A reservoir parametric model is progressively matched and renewed using a covariance localized ensemble Kalman filter (EnKF) approach. The method employs the fast marching method (FMM) to rapidly track pressure wave transmission duration and determine well sensitivity regions. The author is Ruoxuan Zhang, and the dataset is associated with an Open Access (green) license paper.
Use Cases
- Optimizing reservoir parametric models based on pressure wave tracking and well sensitivity analysis.
- Reducing false correlation in data assimilation using a covariance localized EnKF approach.
- Building localized matrices for gradient modification in history matching workflows.
Strengths
- Methodology is described in a paper with an Open Access (green) license.
- The approach integrates the fast marching method for rapid pressure wave tracking.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Last update date is unknown; freshness unverified.
Provenance
- Source
- paperswithcode
- Collection Method
- Likely contains simulation or modeling results from the described reservoir history matching method.