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International Journal for Uncertainty Quantification

Publicou 6 edições por ano

ISSN Imprimir: 2152-5080

ISSN On-line: 2152-5099

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A MULTI-STAGE BAYESIAN PREDICTION FRAMEWORK FOR SUBSURFACE FLOWS

Volume 3, Edição 6, 2013, pp. 499-522
DOI: 10.1615/Int.J.UncertaintyQuantification.2013005281
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RESUMO

We are concerned with the development of computationally efficient procedures for subsurface flow prediction that relies on the characterization of subsurface formations given static (measured permeability and porosity at well locations) and dynamic (measured produced fluid properties at well locations) data. We describe a predictive procedure in a Bayesian framework, which uses a single-phase flow model for characterization aiming at making prediction for a two-phase flow model. The quality of the characterization of the underlying formations is accessed through the prediction of future fluid flow production.

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CITADO POR
  1. Ginting V., Pereira F., Rahunanthan A., Multi-physics Markov chain Monte Carlo methods for subsurface flows, Mathematics and Computers in Simulation, 118, 2015. Crossref

  2. Ginting V., Pereira F., Rahunanthan A., A prefetching technique for prediction of porous media flows, Computational Geosciences, 18, 5, 2014. Crossref

  3. Ali Alsadig, Al-Mamun Abdullah, Pereira Felipe, Rahunanthan Arunasalam, Markov Chain Monte Carlo Methods for Fluid Flow Forecasting in the Subsurface, in Computational Science – ICCS 2020, 12143, 2020. Crossref

  4. Ali Alsadig, Al-Mamun Abdullah, Pereira Felipe, Rahunanthan Arunasalam, Conditioning by Projection for the Sampling from Prior Gaussian Distributions, in Computational Science and Its Applications – ICCSA 2021, 12952, 2021. Crossref

  5. Feldmann R., Gehb C. M., Schaeffner M., Melz T., A Methodology for the Efficient Quantification of Parameter and Model Uncertainty, Journal of Verification, Validation and Uncertainty Quantification, 7, 3, 2022. Crossref

  6. Al-Mamun A., Barber J., Ginting V., Pereira F., Rahunanthan A., Contaminant transport forecasting in the subsurface using a Bayesian framework, Applied Mathematics and Computation, 387, 2020. Crossref

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