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Title: Impact of petrophysical uncertainty on Bayesian hydrogeophysical inversion and model selection

Abstract

Quantitative hydrogeophysical studies rely heavily on petrophysical relationships that link geophysical properties to hydrogeological properties and state variables. Coupled inversion studies are frequently based on the questionable assumption that these relationships are perfect (i.e., no scatter). Using synthetic examples and crosshole ground-penetrating radar (GPR) data from the South Oyster Bacterial Transport Site in Virginia, USA, we investigate the impact of spatially-correlated petrophysical uncertainty on inferred posterior porosity and hydraulic conductivity distributions and on Bayes factors used in Bayesian model selection. Our study shows that accounting for petrophysical uncertainty in the inversion (I) decreases bias of the inferred variance of hydrogeological subsurface properties, (II) provides more realistic uncertainty assessment and (III) reduces the overconfidence in the ability of geophysical data to falsify conceptual hydrogeological models.

Authors:
 [1];  [1]
  1. Univ. of Lausanne, Lausanne (Switzerland). Inst. of Earth Sciences, Applied and Environmental Geophysics Group
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1567104
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Advances in Water Resources
Additional Journal Information:
Journal Volume: 111; Journal Issue: C; Journal ID: ISSN 0309-1708
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
petrophysical uncertainty; hydrogeophysics; Bayesian model selection; Bayesian inversion; evidence; conceptual model

Citation Formats

Brunetti, Carlotta, and Linde, Niklas. Impact of petrophysical uncertainty on Bayesian hydrogeophysical inversion and model selection. United States: N. p., 2018. Web. doi:10.1016/j.advwatres.2017.11.028.
Brunetti, Carlotta, & Linde, Niklas. Impact of petrophysical uncertainty on Bayesian hydrogeophysical inversion and model selection. United States. doi:10.1016/j.advwatres.2017.11.028.
Brunetti, Carlotta, and Linde, Niklas. Mon . "Impact of petrophysical uncertainty on Bayesian hydrogeophysical inversion and model selection". United States. doi:10.1016/j.advwatres.2017.11.028. https://www.osti.gov/servlets/purl/1567104.
@article{osti_1567104,
title = {Impact of petrophysical uncertainty on Bayesian hydrogeophysical inversion and model selection},
author = {Brunetti, Carlotta and Linde, Niklas},
abstractNote = {Quantitative hydrogeophysical studies rely heavily on petrophysical relationships that link geophysical properties to hydrogeological properties and state variables. Coupled inversion studies are frequently based on the questionable assumption that these relationships are perfect (i.e., no scatter). Using synthetic examples and crosshole ground-penetrating radar (GPR) data from the South Oyster Bacterial Transport Site in Virginia, USA, we investigate the impact of spatially-correlated petrophysical uncertainty on inferred posterior porosity and hydraulic conductivity distributions and on Bayes factors used in Bayesian model selection. Our study shows that accounting for petrophysical uncertainty in the inversion (I) decreases bias of the inferred variance of hydrogeological subsurface properties, (II) provides more realistic uncertainty assessment and (III) reduces the overconfidence in the ability of geophysical data to falsify conceptual hydrogeological models.},
doi = {10.1016/j.advwatres.2017.11.028},
journal = {Advances in Water Resources},
number = C,
volume = 111,
place = {United States},
year = {2018},
month = {1}
}

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