Some consequences of applying lognormal theory to pseudolognormal distributions

Link, Richard F.; Koch, George S.

doi:10.1007/bf02080488

Cited by 31 publications

(6 citation statements)

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“…The negative bias in K0 108 estimations was attributed to the deviation from lognormality in the data distributions (David, 1988). Link and Koch (1975) showed that negative bias is possible when lognormal transformation was used for positively skewed but not exactly lognormal distributions. For such data sets, either KO or K0 1 og would be appropriate, depending on the objectives of the investigation.…”

Section: Resultsmentioning

confidence: 99%

A Comparative Study of Interpolation Methods for Mapping Soil Properties

1999

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ABSTRACTand Salas (1985) compared kriging with several other interpolation techniques, including inverse distance, for (Leenaers et al., 1990). for mapping soil P and K levels and found inverse dismental data and estimated results of kriging were higher than those of InvD for 57 out of a total of 60 data sets, kriging mean absolute tance to be relatively more accurate. Gotway et al.errors were lower for 44 data sets, and kriging mean errors were lower (1996) observed the best results in mapping soil organic than those of InvD weighting for 31 data sets.

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Section: Resultsmentioning

confidence: 99%

A Comparative Study of Interpolation Methods for Mapping Soil Properties

1999

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“…The earth's crust meets both these criteria for channelized flow (permeability inhomogeneity and pink noise, scale invariant, spatial ln permeability distribution) as the following references in various areas attest: oil/gas (USEIA 2011), geothermal [30], mineral deposition [31][32][33][34][35][36] and trace elements [37][38][39][40]. The spatially heterogeneous, length-scale dependence of permeability is documented from lab-scale cm to reservoir-scale km [8,[41][42][43][44][45].…”

Section: Summary and Discussionmentioning

confidence: 99%

Observational and Critical State Physics Descriptions of Long-Range Flow Structures

Malin

Leary²,

Cathles

et al. 2020

Geosciences

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Using Fracture Seismic methods to map fluid-conducting fracture zones makes it important to understand fracture connectivity over distances greater 10–20 m in the Earth’s upper crust. The principles required for this understanding are developed here from the observations that (1) the spatial variations in crustal porosity are commonly associated with spatial variations in the magnitude of the natural logarithm of crustal permeability, and (2) many parameters, including permeability have a scale-invariant power law distribution in the crust. The first observation means that crustal permeability has a lognormal distribution that can be described as κ ≈ κ 0 exp ( α ( φ − φ 0 ) ) , where α is the ratio of the standard deviation of ln permeability from its mean to the standard deviation of porosity from its mean. The scale invariance of permeability indicates that αϕο = 3 to 4 and that the natural log of permeability has a 1/k pink noise spatial distribution. Combined, these conclusions mean that channelized flow in the upper crust is expected as the distance traversed by flow increases. Locating the most permeable channels using Seismic Fracture methods, while filling in the less permeable parts of the modeled volume with the correct pink noise spatial distribution of permeability, will produce much more realistic models of subsurface flow.

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“…Part of a That is, repeated independent determinations of £ in a given problem will vary less than repeated independent determinations of 3C. Link and Koch (1975) and PA , or P_ and P , respectively* The percent ile measures are 84 2.5 97.5 valid and appropriate regardless of the form of the sample or population frequency distributions. The disadvantage in using them, however, is that they are estimated only by graphical procedures and they provide no means for further mathematical analysis of the sources of the variability in the data.…”

Section: Some Excellent Discussion Of Geostatistical Concepts and Mementioning

confidence: 99%

Sampling designs for geochemical surveys: syllabus for a short course

Miesch¹

1976

Open-File Report

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Some consequences of applying lognormal theory to pseudolognormal distributions

Cited by 31 publications

References 3 publications

A Comparative Study of Interpolation Methods for Mapping Soil Properties

A Comparative Study of Interpolation Methods for Mapping Soil Properties

Observational and Critical State Physics Descriptions of Long-Range Flow Structures

Sampling designs for geochemical surveys: syllabus for a short course

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