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Control and optimization frameworks ...

Abdul Mujeeb, Salman.

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Control and optimization frameworks for managed pressure drilling process.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Control and optimization frameworks for managed pressure drilling process./
Author:	Abdul Mujeeb, Salman.
Description:	74 p.
Notes:	Source: Masters Abstracts International, Volume: 51-03.
Contained By:	Masters Abstracts International51-03(E).
Subject:	Engineering, Electronics and Electrical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1521718
ISBN:	9781267801210

Control and optimization frameworks for managed pressure drilling process.
Abdul Mujeeb, Salman.

Control and optimization frameworks for managed pressure drilling process. - 74 p.

Source: Masters Abstracts International, Volume: 51-03.

Thesis (M.S.)--Texas A&M University - Kingsville, 2012.

Managed Pressure Drilling (MPD) process regulates the pressure by means of a control framework and equipments within prescribed limits. As the conventional drilling is risk prone and involves constant monitoring of the system parameters, MPD offers advantages such as improved Rate Of Penetration (ROP), improved safety and higher overall operational efficiency.

ISBN: 9781267801210Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

Control and optimization frameworks for managed pressure drilling process.
LDR:02687nam 2200301 4500 001 1958018
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008 150212s2012 ||||||||||||||||| ||eng d
020 $a 9781267801210
035 $a (MiAaPQ)AAI1521718
035 $a AAI1521718
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100 1 $a Abdul Mujeeb, Salman. $3 2092973
245 1 0 $a Control and optimization frameworks for managed pressure drilling process.
300 $a 74 p.
500 $a Source: Masters Abstracts International, Volume: 51-03.
500 $a Adviser: Muhittin Yilmaz.
502 $a Thesis (M.S.)--Texas A&M University - Kingsville, 2012.
520 $a Managed Pressure Drilling (MPD) process regulates the pressure by means of a control framework and equipments within prescribed limits. As the conventional drilling is risk prone and involves constant monitoring of the system parameters, MPD offers advantages such as improved Rate Of Penetration (ROP), improved safety and higher overall operational efficiency.
520 $a This thesis develops an uncertain control-oriented system model for the MPD framework, and proposes both intelligent and robust control frameworks in order to improve the MPD system performance. The process model developed must satisfactorily represent the physical dynamics of the MPD system. The dynamics of an oil well and associated processes are used to obtain models that are suitable for the process optimization. Intelligent and robust control frameworks have been investigated. The bore is sealed and the pressure is regulated using a choke and two pumps, the main mud pump and the back pressure pump. The developed control frameworks uses two control inputs i.e., the main mud pump and the Differential pressure between choke and back pressure pump. Intelligent control is suitable to nonlinear systems such as the MPD process where it is difficult to represent the system dynamics using only system equations. Intelligent control framework has been developed and tested for the MPD application yielding satisfactorily results. Drilling operations involve unexpected disturbances and uncertain parameters. The proposed robust optimization framework design offers improved disturbance rejection as well as guaranteed stability and performance for a family of plants within the design space, with a bounded uncertainty description. Results of both Intelligent and Robust Frameworks are listed, studied and a comparison is made.
590 $a School code: 1187.
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Engineering, Petroleum. $3 1018448
650 4 $a Geotechnology. $3 1018558
690 $a 0544
690 $a 0765
690 $a 0428
710 2 $a Texas A&M University - Kingsville. $3 1022707
773 0 $t Masters Abstracts International $g 51-03(E).
790 $a 1187
791 $a M.S.
792 $a 2012
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1521718