A LEAST-SQUARES MINIMIZATION APPROACH TO DEPTH DETERMINATION FROM MOVING AVERAGE RESIDUAL GRAVITY-ANOMALIES

We have developed a least-squares minimization method to estimate the depth of a buried structure from moving average residual gravity anoma lies. The method involves fitting simple models convolved with the sam e moving average filter as applied to the observed gravity data. As a result, our method can be applied not only to residuals but also to th e Bouguer gravity data of a short profile length. The method is applie d to synthetic data with and without random errors. The validity of th e method is tested in detail on two field examples from the United Sta tes and Senegal.