Gravity inversion using a directional filtering method

TL;DR

This paper introduces a new gravity inversion method using directional filtering of vector gravity components, achieving accurate shallow density reconstructions with asymptotic convergence properties.

Contribution

It develops a novel scalar equation from vector gravity data using a directional filter, enabling iterative inversion with asymptotic accuracy.

Findings

Accurate shallow density field reconstructions

Convergence to true density values at low rates for deep fields

Method effectively uses vector gravity components for inversion

Abstract

The calculation of the underground density field from measured gravity data has been done by a variety of methods of varied types. The use of the vector gravity components is here addressed in order to develop one accurate gravity inversion method. The equation to directly calculate the Cartesian components of the gravity field from the density field is transformed in one non-exact correction equation. The discrete vector equations are transformed into scalar equations by using one vector function as directional filter. The used equations have the property that the convergence of the calculated density field to the exact values may only happen if the same occurs to the gravity field. The equations of the method so admit asymptotic exact solutions to the gravity inversion problem. The use of a smooth directional filter allows the equilibrated influence of all the gravity data over all the calculated density deviation corrections. The unknown density field is calculated by means of one iterative under-relaxed method. Two synthetic gravity fields are inverted by means of the presented method. The calculated shallow density fields are very accurate while the far density fields apparently converge to the correct values at very low convergence rates.