The Research of Case Matching Algorithm in Drilling Fluid Design Expert System

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Abstract:

In the case-based reasoning in drilling fluid design expert system, it selects the corresponding representation method of attributes and matching algorithm according to the characteristics of drilling fluid system and the formulation. The representation methods of attributes in this article include digital, string and range these three methods, therefore, the corresponding matching algorithms also have nearest-neighbor, string matching and range matching these three algorithms. On this basis, and combined with the single parent genetic algorithm to optimize the initial weights combination, we can get the most optimal and realistic drilling fluid system and formula. This design method can greatly improve the efficiency and accuracy of the drilling fluid formula design.

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2209-2213

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June 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Minglu Zhang,Jian Li, Dachuan Liang, Bing Wang. Optimal Design of Drilling Fluid Formula Based on CBR. Proceedings of the 8th International Conference on Fuzzy Systems and Knowledge Discovery,(2011) July 28;Shanghai, China.

DOI: 10.1109/fskd.2011.6019528

Google Scholar

[2] Yuan Yong, Dong Shujie, Liu Wenmei. Case-based reasoning designing system for drilling fluid formulation. Drilling fluid &Completion fluid, ,1,22(2005), in Chinese.

Google Scholar

[3] Cheng Jinxia,Zheng Xiuhua,Xia Boru.Research on Drilling Fluid Optimization Design System with Case-bases Reasoning.China University of Geoscience,Beijing 100083, China, in Chinese.

Google Scholar

[4] Hu Maoyan. The Design System of Drilling Fluids. China University of Geosciences for Doctoral Degree, in Chinese.

Google Scholar

[5] Hu Tangming,He Yanning.The Reasearch of Knowledge Management Based on Case Reasoning.Journal of Intelligence. (2009), in Chinese.

Google Scholar

[6] Zhang Wenling.Research of Knowledge Management on Project Consulting based on CBR. Dalian University of Technology, in Chinese.

Google Scholar

[7] Qin Y P, Yang X K. Study of range attributes similarity of case-based reasoning. Journal of Liaoning Normal University (Natural Science Edition). 4,29( 2006).

Google Scholar