An optimization study was conducted to determine the optimal operating pressure for the oil and gas separation vessels in the West Qurna 1 oil field. The ASPEN HYSYS software was employed as an effective tool to analyze the optimal pressure for the second and third-stage separators while maintaining a constant operating pressure for the first stage. The analysis involved 10 cases for each separation stage, revealing that the operating pressure of 3.0 Kg/cm2 and 0.7 Kg/cm2 for the second and third stages, respectively, yielded the optimum oil recovery to the flow tank. These pressure set points were selected based on serval factors including API gravity, oil formation volume factor, and gas-oil ratio from the flow tank.    To impro

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

The Aaliji Formation in wells (BH.52, BH.90, BH.138, and BH.188) in Bai Hassan Oil Field in Low Folded Zone northern Iraq has been studied to recognize the palaeoenvironment and sequence stratigraphic development. The formation is bounded unconformably with the underlain Shiranish Formation and the overlain Jaddala Formation. The microfacies analysis and the nature of accumulation of both planktonic and benthonic foraminifera indicate the two microfacies associations; where the first one represents deep shelf environment, which is responsible for the deposition of the Planktonic Foraminiferal Lime Wackestone Microfacies and Planktonic Foraminiferal Lime Packstone Microfacies, while the second association represents the deep-sea environme

Knowledge of the distribution of the rock mechanical properties along the depth of the wells is an important task for many applications related to reservoir geomechanics. Such these applications are wellbore stability analysis, hydraulic fracturing, reservoir compaction and subsidence, sand production, and fault reactivation. A major challenge with determining the rock mechanical properties is that they are not directly measured at the wellbore. They can be only sampled at well location using rock testing. Furthermore, the core analysis provides discrete data measurements for specific depth as well as it is often available only for a few wells in a field of interest. This study presents a methodology to generate synthetic-geomechani

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.

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.

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 poros