Forecasting Production in an Oil Reservoir Simulation and Its Challenges

V. Ginting (), F. Pereira () and A. Rahunanthan ()
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V. Ginting: University of Wyoming, Department of Mathematics
F. Pereira: University of Wyoming, Department of Mathematics and School of Energy Resources
A. Rahunanthan: University of Wyoming, Department of Mathematics

A chapter in Numerical Mathematics and Advanced Applications 2011, 2013, pp 693-701 from Springer

Abstract: Abstract A Bayesian approach for uncertainty quantification of oil reservoir parameters in forecasting the production is straightforward in principle. However, the complexity of flow simulators and the nature of the inverse problem at hand present an ongoing practical challenges to addressing uncertainty in all subsurface parameters. In this paper, we focus on two important subsurface parameters, permeability and porosity, and discuss quantifying uncertainty in those parameters.

Keywords: Markov Chain Monte Carlo; Relative Permeability; Injection Well; Production Well; Fractional Flow (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-33134-3_73

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DOI: 10.1007/978-3-642-33134-3_73

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