Wavelet denoising algorithm to refine noisy geoelectrical data for versatile inversion

Abstract

This paper presents a denoising technique based on wavelet algorithm for inverting geoelectrical resistivity data. The presented work compares different denoising process by thresholding wavelet algorithm. Discrete wavelet transform is used to denoise the geoelectrical resistivity data. It is suitable for applying vertical electrical sounding data. The optimum performance is obtained and the result is investigated under several constraints. This method can be adopted to any geophysical data for pre-processing. Daubechies wavelet functions (‘db’) of different decomposition levels with four (“rigsure”,“universal thresholding”,“minimax”,“heursure”) thresholds were attempted and the significant reduction of noise is effectively done. The data is initially subjected to synthetic noisy data with various levels of signal to noise ratio (SNR) and tested results with optimum condition is implemented to the noisy field data which is verified with the nearby ground truth information. Error measures reveal that is algorithm is best suited for denoising the geoelectrical resistivity data.