Modeling of Multi-Agent System for Drilling Simulation

Abstract:

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In view of the characteristics of the oil drilling process and the existing problems of traditional simulation system, a new distributed drilling simulation model was established based on Multi-Agent system (MAS) technology. By means of autonomous, cooperative and reactive characteristic of Agent, the drilling laws and phenomenon can be reflected promptly and accurately under any circumstances. The MAS modeling for oil drilling simulation, the structure and knowledge representation of each Agent and the communication among Agents are described in detail. Finally, an Agent-based normal drilling well control simulation training example was given. The simulation results show that the simulator based on Multi-Agent system has better performances than traditional drilling simulators, and enhances the integrated training function of the drilling simulation system.

Info:

Periodical:

Advanced Materials Research (Volumes 383-390)

Edited by:

Wu Fan

Pages:

1555-1561

DOI:

10.4028/www.scientific.net/AMR.383-390.1555

Citation:

W. L. Wang and Y. J. Wang, "Modeling of Multi-Agent System for Drilling Simulation", Advanced Materials Research, Vols. 383-390, pp. 1555-1561, 2012

Online since:

November 2011

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Price:

$35.00

[1] Shaohuai Zhang, Huacan He, Qi Li, intelligent study on information technology of oil drilling, Journal of petroleum, vol. 17, Oct. 1996, p.114~119.

[2] Zhenchun Sun, Yuequan Xia, well control technology, petroleum industry, in press.

[3] Yingzhuo Xu, cooperative remote control system for diagnosing and treating drilling accident, Journal of petroleum, vol. 24, Oct. 2004. p.84~87.

[4] Whitman D. L, Evers, demonstration and teaching of kick control techniques using microcomputer graphics, petroleum industry application of microcomputers, vol. 14, Jun. 1987, pp.23-26.

DOI: 10.2118/16497-ms

[5] Yanjiang Wang, Buren Qian, Qinzhong Chai, development of well control training simulator, Journal of system simulation, vol. 10, Jun. 1998, p.55~59.

[6] Wooldridge M. , Jennings N. R., Intelligent agents:theory and practice, the knowledge engineering review, vol. 10, Feb. 1995;199. 115-152.

[7] Adelinde M. Uhrmacher, " concepts of object and agent-oriented simulation. TRANSACTION of The Society for Computer Simulation International, vol. Feb. 1997, pp.125-137.

[8] Bonabeau, E., Agent-based modeling: methods and techniques for simulating human systems, , presented at Proc Natl Acad Sci, (2002).

[9] Dongyong Yang , Xuejiang Chen , Jingping Jiang. Multi-agent Cooperation based on Behavior Prediction and Reinforcement Learning Proceedings of the 5Ih World Congress on Intelligent Control and Automation, June 15-19, 2004, Hangzhou, P.R. China.

DOI: 10.1109/wcica.2004.1343636

[10] Fa Zhang, Huiyu Xuan, methodology of multi-agent based simulation for Complex Systems, Journal of system simulation, vol. 21, Apr. 2009, p.113~117.

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