Stats4Grads: Bayesian Deconvolution in Well Test Analysis
8 March 2017 13:00 in CM105
This work focuses on the development of a Bayesian approach to deconvolution in the context of well test analysis, a set of methodologies used in petroleum engineering that provides information about the properties and the structure of the reservoir and the wellbore using pressure and flow rate data. In particular, we are working on the construction of a suitable and meaningful Bayesian framework for the deconvolution in association with Makrov Chain Monte Carlo (MCMC) methods.
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