Enhancing oil–water flow prediction in heterogeneous porous media using machine learning

HIGHLIGHTS

• What: This approach has been demonstrated with applicability to both direct and inverse problems. The authors propose the CL-FNO, which integrates the Fourier neural operator and the convolutional long short-term memory within a U-shaped encoder-decoder configuration.
• Who: Gaocheng Feng et al. from the Civil Engineering School, Qingdao University of Technology, Qingdao, China have published the Article: Enhancing Oil-Water Flow Prediction in Heterogeneous Porous Media Using Machine Learning, in the Journal: Water 2024, 16, x FOR PEER REVIEW of /2024/
• How: In the experiment the authors employed distinct decoding . . .
  

   

  

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