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Abstract

The estimation of reservoir properties from seismic data is a mathematical inverse problem and can be solved by combining geophysical modelling and inverse theory. Successful results have been obtained using either deterministic or statistical methods. One of the advantages of statistical approaches is the uncertainty quantification of the model parameter predictions. Bayesian inverse methods have been applied to seismic inverse problems to predict the point-wise posterior distribution of elastic attributes or petrophysical properties. In this work, we present several examples of Bayesian inversion for reservoir characterization applications.

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/content/papers/10.3997/2214-4609.201701740
2017-06-12
2024-03-28
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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201701740
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