1887
Volume 17, Issue 5
  • ISSN: 1569-4445
  • E-ISSN: 1873-0604

Abstract

ABSTRACT

An algorithm is proposed for the interpretation of resistivity data that allows the 3D parameters (the boundary in plan view and the depth range) of an anomalous resistivity object in a heterogeneous medium to be determined. The proposed method is based on a vector analysis of the apparent resistivity of soil obtained by a pole–pole survey within the measurement window. In the first stage of the algorithm, in each measurement window, the radius vector is calculated, and as a result, vector images of the main directions of change in the resistivity of the medium are constructed. This allows us to estimate the location of a local anomalous object and to correlate the resistivity of the object with that of the background medium. With a consistent variation in the effective depth of investigation, a set of vector images is formed that characterizes the apparent resistivity distribution in the soil layers. Mathematical analysis of the vector images by using the scalar product allows us to estimate the depth range of the anomalous object. The effectiveness of the proposed algorithm has been proven on synthetic models and in comprehensive investigations of archaeological sites. The proposed method does not allow the true resistivity of an anomalous object to be determined, which is a disadvantage. However, this simple algorithm for processing and analysing shallow electrical prospecting data can be directly used at the preliminary data processing stage during a field survey. First, a pole–pole array can be rapidly operated by a single person; second, the user does not need special knowledge in the field of electrical resistivity data processing. The estimated 3D boundaries of local objects will make it possible to determine the area of interest for further detailed surveying and to justify all the parameters of the measurement technique (distance between electrodes, depth range etc.).

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2019-09-13
2020-09-20
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  • Article Type: Research Article
Keyword(s): Data processing , Interpretation , Near‐surface and Resistivity
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