EMS in accordance with ISO 14001: 2015 is considered an entry point to reduce environmental impacts, especially the effects resulting from the oil industry, which is the main source of environmental pollution and waste of natural resources, since the second revision of the standard took place in September 2015. The problem of the research was manifested in the weakness in understanding the correct guidelines that must be followed in order to obtain and maintain the standard. The purpose of this research was to give a general picture of what is behind ISO14001:2015 and how it is possible to create a comprehensive base for understanding its application by seeking the gap between the actually achieved reality, standards requirements

 This paper aims to verify the existence of relationships between product innovation and the reputation of the organization. The study problem is that the State Organization for Marketing of Oil (SOMO) system is inflexible in terms of marketing procedures and needs innovative, unconventional methods in innovating its products and improving performance. The reputation of the organization. The importance of the study lies in that it is an attempt to raise the interest of SOMO in its approach to the research variables in order to enhance its competitive position in the future and improve the marketing business environment, which contributes to enhancing the reputation of the organization by product innovation. The study sample

Particulate matter (PM) emitted from diesel engine exhaust have been measured in terms of mass, using
99.98 % pure ethanol blended directly, without additives, with conventional diesel fuel (gas – oil),to
get 10 % , 15 %, 20 % ethanol emulsions . The resulting PM collected has been compared with those
from straight diesel. The engine used is a stationary single cylinder, variable compression ratio Ricardo
E6/US. This engine is fully instrumented and could run as a compression or spark ignition.
Observations showed that particulate matter (PM) emissions decrease with increasing oxygenate
content in the fuel, with some increase of fuel consumption, which is due to the lower heating value of
ethanol. The reduction in

Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

Horizontal wells have revolutionized hydrocarbon production by enhancing recovery efficiency and reducing environmental impact. This paper presents an enhanced Black Oil Model simulator, written in Visual Basic, for three-dimensional two-phase (oil and water) flow through porous media. Unlike most existing tools, this simulator is customized for horizontal well modeling and calibrated using extensive historical data from the South Rumaila Oilfield, Iraq. The simulator first achieves a strong match with historical pressure data (1954–2004) using vertical wells, with an average deviation of less than 5% from observed pressures, and is then applied to forecast the performance of hypothetical horizontal wells (2008–2011). The result