Quantitative seismic interpretation of reservoir parameters and elastic anisotropy based on rock physics model and neural network framework in the shale oil reservoir of the qianjiang formation, jianghan basin, china

HIGHLIGHTS

• who: Zhiqi Guo and collaborators from the Qianjiang Formation, Jianghan Basin, China College of Geoexploration Science and Technology, Jilin University, Changchun, China have published the article: Quantitative Seismic Interpretation of Reservoir Parameters and Elastic Anisotropy Based on Rock Physics Model and Neural Network Framework in the Shale Oil Reservoir of the Qianjiang Formation, Jianghan Basin, China, in the Journal: Energies 2022, 15, x FOR PEER REVIEW of 29/06/2022
• what: __SECTION__ 5. Conclusions.
• how: The real data application results showed that the optimized BPNN provided more accurate and stable prediction results with . . .
  

   

  

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