Basement depth estimation from gravity anomalies: two 2.5D approaches coupled with the exponential density contrast model

Abstract

We develop two automatic techniques in the spatial domain using the exponential density contrast model (EDCM) to trace the bottom surface of a 2.5D sedimentary basin from the observed gravity anomalies. The interface between the sediments and basement is described with a finite strike polygonal source, whose depth ordinates become the unknown parameters to be estimated. The proposed automatic modeling technique makes use of the forward difference approximation and the inversion solves a system of normal equations using the ridge regression to estimate the unknown parameters. Furthermore, the proposed inversion technique simultaneously estimates the regional gravity background that is associated with the residual gravity anomaly. In either case, forward modeling is realized in the spatial domain through a method that combines both analytical and numerical approaches. The utility of each algorithm was successfully tested on a theoretically produced noisy residual gravity dataset. The validity of the inversion technique is also exemplified with the noisy gravity anomalies attributable to a synthetic structure in the presence of regional gravity background. We demonstrate that the magnitude of gravity anomaly is offset dependent and that it would influence the modeling result. Additionally, some applications with real gravity datasets from the Gediz and Buyuk Menderes grabens in western Turkey using the derived EDCMs have produced geologically reasonable results which are in close agreement with those reported previously.