Oil reservoir recovery factor assessment using Bayesian networks based on advanced approaches to analogues clustering

@article{Andriushchenko2022OilRR,
  title={Oil reservoir recovery factor assessment using Bayesian networks based on advanced approaches to analogues clustering},
  author={Petr D. Andriushchenko and Irina Deeva and Anna V. Bubnova and Anton Voskresenskiy and Nikita V. Bukhanov and Nikolay O. Nikitin and Anna V. Kaluzhnaya},
  journal={ArXiv},
  year={2022},
  volume={abs/2204.00413}
}
The work focuses on the modelling and imputation of oil and gas reservoirs parameters, specifically, the problem of predicting the oil recovery factor (RF) using Bayesian networks (BNs). Recovery forecasting is critical for the oil and gas industry as it directly affects a company’s profit. However, current approaches to forecasting the RF are complex and com-putationally expensive. In addition, they require vast amount of data and are difficult to constrain in the early stages of reservoir… 

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