Electrical resistivity monitoring with buried electrodes and cables: Noise estimation with repeatability tests

摘要

Electrodes and cables are sometimes embedded or buried permanently into the ground in order to minimize electrode location errors during long electrical resistivity monitoring. This procedure is efficient and useful. In order to evaluate the feasibility and suitability of this technique for a long monitoring of water content in a rock mass, electrical resistivity data have been repeatedly acquired from a buried array. Forty-eight steel electrodes composed the array, connected to two multicore cables, which have been buried in a trench since January 2006. A fast resistivity-meter was used to carry out dipole-dipole electrical measurements, over a period of one year, starting in December 2006. Data acquisitions of repeated resistivity measurements have been realized in order to distinguish between variations in electrical resistivity due to noise and to changes in water content. Around once every month, successive dipole-dipole array measurements on the same day (between three and eleven arrays with around 10 minutes for one array) have been performed. Using all the pseudosections recorded the same day, the coefficients of variation have been calculated for each data point. Results show that the variability of the data is six times greater when the data from the first array of the day-series are taken into account. The data collected from this first array are therefore significantly noisier than the following measurements and must be removed for correct interpretation. We propose two main explanations for this effect: 1) polarization of the system array/clay at the time of the first acquisition and 2) damage encountered into the buried cables. Despite this damage, we have shown that the electrical data can be consistent and correctly exploited if the first acquisition of the day is not taken into account. In conclusion, on the basis of the results presented here, we recommend that further studies be made using buried equipment to systematically carry out several acquisitions before starting the long monitoring. We also recommend to remove data from the first acquisition whenever they are found to be significantly noisier than data of the following acquisitions.