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

Authors :
Raúl Ulices Silva-Ávalos
Hugo Enrique Júnez-Ferreira
Julián González-Trinidad
Carlos Bautista-Capetillo
Source :
Applied Sciences, Vol 12, Iss 14, p 7252 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

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.

Details

Language :
English
ISSN :
20763417
Volume :
12
Issue :
14
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.0d1dda82b68c4682890f15e8af027a2b
Document Type :
article
Full Text :
https://doi.org/10.3390/app12147252