Hydrocarbon production might cause changes in dynamic reservoir properties. Thus the consideration of the mechanical stability of a formation under different conditions of drilling or production is a very important issue, and basic mechanical properties of the formation should be determined. There is considerable evidence, gathered from laboratory measurements in the field of Rock Mechanics, showing a good correlation between intrinsic rock strength and the dynamic elastic constant determined from sonic-velocity and density measurements. The values of the mechanical properties determined from log data, such as the dynamic elastic constants derived from the measurement of the elastic wave velocities in the material, should be more accurate than that determined by direct strength tests with core samples. This can be attributed to the scale effect and sampling disturbances. The aim of this study was to present methods of determining measures of some mechanical properties, from available well log data (conventional sonic, density, and gamma ray) for a well in North Rumaila field. The mechanical properties include formation strength and Poisson’s ratio. For the formation strength, combined elastic modulus (Ec) and shear modulus (G) were determined. The Poisson’s ratio was determined by using three different techniques to permit the accuracy of their values. The elastic modulus, shear modulus, and Poisson’s ratio were then correlated with depth and effective stress. The results show that combined correlations are important source of the prediction of overpressure zones which represent a major problem encountered in drilling and production process.
One male specimen of the species Metapenaeus stebbingi Nobili, 1904 was first recorded in November 2021 from the Iraqi territorial waters, Northwest of the Arabian Gulf. Therefore, the investigated shrimp species nominally corresponds to the original description of M. stebbing through the main diagnostic features. It must be adopted in the spread and expansion of species, a new record of the area, and a distinctive addition to the species of commercial shrimp within the Iraqi marine waters.
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In the current study, wild land plant specimens were collected during the flowering and fruiting period of these plants in February, April, June, August, and October 2023 from the riparian area of the Dujail River, Salahaldin Province, north of Baghdad, Iraq. Identified and the results showed that the number of these species were: 104 species, belong to 29 plant families, Included 26 dicotyledon families with 76 genera and 96 species. The asteraceae family was the most diverse, with 30 species, followed by Brassicaceae with (12) species. Additionally, there were 13 families represented by only one species in Dujail River which included: Apocynaceae, Berberidaceae, Capparaceae, Caryophyllaceae, Convolvulaceae, Geraniaceae, Lythraceae
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Amplitude variation with offset (AVO) analysis is an 1 efficient tool for hydrocarbon detection and identification of elastic rock properties and fluid types. It has been applied in the present study using reprocessed pre-stack 2D seismic data (1992, Caulerpa) from north-west of the Bonaparte Basin, Australia. The AVO response along the 2D pre-stack seismic data in the Laminaria High NW shelf of Australia was also investigated. Three hypotheses were suggested to investigate the AVO behaviour of the amplitude anomalies in which three different factors; fluid substitution, porosity and thickness (Wedge model) were tested. The AVO models with the synthetic gathers were analysed using log information to find which of these is the
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Early diagnosis and clinical decision-making depend on accurate brain tumor classification using magnetic resonance imaging (MRI). However, traditional deep learning methods usually rely on centralized medical data, which raises privacy concerns and limits the use of distributed clinical data. This research proposes a privacy-preserving federated learning framework for MRI image-based binary brain tumor classification using a decentralized ResNet-18 architecture that enables collaborative training without sharing raw patient data. To reflect realistic clinical conditions, the framework integrates heterogeneous multi-source datasets in different image formats (PNG and JPG) and evaluates performance under both IID and non-IID settings
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Cloud computing represents the most important shift in computing and information technology (IT). However, security and privacy remain the main obstacles to its widespread adoption. In this research we will review the security and privacy challenges that affect critical data in cloud computing and identify solutions that are used to address these challenges. Some questions that need answers are: (a) User access management, (b) Protect privacy of sensitive data, (c) Identity anonymity to protect the Identity of user and data file. To answer these questions, a systematic literature review was conducted and structured interview with several security experts working on cloud computing security to investigate the main objectives of propo
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Poverty phenomenon is very substantial topic that determines the future of societies and governments and the way that they deals with education, health and economy. Sometimes poverty takes multidimensional trends through education and health. The research aims at studying multidimensional poverty in Iraq by using panelized regression methods, to analyze Big Data sets from demographical surveys collected by the Central Statistical Organization in Iraq. We choose classical penalized regression method represented by The Ridge Regression, Moreover; we choose another penalized method which is the Smooth Integration of Counting and Absolute Deviation (SICA) to analyze Big Data sets related to the different poverty forms in Iraq. Euclidian Distanc
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