This talk and expanded abstract are a branch of my Masters degree
research.
It presents an adaptation of the gravity-gradient inversion to gravity data.

I have added an open-source implementation of the method to the Python
library Fatiando a Terra. In version 0.1 to 0.4,
the code is in module fatiando.gravmag.harvester.

Abstract

This paper presents a novel gravity inversion method for estimating a 3D
density-contrast distribution defined on a grid of prisms. Our method consists
of an iterative algorithm that does not require the solution of a large
equation system. Instead, the solution grows systematically around
user-specified prismatic elements called "seeds". Each seed can have a
different density contrast, allowing the interpretation of multiple bodies with
different density contrasts and interfering gravitational effects. The
compactness of the solution around the seeds is imposed by means of a
regularizing function. The solution grows by the accretion of neighboring
prisms of the current solution. The prisms for the accretion are chosen by
systematically searching the set of current neighboring prisms. Therefore, this
approach allows that the columns of the Jacobian matrix be calculated on
demand. This is a known technique from computer science called "lazy
evaluation", which greatly reduces the demand of computer memory and processing
time. Test on synthetic data and on real data collected over the ultramafic
Cana Brava complex, central Brazil, confirmed the ability of our method in
detecting sharp and compact bodies.

Citation

Uieda, L., and V. C. F. Barbosa (2011), 3D gravity inversion by planting anomalous densities, SBGf 2011 Expanded Abstracts, pp. 1–5, doi:10.1190/sbgf2011-179

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