西南石油大学学报(自然科学版)

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Drilling Site Risk Assessment Based on Bayesian Network

Wang Bing1*, Yang Xiaoying2, Zhao Chunlan3, Xiao Bin1   

  1. 1. School of Computer Science,Southwest Petroleum University,Chengdu,Sichuan,610500,China
    2. School of Petroleum and Natural Gas Engineering,Southwest Petroleum University,Chengdu,Sichuan 610500,China
    3. School of Science,Southwest Petroleum University,Chengdu,Sichuan 610500,China
  • Online:2015-04-01 Published:2015-04-01

Abstract:

In view of the high investment and risk and uncertainties in drilling operation,the safety evaluation about the
drilling operation is carried out in the paper. The method of evaluating risk and seeking risk resource during drilling operation
has been developed by using Bayes network. The 32 risk factors during the drilling operation could be classified into manmade
risk factors and natural risk factors by analyzing the history data and identifying the dangerous factors with the help of
expertise. The Bayes network topological structure and conditional probability table(CPT)was developed for drilling operation
risk;the probability was predicted forward and diagnosed backward;the safety probability of drilling operation was evaluated
quantitative and the most dangerous factor was found out. After applying the Bayes network model to Well L gas drilling
operation,we got the risk probability of man-made risk and natural risk at 0.108 and 0.165,respectively,the risk probability
of Well L gas drilling operation at 0.137. The many dangerous factors are defects in monitor during the drilling process,lack of
security protection facilities,hidden trouble induced by drilling operation,defect in well-control equipment and management
in production. This will provide precise diagnostic data for operators and decision-making for safe production.

Key words: drilling operation, safety assessment, Bayes network model, prediction forward, diagnosis backward