Higher-order statistics correlation stacking for DC electrical data in the wavelet domain

Abstract

DC (direct current) electrical and shallow seismic methods are indispensable to the near surface geophysical exploration, but the near surface areas are very difficult environments for any geophysical exploration due to the random noise caused by near surface inhomogeneities . As a new algorithm based on higher-order statistics theory, the higher-order correlation stacking algorithm for seismic data smoothing in the wavelet domain has been developed and applied efficiently to filter some correlation noise that the conventional second-order correlation stacking could not inhibit. In this paper, this higher-order statistics correlation stacking technology is presented for DC electrical data in wavelet domain. Taking into account the single section and multiple section data, we present two new formulations of correlation stacking for DC electrical data. Synthetic examples with Gaussian noise are designed to analyze the overall efficiency of the new algorithm and to determine its efficacy. Meanwhile, comparison with the traditional least-squares optimization inversion method for field examples from electrical imaging surveys and time-domain IP measurement in China shows its significant advantages. The quality of the new algorithm also has been assessed by physical simulation experiments. This new technology in DC electrical exploration measurements provides a new application in engineering and mining investigation. • The higher order statistics correlation stacking in wavelet domain • Considered the correlation in adjacent electrode resistivity data • Considered the full time decay of the induced polarization response • Presented two new formulations of correlation stacking for DC electrical data • The higher order statistics correlation stacking applied efficiently in DC data