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International Journal for Uncertainty Quantification

ISSN Print: 2152-5080
ISSN Online: 2152-5099

Open Access

International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2013005281
pages 499-522

A MULTI-STAGE BAYESIAN PREDICTION FRAMEWORK FOR SUBSURFACE FLOWS

V. Ginting
Department of Mathematics, University of Wyoming, Laramie, WY 82071, USA
Felipe Pereira
Departments of Chemical and Petroleum Engineering and Mathematics, School of Energy Resources, University of Wyoming, Laramie, WY 82071, USA
A. Rahunanthan
Department of Mathematics and Computer Science, Edinboro University, Edinboro, PA 16444, USA

ABSTRACT

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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