1887

Abstract

Summary

For decision making, it’s necessary to predict reservoir’s behavior using reliable models. Reservoir characterization is an essential step for integrating available data. EnKF (Ensemble Kalman Filter) is a powerful method. It uses recursive updates and provides uncertainty assessment.

EnKF has been rarely applied to characterization of gas reservoirs in spite of its active research for oil reservoirs. Gas reservoirs show typically high recovery and are less sensitive to permeability uncertainty. However, the recovery of gas reservoirs is highly affected by an aquifer and an aquifer has high uncertainty. Therefore, aquifer characterization is crucial to the management of gas reservoirs.

Previously, there are studies about characterization of aquifer factors, which required 4D gravimetric data. However, this approach has limitation due to continuous measurement of gravimetric data with time. This paper suggests a method to characterize permeability distribution and aquifer size of gas reservoirs considering its uncertainty. EnKF is used to integrate available production data.

By applying the proposed method to gas reservoirs, it shows reliable reservoir characterization and future predictions of gas and water productions. Above all, it assimilated very successfully aquifer factors, although we assigned 4 different aquifers for each side of the reservoir.

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/content/papers/10.3997/2214-4609.201412676
2015-06-01
2024-03-28
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References

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