Carbonate reservoirs are an essential source of hydrocarbons worldwide, and their petrophysical properties play a crucial role in hydrocarbon production. Carbonate reservoirs' most critical petrophysical properties are porosity, permeability, and water saturation. A tight reservoir refers to a reservoir with low porosity and permeability, which means it is difficult for fluids to move from one side to another. This study's primary goal is to evaluate reservoir properties and lithological identification of the SADI Formation in the Halfaya oil field. It is considered one of Iraq's most significant oilfields, 35 km south of Amarah. The Sadi formation consists of four units: A, B1, B2, and B3. Sadi A was excluded as it was not filled with hydrocarbons. The structural and petrophysical models were built based on data gathered from five oil wells. The data from the available well logs, including RHOB, NPHI, SONIC, Gamma-ray, Caliper, and resistivity logs, was used to calculate the petrophysical properties. These logs were analyzed and corrected for environmental factors using IP V3.5 software. where the average formation water resistivity (Rw = 0.04), average mud filtrate resistivity (Rmf = 0.06), and Archie's parameters (m = 2, n = 1.9, and a = 1) were determined. The well-log data values calculated the porosity, permeability, water saturation, and net-to-gross thickness ratio (N/G).
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
... Show MoreFour different spectrophotometric methods are used in this study for the determination of Sulfamethoxazole and sulfanilamide drugs in pharmaceutical compounds, synthetic samples, and in their pure forms. The work comprises four chapters which are shown in the following: Chapter One: Includes a brief for Ultraviolet-Visible (UV-VIS) Absorption spectroscopy, antibacterial drugs and sulfonamides with some methods for their determination. The chapter lists two methods for optimization; univariate method and multivariate method. The later includes different types, two of these were mentioned; simplex method and design of experiment method. Chapter Two: Includes reaction of the two studied drugs with sodium nitrite and hydrochloric acid for diazo
... Show MoreThis paper presents two main parts: The first part involves manufacturing the specimens form composite material for mechanical testing (tensile, flexural and fatigue tests), then design a custom foot orthesis (CFO) and manufacturing from composite lamination (3nylglass 2carbon fiber 3nylglass) for patient suffer from flexible flat foot since birth and over-pronation. The second part of this research involves a design a model of custom foot orthesis in (solid work 2018) and then analysis of custom foot orthosis in engineering analysis program (ANSYS V.18.2).The applied pressure in boundary condition adopted from Force Sensor Resistance (FSR 402 ) in various regions in foot after wearing composite CFO. Used a composite materials in engineerin
... Show MorePassive optical network (PON) is a point to multipoint, bidirectional, high rate optical network for data communication. Different standards of PONs are being implemented, first of all PON was ATM PON (APON) which evolved in Broadband PON (BPON). The two major types are Ethernet PON (EPON) and Gigabit passive optical network (GPON). PON with these different standards is called xPON. To have an efficient performance for the last two standards of PON, some important issues will considered. In our work we will integrate a network with different queuing models such M/M/1 and M/M/m model. After analyzing IPACT as a DBA scheme for this integrated network, we modulate cycle time, traffic load, throughput, utilization and overall delay
... Show MoreThis study aims to explore the impact of the interaction of the university leadership and the university organizational environment on the performance level of the staff at Al-Maaqal university. This university was chosen as a field of study because it is a new university and needs studies that develops and contributes to improve its overall performance. The problem defined by the following question: to what extent does the interaction of the university leadership and the university organizational environment affect the performance level of the teaching staff at AlMaaqal University?). The method of this study adopted a major hypothesis in which there is a statistically significant effect of university leadership and university environment o
... Show MoreBecause of the new political stage that Iraq is living in, which called on researchers to choose the subject of political marketing and increase its effectiveness through strategic intuition. The problem of research was reflected in the following question: How can strategic intuition be used to achieve efficiency in marketing marketing to achieve voter acceptance and achieve political success later on? ).
The research derives its importance from the fact that it is related to the developments in the concepts and areas of marketing in various fields, and it has a role in identifying the gain of new markets, where it is specialized to provide a political product and identify the mechanism of marketing the p
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for