A priori models and inversion of gravity gradient data in hilly terrain

The increased popularity of airborne measurements of the gravity gradient tensor for resource studies and geological mapping has resulted in a new awareness of the importance of terrain effects. In these measurements, the terrain effect often overwhelms that of the underlying crust and it becomes important to formulate a strategy for taking it into account when presenting the data and when inverting the data into density models. Using newly acquired data from Northern Sweden, we first attempted to estimate a variable terrain density model by inverting the data using a terrain model with a laterally varying density. Using data weights related to the topography variations, we find the best estimate of the lateral variation of the terrain density. We translate this model into a full three‐dimensional model such that all columns have the same vertical centre of mass as estimated from inspecting the radially averaged power spectrum of the area. This then defines a reference model for subsequent three‐dimensional inversion of the gravity gradient tensor dataset. We tested this approach first on synthetic data calculated from the measured topography including two density anomalies before we applied it to the measured data. The result is a model in which the surface density variations are propagated downwards in a systematic manner now in better agreement with measured densities of rock samples in the area.