Lithologic Reservoirs ›› 2019, Vol. 31 ›› Issue (4): 101-111.doi: 10.12108/yxyqc.20190411

• EXPLORATION TECHNOLOGY • Previous Articles     Next Articles

Application of BP neutral network method to identification of shale lithofacies of Lucaogou Formation in Santanghu Basin

LIU Yuejie, LIU Shuqiang, MA Qiang, YAO Zongsen, SHE Jiachao   

  1. Research Institute of Exploration and Development, PetroChina Tuha Oilfield Company, Hami 839009, Xinjiang, China
  • Received:2019-01-09 Revised:2019-03-20 Online:2019-07-21 Published:2019-06-21

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Abstract: For the identification of shale lithofacies,the traditional method of establishing lithofacies chart does not fully take into account the interference caused by the similarity of logging data and the differences in the scale of experimental data,which results in the overlap of different types of sample points in the established identification chart,the ambiguity of boundaries and the large deviation of prediction. Aiming at this problem,taking the second member of Lucaogou Formation in Malang Sag of Santanghu Basin as an example,based on the full understanding of reservoir characteristics,a BP neutral network method based on principal component analysis was adopted. Firstly,the core data of the study area were used to classified the lithofacies into three types,such as organicrich laminar facies,carbonate-rich laminar facies and rich tuff-grain laminar facies,so as to reduce the scale error with the logging data. Secondly,the lithofacies chart was established to extract logging curves such as AC,GR, DEN,CNL,Rt and so on,which were sensitive to the response of lithofacies,the factor loading geological factors of each principal component were analyzed,and three principal components PC2,PC3,PC4 containing a large amount of lithofacies information were selected. Finally,the mapping relationship between lithofacies and logging curves was established,and the lithofacies identification of well Lu1,a key well in the study area,was carried out. The results show that compared with the traditional chart identification method,the lithofacies identification method combining principal component analysis with BP neural network can effectively eliminate the interference caused by the similarity of logging curves and reduce the error caused by the difference between the core data and the logging data,as so to improve the accuracy of lithofacies identification. This method is practical for shale lithofacies identification and has certain application value.

Key words: principal component, shale lithofacies, BP neural network, logging parameters, Lucaogou Formation, Santanghu Basin

CLC Number: 

  • P631.84
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