Variogram models reconstruction for damaged ERT Profiles
Résumé
Abstract Reconstructing signals which are embedding spatial pattern such as Electrical resistivity tomography, is a process that should require to reconstruct first the spatial correlation of the damaged signals. This paper proposes an approach which implement an Unstationary Kriging (UNK) to reconstruct the experimental var-iogram of a damaged synthetic pseudo section within a set of pseudo sections coming from the same survey. We used and compare 02 other simple methods which are the Linear Regression (LR) and the Ordinary Kriging (OK), to test the hypothesis we formulate to link the experimental variograms coming from a same ERT survey. After an implementation of the hybrid process (UNK) on 02 sets of data which are synthetics, we observed that the LR and the UNK methods present an interest. They both reconstruct signals with a +90% rate of accuracy, but when there are no structure or spatial correlation within the data, the LR is unstable. In the end, we conclude on an evidence that is : the proposed hybrid process is a promising way to reconstruct variographic signals, since we can improve it after more time invested to dig deep into the modeling of each of his components.
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