Corpus ID: 237571361

Capacitance Resistance Model and Recurrent Neural Network for Well Connectivity Estimation : A Comparison Study

@article{Sen2021CapacitanceRM,
  title={Capacitance Resistance Model and Recurrent Neural Network for Well Connectivity Estimation : A Comparison Study},
  author={Deepthi Sen},
  journal={ArXiv},
  year={2021},
  volume={abs/2109.08779}
}
  • Deepthi Sen
  • Published 17 September 2021
  • Computer Science, Mathematics
  • ArXiv
In this report, two commonly used data-driven models for predicting well production under a waterflood setting – the capacitance resistance model (CRM) and recurrent neural networks (RNN) are compared. Both models are completely data-driven and are intended to learn the reservoir behavior during a waterflood from historical data. The python implementation of the CRM model used in this report is available from the associated GitHub repository. 

References

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