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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 May 05 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Classification SINGLE-LEAD ECG by using conventional neural network algorithm
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Publication Date
Fri Dec 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Experimental investigation and modelling of residual stresses in face milling of Al-6061-T3 using neural network
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Milling process is a common machining operation that is used in the manufacturing of complex surfaces. Machining-induced residual stresses (RS) have a great impact on the performance of machined components and the surface quality in face milling operations with parameter cutting. The properties of engineering material as well as structural components, specifically fatigue life, deformation, impact resistance, corrosion resistance, and brittle fracture, can all be significantly influenced by residual stresses. Accordingly, controlling the distribution of residual stresses is indeed important to protect the piece and avoid failure. Most of the previous works inspected the material properties, tool parameters, or cutting parameters, bu

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Publication Date
Sat Nov 28 2020
Journal Name
Iraqi Journal Of Science
Microfacies Analysis and Basin Development of Hartha Formation in East Baghdad Oil field, Central Iraq
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The Hartha Formation is one of the important formations deposited during Late Campanian age.

The present study deals with four boreholes (EB-53, 54, 55 and 56) within the East Baghdad oil field to diagnoses the microfacies and interpret the depositional environments.

Six major microfacies were recognized in the succession of the Hartha Formation. Their characteristic grain types and depositional texture enabled the recognition of paleoenvironment. There are Orbitoides  wackestone-packstone , Orbitoides - miliolid wackestone, Peloidal and Pellets - echinoderm wackestone to packstone, Peloidal wackestone to packstone, Pelletal wackestone to packstone, and Planktonic foraminifera wackestone-packstone.

Four assoc

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Publication Date
Mon Dec 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Permeability Prediction of Un-Cored Intervals Using FZI Method and Matrix Density Grouping Method: A Case Study of Abughirab Field/Asmari FM., Iraq
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Knowledge of permeability is critical for developing an effective reservoir description. Permeability data may be calculated from well tests, cores and logs. Normally, using well log data to derive estimates of permeability is the lowest cost method. This paper will focus on the evaluation of formation permeability in un-cored intervals for Abughirab field/Asmari reservoir in Iraq from core and well log data. Hydraulic flow unit (HFU) concept is strongly related to the flow zone indicator (FZI) which is a function of the reservoir quality index (RQI). Both measures are based on porosity and permeability of cores. It is assumed that samples with similar FZI values belong to the same HFU. A generated method is also used to calculate permea

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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
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

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Publication Date
Tue Sep 25 2018
Journal Name
Iraqi Journal Of Science
3D Seismic Structural and Stratigraphy Study of Shuaiba Formation in Kumait Oil Field-Southern Iraq
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The Kumait Oil field was interpreted using 3-D seismic data from Oil Exploration company. The Shuaiba Formation (Cretaceous Age) reflector is detected.Structural map of formation is prepared to obtain the location and direction of  the sedimentary basin and shoreline. Depth maps was drawn depending on the structural interpretation of  the picked reflector and show several structural feature as closures.The seismic interpretation of the area approves the presence of some stratigraphic features in the studied formation. Some distributary mound and flatspot were observed within the study area, but they are not continuous due to the tectonic effects. These activity elements give reasonable explanation for the hydrocarbon distributi

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Publication Date
Wed Mar 20 2024
Journal Name
Journal Of Petroleum Research And Studies
Advanced Machine Learning application for Permeability Prediction for (M) Formation in an Iraqi Oil Field
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Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Biostratigraphy of Hartha Formation from Selected Wells in Nasiriyah Oil Field, Southern Iraq
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     The Hartha Formation has been investigated from a biostratigraphic view in three subsurface sections in the Nasiriyah Oil field, wells Ns1, Ns3, and Ns4, South of Iraq. Hartha Formation is composed of limestone and has various areas of intense dolomitization alternating with marly limestone. The formation ranges in thickness from 126 to 182 meters. Thirteen large and small benthic foraminifer species and genera are identified from Hartha Formation. Based on the large benthic foraminifer's assemblage, one distinct biozone was recognized after an examination of the paleontological datum in the investigated area showed that the studied wells contained a diversity of foraminiferal species, the larger foraminifers biozone was propose

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Publication Date
Tue Oct 31 2023
Journal Name
Iraqi Geological Journal
Evaluating Petrophysical Properties of Sa'di Reservoir in Halfaya Oil Field
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The petrophysical characteristics of five wells drilled into the Sa'di Formation in the Halfaya oil field were evaluated using IP software to determine a reservoir and explore hydrocarbon reserve zones. The lithology was evaluated using the M-N cross-plot method. The diagram showed that the Sa'di Formation was mainly composed of calcite (represented by the limestone region) is the main mineral in the Sa′di Reservoir. Using a density-neutron cross plot to identify the lithology showed that the formation mainly consists of limestone with minor shale. Gamma-ray logs were employed to calculate the shale quantity in each well. The porosity at weak hole intervals was calculated using a sonic log and neutron-density log at the reservoir

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