Non-Linear 3D Satellite Gravity Inversion for Depth to the Basement Estimation in a Mexican Semi-Arid Agricultural Region

Abstract

In Mexico, agriculture in semi-arid regions is highly dependent on groundwater resources, where most of the aquifers’ characterization is a pending task. In particular, the depth to the basement is unknown for most of the Mexican territory. Hence, the development and performance of new techniques for the basement relief estimation is imperative for further hydrogeological studies. In this paper, we present a depth to the basement estimation using non-linear gravimetric inversion employing satellite data. Gravity forward modeling was implemented using both gravitational attraction due to juxtapositioned blocks and gravimetric non-linear inversion using conjugate gradient least squares to minimize the objective function in terms of a depth model. All of this took place under the sparse system framework. We present a synthetic result using the SEG-Bishop depth model taken for calibration purposes. Then, we recollected gravity data from The Satellite Geodesy group from SCRIPPS for the depth to the basement estimation of an unconfined aquifer in the northern-central semi-arid region of Zacatecas, Mexico. Both synthetic and satellite data were recovered, consistent depth models for both cases were presented, and a comparison with conventional gravimetric linear inversion for density estimation was performed.