Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is used to train the model, where the model prediction result is validated with core permeability. Seven oil well logs were used as input parameters, and the model was constructed with Techlog software. The predicted permeability with the model compared with Schlumberger-Doll-Research permeability as a cross plot, which results in the correlation coefficient of 94%, while the predicted permeability validated with the core permeability of the well, which obtains good agreement where R2 equals 80%. The model was utilized to forecast permeability in a well that did not have a nuclear magnetic resonance log, and the predicted permeability was cross-plotted against core permeability as a validation step, with a correlation coefficient of 77%. As a result, the low percentage of matching was due to data limitations, which demonstrated that as the amount of data used to train the model increased, so did the precision.
The current study was designed to remove Lead, Copper and Zinc from industrial wastewater using Lettuce leaves (Lactuca sativa) within three forms (fresh, dried and powdered) under some environmental factors such as pH, temperature and contact time. Current data show that Lettuce leaves are capable of removing Lead, Copper and Zinc ions at significant capacity. Furthermore, the powder of Lettuce leaves had highest capability in removing all metal ions. The highest capacity was for Lead then Copper and finally Zinc. However, some examined factors were found to have significant impacts upon bioremoval capacity of studied ions, where best biosorption capacity was found at pH 4, at temperature 50º C and contact time of 1 hour.
Background: laparoscopic cholecystectomy (LC) is getting popularity for the treating of symptomatic gall bladder disease; conversion from laparoscopic to open cholecystectomy (OC) is also common.
Objective : To find out the prevalence of causes, risk factors of conversion from LC to OC among patient suffering from gall bladder disease, and to explore the most common causes of conversion from laparoscopic to open cholecystectomy.
Methods: This prospective study was conducted in the department of general surgery at Alkindy teaching hospital from first of January 2016 to the end of December 2017 .Nine hundred twenty patient were included. Patient age, gender, his
... Show MoreViolence is a very serious phenomenon affecting the upbringing and culture kids, are playing the most violent forms of development of these Phenomenon, the research aims to determine the role of the media in reducing violence, and conducted a field study on parents Children by 200 form, the results revealed the importance of the media in raising awareness of the risks of violence on the child Especially television, which hugely increased Show features, as well as the role of parents in guiding the child to buy Useful because the game to play negative impact of violence on children's health, and the media play an important role in raising awareness of these Risks through educational programs and television commercials, and o
... Show MoreEvery so often, a confluence of novel technologies emerges that radically transforms every aspect of the industry, the global economy, and finally, the way we live. These sharp leaps of human ingenuity are known as industrial revolutions, and we are currently in the midst of the fourth such revolution, coined Industry 4.0 by the World Economic Forum. Building on their guideline set of technologies that encompass Industry 4.0, we present a full set of pillar technologies on which Industry 4.0 project portfolio management rests as well as the foundation technologies that support these pillars. A complete model of an Industry 4.0 factory which relies on these pillar technologies is presented. The full set of pillars encompasses cyberph
... Show MoreBackground: Measuring implant stability is an important issue in predicting treatment success. Dental implant stability is usually measured through resonance frequency analysis (RFA). Osstell® RFA devices can be used with transducers (Smartpeg™) that correspond to the implants used as well as with transducers designed for application with Penguin® RFA devices (Multipeg™). Aims: This study aims to assess the reliability of a MultiPeg™ transducer with an Osstell® device in measuring dental implant stability. Materials and Methods: Sixteen healthy participants who required dental implant treatment were enrolled in this study. Implant stability was measured by using an Osstell® device with two transducers, namely, Smartpeg™ and M
... Show MoreThis research examines the future of television work in light of the challenges posed by artificial intelligence (AI). The study aims to explore the impact of AI on the form and content of television messages and identify areas where AI can be employed in television production. This study adopts a future-oriented exploratory approach, utilizing survey methodology. As the research focuses on foresight, the researcher gathers the opinions of AI experts and media specialists through in-depth interviews to obtain data and insights. The researcher selected 30 experts, with 15 experts in AI and 15 experts in media. The study reveals several findings, including the potential use of machine learning, deep learning, and na
... Show MoreABSTRACT This study presents an efficient approach for the separation and preconcentration of norepinephrine (NOR) from pharmaceutical formulations, environmental water, and human urine samples using a dispersive micro – solid phase extraction (DμSPE) technique employing magnetic nanoadsorbents. Two adsorbents, Fe3O4@TTAB and Fe3 O4@SiO2@TTAB, were prepared by functionalising iron oxide and silicacoated iron oxide nanoparticles with the cationic surfactant tetradecyltrimethylammonium bromide (TTAB). NOR was first converted into a sensitive diazonium dye via reaction with diazotised sulphamethazine and then extracted using mixed ademicelle – hemimicelle magnetic solid-phase extraction, followed by spectrophotometric quantification. Key
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Magnetic abrasive finishing (MAF) is one of the advanced finishing processes, which produces a high level of surface quality and is primarily controlled by a magnetic field. This paper study the effect of the magnetic abrasive finishing system on the material removal rate (MRR) and surface roughness (Ra) in terms of magnetic abrasive finishing system for eight of input parameters, and three levels according to Taguchi array (L27) and using the regression model to analysis the output (results). These parameters are the (Poles geometry angle, Gap between the two magnetic poles, Grain size powder, Doze of the ferromagnetic abrasive powder, DC current, Workpiece velocity, Magnetic poles velocity, and Finishi
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