Accelerated 2.5-D inversion of airborne transient electromagnetic data using reduced 3-D meshing. Issue 1 (25th February 2022) - Engebretsen, Kim Wann; Zhang, Bo; Fiandaca, Gianluca; Madsen, Line Meldgaard; Auken, Esben; Christiansen, Anders Vest
SUMMARY: Airborne systems collecting transient electromagnetic data are able to gather large amounts of data over large areas in a very short time. These data are most often interpreted through 1-D inversions, due to the availability of robust, fast and efficient codes. However, in areas where the subsurface contains complex structures or large conductivity contrasts, 1-D inversions may introduce artefacts into the models, which may prevent correct interpretation of the results. In these cases, 2-D or 3-D inversion should be used. Here, we present a 2.5-D inversion code using 3-D forward modelling combined with a 2-D model grid. A 2.5-D inversion is useful where the flight lines are spaced far apart, in which case a 3-D inversion would not add value in relation to the added computational cost and complexity. By exploiting the symmetry of the transmitter and receiver system we are able to perform forward calculations on a reduced 3-D mesh using only half the domain transecting the centre of the transmitter and receiver system. The forward responses and sensitivities from the reduced 3-D mesh are projected onto a structured 2-D model grid following the flight direction. The difference in forward calculations is within 1.4 per cent using the reduced mesh compared to a full 3-D solution. The inversion code is tested on a synthetic example constructed with complex geology and high conductivity contrasts and the results are compared to a 1-D inversion. We find that the 2.5-D inversion recovers both the conductivity values and shape of the true model with a significantly higher accuracy than the 1-D inversion. Finally, the results are supported by a field case using airborne TEM data from the island of Mayotte. The inverted flight line consisted of 418 soundings, and the inversion spent an average of 6750 s per iteration, converging in 16 iterations with a peak memory usage of 97 GB, using 18 logical processors. In general, the total time of the 2-D inversions compared to a full 3-D inversion is reduced by a factor of 2.5 while the memory consumption was reduced by a factor of 2, reflecting the half-mesh approach.