A least-squares minimization approach to interpret gravity data due to 2D horizontal thin sheet of finite width

In the present paper, we have developed a least-squares minimization approach to estimate simultaneously the depth and the width of a buried 2D thin sheet from moving average residual gravity anomalies using the window-curves method. The method involves fitting the 2D thin sheet model convolved with the same moving average filter as applied to the observed data. As a result, our method can be applied not only to residuals but also to the Bouguer gravity data. A scheme for analysis of gravity data has been formulated to determine the model parameters of the thin sheet. The method is applied to synthetic data with and without random errors and tested on a field example from Egypt.