Interpretation of multi-scale permeability data through an information theory perspective
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Published:2020-06-16
Issue:6
Volume:24
Page:3097-3109
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ISSN:1607-7938
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Container-title:Hydrology and Earth System Sciences
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language:en
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Short-container-title:Hydrol. Earth Syst. Sci.
Author:
Dell'Oca Aronne,Guadagnini Alberto,Riva Monica
Abstract
Abstract. We employ elements of information theory to quantify (i) the information content related to data collected at given measurement scales within the
same porous medium domain and (ii) the relationships among information contents of datasets associated with differing scales. We focus on gas permeability data collected over Berea Sandstone and Topopah Spring Tuff
blocks, considering four measurement scales. We quantify the way information
is shared across these scales through (i) the Shannon entropy of the data
associated with each support scale, (ii) mutual information shared between
data taken at increasing support scales, and (iii) multivariate mutual
information shared within triplets of datasets, each associated with a given
scale. We also assess the level of uniqueness, redundancy and synergy
(rendering, i.e., information partitioning) of information content that the
data associated with the intermediate and largest scales provide with
respect to the information embedded in the data collected at the smallest
support scale in a triplet. Highlights.
Information theory allows characterization of the information content of permeability data related to differing measurement scales. An increase in the measurement scale is associated with quantifiable loss of information about permeability. Redundant, unique and synergetic contributions of information are evaluated for triplets of permeability datasets, each taken at a given scale.
Publisher
Copernicus GmbH
Subject
General Earth and Planetary Sciences,General Engineering,General Environmental Science
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