1887

Abstract

Summary

Uncertainty quantification is of importance for reservoir appraisals. In this work, we provide an automated method for uncertainty quantification of geological model using well borehole data for the reservoir appraisal. In our method, when new wells are drilled, multiple components of the geological model are updated jointly and automatically by means of a sequential decomposition following geological rules. During updating, we extend the direct forecasting method to perform such joint model uncertainty reduction. Our approach also enables updating geological model uncertainty without conventional model rebuilding, which significantly reduces the time-consumption. The application to a gas reservoir shows that, this proposed framework can efficiently update the geological model and reduce the prediction uncertainty of the gas storage volume jointly with all model variables.

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/content/papers/10.3997/2214-4609.201902210
2019-09-02
2024-03-28
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References

  1. Satija, A., Scheidt, C., Li, L. and Caers, J.: Direct forecasting of reservoir performance using production data without history matching, Comput. Geosci., 21(2), 315–333
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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201902210
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