Extending MARE2DEM to Semi-Airborne and Full Airborne EM Inversion: Synthetic Validation

MARE2DEM (Modeling with Adaptively Refined Elements for 2-D EM) is a freely available 2-D inversion code originally developed by Dr. Kerry Key for marine electromagnetic (EM) surveys. Since the code is open-source, other researchers have extended it to new domains. This demonstrates the flexibility of MARE2DEM for different survey environments beyond its initial marine focus.

In this study, we adapted MARE2DEM to invert semi-airborne and full airborne EM data. The semi-airborne configuration consists of a grounded electric or magnetic dipole transmitter on land with magnetic field receivers flown in air (operating in the ~1–12 kHz band). The inversion results for the semi-airborne case successfully imaged all the detailed structures in the synthetic resistivity models when the recording locations are within 15 m height, confirming that MARE2DEM performs robustly for this new application. Such semi-airborne surveys are well-suited for our targets, such as quick clay deposits and mineral deposits.

By contrast, the full airborne EM case proved challenging. We applied MARE2DEM to a helicopter-borne frequency-domain system (NGU’s “Hummingbird” system) operating at five frequencies (approximately 880 Hz, 6.6 kHz, 34 kHz in horizontal coplanar, and 980 Hz, 7 kHz in vertical coaxial mode) with 5-6 m transmitter–receiver separations. In this scenario, where both transmitter and receivers are airborne and moving, we encountered inaccuracies in the forward modelling. High-frequency airborne EM data are particularly numerically demanding to model it accurately, as the free-space transmitter geometry and high frequency range require very fine discretization. We found that the standard adaptive meshing in MARE2DEM needed further refinement to capture the decaying fields in air. To improve the forward accuracy, we tested a range of strategies, including using more finely discretized meshes and carefully tuning the wavenumber sampling for the 2.5D solver. These measures reduced the modelling errors, but we still did not reach the same level of accuracy for full airborne modelling as in the marine or semi-airborne cases. The results indicate that additional developments are required for full airborne EM data modelling and inversion. In summary, our extension of MARE2DEM works well for semi-airborne EM surveys, achieving resolution comparable to the original marine applications, whereas the full airborne case remains problematic in forward modelling. Further improvements are being explored to enable reliable forward modelling and inversion of full airborne EM datasets.