Joint 3D Inversion of ZTEM Airborne and Ground MT Data with Application to Geothermal Exploration

ZTEM is an airborne electromagnetic (EM) geophysical technique developed by Geotech Inc® where naturally propagated EM fields originating with regional and global lightning discharges (sferics) are measured as a means of inferring subsurface electrical resistivity structure. A helicopter-borne coil platform (bird) measuring the vertical component of magnetic (H) field variations along a flown profile is referenced to a pair of horizontal coils at a fixed location on the ground in order to estimate a tensor H-field transfer function. The ZTEM method is distinct from the traditional magnetotelluric (MT) method in that the electric (E) fields are not considered because of the technological challenge of measuring E-fields in the dielectric air medium. This can lend some non-uniqueness to ZTEM interpretation because a range of conductivity structures in the earth depending upon an assumed background earth resistivity model can fit ZTEM data to within tolerance. MT data do not suffer this particular problem, but they are cumbersome to acquire in their common need for land-based transport often in near-roadless areas and for laying out and digging the electrodes and H coils. The complementary nature of ZTEM and MT logistics and resolution has motivated development of schemes to acquire appropriate amounts of each data type in a single survey and to produce an earth image through joint inversion. In particular, consideration is given to surveys where only sparse MT soundings are needed to drastically reduce the non-uniqueness associated with background uncertainty while straining logistics minimally. Synthetic and field data are analysed using 2D and 3D finite element platforms developed for this purpose. Results to date suggest that indeed dense ZTEM surveys can provide detailed heterogeneous model images with large-scale averages constrained by a modest number of MT soundings. Further research is needed in determining the allowable degree of MT sparseness and the relative weighting of the two data sets in joint inversion.