Which geoelectric array sees the deepest in a noisy environment? Depth of detectability values of multielectrode systems for various two-dimensional models

Szalai, S.; Novák, Attila; Szarka, László

doi:10.1016/j.pce.2011.01.008

Cited by 20 publications

(29 citation statements)

References 17 publications

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“…In the present paper we demonstrate the way how we theoretically obtained specific ME-arrays which supposed to provide higher DD values than the conventional ones which were studied by Szalai et al, (2011). Computations of the DD values of these specific arrays have confirmed that certain ones have larger DD values than the conventional ones.…”

supporting

confidence: 56%

“…3a) 30 various electrode distances were applied; for the pole-dipole (P-DP) and dipole axial (DP-ax) arrays the dipole length was equal to the electrode distance and 50 different values for the distance between the dipoles were considered. These are the same arrays that have been studied in a former work by Szalai et al, (2011). In the present paper we completed the cited study with 10 further arrays, the γ 11n Fig.…”

Section: Methods To Calculate the Dd Values And The Studied Me Arraysmentioning

confidence: 70%

“…Moreover DI calculations haven't taken into consideration the effect of the noise. Ignoring the evidently present noise may lead to infinite DI values (Szalai et al, 2011). Szalai et al, (2011) introduced therefore the depth of detectability (DD) value providing a suitable parameter.…”

mentioning

confidence: 99%

“…Ignoring the evidently present noise may lead to infinite DI values (Szalai et al, 2011). Szalai et al, (2011) introduced therefore the depth of detectability (DD) value providing a suitable parameter. DD is the maximal depth, where a given inhomogeneity can still be detected by means of a given ME-array, in the presence of a given level of noise.…”

mentioning

confidence: 99%

“…Apart from the ones that have been studied by Szalai et al, (2011) almost hundred other arrays have been applied before (Szalai and Szarka, 2008a).…”

mentioning

confidence: 99%

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Multiplication of the depth of detectability using γ11n arrays

Szalai¹,

Lemperger²,

Metwaly³

et al. 2014

Journal of Applied Geophysics

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The depth from which one can get information has always been a crucial parameter in the geophysical exploration. This paper deals with the depth of detectability (DD) of 2D electric resistivity tomography configurations. DD is the maximal depth from which a given model body is detectable in the presence of a given noise level. Based on previous DD calculations for conventional electrode arrays it is shown in this paper that there is a nearly linear relation between the maximum value of their parameter-sensitivity (PS) maps and their DD values. Studying the PS maps of other arrays, as well, we found that many of them have higher PS max values than those of the conventional arrays. These so-called γ 11n arrays are therefore expected to have larger DD values, too. The performed DD-calculations have confirmed this expectation. γ 11n arrays are linear geoelectric arrays where γ refers to the CPCP order of the current (C) and potential (P) electrodes whilst the subscript numbers refer to the distance of the neighbouring electrodes. In case of the studied prism and dyke models the γ 11n arrays -if n is larger or equal to 2 -consistently produced higher DD-values than the best conventional arrays. The DD value of these arrays can be even 2-3 times larger than that of the best conventional array value. Such an increase in the DD value is especially useful if the available place for measurements is limited, e.g. due to infrastructural conditions. Anomalies in large depth, for example, which are not seen by traditionally used arrays, may become detectable using γ 11n arrays as it was verified also by numerical studies. These arrays require moreover less measurement than most conventional arrays resulting in shorter measuring time.

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supporting

confidence: 56%

Section: Methods To Calculate the Dd Values And The Studied Me Arraysmentioning

confidence: 70%

mentioning

confidence: 99%

mentioning

confidence: 99%

“…Apart from the ones that have been studied by Szalai et al, (2011) almost hundred other arrays have been applied before (Szalai and Szarka, 2008a).…”

mentioning

confidence: 99%

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Multiplication of the depth of detectability using γ11n arrays

Szalai¹,

Lemperger²,

Metwaly³

et al. 2014

Journal of Applied Geophysics

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Different techniques for the assessment of geoelectrical data errors to improve the electrical images obtained at an industrial plant

Martinélli

Osella

Vega

et al. 2018

Near Surface Geophysics

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The objective of this work was to characterise the bases of columns belonging to an industrial plant. We had to design a proper methodology for characterising these structures, in a place with limited available space and time for the deployment of sensors, and with other environmental constraints, such as high electromagnetic noise level, soil vibrations due to operating machines, and complex soil composition. In particular, the floor had a stainless steel cover about 1‐cm thick, below which there was first a layer of concrete about 30‐cm thick and then clay material used to absorb the oils of the machines. Finally, there was the natural soil on which the column bases stood. Given these characteristics, we performed dipole–dipole geoelectric profiles. Holes were drilled through the metallic cover and the concrete layer, with fixed spacings, to insert the electrodes. Because of this and the space and time restrictions, only one profile could be performed for each column. Since we knew that the data could have high noise levels and other errors negatively impacting the data quality, and also because there was a limitation to the length of the profiles, we optimised the measurement configuration by jointly using several electrode apertures, to ensure the best possible resolution and sufficient penetration depth. To obtain adequate error estimations, we performed direct and reciprocal measurements. As an alternative technique, we also carried out a second set of direct measurements, after removing and reinstalling the electrodes. Then, for each profile, we performed 2D inversions of the three datasets separately, without considering data errors. Besides, we inverted the datasets obtained by combining the first direct and the reciprocal measurements, and the first and second direct measurements, considering the two obtained error estimates. In addition, numerical simulations were made, combining direct 3D modelling with 2D inversions. To analyse the results, we took into account the knowledge we had in advance about the main characteristics of the structures. The first conclusion obtained is that, at least for this type of structures, inverting each dataset without considering data errors provided more realistic images. However, although the best results were obtained by inverting without considering errors, it was still fundamental to have different sets of data, for evaluating the reliability of the images and for discarding possible spurious artefacts. This is especially important in environmentally complex urban sites, where errors could be particularly high. Finally, through the numerical simulations, a more rigorous interpretation could be made, and also, the effect of data errors in the quality of the images could be assessed.

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