A gathered EnKF for continuous reservoir model updating
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- 作者：Yuanyuan Shuaia ; yuanyuan.shuai@shell.com" class="auth_mail" title="E-mail the corresponding author ; Christopher Whiteb ; Ting Sunc ; Yin Fengd
- 关键词：Ensemble Kalman filter ; Ensemble smoother ; Sampling error ; Gathered EnKF ; Reservoir model updating ; Simulation
- 刊名：Journal of Petroleum Science and Engineering
- 出版年：2016
- 出版时间：March 2016
- 年：2016
- 卷：139
- 期：Complete
- 页码：205-218
- 全文大小：4241 K
文摘
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Gathering the observations was proven to reduce sampling errors in the Kalman gain, reducing bias in the ensemble covariance.
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The gathered EnKF was tested with scalar and 2D reservoir history matching cases. These verified the improved estimation of the ensemble covariance and suggested improved estimation of the ensemble mean.
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Improved estimation of the ensemble mean and the more diverse ensembles provided by gathering imply greater stability compared with the standard EnKF.