2-D gravity modeling with analytically defined geometry and quadratic polynomial density functions

Abstract

New methods for 2-D modeling of gravity anomaly data are developed following an approach that uses both analytic and numerical methods of integration. The forward‐model solution developed here is suitable to calculate the gravity effect caused by a 2-D source body bounded either laterally or vertically by continuous functions. In our models, the density contrast is defined by a second‐order polynomial function of depth and distance along the profile. We present several examples to show that our models are capable of accommodating a broad variety of geologic structures.

Gravity anomaly modelling of multiple geological sources having differing strike lengths and arbitrary density contrast variations

“…Martin‐Atienza and Garcia‐Abdeslem () developed a technique to calculate gravity anomalies of 2D sources with an analytically defined geometry and second‐order polynomial functions of depth and distance along the profile. Zhang et al .…”

Gravity anomalies of strike limited listric fault sources with analytically defined fault planes and arbitrary density contrast variations with depth

“…The above interpretational strategies, which assume planar surfaces for the fault planes, find limited application in modelling of gravity anomalies due to strike limited listric fault sources. Although a few interpretational methods exist that can accommodate the geometry of listric fault structures to realize forward gravity modelling (Martín‐Atienza and García‐Abdeslem ; García‐Abdeslem , ; Zhang et al . ; Zhou , ), these methods are efficient only with 2D sources.…”

A generalized algorithm for gravity or self-potential data inversion with application to mineral exploration

“…SP and gravity interpretations can be based on a model defined by a fixed simple geometry such as sphere, horizontal cylinder and vertical cylinder, and the objective in this case is to determine the shape and the depth of the buried structure from residuals and/or observed data. Several methods have been developed for this category to interpret gravity or SP data (Martin-Atienza, and Garcia-Abdeslem, 1999;Abdelrahman et al, 2003;Essa et al, 2008). The drawback of these methods is that they are highly subjective, need a priori information about the shape (shape factor) of the anomalous body and they use few characteristic points when inverting for the remaining parameters.…”