 
          An International Publisher for Academic and Scientific Journals
      Author Login 
      
    Scholars Journal of Engineering and Technology | Volume-3 | Issue-05
        Diagnosis method of casing damage based on BP neural network
        XU Jian-guo, ZHANG Ying, JANG Yanying, Yang Pingping
        
            Published:  May 22, 2015 | 
             210
             156
        
        DOI:  10.36347/sjet
        Pages:  563-566
        Downloads
        
        Abstract
        One of the major problems faced by the oilfields in the middle time is casing damage. The neural network, the
improvement BP as well as the three-layer feed forward neural network applied in damage diagnosis is a key way to
prevent damage. The formations of the damage are corresponded to the input vector. Factors such as casing age limit,
strata stress, soaking time are described as real Numbers between 0 ~ 1. Multi -factor constitute a fuzzy vector. Thus,
working status such as the output of neural network, a large number of field data and categorical reduction constitute the
training simple. After those trainings, predictions of the casing status can be completed.
    

