Radiological assessment for the East Baghdad oilfield-southern part was conducted in the current study. 10 samples (scale, soil, sludge, water, and oil) from the different stages of oil production were collected. 232Th, 226Ra, and 40K in the samples were analyzed with 40% efficiency for Gamma spectrometry. system based on HPGe. The findings indicated that the examined sites exhibit comparatively lower levels of NORM contamination, in contrast to other global oilfields. Nevertheless, certain areas, particularly those within separation stages, demonstrate relatively elevated NORM concentrations exceeding the global average in soil and sludge. The maximum value of 226Ra, 232Th, was found in sludge sample the findings indicated that ove

   Petrophysical characterization is the most important stage in reservoir management. The main purpose of this study is to evaluate reservoir properties and lithological identification of Nahr Umar Formation in Nasiriya oil field. The available well logs are (sonic, density, neutron, gamma-ray, SP, and resistivity logs). The petrophysical parameters such as the volume of clay, porosity, permeability, water saturation, were computed and interpreted using IP4.4 software. The lithology prediction of Nahr Umar formation was carried out by sonic -density cross plot technique. Nahr Umar Formation was divided into five units based on well logs interpretation and petrophysical Analysis: Nu-1 to Nu-5. The formation lithology is mainly

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

Intelligent or smart completion wells vary from conventional wells. They have downhole flow control devices like Inflow Control Devices (ICD) and Interval Control Valves (ICV) to enhance reservoir management and control, optimizing hydrocarbon output and recovery. However, to explain their adoption and increase their economic return, a high level of justification is necessary. Smart horizontal wells also necessitate optimizing the number of valves, nozzles, and compartment length. A three-dimensional geological model of the As reservoir in AG oil field was used to see the influence of these factors on cumulative oil production and NPV. After creating the dynamic model for the As reservoir using the program Petrel (2017.4), we

The current study presents an experimental investigation of heat transfer and flow characteristic for subcooled flow boiling of deionized water in the microchannel heat sink. The test section consisted of a single microchannel having 300μm wide nominal dimensions and 300μm height (hydraulic diameter of 300μm). The test section formed of oxygen-free copper with 72mm length and 12mm width. Experimental operation conditions spanned the heat flux (78-800) kW/m², mass flux (1700 and 2100) kg/m².s at 31˚C subcooled inlet temperature. The boiling heat transfer coefficient is measured and compared with existing correlations. Also, the experimental pressure drop is measured and compared with microscale p

AI in teaching English is reshaping language learning. While interest in AI-supported education is growing worldwide, research in this area is still emerging in Iraq. This review synthesizes empirical AI-based intervention studies to enhance English language learning in Iraqi higher education, and the perceptions of stakeholders regarding AI tools in language instruction. The reviewed intervention studies, comprising studies employed different AI platforms to support grammar instruction, speaking fluency, writing feedback, and pragmatic competence. These interventions yielded improvements in learners’ performance, motivation, and communicative confidence. In parallel, perception-focused studies revealed positive attitudes toward A

Social risks posed a great challenge to the development path in Iraq, which resulted in widening the development gaps, whether these gaps were between rural and embargoed areas, or between Iraqi governorates, and the gender gap. Besides, the nature of the reciprocal relationship between the social risks and the development process requires the adoption of development trends that are sensitive to the risks that take upon themselves the prompt and correct response to these risks, away from randomness and confusion that Iraq suffered from for decades. However, currently, the situation has differed a great deal. This is because the size and types of such gaps have widened and become more complicated than before; a matter which has led to hav

The use of non-parametric models and subsequent estimation methods requires that many of the initial conditions that must be met to represent those models of society under study are appropriate, prompting researchers to look for more flexible models, which are represented by non-parametric models                  

          In this study, the most important and most widespread estimations of the estimation of the nonlinear regression function were investigated using Nadaraya-Watson and Regression Local Ploynomial, which are one of the types of non-linear

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

The Research Aims To Clarify The Role Of Knowledge Innovation On The Administrative Process Represented by Managing Strategic Momentum, The Research Problem Focuses on Administrative leader Interest In And Implementation Of The Innovation Element Of Knowledge In The Organization By " Managing Strategic Momentum" As Well As The Focus By Management About The Innovators And Makers Of Knowledge And Strategic Planners In The Design And Formulation Of Strategic. Research does Contribute In Solving Part Of The Organizational Problems Of Vision, Innovation And Their Impact On The Momentum Management To Determine The Extent On Which The Procedures Of The Assessed Companies And Plan To Regulate Innovation Under The Momentu