Simulation error models for improved reservoir prediction

A. O'Sullivan, M. Christie

    Research output: Contribution to journalArticlepeer-review

    11 Citations (Scopus)


    Successful reservoir prediction requires an accurate estimation of parameters to be used in the reservoir model. This research focuses on developing models for simulation error within the petroleum industry, enabling accurate parameter estimation. The standard approach in the oil industry to parameter estimation in a Bayesian framework includes inappropriate assumptions about the error data. This leads to the parameter estimations being biased and overconfident. An error model is designed to significantly reduce the bias effect and to estimate an accurate range of spread. A 2D viscous fingering example problem will be used to demonstrate both construction of the error model, and the benefits gained in doing so. © 2005 Elsevier Ltd. All rights reserved.

    Original languageEnglish
    Pages (from-to)1382-1389
    Number of pages8
    JournalReliability Engineering and System Safety
    Issue number10-11
    Publication statusPublished - Oct 2006


    • Error model
    • Likelihood
    • Parameter estimation
    • Simulation error
    • Viscous fingering


    Dive into the research topics of 'Simulation error models for improved reservoir prediction'. Together they form a unique fingerprint.

    Cite this