SERIES EXPANSION BASED TAU-TRANSFORMATION WITH APPLICATION TO TDIP DATASET

Abstract

Geophysical data processing in the TDIP has shown itself to be an important and effective tool in ore exploration. The recovered images from the induced polarization (IP) survey are interpreted by geologists to understand the near-surface geological structures and to guide further exploration activities such as spotting drill holes. However, it does not always provide an exact near-surface image that reliably reflects the structural and physical properties of the target for many reasons. This paper aims to investigate the combination between the TAU transformation and the series expansion inverse method based on the overdetermined inverse problem (linearized Gaussian least squares method) in the data analysis of IP data. We also developed a stable algorithm to solve TAU transformation through the overdetermined problem (GLSQ). In this algorithm, the series expansion technique and a logarithmic transformation have been extended to define the unknown parameters. This algorithm is useful for the quick processing of TDIP data and may assist in accuracy improvement of the interpretation of a geoelectric survey in ore exploration.