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.
Knowledge 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 MoreIn this experimental and numerical analysis, three varieties of under-reamed piles comprising one bulb were used. The location of the bulb changes from pile to pile, as it is found at the bottom, center, and top of the pile, respectively.
In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe
... Show MoreThis work aims to optimize surface roughness, wall angle deviation, and average wall thickness as output responses of ALuminium-1050 alloy cone formed by the single point incremental sheet metal forming process. The experiments are accomplished based on the use of a mixed level Taguchi experimental design with an L18 orthogonal array. Six levels of step depth, three levels of tool diameter, feed rate, and tool rotational speed have been considered as input process parameters. The analyses of variance (ANOVA) have been used to investigate the significance of parameters and the effect of their levels for minimum surface roughness, minimum wall angle deviation, and maximum average wall thickness. The results indicate that step depth and tool r
... Show MoreBackground: The study was designed for the assessment of the knowledge of medical students regarding pandemics. In the current designed study, the level of awareness was checked and the majority of students were found aware of SARS-CoV and SARS-Cov2 (Covid-19).
Objective: To assess the awareness of SARS-CoV and SARS-Cov2 (Covid-19) among medical students of Pakistan.
Subjects and Methods: A cross-sectional survey was carried out in different universities of Pakistan from May to August 2020. A self-constructed questionnaire by Pursuing the clinical and community administration of COVID-19 given by the National Health Commission of the People's Republic of China was used am
... Show MoreThis work is the first study of the Curculionoidea fauna from Kurdistan region of Iraq, based on the intensive survey in different localities of Kurdistan from March 2016 to November 2017. In total, 41 species belonging to 28 genera, 21 tribes and 3 families were collected and identified, including 25 species newly recorded for the Iraqi fauna.
General distribution, collecting localities and methods, with plant association data for each species are given.
Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.
In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation
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