviation (RSD%) for 1 mMol.L-1mebeverine solution was lower than 3% (n=6). Three pharmaceutical drugs were used as an application for the determination of mebeverine. A comparison was made between the newly developed method of analysis wit

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Publication Date
Tue Jun 30 2015
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
Possibilty Of Implementing Hazard Analysis Critical Control Points (HACCP) In One Of Local Dairy Plants.: Possibilty Of Implementing Hazard Analysis Critical Control Points (HACCP) In One Of Local Dairy Plants.
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To limit or reduce common microbial contamination occurrence in dairy products in general and in soft cheese in particular, produced in locally plants, this study was performed to demonstrate the possibility of implementing HACCP in one of dairy plants in Baghdad city

            HACCP plan was proposed in soft cheese production line. A pre-evaluation was performed in soft cheese line production, HACCP Pre-requisites programs was evaluated from its presence and effectiveness. The evaluation was demonstrated risk in each of: Good Manufacturing Practice (GMP) program, evaluated as microbial and physical risk and considered as critical r

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Publication Date
Wed Sep 01 2021
Journal Name
Journal Of Engineering
Spike neural network as a controller in SDN network
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The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.

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