EGU26-16207, updated on 14 Mar 2026
https://doi.org/10.5194/egusphere-egu26-16207
EGU General Assembly 2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Data-Driven LSTM Architectures for Reservoir Inflow Forecasting
Devesh Mani1 and Vimal Mishra1,2
Devesh Mani and Vimal Mishra
  • 1Indian Institute of Technology (IIT) Gandhinagar, Civil Engineering, India (24350007@iitgn.ac.in)
  • 2Indian Institute of Technology (IIT) Gandhinagar, Earth Sciences, India (vmishra@iitgn.ac.in )

How to cite: Mani, D. and Mishra, V.: Data-Driven LSTM Architectures for Reservoir Inflow Forecasting, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16207, https://doi.org/10.5194/egusphere-egu26-16207, 2026.

This abstract has been withdrawn on 11 Aug 2026.