Determining the depth of certain gravity sources without a priori specification of their structural index

• Published in: Journal of applied geophysics Vol. 122; pp. 172 - 180
• Main Authors: Zhou, Shuai, Huang, Danian
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.11.2015
• Subjects: Generalized Tilt-depth; Gravity tensor data; Semiautomatic interpretation; Semiautomatic interpretation; Gravity tensor data; Generalized Tilt-depth
• ISSN: 0926-9851; 1879-1859
• DOI: 10.1016/j.jappgeo.2015.09.021

We have developed a new method for the interpretation of gravity tensor data based on the generalized Tilt-depth method. Cooper (2011, 2012) extended the magnetic Tilt-depth method to gravity data. We take the gradient-ratio method of Cooper (2011, 2012) and modify it so that the source type does not need to be specified a priori. We develop the new method by generalizing the Tilt-depth method for depth estimation for different types of source bodies. The new technique uses only the three vertical tensor components of the full gravity tensor data observed or calculated at different height plane to estimate the depth of the buried bodies without a priori specification of their structural index. For severely noise-corrupted data, our method utilizes different upward continuation height data, which can effectively reduce the influence of noise. Theoretical simulations of the gravity source model with and without noise illustrate the ability of the method to provide source depth information. Additionally, the simulations demonstrate that the new method is simple, computationally fast and accurate. Finally, we apply the method using the gravity data acquired over the Humble Salt Dome in the USA as an example. The results show a good correspondence to the previous drilling and seismic interpretation results. •A method called generalized Tilt-depth is presented to interpret gravity data.•The technique uses different height plane data to estimate the source depth.•The method doesn't need a prior specification of source structural index.