Assessment of Uncertainty in Reservoir Production Forecasts Using Upscaled Flow Models

  • Ole Petter Lødøen
  • Henning Omre
  • Louis J. Durlofsky
  • Yuguang Chen
Part of the Quantitative Geology and Geostatistics book series (QGAG, volume 14)

Production forecasts for a given reservoir, with associated uncertainties, must be based on a stochastic model of the reservoir coupled with a fluid flow simulator. These flow simulations may be computationally prohibitive if they are performed on the fine scale geostatistical model. To accelerate these computations, coarsened (or upscaled) reservoir models are generally simulated. The recovery predictions generated using the upscaled models will inevitably differ from those of the underlying fine scale models and may display severe biases and erroneous uncertainties. In this paper, a model that accounts for these biases and changes in uncertainties is described. Issues related to the selection of fine scale calibration runs and the performance of the method using different upscaling procedures are considered. Two test cases involving water injection are presented. These examples demonstrate the large errors that can result from standard upscaling techniques, the ability of the error modeling procedure to nonetheless provide accurate predictions (following appropriate calibration), and the benefits of using a more accurate upscaling procedure.

Keywords

Permeability Porosity Petroleum Covariance Shale 

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Copyright information

© Springer 2005

Authors and Affiliations

  • Ole Petter Lødøen
    • 1
  • Henning Omre
    • 1
  • Louis J. Durlofsky
    • 2
  • Yuguang Chen
    • 2
  1. 1.Department of Mathematical SciencesNorwegian University of Science and TechnologyNorway
  2. 2.Department of Petroleum EngineeringStanford UniversityStanfordUSA

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