Title :
Optimal design of drilling fluid formula based on CBR
Author :
Zhang Minglu ; Li Jian ; Wang Bing ; Liang Dachuan
Author_Institution :
Sch. of Comput. Sci., Southwest Pet. Univ., Chengdu, China
Abstract :
Case-Based Reasoning (CBR) is a most promising direction in artificial intelligence field. To bring actual case reasoning tech into drilling fluid formula optimal design, and to join the actual course, it is the first time to adopt a mixed searching strategy that involves knowledge guided method, nearest neighbor method and improved range similarity match method. To be exact, first to find the similar drilling fluid type, then to modify its performance parameter value till maximum optimized and rematch, finally get the most optimal drilling fluid formula. Such design method can largely improve the efficiency and accuracy of drilling fluid formula.
Keywords :
case-based reasoning; drilling (geotechnical); pattern clustering; search problems; CBR; artificial intelligence; case based reasoning; drilling fluid formula optimal design; knowledge guided method; mixed searching strategy; nearest neighbor method; performance parameter value; range similarity match method; Accuracy; Cognition; Educational institutions; Feature extraction; Fluids; Petroleum; Search problems; case base; case-based reasoning; drilling fluid; range similarity; similarity;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-180-9
DOI :
10.1109/FSKD.2011.6019528