Lithotype discrimination within a gridded model by inverting gravity data

In this paper we present a method which allows delineation of geologic structures in a bi-modal lithotype setting. We propose to use gravity data in combination with a priori information about the density contrast between the two lithotypes. The iterative method uses an objective function with five tunable parameters which need to be set. Using an efficient parameter search, suitable ranges of these are investigated to determine their optimal values, respectively, which in turn, ensures good inversion results. The approach produces structural images of the subsurface, without the need of an a priori density model; the depth to the top of the inhomogeneity is also retrieved. Besides synthetic simulations, the methodology has also been applied to a small gravity data set, acquired by the industry over a basinal structure. A consistent, bi-modal image of the bedrock depression is obtained from the data, which, in this case, was the goal. Other potential areas of application include delineation of salt structures and ore deposits.