The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value <0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, temperature 46.4 °C, pressure 21 Mpa, and flowrate 27,000 m3/day which is nearly closed to suggested oily content 8.5 ppm. An artificial neural network (ANN) technique was employed in this study to estimate the oil content in the treatment process. An artificial neural network model was remarkably accurate at simulating the process under investigation. A low mean squared error (MSE) and relative error (RE) equal to 1.55 × 10−7 and 2.5, respectively, were obtained during the training phase, whilst the testing results demonstrated a high coefficient of determination (R2) equal to 0.99.
The Hartha Formation is a major carbonate succession deposited during the Late Campanian period. The current study depends on four selected wells (EB 1, 2, 4 and 30) within the East Baghdad oil field to study electrofacies and petrophysical properties related to the reservoir characterization.
The Hartha Formation is divided into three electro-facies units using GR and SP logs in Petrel software. The upper unit of the Hartha Formation is composed mainly of limestone. The middle unit is composing of thick layers of shale. The lower unit is composed mainly of limestone with few shale layers. The three units are divided into three types of rocks in relation to the total porosity: 1. High-moderate active porosity rocks (type I)
... Show MoreThe studied succession (Lower Miocene-Early Middle Miocene) In central Iraq is distinguished by a wide range of fossils, mostly benthic foraminifera, and other fossils including bivalves, gastropods, echinoids fragments, red algae and coral are also presented. Index fossils of benthic foraminifera have been used for the purpose of determining the age of the Euphrates and Jeribe formations, because of their young age, wide geographical distribution and abundance in the selected wells.
The present study involves four selected wells of Ajil oil field and in terms of the biostratigraphy of the Euphrates, Dhiban, and Jeribe formations depending on benthic foraminifera and other associated fossils. Some of these fossils have a short ve
... Show MoreThe Zubair Formation is the most significant sandstone reservoir in Iraq which deposited during the Barremian. The study area is located in the central part of Iraq at the Kifl oil field, in the northern part of the Mesopotamian Zone.
The petrographic study showed that quartz mineral is the main component of the sandstone in Zubair Formation with very low percentage of feldspar and rare rock fragments to classified as quartz arenite sandtone. There are five lithologic changes (lithofacies) that have characterized the studied succession: - well sorted quartz arenite, poorly sorted quartz arenite, poorly sorted graywacke, sandy shale, and shale. These lithofacieses were deposited in the deltaic environments as three associate
... Show More<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
... Show More<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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The research aims to identify the mediator role of workplace spirituality in the relationship between psychological capital and entrepreneurial behavior: field research to a sample opinions from employees at the center of the Iraqi ministry of Oil . The importance of the current research emerged from paucity of studies that have attempted to identify and know the nature of the relationship between the variables as well as trying to find the current address and realistic problem directly affects the performance of employees in the Iraqi oil sector.
In order to achieve the goal of research the use of the analytical method (quantitative)
... Show MoreThis work presents a novel technique for the detection of oil aging in electrical transformers using a single mode optical fiber sensor based on surface plasmon resonance (SPR). The aging of insulating oil is a critical issue in the maintenance and performance of electrical transformers, as it can lead to reduce insulation properties, increase risk of electrical breakdown, and decrease operational lifespan. Many parameters are calculated in this study in order to examine the efficiency of this sensor like sensitivity (S), signal to noise ratio (SNR), resolution (refractive index unit) and figure of merit (FOM) and the values are for figure of merit is 11.05, the signal to noise ratio is 20.3, the sensitivity is 6.63, and the resolution is 3
... Show MoreTight oil reservoirs have been a concerned of the oil industry due to their substantial influence on oil production. Due to their poor permeability, numerous problems are encountered while producing from tight reservoirs. Petrophysical and geomechanical rock properties are essential for understanding and assessing the fracability of reservoirs, especially tight reservoirs, to enhance permeability. In this study, Saadi B reservoir in Halfaya Iraqi oil field is considered as the main tight reservoir. Petrophysical and geomechanical properties have been estimated using full-set well logs for a vertical well that penetrates Saadi reservoir and validated with support of diagnostic fracture injection test data employing standard equations
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The critical success factors of the means of the most modern in determining the main directions for organizations to achieve competitive advantage. and can be a critical success factors in organizations that overlap in the functional areas of the organization. that successful organizations use these factors to get to the uniqueness and distinction. as the entrance of critical success factors with the capacity Evaluative phase correction because discovery increases the perception of managers of what is important to the organization and using them to get to the Strategic Entrepreneurship. as it begins in terms of permanence of success and
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