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Oil well logging, also known as wireline logging, is a method of collecting data from the well environment to determine subterranean physical properties and reservoir parameters. Measurements are collected against depth along the well's length, and many types of wire cabling tools depend on the physical property of interest. Well probes generally has a dynamic respon to changes in rock layers and fluid composition. These probes or well logs are legal documents that record the history of a well during the drilling stages until its completion. Well probes record the physical properties of the well, which must then be interpreted in petrographic terms to obtain the characteristics of the rocks and flui

   Gas lift is one of the most important artificial lift methods for increasing oil production, as wells often require this method after the reservoir's energy has decreased. In this research, an optimal gas lift system is designed for five horizontal wells in the Ahdab oil field, which suffers from low production. At the same time, water cut in some of these wells reaches 66%, while the productivity index is low in others, which makes the challenges clear, and a deep analysis is needed to find an optimal system. The Pipesim program is used to design the optimal gas lift system, which contains features that facilitate the implementation of the appropriate design and provide the ability to analyze and determine the optimal design v

Purpose - This study relies on the descriptive and analytical approach through collecting and analyzing the necessary data, as this approach focuses on polling the opinions of the research sample and its directions, and aims to develop a model that studies the relationship between knowledge creation and organizational ambidexterity in Iraqi private banks and verifying its validity experimentally. Design / Methodology / Introduction - A survey was conducted through a questionnaire form to collect data from a sample of (113) managers in private commercial banks. In addition, this study used the AMOS program and the ready-to-use statistical program package (SPSS V.25) to test the proposed hypotheses of the theoretical model experimentally. Res

Generalized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used

In this paper an attempt to provide a single degree of freedom lumped model for fluid structure interaction (FSI) dynamical analysis will be presented. The model can be used to clarify some important concept in the FSI dynamics such as the added mass, added stiffness, added damping, wave coupling ,influence mass coefficient and critical fluid depth . The numerical results of the model show that the natural frequency decrease with the increasing of many parameters related to the structure and the fluid .It is found that the interaction phenomena can become weak or strong depending on the depth of the containing fluid .The damped and un damped free response are plotted in time domain and phase plane for different model parameters It is fou

In this study, a mathematical model for the kinetics of solute transport in liquid membrane systems (LMSs) has been formulated. This model merged the mechanisms of consecutive and reversible processes with a “semi-derived” diffusion expression, resulting in equations that describe solute concentrations in the three sections (donor, acceptor and membrane). These equations have been refined into linear forms, which are satisfying in the special conditions for simplification obtaining the important kinetic constants of the process experimentally.

Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet