Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

The research aims to get acquainted with the evaluation of the reality of the application of the curriculum axis from among the eight Iraqi academic accreditation standards in a sample of governmental and private universities and colleges in Iraq and to identify the main and secondary reasons for it as well as to provide proposed mechanisms and procedures to help reduce gaps, If the research problem is represented in the weak availability of the requirements of the curriculum axis in universities and colleges (the study sample) due to the weak documentation and successful implementation of them and interest in them is still below the level of ambition, In order to arrive at scientific facts, the researchers adopted the comparativ

Nanoparticles (NPs) based techniques have shown great promises in all fields of science and industry. Nanofluid-flooding, as a replacement for water-flooding, has been suggested as an applicable application for enhanced oil recovery (EOR). The subsequent presence of these NPs and its potential aggregations in the porous media; however, can dramatically intensify the complexity of subsequent CO2 storage projects in the depleted hydrocarbon reservoir. Typically, CO2 from major emitters is injected into the low-productivity oil reservoir for storage and incremental oil recovery, as the last EOR stage. In this work, An extensive serious of experiments have been conducted using a high-pressure temperature vessel to apply a wide range of CO2-pres

The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme

Removing hazardous organic pollutants, such as 4-nitrophenol (4-NP) and Congo red (CR) dyes from aqueous media and CO2 from the atmospheric medium remains a significant challenge. Herein, we report a facile in-situ synthetic approach for fabricating CuO-ZnO heterostructure photocatalysts through the surfactant-assisted co-precipitation method. The catalytic results demonstrate that the Cu1O-ZnO photocatalyst exhibits excellent activity under direct sunlight irradiation, owing to the heterostructure formation between the CuO and ZnO. The Cu1O-ZnO photocatalyst showed higher reaction rate constant (k) values of 0.20 min−1 for 4-NP and 0.09 min−1 for CR compared to previous reports. Additionally, efficient CO2 reduction was also achiev

Water pollution has created a critical threat to the environment.‎‎ A lot of research has been done ‎recently to use surface-enhanced Raman spectroscopy (SERS) to detect multiple pollutants in water. This study aims to use Ag colloid nanoflowers as liquid SERS enhancer. Tri sodium phosphate (Na₃PO₄) was investigated as a pollutant using liquid SERS ‎based on colloidal Ag ‎nanoflowers. The chemical method was used to synthesize nanoflowers from silver ‎ions. Atomic Force Microscope (AFM), Scanning Electron Microscope (SEM), and X-ray diffractometer (XRD) were employed to characterize the silver nanoflowers. This ‎nanoflowers SERS action in detecting Na₃PO₄ was reported and analyzed

Abstract—In this study, we present the experimental results of ultra-wideband (UWB) imaging oriented for detecting small malignant breast tumors at an early stage. The technique is based on radar sensing, whereby tissues are differentiated based on the dielectric contrast between the disease and its surrounding healthy tissues. The image reconstruction algorithm referred to herein as the enhanced version of delay and sum (EDAS) algorithm is used to identify the malignant tissue in a cluttered environment and noisy data. The methods and procedures are tested using MRI-derived breast phantoms, and the results are compared with images obtained from classical DAS variant. Incorporating a new filtering technique and multiplication procedure, t

Reservoir characterization is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling. This comprehensive research paper delves into the complex interplay of rock materials, rock formation techniques, and geological modeling techniques for improving reservoir quality. The research plays an important role dominated by petrophysical factors such as porosity, shale volume, water content, and permeability—as important indicators of reservoir properties, fluid behavior, and hydrocarbon potential. It examines various rock cataloging techniques, focusing on rock aggregation techniques and self-organizing maps (SOMs) to identify specific and

Vehicular Ad Hoc Networks (VANETs) are integral to Intelligent Transportation Systems (ITS), enabling real-time communication between vehicles and infrastructure to enhance traffic flow, road safety, and passenger experience. However, the open and dynamic nature of VANETs presents significant privacy and security challenges, including data eavesdropping, message manipulation, and unauthorized access. This study addresses these concerns by leveraging advancements in Fog Computing (FC), which offers lowlatency, distributed data processing near-end devices to enhance the resilience and security of VANET communications. The paper comprehensively analyzes the security frameworks for fog-enabled VANETs, introducing a novel taxonomy that c

The research aimed to evaluate the financial performance of the Public Company for the manufacture of medicines and medical supplies / Samarra - Iraq to know the strengths and weaknesses that affect its performance, as well as to compare its performance in the years between (2017-2019), which are characterized by security stability with its performance in previous years (2014 -2016) which is characterized by security instability, to assess the extent of its ability to achieve growth in performance, by answering the main question, what is the evaluation of the performance of the Public Company for the manufacture of medicines and medical supplies / Samarra - Iraq in the light of financial indicators?