RT Journal Article ID 7556678f05f59b88 A1 Ginting, V. A1 Pereira, Felipe A1 Rahunanthan, A. T1 A MULTI-STAGE BAYESIAN PREDICTION FRAMEWORK FOR SUBSURFACE FLOWS JF International Journal for Uncertainty Quantification JO IJUQ YR 2013 FD 2013-10-25 VO 3 IS 6 SP 499 OP 522 K1 Bayesian statistics K1 GPUs K1 Markov chain Monte Carlo K1 single-phase K1 two-phase K1 uncertainty quantification AB 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. PB Begell House LK https://www.dl.begellhouse.com/journals/52034eb04b657aea,434f931a2c135597,7556678f05f59b88.html