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Uncertainty of flow in porous media

By Joyce Aitchison, Linda Cummings, Giles Richardson and Jonathan Rougier


The problem posed to the Study Group was, in essence, how to estimate the probability distribution of f(x) from the probability distribution of x. Here x is a large vector and f is a complicated function which can be expensive to evaluate. For Schlumberger's applications f is a computer simulator of a hydrocarbon reservoir, and x is a description of the geology of the reservoir, which is uncertain

Topics: Energy and utilities, Materials
Year: 2005
OAI identifier: oai:generic.eprints.org:33/core70

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  3. (1999). Bayes Linear Analysis’. In:
  4. (1996). Bayes Linear Strategies for Matching Hydrocarbon Reservoir History’. In:
  5. (2001). Bayesian calibration of computer models’.
  6. (2001). Bayesian Forecasting for Complex Systems Using Computer Simulators’.
  7. (1992). Bayesian Statistics Without Tears: A SamplingResampling Perspective’. doi
  8. (1998). Constructing Partial Prior Specifications for Models of Complex Physical Systems’.
  9. (1999). Monte Carlo Statistical Methods. doi
  10. (1997). Pressure Matching for Hydrocarbon Reservoirs: A Case Study in the Use of Bayes Linear Strategies for Large Computer Experiments’.
  11. (2004). Probabilistic Formulations for Transferring Inferences from Mathematical Models to Physical Systems’.
  12. (1987). Stochastic Simulation. doi
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