The importance of localization in the assimilation of 4D seismic data in the data assimilation process using the EnKF
Author:
Affiliation:
1. Delft University of Technology
2. Delft University of technology and TNO
3. TNO
4. Shell International E&P B. V.
Publisher
Society of Exploration Geophysicists
Link
https://library.seg.org/doi/pdf/10.1190/1.3255667
Reference4 articles.
1. Arroyo‐Negrete, E., D. Devegowda, and A. Datta‐Gupta, 2006, Streamline assisted ensemble Kaiman filter for rapid and continuous reservoir model updating: International Oil & Gas Conference and Exhibition, SPE, 104255.
2. Devegowda, D., E. Arroyo‐Negrete, and A. Datta‐Gupta, 2007, Efficient and robust reservoir model updating using ensemble Kaiman filter with sensitivity‐based covariance localization: Reservoir Simulation Symposium, SPE, 106144.
3. A Sequential Ensemble Kalman Filter for Atmospheric Data Assimilation
4. Skjervheim, J. A., B. O. Ruud, S. I. Aanonsen, G. Evensen, and T. A. Johansen, 2006, Using the ensemble Kaiman filter with 4D data to estimate properties and lithology of reservoir rocks: 10th Conference and Exhibition, EAGE, Expanded Abstracts, A028.
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Sequential multilevel assimilation of inverted seismic data;Computational Geosciences;2023-02-18
2. Ensemble-based conditioning of reservoir models to seismic data;Computational Geosciences;2010-09-17
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