The current study focuses on utilizing artificial intelligence (AI) techniques to identify the optimal locations of production wells and types for achieving the production company’s primary objective, which is to increase oil production from the Sa’di carbonate reservoir of the Halfaya oil field in southeast Iraq, with the determination of the optimal scenario of various designs for production wells, which include vertical, horizontal, multi-horizontal, and fishbone lateral wells, for all reservoir production layers. Artificial neural network tool was used to identify the optimal locations for obtaining the highest production from the reservoir layers and the optimal well type. Fo
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
... Show MoreAn 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
... Show MoreKnowledge 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
... Show MoreThe 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
... Show MoreThe skin temperature of the earth’s surface is referred to as the Land Surface Temperature (LST). the availability of long-term and high-quality temperature records is important for various uses that affect people’s lives and livelihoods. Much valid information was provided to this research from remote sensing technology by using Landsat 8 (L8) imagery to estimate LST for Al-Ahdab oil field in Wasit city in Iraq. The aim of this research is to analyze LST variations based on Landsat 8 data for 2022 (January, April, July, and October). ArcMap 10.8 was used to estimate LST results. The results values ranged from (about 10 C in January to about 46 C in July). The results show that LS