Summary
Recently, the ensemble Kalman Filter (EnKF) has gained popularity in
atmospheric science for the assimilation of data and the assessment of
uncertainty in forecasts for complex, large-scale problems. A handful of papers
have discussed reservoir characterization applications of the EnKF, which can
easily and quickly be coupled with any reservoir simulator. Neither adjoint
code nor specific knowledge of simulator numerics is required for
implementation of the EnKF. Moreover, data are assimilated (matched) as they
become available; a suite of plausible reservoir models (the ensemble, set of
ensemble members or suite or realizations) is continuously updated to honor
data without rematching data assimilated previously. Because of these features,
the method is far more efficient for history matching dynamic data than
automatic history matching based on optimization algorithms. Moreover, the set
of realizations provides a way to evaluate the uncertainty in reservoir
description and performance predictions.
Here we establish a firm theoretical relation between randomized maximum
likelihood and the ensemble Kalman filter. Although we have previously
generated reservoir characterization examples where the method worked well,
here we also provide examples where the performance of EnKF does not provide a
reliable characterization of uncertainty.
Introduction
Our main interest is in characterizing the uncertainty in reservoir
description and reservoir performance predictions in order to optimize
reservoir management. To do so, we wish to generate a suite of plausible
reservoir models (realizations) that are consistent with all information and
data. If the set of models is obtained by correctly sampling the pdf, then the
set of models give a characterization of the uncertainty in the reservoir
model. Thus, by predicting future reservoir performance with each of the
realizations, and calculating statistics on the set of outcomes, one can
evaluate the uncertainty in reservoir performance predictions.
© 2007. Society of Petroleum Engineers
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History
- Original manuscript received:
13 July 2005
- Meeting paper published:
9 October 2005
- Revised manuscript received:
31 March 2007
- Manuscript approved:
9 April 2007
- Version of record:
20 September 2007
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