Probabilistic linear inversion of satellite gravity gradient data
applied to the northeast Atlantic
Abstract
We explore the mantle density structure of the northeast Atlantic region
using constrained linear inversion of the satellite gravity gradient
data based on statistical prior information and assuming a Gaussian
model. The uncertainty of residual gravity gradient signal is
characterized by covariance matrix obtained using geostatistical
analysis of controlled-source seismic data. The forward modelling of the
gravity gradients in the 3D reference crustal model is performed using a
global spherical harmonics analysis. We estimate the model covariance
function in the radial and angular directions using a variogram method.
We compute volumetric gravity gradient kernels for a spherical shell
covering the northeast Atlantic region down to the upper limit of the
mantle transition zone (410 km depth). The solution of the linear
inverse problem in the form the mean density model follows a
least-squares approach. The results indicate a direct relationship
between the seismic velocity and density anomalies in the Iceland-Jan
Mayen region, Greenland and the Norwegian passive margin. The predicted
low-density anomalies at the depth of 100-150 km underneath the
northeast Atlantic Ocean are correlated with the distribution of
Cenozoic underwater volcanoes and seamount-like features of the
seafloor.