Summary
Noise is a fundamentally limiting factor for what aspects of the subsurface can be imaged using an AEM system. This paper compares the use of two inversion techniques and two different methods of estimating data noise, to determine how the choice of noise handling impacts inversion results. The use of processing to remove noisy data from an AEM dataset is shown to provide an improved result over using more traditional survey wide system noise level estimates. This result highlights the importance of critically assessing noise present within AEM data and provides a foundation for further development of techniques which can identify and remove noisy data.