Binary mixtures of three, heavy oil-stocks was subjected to density measurements at temperatures of 30, 35 and 40 °C. and precise data was acquired on the volumetric behavior of these systems. The results are reported in terms of equations for excess specific volumes of mixtures. The heavy oil-stocks used were of good varity, namely 40 stock, 60 stock, and 150 stock. The lightest one is 40 stock with °API gravity 33.69 while 60 stock is a middle type and 150 stock is a heavy one, with °API gravity 27.74 and 23.79 respectively. Temperatures in the range of 30-40 °C have a minor effect on excess volume of heavy oil-stock binary mixture thus, insignificant expansion or shrinkage is observed by increasing the temperature this effect becomes more significant although the heavy oil-stocks is spiked with hydrocarbons like (gas oil, toluene and reformate). Blending of Heavy oil-stocks with hydrocarbons spikes (gas oil, toluene and reformate) form non-ideal mixtures, for which excess volume can be positive or negative depending on nature species. Spiking of Heavy oil-stocks with either gas oil or reformate resulted in negative excess volume. This shrinkage is greater for the lowest boiling point spike as in the case of reformate, While, the presence of methyl groups in aromatic rings results in a positive excess volume, as shown in toluene when blended with 40 stock but a negative excess volume was found when blended with 60 stock and 150 stock. The API gravity of heavy oil-stocks has an effect on excess volume when the oil-stocks spiked with hydrocarbons like (gas oil, toluene and reformate). This 40 stocks as a typical light types resulted in minimum negative excess volume of -0.47 at 30 °C, when it was spiked with the gas oil; while the spiked heavy oil-stock with kerosene shows a maximum excess volume of -15.56 at 40 °C.
The downhole flow profiles of the wells with single production tubes and mixed flow from more than one layer can be complicated, making it challenging to obtain the average pressure of each layer independently. Production log data can be used to monitor the impacts of pressure depletion over time and to determine average pressure with the use of Selective Inflow Performance (SIP). The SIP technique provides a method of determining the steady state of inflow relationship for each individual layer. The well flows at different stabilized surface rates, and for each rate, a production log is run throughout the producing interval to record both downhole flow rates and flowing pressure. PVT data can be used to convert measured in-situ rates
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Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are
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PMMA (Poly methyl methacrylate) is considered one of the most commonly used materials in denture base fabrication due to its ideal properties. Although, a major problem with this resin is the frequent fractures due to heavy chewing forces which lead to early crack and fracture in clinical use. The addition of nanoparticles as filler performed in this study to enhance its selected mechanical properties. The Nano-additive effect investigated in normal circumstances and under a different temperature during water exposure. First, tests applied on the prepared samples at room temperature and then after exposure to water bath at (20, 40, 60) C° respectively. SEM, PSD, EDX were utilized for samples evaluation in this study. Flexural
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The study was conducted to evaluate the antifungal activity of the aqueous and
alcoholic extract and the essential oil of E. incrassata leaves toward some biological
characteristics of the water mold S. ferax. Chemical analysis of the plant leaves using HPLC
showed the content of several active compounds included 1,8-Cineole, Terpineal, Citronellal,
Phellendrene and Citiric acid.
Treatment of the fungus growing on solid media containing different concentrations of
the extracts showed significant gradual decrease in radial growth with the increasing
concentration, and the effect varied with the different extracts.
Treatment of the fungus grown in distilled water on sesame seeds with different
concentratio
The investment government expenditure is considered the fundamental of enhancing the economic activity as it has become a mean for achieving capital accumulation in all economic sectors, The Iraqi economy is characterized of being yield unilateral depending petroleum revenues as an essential resource of financing government expenditure , as the contribution of petroleum sector in GDP is large in proportions to other economic sectors contribution.
The relationship between investing government expenditure, and non-oil GDP is about to be not existent during the
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Computational study of three-dimensional laminar and turbulent flows around electronic chip (heat source) located on a printed circuit board are presented. Computational field involves the solution of elliptic partial differential equations for conservation of mass, momentum, energy, turbulent energy, and its dissipation rate in finite volume form. The k-ε turbulent model was used with the wall function concept near the walls to treat of turbulence effects. The SIMPLE algorithm was selected in this work. The chip is cooled by an external flow of air. The goals of this investigation are to investigate the heat transfer phenomena of electronic chip located in enclosure and how we arrive to optimum level for cooling of this chip. These par
... Show MoreThin films of pure polycarbonate (PC) with anthracene doping PC films for different doping ratios (10, 20, 30, 40, 50 and 60 ml) were prepared by using a casting method. The influence of anthracene doping ratio on photo-fries rearrangement of polycarbonate was systematic investigated. Furthermore, pure PC and anthracene doping PC films were irradiated via UV light at a wavelength (254 nm) for different periods (5, 240, 288, and 360 hrs). The photo-fries rearrangement occurring in pure PC and anthracene doping PC films were monitored using UV and FTIR spectroscopies. The photo-fries rearrangement leads to scission the carbonate linkage and formation phenylsalicylate and dihydroxybenzophenes. The result of the UV spectrum confirms disappea
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This work involves hard photon rate production from quark -gluon plasma QGP interaction in heavy ion collision. Using a quantum chromodynamic model to investigate and calculation of photons rate in 𝑐𝑔 → 𝑠𝑔𝛾 system due to strength coupling, photons rate, temperature of system, flavor number and critical. The photons rate production computed using the perturbative strength models for QGP interactions. The strength coupling was function of temperature of system, flavor number and critical temperature. Its influenced by force with temperature of system, its increased with decreased the temperature and vice versa. The strength coupling has used to examine the confinement and deconfinement of quarks in QGP properties and inf
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The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti
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