The maximization of the net present value of the investment in oil field improvements is greatly aided by the optimization of well location, which plays a significant role in the production of oil. However, using of optimization methods in well placement developments is exceedingly difficult since the well placement optimization scenario involves a large number of choice variables, objective functions, and restrictions. In addition, a wide variety of computational approaches, both traditional and unconventional, have been applied in order to maximize the efficiency of well installation operations. This research demonstrates how optimization approaches used in well placement have progressed since the last time they were examined. Following that, the research looked at a variety of different optimization strategies, and it demonstrated the limitations of each strategy as well as the scope of its application in order to achieve a suitable level of accuracy and simulation run time. In conclusion, this study presents an all-encompassing analysis of the well location optimization approaches that are applied in the petroleum engineering area, ranging from traditional methods to contemporary methods that make use of artificial intelligence.
Gas-lift technique plays an important role in sustaining oil production, especially from a mature field when the reservoirs’ natural energy becomes insufficient. However, optimally allocation of the gas injection rate in a large field through its gas-lift network system towards maximization of oil production rate is a challenging task. The conventional gas-lift optimization problems may become inefficient and incapable of modelling the gas-lift optimization in a large network system with problems associated with multi-objective, multi-constrained, and limited gas injection rate. The key objective of this study is to assess the feasibility of utilizing the Genetic Algorithm (GA) technique to optimize t
In this article, a new deterministic primality test for Mersenne primes is presented. It also includes a comparative study between well-known primality tests in order to identify the best test. Moreover, new modifications are suggested in order to eliminate pseudoprimes. The study covers random primes such as Mersenne primes and Proth primes. Finally, these tests are arranged from the best to the worst according to strength, speed, and effectiveness based on the results obtained through programs prepared and operated by Mathematica, and the results are presented through tables and graphs.
Background and objective: Viral Hepatitis Type B&C is serious public health challenge throughout the world.Hepatitis B and C viruses still remain to be the major causes of chronic hepatitis.It is estimated that around 350-400 million people in the world are chronic carriers of HBV, which represents approximately 7% of the total populationwhereas infection with HCV is found in approximately 3% of the world population, which represents 160 million people. Hepatitis B infection has a wide range of seroprevalence in the Mediterranean countries ranging from intermediate (=>2% ) to high prevalence ( =>7%). World Health Organization estimated a prevalence rate for HCV infection of about 4.6% in Eastern Mediterranean in 1999. During the eightieths
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This research aims to understand complexity management and its impact on the use of the dynamic capabilities of a sample of private colleges. Private colleges are currently facing many crises, changes, unrest and high competitive pressures. Which is sometimes difficult or even impossible to predict. The recruitment of dynamic capabilities is also one of the challenges facing senior management at private colleges to help them survive and survive. Thus, the problem of research was (there is a clear insufficiency of interest in Complexity Management and trying to employ it in improving the dynamic capabilities of Colleges that have been discussed?). A group of private colleges was selected as a
... Show MoreShiranish formation has been divided into two microfacies units: 1 - Many biowackestone facies and 2 - maly packstone using planktonic foraminifera and other carbonate components in the rock cutting and core slides. Microfacies reflect marin deep shelf margin in the lower part of the formation, the upper part was deeper. The thickness of the formation is determined, depending on addition to the presence of echinoderm framents debris and spines. This is in disagreement with the 195 ft thickness reported by the Oil Exploration Company The age of the formation is estimated depending on the recognized biostratigraphic zone using the index fossils to be Upper - Middle Mastrichtion.
The aim: to evaluate combined microscopy techniques for determining the morphological and optical properties of methadone hydrochloride (MDN) crystals. Materials and methods: MDN crystal formation was optimized using a closed container method and crystals were characterized using polarized light microscope (PLM), scanning electron microscopy (SEM) and confocal microscopy (CM). SEM and CM were used to determine MDN crystal thickness and study its relationship with crystal retardation colours using the Michel-Levy Birefringence approach. Results: Dimensions (mean±SD) of diamond shaped MDN crystals were confirmed using SEM and CM. Crystals were 46.4±15.2 Vs 32.0±8.3 µm long, 28.03±8.2 Vs 20.85±5.5 µm wide, and 6.62±
... Show MoreIn oil and gas well cementing, a strong cement sheath is wanted to insure long-term safety of the wells. Successful completion of cementing job has become more complex, as drilling is being done in highly deviated and high pressure-high temperature wells. Use of nano materials in enhanced oil recovery, drilling fluid, oil well cementing and other applications is being investigated. This study is an attempt to investigate the effect of nano materials on oil well cement properties. Two types of nano materials were investigated, which are Nano silica (>40 nm) and Nano Alumina (80 nm) and high sulfate-resistant glass G cement is used. The investigated properties of oil well cement included compressive strength, thickening
... Show MoreThe recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach
... Show MoreDiverting river flow during construction of a main dam involves the construction of cofferdams, and tunnels, channels or other temporary passages. Diversion channels are commonly used in wide valleys where the high flow makes tunnels or culverts uneconomic. The diversion works must form part of the overall project design since it will have a major impact on its cost, as well as on the design, construction program and overall cost of the permanent works. Construction costs contain of excavation, lining of the channel, and construction of upstream and downstream cofferdams. The optimization model was applied to obtain optimalchannel cross section, height of upstream cofferdam, and height of downstream cofferdamwith minimum construction cost
... Show MoreThe 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