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The point‐spread function measure of resolution for the 3‐D electrical resistivity experiment
Author(s) -
Oldenborger Greg A.,
Routh Partha S.
Publication year - 2009
Publication title -
geophysical journal international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.302
H-Index - 168
eISSN - 1365-246X
pISSN - 0956-540X
DOI - 10.1111/j.1365-246x.2008.04003.x
Subject(s) - electrical resistivity tomography , gaussian , point spread function , inverse problem , computation , diagonal , measure (data warehouse) , algorithm , impulse response , computer science , mathematics , mathematical analysis , electrical resistivity and conductivity , artificial intelligence , physics , geometry , data mining , quantum mechanics
SUMMARY The solution appraisal component of the inverse problem involves investigation of the relationship between our estimated model and the actual model. However, full appraisal is difficult for large 3‐D problems such as electrical resistivity tomography (ERT). We tackle the appraisal problem for 3‐D ERT via the point‐spread functions (PSFs) of the linearized resolution matrix. The PSFs represent the impulse response of the inverse solution and quantify our parameter‐specific resolving capability. We implement an iterative least‐squares solution of the PSF for the ERT experiment, using on‐the‐fly calculation of the sensitivity via an adjoint integral equation with stored Green's functions and subgrid reduction. For a synthetic example, analysis of individual PSFs demonstrates the truly 3‐D character of the resolution. The PSFs for the ERT experiment are Gaussian‐like in shape, with directional asymmetry and significant off‐diagonal features. Computation of attributes representative of the blurring and localization of the PSF reveal significant spatial dependence of the resolution with some correlation to the electrode infrastructure. Application to a time‐lapse ground‐water monitoring experiment demonstrates the utility of the PSF for assessing feature discrimination, predicting artefacts and identifying model dependence of resolution. For a judicious selection of model parameters, we analyse the PSFs and their attributes to quantify the case‐specific localized resolving capability and its variability over regions of interest. We observe approximate interborehole resolving capability of less than 1–1.5 m in the vertical direction and less than 1–2.5 m in the horizontal direction. Resolving capability deteriorates significantly outside the electrode infrastructure.

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