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  • 标题:Forecast on Water Locking Damage of Low Permeable Reservoir with Quantum Neural Network
  • 本地全文:下载
  • 作者:Jingyuan Zhao ; Yuxue Sun ; Fuping Feng
  • 期刊名称:IOP Conference Series: Earth and Environmental Science
  • 印刷版ISSN:1755-1307
  • 电子版ISSN:1755-1315
  • 出版年度:2018
  • 卷号:108
  • 期号:3
  • 页码:032008
  • DOI:10.1088/1755-1315/108/3/032008
  • 语种:English
  • 出版社:IOP Publishing
  • 摘要:It is of great importance in oil-gas reservoir protection to timely and correctly forecast the water locking damage, the greatest damage for low permeable reservoir. An analysis is conducted on the production mechanism and various influence factors of water locking damage, based on which a quantum neuron is constructed based on the information processing manner of a biological neuron and the principle of quantum neural algorithm, besides, the quantum neural network model forecasting the water locking of the reservoir is established and related software is also made to forecast the water locking damage of the gas reservoir. This method has overcome the defects of grey correlation analysis that requires evaluation matrix analysis and complicated operation. According to the practice in Longxi Area of Daqing Oilfield, this method is characterized by fast operation, few system parameters and high accuracy rate (the general incidence rate may reach 90%), which can provide reliable support for the protection technique of low permeable reservoir.
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