MRS Parameter Estimation – Improvement by Joint and Laterally Constrained Inversion of MRS and TEM Data

Abstract

We present a new scheme for joint and laterally constrained inversion (LCI) of magnetic resonance sounding (MRS) data and transient electromagnetic (TEM) data, which greatly improves the estimation of the MRS model parameters. MRS is a non-invasive geophysical technique which directly quantifies the water content distribution from surface measurements. The resistivity information of the subsurface is obtained from a complementary geophysical method such as TEM or DC resistivity methods. The conventional inversion of MRS data assumes the resulting resistivity structure to be true and considers a constant MRS kernel through the inversion. We show that this assumption may introduce an error to the forward modeling and consequently result in erroneous parameter estimations. We discuss the advantage of TEM for the joint inversion compared to DC resistivity. A fast and numerically efficient MRS forward routine makes it possible to invert the MRS and TEM data sets simultaneously along profiles. As results, a more reliable and robust estimation of all parameters is achieved. We examine the approach through a field example in Denmark where good agreement with borehole data is demonstrated with clear correlation between the relaxation time T_2^* and the grain size distribution of a sandy aquifer.