IMPLICATION OF GEOMECHANICAL EVALUATION ON TIGHT RESERVOIR DEVELOPMENT / SADI RESERVOIR HALFAYA OIL FIELD

This study aims to determine the impact of organization values as an independent variable across its dimensions (organization management values, organization mission values, relations management values, and environment management values) on achieve the strategic success which is the dependent variable and include its dimensions  (environmental analysis, creative thinking, strategic decision, effective implementation, and leadership capacities). The study is conducted in the Iraq Oil Ministry. It deployed the analytical descriptive approach. It focuses on the study problem enquiries throughout addressing several principal and sub-hypothesizes in regards to cause and effect relationship. To achieve this result

The majority of real-world problems involve not only finding the optimal solution, but also this solution must satisfy one or more constraints. Differential evolution (DE) algorithm with constraints handling has been proposed to solve one of the most fundamental problems in cellular network design. This proposed method has been applied to solve the radio network planning (RNP) in the forthcoming 5G Long Term Evolution (5G LTE) wireless cellular network, that satisfies both deployment cost and energy savings by reducing the number of deployed micro base stations (BSs) in an area of interest. Practically, this has been implemented using constrained strategy that must guarantee good coverage for the users as well. Three differential evolution

Shiranish formation has been divided into two microfacies units: 1-Marly biowacke stone facies 2-Biogenic pack stone facies These microfacies reflected marine deep shelf margin in the upper part of the formation, the lower part was deeper. 238 slides were investigated depending on Mineralogical, compositional and Biological processes, which reflect deep shelf margin at upper part of the formation, but at the lower part open sea environment. The age of the formation is estimated depending on the recognized biostratigraphic zone using the index fossils to be Upper- Middle Maestrichtian.

A new Differential Evolution (ARDE) algorithm is introduced that automatically adapt a repository of DE strategies and parameters adaptation schemes of the mutation factor and the crossover rate to avoid the problems of stagnation and make DE responds to a wide range of function characteristics at different stages of the evolution. ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. Then a new adaptive procedure called adaptive repository (AR) has been developed to select the appropriate combinations of the JADE strategies and the parameter control schemes of the MDE_pBX to generate the next population based on their fitness values. Experimental results have been presented to confirm the reli

The research studies the sculptural formation in the third millennium: styles and trends, by taking the most important results of sculpture in the third millennium. The problem of the research is to search for the new sculptural formation in what it constitutes of social and human importance, and what are the important factors in forming the   contemporary sculptural structure, and what is the mechanism of showing and producing the new formation. The research requires the study of the most important thing that the (sculptural formation in the third millennium styles and trends) represents. The importance of research depends on the importance of the sculptural formation after the twentieth century and the importance that the for

هدف البحث الى بيان طبيعة ارتباط والتأثير بين الضغوط التنافسية (المتغير المستقل) والتجديد الاستراتيجي (المتغير التابع) ، تم تطبيق البحث في فنادق الدرجة الممتازة في بغداد. وبلغت عدد افراد عينة البحث (99) مديراً يعملون في (6) فنادق من الدرجة (الممتازة) ببغداد، وهي (فندق الرشيد، فندق عشتار، فندق ميريديان، فندق المنصور، فندق بابل، وفندق بغداد) وتم اجراء التحليل الاحصائي باستخدام البرنامج الاحصائي AMOS وظهرت وجود تنافسي

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