Diagnosis method of casing damage based on BP neural network

Journal Title: Scholars Journal of Engineering and Technology - Year 2015, Vol 3, Issue 5

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. Keywords: oil and water Wells casing; Multi-factor; Neural network; Fuzzy evaluation

Authors and Affiliations

XU Jian-guo, ZHANG Ying, JANG Yanying, Yang Pingping

Keywords

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  • EP ID EP385168
  • DOI -
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How To Cite

XU Jian-guo, ZHANG Ying, JANG Yanying, Yang Pingping (2015). Diagnosis method of casing damage based on BP neural network. Scholars Journal of Engineering and Technology, 3(5), 563-566. https://europub.co.uk/articles/-A-385168