Optimum perforation location selection is an important study to improve well production and hence in the reservoir development process, especially for unconventional high-pressure formations such as the formations under study. Reservoir geomechanics is one of the key factors to find optimal perforation location. This study aims to detect optimum perforation location by investigating the changes in geomechanical properties and wellbore stress for high-pressure formations and studying the difference in different stress type behaviors between normal and abnormal formations. The calculations are achieved by building one-dimensional mechanical earth model using the data of four deep abnormal wells located in Southern Iraqi oil fields. The magnitude of different stress types and geomechanical properties was estimated from well-log data using the Techlog software. The directions of the horizontal stresses are determined in the current wells utilizing image-log formation micro-imager (FMI) and caliper logs. The results in terms of rock mechanical properties showed a reduction in Poisson’s ratio, Young modulus, and bulk modulus near the high-pressure zones as compared to normal pressure zones because of the presence of anhydrite, salt cycles, and shales. Low maximum and minimum horizontal stress values are also observed in high-pressure zones as compared to normal pressure zones indicating the effects of geomechanical properties on horizontal stress estimation. Around the wellbore of the studied wells, formation breakouts are the most expected situation according to the results of the wellbore stress state (effective vertical stress (
After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings
... Show MoreGender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea
... Show MoreThe aim of the present work is the synthesis of new carbohydrate derivatives containing 1,2,4-triazole from D-fructose . To obtain these derivatives, the diacetone fructose (1 ) was chosen as the starting material, which was obtained from the reaction of anhydrous fructose with dry acetone in presence of anhydrous ferric chloride. Oxidation of ( 1) with potassium permanganate in potassium hydroxide solution gave the acid ( 2). Esterification of the acid with dimethyl sulphate gave the methyl ester (3 ). Treatment of the methyl ester (3 ) with hydrazine hydrate gave the hydrazide (4 ), which is the desired Chiron. The hydrazide (4 ) was used for the preparation of 1,2,4-triazole-5-one (6 ) derivative. These compounds was synthesized by the i
... Show MoreThe world's population growth and the increasing demand for new infrastructure facilities and buildings , present us with the vision of a higher resources consumption, specially in the form of more durable concrete such as High Performance Concrete (HPC) . Moreover , the growth of the world pollution by plastic waste has been tremendous. The aim of this research is to investigate the change in mechanical properties of HPC with added waste plastics in concrete. For this purpose 2.5%, 5% and 7.5% in volume of natural fine aggregate in the HPC mixes were replaced by an equal volume of Polyethylene Terephthalate (PET) waste , got by shredded PET bottles. The mechanical propert
... Show MoreThe soap content in biodiesel is an important challenge during the production and purification processing of biodiesel. Natural deep eutectic solvents (NADES) have recently attracted considerable interest as an environmentally suitable substitute for traditional solvents in the biodiesel industry. This work investigates the soap removal from the contaminated biodiesel using NADES. Eight choline chloride‐based deep eutectic solvents (DESs) were screened using the conductor‐like screening model for real solvents (COSMO‐RS) to identify the most suitable solvent for soap removal and were validated experimentally. The effect of NADES molar ratio, NADES:biodiesel ratio, mixing speed and extraction ti
Background: Hypertension is a major global health concern that increases the risk of cardiovascular disease. Understanding the impact of age and treatment types on blood pressure control is essential for optimizing therapeutic strategies. Aim: This study aims to assess how different treatment types and patient age influence blood pressure control in hypertensive patients. Methodology: A binary logistic regression model was employed to analyze data from 48 patients diagnosed with hypertension. The study investigated the impact of two treatment regimens and patient age on the likelihood of achieving optimal blood pressure levels. The statistical significance of the findings was evaluated using chi-square tests and p-values. Results: T
... Show MoreHypothesis Nanofluid flooding has been identified as a promising method for enhanced oil recovery (EOR) and improved Carbon geo-sequestration (CGS). However, it is unclear how nanoparticles (NPs) influence the CO2-brine interfacial tension (γ), which is a key parameter in pore-to reservoirs-scale fluid dynamics, and consequently project success. The effects of pressure, temperature, salinity, and NPs concentration on CO2-silica (hydrophilic or hydrophobic) nanofluid γ was thus systematically investigated to understand the influence of nanofluid flooding on CO2 geo-storage. Experiments Pendant drop method was used to measure CO2/nanofluid γ at carbon storage conditions using high pressure-high temperature optical cell. Findings CO2/nano
... Show MoreThe issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator
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