In the present work, the efficiency of Tri-octyl Methyl Ammonium Chloride (TOMAC) ionic liquid was investigated as new and green demulsifier for three types of Iraqi crude oil emulsions (Nafut Khana (NK), Kirkuk and Basrah). The separation efficiency was studied at room temperature and by using microwave heating technique. Several batch experiments were done to specify the suitable conditions for the emulsification and demulsification which were specified as 45 minutes and 3000 rpm for crude oil emulsification while the ionic liquid doses were (500,300,150,50) ppm and the conditions of microwave heating were 1000 watt and 50 second as irradiation time. The results were very encouraging especially for NK and Kirkuk crude oil emulsions whe

The Jeribe reservoir in the Jambour Oil Field is a complex and heterogeneous carbonate reservoir characterized by a wide range of permeability variations. Due to limited availability of core plugs in most wells, it becomes crucial to establish correlations between cored wells and apply them to uncored wells for predicting permeability. In recent years, the Flow Zone Indicator (FZI) approach has gained significant applicability for predicting hydraulic flow units (HFUs) and identifying rock types within the reservoir units.

   This paper aims to develop a permeability model based on the principles of the Flow Zone Indicator. Analysis of core permeability versus core porosity plot and Reservoir Quality Index (RQI) - Normalized por

Abstract

      This research aims to know the effect of job burnout in the worker’s performance. The researcher presented a theoretical basis for job burnout and the worker's performance. In order to achieve the objectives of the research, a hypothesis was drawn up that determines the nature of the relationship between the independent variable of job burnout and its dimensions (reduced personal accomplishment, depersonalization, Emotional Exhaustion) and variable dependent performance of workers dimensions (productivity, job satisfaction, organizational commitment, creativity), And to represent the volume of this community according to (de Morgan, D. Morgan) glo

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

The research dealt with the analysis of the relations between the GDP of the agricultural sector in Iraq, oil prices, the exchange rate and the GDP both on the short term and long term. The research adopted data analysis for the period from 1980-2019 using the ARDL model. the results indicate the existence of long-term relationships between oil prices and the prices of each agricultural commodity at a significance level of 5%. Also, oil prices have a negative consequence on agricultural production in Iraq, and the Iraqi economy is a rentier economy that depends mainly on oil as a source of income and budget financing.

Gypseous soil covers approximately 30% of Iraqi lands and is widely used in geotechnical and construction engineering as it is. The demand for residential complexes has increased, so one of the significant challenges in studying gypsum soil due to its unique behavior is understanding its interaction with foundations, such as strip and square footing. This is because there is a lack of experiments that provide total displacement diagrams or failure envelopes, which are well-considered for non-problematic soil. The aim is to address a comprehensive understanding of the micromechanical properties of dry, saturated, and treated gypseous sandy soils and to analyze the interaction of strip base with this type of soil using particle image

Exploring the antibacterial potential of neem oil (Azadirachta indica) in combination with gentamicin (GEN) against pathogenic molds, especially Pseudomonas aeruginosa, has drawn concern due to the quest for natural treatment options against incurable diseases. Prospective research directions include looking for natural cures for many of the currently incurable diseases available now. microbial identification system, were used to identify the isolates. The research utilized a range of methods, such as the diffusion agar well (AWD) assays, TEM (transmission electron microscopy) analysis, minimum inhibitory concentration (MIC) assays, and real-time PCR (RT-qPCR) to analyze bacterial expression and the antibacterial action of neem oil (Azadira

This review examines how artificial intelligence (AI) including machine learning (ML), deep learning (DL), and the Internet of Things (IoT) is transforming operations across exploration, production, and refining in the Middle Eastern oil and gas sector. Using a systematic literature review approach, the study analyzes AI adoption in upstream, midstream, and downstream activities, with a focus on predictive maintenance, emission monitoring, and digital transformation. It identifies both opportunities and challenges in applying AI to achieve environmental and economic goals. Although adoption levels vary across the region, countries such as Saudi Arabia, the UAE, and Qatar are leading initiatives that align with global sustainability targets.