Can geostatistical models represent nature's variability? an analysis using flume experiments

C. Scheidt, A. Fernandes, C. Paola, J. Caers

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

One of the difficulties in multi-point geostatistics (MPS) is the definition of the training image (TI). In the context of uncertainty modeling, the construction of a set of TIs is desirable, but the number of TIs and the characteristics that should to be varied in the TI are not well understood. In this research, we explore the question of the definition of the TIs using tank experiments. A set of snapshots of delta deposits seen in the tank are used to explore the variability of the system over time and to see if MPS can reproduce the variability of the set of images using only a few, well-selected images that are taken as TI. Preliminary methodologies are explored to select representative images, where the variation of the deposits over time is studied. Our results show that MPS was able to reproduce the variability in the full set of images, hence the variability of the studied system. Analyzing the characteristics of the selected images is a first step forward in the attempt to define TIs. This study only present preliminary investigations and more general answers will be explored.

Original languageEnglish (US)
Title of host publicationPetroleum Geostatistics 2015
PublisherEuropean Association of Geoscientists and Engineers, EAGE
Pages198-202
Number of pages5
ISBN (Electronic)9781510814110
StatePublished - Jan 1 2015
Externally publishedYes
EventPetroleum Geostatistics 2015 - Biarritz, France
Duration: Sep 7 2015Sep 11 2015

Other

OtherPetroleum Geostatistics 2015
CountryFrance
CityBiarritz
Period9/7/159/11/15

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    Scheidt, C., Fernandes, A., Paola, C., & Caers, J. (2015). Can geostatistical models represent nature's variability? an analysis using flume experiments. In Petroleum Geostatistics 2015 (pp. 198-202). European Association of Geoscientists and Engineers, EAGE.