Data Assimilation in Truncated Plurigaussian Models: Impact of the Truncation Map
Assimilation of production data into reservoir models for which the distribution of porosity and permeability is largely controlled by facies has become increasingly common. When the locations of the facies bodies must be conditioned to observations, the truncated plurigaussian model has been often shown to be a useful method for modeling as it allows gaussian variables to be updated instead of facies types. Previous experience has also shown that ensemble Kalman filter-like methods are particularly effective for assimilation of data into truncated plurigaussian models. In this paper, some limitations are shown of the ensemble-based or gradient-based methods when applied to truncated plurigaussian models of a certain type that is likely to occur for modeling channel facies. It is also shown that it is possible to improve the data match and increase the ensemble spread by modifying the updating step using an approximate derivative of the truncation map.
KeywordsInverse problem Ensemble Kalman filter Categorical variables Data assimilation Truncated plurigaussian model
Primary support for Oliver has been provided by the CIPR/IRIS cooperative research project “4D Seismic History Matching” which is funded by industry partners Eni Norge, Petrobras, and Total, as well as the Research Council of Norway (PETROMAKS2 program). The second author thanks Total for permission to publish this work.
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