Recent advances in scalable non-Gaussian geostatistics: The generalized sub-Gaussian model

Guadagnini, Alberto; Riva, Mònica; Neuman, Shlomo P.

doi:10.1016/j.jhydrol.2018.05.001

Cited by 24 publications

(32 citation statements)

References 47 publications

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“…In this context, experimental evidence at the laboratory scale (observation scale on the order 0.1-1.0 m) suggests that the mean value and the correlation length of the permeability field tend to increase with the size of the data support, the opposite trend being documented for the variance (e.g., Wilson, 1999a, b, 2000). Similar observations, albeit with some discrepancies, are also tied to investigations at larger scales (i.e., 10-1000 m) (Andersson et al, 1988;Guzman et al, 1994Guzman et al, , 1996Neumann, 1994;Schulze-Makuch and Cherkauer, 1998;Zlotnik et al, 2000). We consider here laboratory-scale permeability datasets which are associated with various measurement scales.…”

Section: Introductionsupporting

confidence: 64%

Interpretation of multi-scale permeability data through an information theory perspective

Dell’Oca

Guadagnini

Riva

2020

Hydrol. Earth Syst. Sci.

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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.

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Section: Introductionsupporting

confidence: 64%

Interpretation of multi-scale permeability data through an information theory perspective

Dell’Oca

Guadagnini

Riva

2020

Hydrol. Earth Syst. Sci.

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“…Analyzing the hydrological processes is further challenged by the interconnectivity of the components. Applying basic statistical techniques oversimplifies the convolution involved in the intercorrelated hydrological sub-systems (Guadagnini et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Identifying and quantifying the latent factors controlling spring discharge in an industrialized karst watershed

Jamshidi

Qian

et al. 2021

Preprint

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Karst springs have largely been impacted by human activity and climate change, which increases the uncertainties to supply and management of water resources. It’s essential to understand the footprint of the controlling factors on their hydrological behavior. Taking the example of Niangziguan springs in China, this study explores the time series of spring discharge over a 50-year time-window (1959–2007). Local Hurst exponent is employed to analyze its temporal correlation behavior. The prime latent factors of spring discharge are extracted and identified using dynamic factor analysis and wavelet analysis, respectively. Moreover, we quantified the contributions of latent factors to spring discharge. The results exhibit that the spring discharge is controlled by the positive feedback mechanism before the exploitation of karst groundwater, however, human activities lead to the feature of noise for spring discharge fluctuations. With the development of industry and agriculture, the effect of the combination of controlling factors on spring discharge tends to be stable. Before groundwater exploited, the local recharge cycle of groundwater shows the largest contribution (43%) on spring discharge focusing on the scales of 4–16 months, and the construction of the industrial region weakens the impact of local groundwater recharge (41%). The contribution of human activities, regional groundwater recharge, and rainfall/runoff to spring discharge (27%-30%) is almost equal. Therefore, human activities have become one of the most important factors controlling the spring discharge. The WNPM (West North Pacific Monsoon) and ISM (Indian Summer Monsoon) show the smallest effect (3%) on spring discharge.

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“…This lack of information propagates to uncertainty in our evaluations of reservoir performance and of the resulting oil recovery. A variety of studies framed in the context of a stochastic approach have been performed for single phase fluid flow and transport (e.g., Dagan, 1989;Gelhar, 1993;Dagan and Neuman, 1997;Zhang and Winter 1999;Sanchez-Vila et al, 2006;Guadagnini et al, 2018 and references therein). Here, we consider a two-phase flow setting taking place in a randomly heterogeneous (correlated) permeability field and study competitive effects on fractional flow due to (a) viscous and (b) gravity forces through a suite of detailed computational experiments.…”

Section: Introductionmentioning

confidence: 99%

Feedback Between Gravity and Viscous Forces in Two-phase Buckley-Leverett Flow in Randomly Heterogeneous Permeability Fields

Alikhani¹,

Guadagnini²,

Inzoli³

2019

Petroleum Geostatistics 2019

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Recent advances in scalable non-Gaussian geostatistics: The generalized sub-Gaussian model

Cited by 24 publications

References 47 publications

Interpretation of multi-scale permeability data through an information theory perspective

Interpretation of multi-scale permeability data through an information theory perspective

Identifying and quantifying the latent factors controlling spring discharge in an industrialized karst watershed

Feedback Between Gravity and Viscous Forces in Two-phase Buckley-Leverett Flow in Randomly Heterogeneous Permeability Fields

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