Abstract

        This research aims to evaluate the application of the inspectors general of global indicators offices according to the axles (leadership, strategy and planning, employees, partners and resources, process management) and through the assumption main research which states that (there is an application for global indicators to evaluate performance in the offices of the ministries under study) which are subdivided into five sub-hypotheses according to the classification and division of the five axes of the checklist.

The researchers have taken refuge in the process of assessing the performance of the check list which included global i

This study focuses on evaluating the suitability of three interpolation methods in terms of their accuracy at climate data for some provinces of south of Iraq. Two data sets of maximum and minimum temperature in February 2008 from nine meteorological stations located in the south of Iraq using three interpolation methods. ArcGIS is used to produce the spatially distributed temperature data by using IDW, ordinary kriging, and spline. Four statistical methods are applied to analyze the results obtained from three interpolation methods. These methods are RMSE, RMSE as a percentage of the mean, Model efficiency (E) and Bias, which showed that the ordinary krigingis the best for this data from other methods by the results that have b

This study utilizes streamline simulation to model fluid flow in the complex subsurface environment of the Mishrif reservoir in Iraq's Buzurgan oil field. The reservoir faces challenges from high-pressure depletion and a substantial increase in water cut during production, prompting the need for innovative reservoir management. The primary focus is on optimizing water injection procedures to reduce water cuts and enhance overall reservoir performance. Three waterflooding tactics were examined: normal conditions without injectors or producers, normal conditions with 30 injectors and 80 producers and streamline simulation using the frontsim simulator. Three main strategies were employed to streamline water injection in targeted areas.

The most significant function in oil exploration is determining the reservoir facies, which are based mostly on the primary features of rocks. Porosity, water saturation, and shale volume as well as sonic log and Bulk density are the types of input data utilized in Interactive Petrophysics software to compute rock facies. These data are used to create 15 clusters and four groups of rock facies. Furthermore, the accurate matching between core and well-log data is established by the neural network technique. In the current study, to evaluate the applicability of the cluster analysis approach, the result of rock facies from 29 wells derived from cluster analysis were utilized to redistribute the petrophysical properties for six units of Mishri

Accurate pore and fracture pressure detection is a major step in successful drilling operations design. The overestimation of these parameters absolutely leads to serious problems throughout and after well drilling. This study is concerned with the characterization and analysis of the most significant diagenetic processes that degrade or improve the reservoir characteristics of the Mauddud Formation in the Badra oil field. The primary goal of this research is to estimate the pore pressure and fracture pressure using well logging data by Techlog 2015 software in order to assess the impact on the estimation of the mud weight window (MWW). The estimated values of formation pressures are then analyzed according to different diagenetic p

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

Records of two regionalized variables were processed for each of porosity and permeability of reservoir rocks in Zubair Formation (Zb-109) south Iraq as an indication of the most important reservoir property which is the homogeneity,considering their important results in criterion most needed for primary and enhanced oil reservoirs.The results of dispersion treatment,the statistical incorporeal indications,boxes plots,rhombus style and tangents angles of intersected circles indicated by confidence interval of porosity and permeability data, have shown that the reservoir rocks of Zubair units (LS),(1L) and (DJ) have reservoir properties of high quality,in contrast to that of Zubair units (MS) and (AB)which have reservoir properties of less q