Mapping the Depth to Basement by Iterative Rescaling of Gravity or Magnetic Data

I propose a new method to estimate the morphology of the basement under sedimentary basins, starting from measured gravity or magnetic anomalies. The method is based on a simple relation existing between the depth to basement and gravity or pseudogravity fields. This simple relation (approximately linear for homogeneous sediment basins) is fitted by a polynomial regression, and the data can be immediately rescaled in terms of depth to the basement. The use of this method is possible when several depth constraints are available, such as wells perforating the basement or other geophysical data interpretations indicating the depth to basement at some locations. The first-approximation model is iteratively improved by rescaling the misfit between the observed and the model-generated field and by adding this correction to the first model. A further output of the method is the estimation of a constant density/magnetization contrast or of a depth-density function. The method does not consider lateral variations in the basin fill density, nor variations in the basement magnetization. The method is demonstrated on a synthetic complex basement model in the cases of a constant density contrast, with or without noise, and in the case of a variable depth-density function. The method is computationally very efficient, as it involves no matrix inversion nor multiplication. The applicability of the method to real gravity data is finally demonstrated by the modeling of the gravity anomalies of the Pannonian basin (Austria). The obtained model compares well to a previous interpretation of the same data using different constraints.