Articles | Volume 19, issue 2
https://doi.org/10.5194/hess-19-729-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-19-729-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
04 Feb 2015
Research article |
| 04 Feb 2015
Scalable statistics of correlated random variables and extremes applied to deep borehole porosities
A. Guadagnini
Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona 85721, USA
Dipartimento di Ingegneria Civile e Ambientale, Politecnico di Milano, Piazza L. Da Vinci 32, 20133 Milan, Italy
S. P. Neuman
Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona 85721, USA
T. Nan
CORRESPONDING AUTHOR
Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona 85721, USA
M. Riva
Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona 85721, USA
Dipartimento di Ingegneria Civile e Ambientale, Politecnico di Milano, Piazza L. Da Vinci 32, 20133 Milan, Italy
C. L. Winter
Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona 85721, USA
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Cited
12 citations as recorded by crossref.
- Theory and generation of conditional, scalable sub‐Gaussian random fields M. Panzeri et al. 10.1002/2015WR018348
- Generalized Sub‐Gaussian Processes: Theory and Application to Hydrogeological and Geochemical Data M. Siena et al. 10.1029/2020WR027436
- A Gaussian-Mixture based stochastic framework for the interpretation of spatial heterogeneity in multimodal fields M. Siena et al. 10.1016/j.jhydrol.2022.128849
- Simulation and analysis of scalable non-Gaussian statistically anisotropic random functions M. Riva et al. 10.1016/j.jhydrol.2015.06.066
- A High‐Resolution Global Map of Soil Hydraulic Properties Produced by a Hierarchical Parameterization of a Physically Based Water Retention Model Y. Zhang et al. 10.1029/2018WR023539
- Upscaling thermal conductivities of sedimentary formations for geothermal exploration W. Rühaak et al. 10.1016/j.geothermics.2015.08.004
- Analysis of heterogeneity in a sedimentary aquifer using Generalized sub-Gaussian model based on logging resistivity K. Li et al. 10.1007/s00477-021-02054-5
- Statistical modeling of gas-permeability spatial variability along a limestone core M. Siena et al. 10.1016/j.spasta.2017.07.007
- Multifractal analysis in soil properties: Spatial signal versus mass distribution M. Morató et al. 10.1016/j.geoderma.2016.08.004
- Assessing soil water content variability through active heat distributed fiber optic temperature sensing S. Zubelzu et al. 10.1016/j.agwat.2018.08.008
- Recent advances in scalable non-Gaussian geostatistics: The generalized sub-Gaussian model A. Guadagnini et al. 10.1016/j.jhydrol.2018.05.001
- Characterization of conductivity fields through iterative ensemble smoother and improved correlation-based adaptive localization C. Xia et al. 10.1016/j.jhydrol.2024.131054
12 citations as recorded by crossref.
- Theory and generation of conditional, scalable sub‐Gaussian random fields M. Panzeri et al. 10.1002/2015WR018348
- Generalized Sub‐Gaussian Processes: Theory and Application to Hydrogeological and Geochemical Data M. Siena et al. 10.1029/2020WR027436
- A Gaussian-Mixture based stochastic framework for the interpretation of spatial heterogeneity in multimodal fields M. Siena et al. 10.1016/j.jhydrol.2022.128849
- Simulation and analysis of scalable non-Gaussian statistically anisotropic random functions M. Riva et al. 10.1016/j.jhydrol.2015.06.066
- A High‐Resolution Global Map of Soil Hydraulic Properties Produced by a Hierarchical Parameterization of a Physically Based Water Retention Model Y. Zhang et al. 10.1029/2018WR023539
- Upscaling thermal conductivities of sedimentary formations for geothermal exploration W. Rühaak et al. 10.1016/j.geothermics.2015.08.004
- Analysis of heterogeneity in a sedimentary aquifer using Generalized sub-Gaussian model based on logging resistivity K. Li et al. 10.1007/s00477-021-02054-5
- Statistical modeling of gas-permeability spatial variability along a limestone core M. Siena et al. 10.1016/j.spasta.2017.07.007
- Multifractal analysis in soil properties: Spatial signal versus mass distribution M. Morató et al. 10.1016/j.geoderma.2016.08.004
- Assessing soil water content variability through active heat distributed fiber optic temperature sensing S. Zubelzu et al. 10.1016/j.agwat.2018.08.008
- Recent advances in scalable non-Gaussian geostatistics: The generalized sub-Gaussian model A. Guadagnini et al. 10.1016/j.jhydrol.2018.05.001
- Characterization of conductivity fields through iterative ensemble smoother and improved correlation-based adaptive localization C. Xia et al. 10.1016/j.jhydrol.2024.131054
Latest update: 21 Nov 2024
Short summary
Previously we have shown that many earth-system and other variables can be viewed as samples from scale mixtures of truncated fractional Brownian motion or fractional Gaussian noise. Here we study statistical scaling of extreme absolute increments associated with such samples. As a real example we analyze neutron porosities from deep boreholes in diverse depositional units. Phenomena we uncover are relevant to the analysis of fluid flow and solute transport in complex hydrogeologic environments.
Previously we have shown that many earth-system and other variables can be viewed as samples...
