A hybrid correlation denoising method based on complex resistivity and application on spread-spectrum induced-polarization data

Abstract

In electrical exploration techniques, an effective suppression method for Gaussian and impulsive random noise in spread-spectrum induced-polarization (SSIP) data continues to be challenging for conventional denoising methods. Remnant noise influences the complex resistivity spectrum and damages the subsequent interpretation of geophysical surveys. We have developed a hybrid method based on a correlation function and complex resistivity, which introduces the correlation analyses among the transmitting source, the measured potential, and the injected current signal. According to the analyses, reliable results for complex resistivity spectra can be calculated, which can be further used for noise suppression. We apply the hybrid method to numerical and field experiments to process the measured SSIP data. Simulation tests find that the hybrid method not only suppresses the two types of noise but also improves the relative error of the complex resistivity spectrum. Field data processing indicates that the hybrid method can minimize the standard deviation of the data and can have a greater ability to distinguish adjacent objects, which can improve the reliability of the data in subsequent processing and interpretation.