Assessing the Probability of Training Image-Based Geological Scenarios Using Geophysical Data View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2014

AUTHORS

Thomas Hermans , Jef Caers , Frédéric Nguyen

ABSTRACT

The construction of training images (TIs) depicting the geological prior is one of the most critical step in multiple-point statistics. Geophysical techniques may be used to reduce the uncertainty in the understanding of prior geological scenarios. We developed a methodology to verify the consistency of geophysical data with independently-built TIs. Synthetic geophysical models built from TI scenarios are compared, using multidimensional scaling, with inverted models from field surveys to check if TIs are consistent with geophysical models. Then, the probability of each TI scenario is computed. A cluster analysis enables to determine which parameters used in building the TIs are most impacting the geophysical response. The methodology is tested using ERT to analyze TI scenarios in the Meuse River alluvial aquifer (Belgium) More... »

PAGES

679-682

References to SciGraph publications

Book

TITLE

Mathematics of Planet Earth

ISBN

978-3-642-32407-9
978-3-642-32408-6

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-32408-6_147

DOI

http://dx.doi.org/10.1007/978-3-642-32408-6_147

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1030013563


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