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On the Limitations of Applying Petrophysical Models to Tomograms: A Comparison of Correlation Loss for Cross-Hole Electrical-Resistivity and Radar Tomography.

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On the Limitations of Applying Petrophysical Models to Tomograms: A Comparison of Correlation Loss for Cross-Hole Electrical-Resistivity and Radar Tomography. / Day-Lewis, Frederick D.; Singha, Kamini; Binley, Andrew M.
In: Journal of Geophysical Research: Solid Earth, Vol. 110, No. B8, B08206, 08.2005.

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Day-Lewis FD, Singha K, Binley AM. On the Limitations of Applying Petrophysical Models to Tomograms: A Comparison of Correlation Loss for Cross-Hole Electrical-Resistivity and Radar Tomography. Journal of Geophysical Research: Solid Earth. 2005 Aug;110(B8):B08206. doi: 10.1029/2004JB003569

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@article{03461265af4a4be9b4c53f5aba8b345e,
title = "On the Limitations of Applying Petrophysical Models to Tomograms: A Comparison of Correlation Loss for Cross-Hole Electrical-Resistivity and Radar Tomography.",
abstract = "Geophysical imaging has traditionally provided qualitative information about geologic structure; however, there is increasing interest in using petrophysical models to convert tomograms to quantitative estimates of hydrogeologic, mechanical, or geochemical parameters of interest (e.g., permeability, porosity, water content, and salinity). Unfortunately, petrophysical estimation based on tomograms is complicated by limited and variable image resolution, which depends on (1) measurement physics (e.g., electrical conduction or electromagnetic wave propagation), (2) parameterization and regularization, (3) measurement error, and (4) spatial variability. We present a framework to predict how core-scale relations between geophysical properties and hydrologic parameters are altered by the inversion, which produces smoothly varying pixel-scale estimates. We refer to this loss of information as “correlation loss.” Our approach upscales the core-scale relation to the pixel scale using the model resolution matrix from the inversion, random field averaging, and spatial statistics of the geophysical property. Synthetic examples evaluate the utility of radar travel time tomography (RTT) and electrical-resistivity tomography (ERT) for estimating water content. This work provides (1) a framework to assess tomograms for geologic parameter estimation and (2) insights into the different patterns of correlation loss for ERT and RTT. Whereas ERT generally performs better near boreholes, RTT performs better in the interwell region. Application of petrophysical models to the tomograms in our examples would yield misleading estimates of water content. Although the examples presented illustrate the problem of correlation loss in the context of near-surface geophysical imaging, our results have clear implications for quantitative analysis of tomograms for diverse geoscience applications.",
author = "Day-Lewis, {Frederick D.} and Kamini Singha and Binley, {Andrew M.}",
note = "Collaborative project between USGS (US), Stanford (US) and Lancaster. Binley provided methodology for resistivity tomography analysis aspect of work and assisting in development of overall concept and application to test dataset. RAE_import_type : Journal article RAE_uoa_type : Earth Systems and Environmental Sciences",
year = "2005",
month = aug,
doi = "10.1029/2004JB003569",
language = "English",
volume = "110",
journal = "Journal of Geophysical Research: Solid Earth",
publisher = "Wiley-Blackwell",
number = "B8",

}

RIS

TY - JOUR

T1 - On the Limitations of Applying Petrophysical Models to Tomograms: A Comparison of Correlation Loss for Cross-Hole Electrical-Resistivity and Radar Tomography.

AU - Day-Lewis, Frederick D.

AU - Singha, Kamini

AU - Binley, Andrew M.

N1 - Collaborative project between USGS (US), Stanford (US) and Lancaster. Binley provided methodology for resistivity tomography analysis aspect of work and assisting in development of overall concept and application to test dataset. RAE_import_type : Journal article RAE_uoa_type : Earth Systems and Environmental Sciences

PY - 2005/8

Y1 - 2005/8

N2 - Geophysical imaging has traditionally provided qualitative information about geologic structure; however, there is increasing interest in using petrophysical models to convert tomograms to quantitative estimates of hydrogeologic, mechanical, or geochemical parameters of interest (e.g., permeability, porosity, water content, and salinity). Unfortunately, petrophysical estimation based on tomograms is complicated by limited and variable image resolution, which depends on (1) measurement physics (e.g., electrical conduction or electromagnetic wave propagation), (2) parameterization and regularization, (3) measurement error, and (4) spatial variability. We present a framework to predict how core-scale relations between geophysical properties and hydrologic parameters are altered by the inversion, which produces smoothly varying pixel-scale estimates. We refer to this loss of information as “correlation loss.” Our approach upscales the core-scale relation to the pixel scale using the model resolution matrix from the inversion, random field averaging, and spatial statistics of the geophysical property. Synthetic examples evaluate the utility of radar travel time tomography (RTT) and electrical-resistivity tomography (ERT) for estimating water content. This work provides (1) a framework to assess tomograms for geologic parameter estimation and (2) insights into the different patterns of correlation loss for ERT and RTT. Whereas ERT generally performs better near boreholes, RTT performs better in the interwell region. Application of petrophysical models to the tomograms in our examples would yield misleading estimates of water content. Although the examples presented illustrate the problem of correlation loss in the context of near-surface geophysical imaging, our results have clear implications for quantitative analysis of tomograms for diverse geoscience applications.

AB - Geophysical imaging has traditionally provided qualitative information about geologic structure; however, there is increasing interest in using petrophysical models to convert tomograms to quantitative estimates of hydrogeologic, mechanical, or geochemical parameters of interest (e.g., permeability, porosity, water content, and salinity). Unfortunately, petrophysical estimation based on tomograms is complicated by limited and variable image resolution, which depends on (1) measurement physics (e.g., electrical conduction or electromagnetic wave propagation), (2) parameterization and regularization, (3) measurement error, and (4) spatial variability. We present a framework to predict how core-scale relations between geophysical properties and hydrologic parameters are altered by the inversion, which produces smoothly varying pixel-scale estimates. We refer to this loss of information as “correlation loss.” Our approach upscales the core-scale relation to the pixel scale using the model resolution matrix from the inversion, random field averaging, and spatial statistics of the geophysical property. Synthetic examples evaluate the utility of radar travel time tomography (RTT) and electrical-resistivity tomography (ERT) for estimating water content. This work provides (1) a framework to assess tomograms for geologic parameter estimation and (2) insights into the different patterns of correlation loss for ERT and RTT. Whereas ERT generally performs better near boreholes, RTT performs better in the interwell region. Application of petrophysical models to the tomograms in our examples would yield misleading estimates of water content. Although the examples presented illustrate the problem of correlation loss in the context of near-surface geophysical imaging, our results have clear implications for quantitative analysis of tomograms for diverse geoscience applications.

U2 - 10.1029/2004JB003569

DO - 10.1029/2004JB003569

M3 - Journal article

VL - 110

JO - Journal of Geophysical Research: Solid Earth

JF - Journal of Geophysical Research: Solid Earth

IS - B8

M1 - B08206

ER -