Joint inversion method to reduce influence of noise in the inversion of potential field data

Abstract

Rational inversion and interpretation of potential field data gives a view of the earth that highlights geological bodies, structures and boundaries. However, data collected in the field contains different kinds of noise that may have a large passive effect on its inversion. In the presented paper, we tried to utilize joint inversion method to reduce influence of noise in the separate inversion of potential field data. We formulate an iterative procedure based on cross gradient function for joint inversion of different geophysical data. Multiple data set give more information about the subsurface and can reduce influence of noise in the inversion of single potential field data set. The method is applied to synthetic data for typical models of gravity and magnetic anomalies. Experimental results show this method is feasible.