Advances in Earth Science ›› 2020, Vol. 35 ›› Issue (7): 761-768. doi: 10.11867/j.issn.1001-8166.2020.046

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Application of Seagull Optimization Algorithm Log Interpretation to Shale Gas Reservoir of Well H in Sichuan Basin Yuxi Block

Yuanyuan Chen 1( ), Xiao Yang 1, Xiaojiang Deng 1, Xiaolan Wang 1, Qi He 1, Lili Cheng 1, Kegui Chen 2   

  1. 1.Southwest Geophysical Research Institute of BGP CNPC, Chengdu 610213, China
    2.School of Geoscience and Technology, Southwest Petroleum University, Chengdu 610500, China
  • Received:2020-03-02 Revised:2020-05-13 Online:2020-08-20 Published:2020-08-20
  • About author:Chen Yuanyuan (1988-), female, Chengdu City, Sichuan Province, Engineer. Research areas include logging interpretation and seismic geology comprehensive research. E-mail: chenyy_wt@cnpc.com.cn
  • Supported by:
    the National Natural Science Foundation of China “Research on the geophysical evaluation method of oil and potassium simultaneous exploration in the Sichuan Basin”(41372103);The Sichuan Science and Technology Plan Project “Research on the evaluation and development of deep potassium salt in the Sichuan Basin”(2019YJ0312)

Yuanyuan Chen, Xiao Yang, Xiaojiang Deng, Xiaolan Wang, Qi He, Lili Cheng, Kegui Chen. Application of Seagull Optimization Algorithm Log Interpretation to Shale Gas Reservoir of Well H in Sichuan Basin Yuxi Block[J]. Advances in Earth Science, 2020, 35(7): 761-768.

Due to the diversity of mineral types in shale gas reservoirs, it is difficult to establish reservoir parameter volume model by conventional log interpretation methods. The optimization log interpretation method can evaluate complex lithology reservoirs effectively, and the key is optimization algorithm. With the newly proposed seagull optimization algorithm method, we calculate the mineral and physical parameters of shale gas reservoir in Well H of Yuxi block, Sichuan Basin, and compare with the genetic algorithm and the genetic algorithm-complex hybrid algorithm. It shows that calculation results of seagull optimization algorithm optimization log interpretation match well with core analysis data, and calculation error is small, calculation speed is fast. Seagull optimization algorithm also makes up for the shortcomings of premature convergence and easy to fall into local optimization of genetic algorithm, the need for secondary optimization and slow search speed of genetic-complex hybrid algorithm. It provides a reference for the application of seagull optimization algorithm in other shale gas reservoirs regions.

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