Reservoir Characterization Using a Streamline-Assisted Ensemble Kalman Filter with Covariance Localization
Author:
Affiliation:
1. Asia Exploration Department, Korea National Oil Corporation, Anyang 431-711, South Korea
2. Department of Energy Systems Engineering, Seoul National University, Seoul 151-742, South Korea
Publisher
SAGE Publications
Subject
Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment
Link
http://journals.sagepub.com/doi/pdf/10.1260/0144-5987.30.4.645
Reference11 articles.
1. The Ensemble Kalman Filter in Reservoir Engineering--a Review
2. Modeling Petroleum Resources in Provinces of the Former Soviet Union
3. Continuous Reservoir Model Updating Using Streamline Assisted Ensemble Kalman Filter
4. Efficient and Robust Reservoir Model Updating Using Ensemble Kalman Filter With Sensitivity-Based Covariance Localization
5. A Sequential Ensemble Kalman Filter for Atmospheric Data Assimilation
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2. Use of Channel Information Update and Discrete Cosine Transform in Ensemble Smoother for Channel Reservoir Characterization;Journal of Energy Resources Technology;2019-07-12
3. Geological model sampling using PCA-assisted support vector machine for reliable channel reservoir characterization;Journal of Petroleum Science and Engineering;2018-08
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