Abstract
About a decade ago, the PERTI algorithm was launched as a tool for a data-adaptive probability-based analysis of electrical resistivity tomography datasets. It proved to be an easy and versatile inversion method providing estimates of the resistivity values within a surveyed volume as weighted averages of the whole apparent resistivity dataset. In this paper, with the aim of improving the interpretative process, the PERTI method is extended by exploiting some peculiar aspects of the general theory of probability. Bernoulli’s conceptual scheme is assumed to comply with any resistivity dataset, which allows a multiplicity of mutually independent subsets to be extracted and analysed singularly. A standard least squares procedure is at last adopted for the statistical determination of the model resistivity at each point of the surveyed volume as the slope of a linear equation that relates the multiplicity of the resistivity estimates from the extracted data subsets. A 2D synthetic test and a field apparent resistivity dataset collected for archaeological purposes are discussed using the new extended PERTI (E-PERTI) approach. The comparison with the results from the original PERTI shows that by the E-PERTI approach a significantly greater robustness against noise can be achieved, besides a general optimisation of the estimates of the most probable resistivity values.
Highlights
Electrical resistivity prospecting is a geophysical technique for imaging sub-surface structures through measurements collected from the surface or in boreholes
About a decade ago, the probability-based ERT inversion (PERTI) algorithm was launched as a tool for a data-adaptive probability-based analysis of electrical resistivity tomography datasets
A 2D synthetic test and a field apparent resistivity dataset collected for archaeological purposes are discussed using the new extended PERTI (E-PERTI) approach
Summary
Electrical resistivity prospecting is a geophysical technique for imaging sub-surface structures through measurements collected from the surface or in boreholes. As outlined in [18], the main peculiarities of the PERTI method are: (i) Unnecessity of a priori information, meant as details not obtainable from the apparent resistivity data set, and full and unconstrained data-adaptability; (ii) decrease of computing time, even two orders of magnitude shorter than that required by commercial softwares in complex 3D cases using the same calculator; (iii) real-time inversion directly in the field, allowing for fast modifications of the survey plan to better focus the expected targets; (iv) total independence from data acquisition techniques and spatial regularity; (v) possibility to be used as an optimum starting model in standard iterative inversion processes in order to speed up convergence and improve resistivity estimation. We present the E-PERTI approach and the evaluation of the new procedure on a synthetic test and on an apparent resistivity dataset collected for archaeological purposes
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
