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Simulation of Kick Control Process During Drilling with Assumption of Two-phase Flow
, M.Sc. Thesis Sharif University of Technology ; Jamshidi, Saeed (Supervisor)
Abstract
During the drilling of oil and gas wells, the probability of a kick resulting in blow out is high. In the event of a kick, well should be controlled immediately and prevented blowing out. Common methods include: driller method, wait and weight method and concurrent method. In this project, simulation of well control process is done for common well control methods, for water based muds and oil based muds. Movement of different fluids, their combination and removal of fluid from the well are simulated and the results are listed. The flash calculations are done for oil based mud and dissolution of kick fluid in the oil based mud is considered. After simulating and calculating necessary...
Iran’s oil development scenarios by 2025 [electronic resource]
, Article Energy Policy ; Volume 56, May 2013, Pages 612-622 ; Sharif University of TechnologyImaging Method To Detect Low Probability of Intercept Radars
, Ph.D. Dissertation Sharif University of Technology ; Nayebi, Mohammad Mahdi (Supervisor) ; Norouzi, Yaser (Co-Advisor)
Abstract
In this thesis, a new passive method suitable for Geolocating LPI radars is introduced. The method uses two Electronic Support (ES) receivers placed on a fast moving platform (e.g., an airplane or a satellite). The proposed method has a high processing gain, which makes it highly suitable for very weak LPI signals. The processing gain of the method was analytically derived and illustrated with simulation to determine if the proposed method can detect LPI radars in much lower SNRs compared to regular time-frequency LPI detection methods. Also, the resolution of the proposed method in both range and cross-range direction in radar location finding was analyzed. Furthurmore, the effect of the...
Modelling the Physics of Collective Decision Making and Commuication by Signal Exchange
, Ph.D. Dissertation Sharif University of Technology ; Rouhani, Shahin (Supervisor) ; Roudi, Yaser (Co-Supervisor)
Abstract
In many biological populations, information about environmental conditions is acquired collectively, through information sharing among individuals, by exchanging signals. In order to achieve a better understanding of such systems, using methods borrowed from statistical physics, we introduce two mathematical models. First, a collective decision making model, for a community of individuals residing on a communication network, who live in an uncertain environment, in which individuals try to collectively find the environmental state. In the second model, a collective movement model, we consider a population of collectively moving individuals, in which individuals try to collectively find and...