Reservoir history matching and inversion using an iterative ensemble Kalman filter with covariance localization
نویسندگان
چکیده
منابع مشابه
History matching of petroleum reservoir models by the Ensemble Kalman Filter and parameterization methods
The Ensemble Kalman Filter (EnKF) has been successfully applied in petroleum engineering during the past few years to constrain reservoir models to production or seismic data. This sequential assimilation method provides a set of updated static variables (porosity, permeability) and dynamic variables (pressure, saturation) at each assimilation time. However, several limitations can be pointed o...
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This paper was selected for presentation by an SPE Program Committee following review of information contained in a proposal submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the Society of Petroleum ...
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In this paper we propose a way to integrate data at different spatial scales using the ensemble Kalman filter (EnKF), such that the finest scale data is sequentially estimated, subject to the available data at the coarse scale (s), as an additional constraint. Relationship between various scales has been modeled via upscaling techniques. The proposed coarse-scale EnKF algorithm is recursive and...
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ژورنال
عنوان ژورنال: Petroleum Science
سال: 2011
ISSN: 1672-5107,1995-8226
DOI: 10.1007/s12182-011-0148-7