Reducing reservoir prediction uncertainty by updating a stochastic model using seismic history matching

    Research output: Contribution to journalArticlepeer-review

    22 Citations (Scopus)


    We have developed a method in which spatial and dynamic information offered by time-lapse, or 4D, seismic surveys is used in history matching of reservoir simulations. Improved predictions of both recovery and areal sweep are then obtained by reducing uncertainty. Flow simulations are converted to predictions of seismic-impedance attributes using a petroelastic transform and suitable rescaling. The resulting misfit between the model and observed data is combined with an equivalent measure for well data, and these are used to constrain simulations by iteratively updating the model. Updated-model probabilities can then be used to analyze uncertainty. The method has been applied to the Schiehallion UK Continental Shelf (UKCS) reservoir. We first found a good match to production and seismic data in the field. From the updated probability distribution of the parameters, we then took the best models from the history-matching process and made predictions to determine the most likely outcomes. We have found that the 4D data reduces uncertainty in predictions of the areal sweep and the pressure distribution. The seismic response is strongest at the injector wells but also helps in the interwell regions. Conventional history matching often struggles to constrain parameters in these regions because of the inherent nonuniqueness of the problem. The uncertainty of permeability- and fault-transmissibility multipliers was also determined in those areas. Copyright © 2008 Society of Petroleum Engineers.

    Original languageEnglish
    Pages (from-to)991-999
    Number of pages9
    JournalSPE Reservoir Evaluation and Engineering
    Issue number6
    Publication statusPublished - Dec 2008


    Dive into the research topics of 'Reducing reservoir prediction uncertainty by updating a stochastic model using seismic history matching'. Together they form a unique fingerprint.

    Cite this