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Prediction of Well Logs Data and Estimation of Petrophysical Parameters of Mishrif Formation, Nasiriya Field, South of Iraq Using Artificial Neural Network (ANN)
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    Petrophysical properties including volume of shale, porosity and water saturation are significance parameters for petroleum companies in evaluating the reservoirs and determining the hydrocarbon zones. These can be achieved through conventional petrophysical calculations from the well logs data such as gamma ray, sonic, neutron, density and deep resistivity. The well logging operations of the targeted limestone Mishrif reservoirs in Ns-X Well, Nasiriya Oilfield, south of Iraq could not be done due to some problems related to the well condition. The gamma ray log was the only recorded log through the cased borehole. Therefore, evaluating the reservoirs and estimating the perforation zones has not performed and the drilled well was abandoned. This paper presents a solution to estimate the missing open-hole logs of Mishrif Formation including sonic, neutron, density and deep resistivity using supervised Artificial Neural Network (ANN) in Petrel software (2016.2). Furthermore, the original gamma-ray log along with the predicted logs data from ANN models were processed, and the petrophysical properties including volume of shale, effective porosity and water saturation were calculated to determine the hydrocarbon zones. The ANN Mishrif Formation models recorded coefficient of determination (R2) of 0.65, 0.77, 0.82, and 0.04 between the predicted and the tested logs data with total correlations of 0.67, 0.91, 0.84 and 0.57 for sonic, neutron, density, and resistivity logs respectively. The best possible hydrocarbon-bearing zone ranges from the depth of about 1980-2030 m in the mB1unit. The ANN provides a good accuracy and data matching in clean and non-heterogeneous formations compared to those with higher heterogeneity that contain more than one type of lithology. The Ns-X Well can, therefore, be linked to the development plans of the Nasiriya Field instead of neglect it.

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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Application of Artificial Neural Network for Predicting Iron Concentration in the Location of Al-Wahda Water Treatment Plant in Baghdad City
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Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul

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Publication Date
Wed May 01 2019
Journal Name
Iraqi Journal Of Science
Application of Static Correction Technique on 2D Land Seismic Data in the South of Iraq
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In our research, several different Statics solutions have been implemented in the processing of seismic data in the south of Iraq for (2D) line seismic survey (AK18)  of Abu-khama project with length 32.4 Km and their corresponding results have been compared in order to find optimum static solutions. The static solutions based on the tomographic-principle or combining the low frequency components of field statics with high frequency ones of refraction statics can provide a reasonable static solution for seismic data in the south of Iraq. The quality of data was bad and unclear in the seismic signal, but after applying field statics there is an enhancement of data quality. The Residual static correction improved the qualities of seis

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Retrieving Encrypted Images Using Convolution Neural Network and Fully Homomorphic Encryption
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A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

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Publication Date
Wed Feb 08 2023
Journal Name
Iraqi Journal Of Science
Subsurface Investigation of Tuba Oil Field Depending on 2D Seismic Reflection South Iraq
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This study deals with the seismic reflection interpretation of Cretaceous Formations in Tuba oil field, southern Iraq, including structural and stratigraphic techniques. The study achieved by using Geofram , Geolog and Petrel software. The interpretation process, of 2-D seismic data and well logs have been used. Based on well logs and synthetic traces two horizons were identified and picked which are the tops of Mishrif and Zubair Formations. These horizons were followed over all the area in order to obtain their structural setting. Structural interpretation indicates that the Tuba oil field is an anticline structure as well as the presence of normal fault near Mishrif Formation trending NE-SW. Information from the wells appeared Mishrif

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Publication Date
Tue Jul 01 2008
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
THE STUDY OF MINERALOGICAL AND MICROFACIES ANALYSIS SHIRANISH FORMATION WELL (KH-6) ANSAB AREA IN SOUTHERN IRAQ
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The study of Shiranish Formation rocks in southern part of Iraq at Ansab area well (KH-6)
were carried out. The formation is tongued with tayarat formation, which bounded from top
and bottom, the upper tongue at thickness 49m. and tongued at depth (476-525m.) the lower
tongue at thickness 4m. tongued at (541-537m.).
The rocks of this formation were divided into three sedimentary microfacies:
1- Dolomitized formininferal Wackestone facies.
2- Dolomitized formininferal Mudstone facies.
3- Dolostone facies.
34 slides were investigated depending on mineralogical, compositional and biological
processes and compared diagenesis which reflect open marine shelf at lower part of formation
(F.Z.2) (S.M.F.8), but at the

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Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Geological Journal
Study of Petrophysical Properties of the Yamama Formation in Siba Oilfield
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Evaluating a reservoir to looking for hydrocarbon bearing zones, by determining the petrophysical properties in two wells of the Yamama Formation in Siba field using Schlumberger Techlog software. Three porosity logs were used to identify lithology using MN and MID cross plots. Shale volume were calculated using gamma ray log in well Sb-6ST1 and corrected gamma ray in well Sb-5B. Sonic log was used to calculate porosity in bad hole intervals while from density log at in-gauge intervals. Moreover, water saturation was computed from the modified Simandoux equation and compared to the Archie equation. Finally, Permeability was estimated using a flow zone indicator. The results show that the Yamama Formation is found to be mainly limest

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Publication Date
Wed Mar 01 2017
Journal Name
International Communications In Heat And Mass Transfer
Optimization, modeling and accurate prediction of thermal conductivity and dynamic viscosity of stabilized ethylene glycol and water mixture Al 2 O 3 nanofluids by NSGA-II using ANN
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In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

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Publication Date
Tue Aug 27 2024
Journal Name
Tem Journal
Preparing the Electrical Signal Data of the Heart by Performing Segmentation Based on the Neural Network U-Net
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Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files tha

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Publication Date
Tue Sep 25 2018
Journal Name
Iraqi Journal Of Science
Facies Analysis and Geological modeling of Euphrates Formation in Ajeel Oil Field, Northern Iraq
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The current study summarized the construction of a three-dimensional geological model of the Aquitanian sediments age, which represented by the Euphrates and Serikagni formation in Ajeel Oil Field, where Ajeel Oil Field has structural closure towards northwest - southeast. Sedimentary of the current study consist of limestone, dolomitic limestone, dolomite (compose of skeletal grains, non-skeletal grains and cement) and the appearance of some anhydrite rocks.

     The petrographic study of the Euphrates Formation were prepared using a thin section of wells (Aj-1, Aj-4, Aj-5, Aj-6 and Aj-7), Previous studies and geological reports, as well as use well logs data  in the statistical analysis by Petrel softwa

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Publication Date
Sat Jun 27 2020
Journal Name
Iraqi Journal Of Science
Diagenetic Processes Overprint and Pore Types of Mauddud Formation, Badra Oil Field, Central Iraq
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Diagenetic processes and types of pores that control the reservoir properties are studied for Mauddud Formation in selected wells of Badra oil field, central Iraq. The microscopic study of the thin sections shows the effects of micritization, cementation, neomorphism, dissolution, dolomitization, compaction, and fracturing on Mauddud Formation carbonate microfacies. The decrease of porosity is resulted from cementation, compaction, and neomorphism. Different types of calcite cement occlude pore spaces such as drusy cement, syntaxial rim cement, and granular (blocky) cement. The neomorphism of micritic matrix and skeletal grains reduces porosity as indicated by development of microspar or pseudospar. Evidence of decreasing porosity by com

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