Consistency investigation, vertical gravity estimation, and inversion of airborne gravity gradient data — A case study from northern Sweden

Abstract

For airborne gravity gradient data, it is a challenge to distinguish between high-frequency intrinsic and dynamically produced noise caused by the aircraft and small-scale effects from shallow density variations. To facilitate consistent interpretation, techniques that include all of the measured gravity gradient components are particularly promising. We represented the measurements by a common potential function accounting for lateral and height variations. Thus, it was possible to evaluate the internal consistency between the measured components and to identify components with bias or particularly strong noise. As an extra benefit for data sets that contain terrain-corrected and nonterrain-corrected gravity gradient measurements at flight altitude, we estimated terrain-corrected anomalies on the topographic relief using downward continuation and retrieved nonterrain-corrected gravity gradient data suitable for inversion using upward continuation. For a field data set from northern Sweden, the largest differences (up to 50 eotvos) between the measured and estimated components of the gravity gradient data were found in areas of high topographical relief. But the average residual standard deviations of the individual components were between 3.6 and 7.4 eotvos, indicating that the components were consistent in an average sense. We have determined the successful conversion of terrain-corrected airborne gravity gradient data to Bouguer gravity data on the topographic relief using ground-based vertical gravity data as a reference. A 3D inverse model computed from the nonterrain-corrected data clearly showed the depth extent of the geologic structures observed at the surface, but it only produced a weak representation of the shallow structure. In contrast, a 2D surface density model in which only lateral variations of density in the topographic relief was allowed exhibited more realistic density distributions in fair correlation with geology.