1887

Abstract

Summary

We present an extension for a methodology proposed by , known as Reservoirs Analogues (RA). This method finds analogues using machine learning to complete a dataset. Our concern is this methodology does not track error carried from the imputation of missing values until ranking lists of analogues. This study aims to analyze the inherent uncertainty of this step discussing how it can be beneficial to obtain accurate information for reservoirs with limited information.

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/content/papers/10.3997/2214-4609.201803029
2018-11-30
2020-04-08
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References

  1. Perez-Valiente, M. L., Martin Rodriguez, H., Santos, C. N., Vieira, M. R., & Embid, S. M.
    (2014, April). Identification of Reservoir Analogues in the Presence of Uncertainty. In SPE Intelligent Energy Conference & Exhibition. Society of Petroleum Engineers.
    [Google Scholar]
  2. Martín Rodríguez, H., Escobar, E., Embid, S., Rodriguez Morillas, N., Hegazy, M., & Lake, L. W.
    (2014). New Approach to Identify Analogous Reservoirs. SPE Economics & Management, 6(04), 173–184.
    [Google Scholar]
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