Approaches in Highly Parameterized Inversion: bgaPEST, a Bayesian Geostatistical Approach Implementation With PEST?Documentation and Instructions - Softcover

Fienen, Michael N; D'Oria, Marco; Doherty, John E; Hunt, Randall J

 
9781500297459: Approaches in Highly Parameterized Inversion: bgaPEST, a Bayesian Geostatistical Approach Implementation With PEST?Documentation and Instructions
Softcover
ISBN 10: 1500297453 ISBN 13: 9781500297459
Publisher: CreateSpace Independent Publishing Platform, 2014

Synopsis

The application bgaPEST is a highly parameterized inversion software package implementing the Bayesian Geostatistical Approach in a framework compatible with the parameter estimation suite PEST. Highly parameterized inversion refers to cases in which parameters are distributed in space or time and are correlated with one another. The Bayesian aspect of bgaPEST is related to Bayesian probability theory in which prior information about parameters is formally revised on the basis of the calibration dataset used for the inversion. Conceptually, this approach formalizes the conditionality of estimated parameters on the specific data and model available.

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Publisher
CreateSpace Independent Publishing Platform
Publication date
2014
Language
English
ISBN 10 
1500297453
ISBN 13 
9781500297459
Binding
Paperback
Number of pages
94