Coupled hydrogeophysical inversion using time-lapse magnetic resonance sounding and time-lapse gravity data for hydraulic aquifer testing: Will it work in practice?

Temporal changes in water content can be directly related to the time-lapse signals retrieved using magnetic resonance sounding (TL-MRS) and relative gravimetry (TL-RG). Previous studies suggest that TL-RG measurements can potentially provide accurate estimates of aquifer characteristics in an aquifer pumping test experiment when used in a coupled hydrogeophysical inversion approach. However, these studies considered highly idealized conditions. The aim of this paper is twofold: first, we investigate three major issues which likely limit the practical utility of TL-RG for pumping test monitoring: partially penetrating pumping wells in anisotropic aquifers, delayed drainage effects, and typical data errors for TL-RG. Second, we introduce TL-MRS in a similar coupled hydrogeophysical inversion framework and compare the performance of TL-MRS and TL-RG for pumping test monitoring. For this purpose we consider a virtual pumping test, for which we generate synthetic drawdown, TL-MRS and TL-RG observations, and subsequently determine the aquifer parameters in an inverse parameter estimation approach. The inclusion of TL-RG and TL-MRS data did slightly improve parameter estimates for the specific yield and hydraulic conductivity when considering a fully penetrating well and minimal data error. Using more conservative TL-RG and TL-MRS data error estimates according our own field experience strongly limited the informative value of the TL-RG data; TL-MRS data was less affected by this. For a partially penetrating well under anisotropic conditions, parameter uncertainty could be reduced more effectively compared to a fully penetrating well. Delayed drainage effects did not limit the ability of the TL-MRS and TL-RG data to reduce parameter uncertainty significantly. The incorporation of representative measurement error correlation in the TL-RG data did not affect its informative value. A local sensitivity analysis showed that observations were most sensitive to the pumping rate and the thickness, specific yield, and hydraulic conductivity of the aquifer. The inclusion of TL-MRS data proved to be more effective to constrain the aquifer parameters compared with TL-RG. The inclusion of both TL-RG and TL-MRS had limited added value compared to TL-MRS only. We conclude that this particular application of coupled hydrogeophysical inversion has limited potential for TL-RG, while TL-MRS appears to be a more promising method.