Computer Science ›› 2019, Vol. 46 ›› Issue (6A): 605-608.

• Interdiscipline & Application • Previous Articles    

Analysis and Establishment of Drilling Speed Prediction Model for Drilling MachineryBased on Artificial Neural Networks

LIU Sheng-wa1, SUN Jun-ming2, GAO Xiang2, WANG Min2   

  1. Department of CNPC Chuanqing Drilling Engineering Company,Xi'an 710018,China1;
    School of Computer Science,Northwest Polytechnical University,Xi'an 710072,China2
  • Online:2019-06-14 Published:2019-07-02

Abstract: Various departments of Changqing Drilling Company have accumulated a great deal of drilling data in the past ten years.With the completion of the construction and operation of the enterprise cloud platform,data integration technology has been adopted to collect and standardize the data of various departments.Mining these accumulated valuable data can provide reference for making drilling plan scientifically.Accurate prediction of penetration rate plays an important role in scientific allocation of drilling resources and reducing drilling cost.This paper proposed a novel method based on neural networks for predicting the penetration rate of directional wells.The network inputs and outputs are determined by drilling experts.The network topology and network training are designed by data engineers.The experimental results show that the prediction model constructed by neural networks hashigh accuracy and can meet the needs of users under the condition of sufficient data and high data quality.

Key words: Artificial intelligence, Big data, Neural network

CLC Number: 

  • TP391
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