Lithologic Reservoirs ›› 2013, Vol. 25 ›› Issue (5): 86-88.doi: 10.3969/j.issn.1673-8926.2013.05.015

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Application of self-adaptive BP neural network to the prediction of shear wave velocity

WANG Xiaoguang   

  1. Research Institute of Exploration and Development， PetroChina Liaohe Oilfield Company， Panjin 124010， China
  • Online:2013-09-26 Published:2013-09-26

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Abstract:

Accurate shear wave velocity is the necessary information for prestack inversion and prestack attribute analysis, but it is always deficient in actual production. The prediction methods are numerous and complicated and the accuracy is difficult to ensure. By selecting the parameters such as relative natural gamma-ray value, acoustic slowness, density and resistivity, this paper used the method of self-adaptive BP neural network to establish the prediction model of shear wave velocity. The actual data in Liaohe Oilfield showthe high precision of the prediction value, and the results can meet production requirements.

Key words: reservoir heterogeneity, sedimentarymicrofacies, diagenesis, Nen 3 member, Xinli area

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