# Offset errors in probabilistic inversion of small-loop frequency-domain electromagnetic data: a synthetic study on their influence on magnetic susceptibility estimation

## TL;DR

This study investigates how systematic offset errors in small-loop frequency-domain electromagnetic data affect the estimation of magnetic susceptibility, demonstrating that joint estimation of offsets improves inversion accuracy.

## Contribution

It introduces a probabilistic inversion method that jointly estimates measurement offsets along with subsurface properties, enhancing susceptibility estimation accuracy.

## Key findings

- Joint offset and property estimation reduces bias in susceptibility results.
- Using multiple measurement heights improves offset correction.
- Systematic errors significantly impact magnetic susceptibility estimates.

## Abstract

Small-loop frequency-domain electromagnetic (FDEM) devices measure a secondary magnetic field caused by the application of a stronger primary magnetic field. Both the in-phase and quadrature component of the secondary field commonly suffer from systematic measurement errors, which would result in a non-zero response in free space. The in-phase response is typically strongly correlated to subsurface magnetic susceptibility. Considering common applications on weakly to moderately susceptible grounds, the in-phase component of the secondary field is usually weaker than the quadrature component, making it relatively more prone to systematic errors. Incorporating coil-specific offset parameters in a probabilistic inversion framework, we show how systematic errors in FDEM measurements can be estimated jointly with electrical conductivity and magnetic susceptibility. Including FDEM measurements from more than one height, the offset estimate becomes closer to the true offset, allowing an improved inversion result for the subsurface magnetic susceptibility.