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.
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Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re
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The deployment of UAVs is one of the key challenges in UAV-based communications while using UAVs for IoT applications. In this article, a new scheme for energy efficient data collection with a deadline time for the Internet of things (IoT) using the Unmanned Aerial Vehicles (UAV) is presented. We provided a new data collection method, which was set to collect IoT node data by providing an efficient deployment and mobility of multiple UAV, used to collect data from ground internet of things devices in a given deadline time. In the proposed method, data collection was done with minimum energy consumption of IoTs as well as UAVs. In order to find an optimal solution to this problem, we will first provide a mixed integer linear programming m
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Finding orthogonal matrices in different sizes is very complex and important because it can be used in different applications like image processing and communications (eg CDMA and OFDM). In this paper we introduce a new method to find orthogonal matrices by using tensor products between two or more orthogonal matrices of real and imaginary numbers with applying it in images and communication signals processing. The output matrices will be orthogonal matrices too and the processing by our new method is very easy compared to other classical methods those use basic proofs. The results are normal and acceptable in communication signals and images but it needs more research works.
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Most studies and research have tried to shed light on unemployment and employment in general, with less focus on the problems facing working women and the resulting social and economic consequences that threaten their human and professional lives. For women, working is one of the basic necessities for the sustainability of human life, and it constitutes an essential axis for both sexes and through it. It also gives a person the status and social status where the individual finds a ready opportunity to practice his intentions and desires, test his abilities and talents, and achieve his ambitions. The availability of full employment in general and the joining of women to the labor market is an important and fundamental factor in the sustai
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Abstract
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)
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The Normalized Difference Vegetation Index (NDVI) is commonly used as a measure of land surface greenness based on the assumption that NDVI value is positively proportional to the amount of green vegetation in an image pixel area. The Normalized Difference Vegetation Index data set of Landsat based on the remote sensing information is used to estimate the area of plant cover in region west of Baghdad during 1990-2001. The results show that in the period of 1990 and 2001 the plant area in region of Baghdad increased from (44760.25) hectare to (75410.67) hectare. The vegetation area increased during the period 1990-2001, and decreases the exposed area.