Improvement In Depth And Structural Index Estimation Of Potential Field Sources By Using Curvature Attributes

Interpretation of potential field data generally is quantitative or qualitative. An important factor in the issue of interpretation is how much interpreter is confident on data that provides the information needed to achieve the objectives of the study. Reliance on interpretation can be increased by the use of effective methods for parameters determination of causative sources. Although in most of methods not required to know the density or susceptibility contrast, but these methods are based on the assumption that the source is a certain type (horizontal slab, vertical dykes, etc.) and in two-dimension. By selecting the wrong type of sources, large errors may occur. Despite all these problems, numerous automatic techniques are designed that can be applied over the magnetic or gravity anomalies to quickly estimate the depth of sources.
Curvature method is used to analyze and interpretation of potential field anomalies. Potential field anomalies can be transformed into special functions that formed peaks and ridges over isolated sources. All of these special functions have a mathematical form over sources that lead to a common equation to estimate the depth of the source from the peak value and curvature at the peak. Curvature attributes that used at this case called most negative curvature. Special functions are divided into two categories: Model-specific special functions and Model-independent special functions. Model-specific special functions usually are calculated from a transformed potential field for locating of specific sources such as a vertical magnetic contact, vertical density contact, etc. The horizontal gradient magnitude (HGM) and observed potential field (absolute value) are two types of model-specific special functions that formed ridges over specific sources. Model-independent special functions are used to calculate locations for various types of sources from the observational or modified potential field. Total gradient (TG), also called the analytic signal, and local wavenumber (LW) fall into this group.
Usually, special functions need that the potential field undergoes a transformation, such as reduction-to-pole and vertical derivative. For gridded data, eigenvalues of the curvature matrix associated with quadratic surface is fitted to a special function within 3×3 window, to locate and estimate the depth of sources.
Another curvature attributes is shape index that quantitatively stated the local shape in terms of bowl, valley, flat, ridge and dome. Shape index attribute (SHI) and Geometry factor provide a way to easily reject some of invalid estimations.
In this study, method of curvature attributes has been applied on noisy and noise free synthetic data by using Model-specific (HGM and absolute value) and Model-independent special functions (Total gradient and local wavenumber). Finally, this method was tested on real data from Mobrun massive sulfide ore of Canada by using special functions of two models and was estimated a structural index (SI) from local wavenumber special function for the mine. The results of estimating the depth by this method had a good match with the results of the boreholes. Finally, the depth results of this method were compared with Euler deconvolution method which shows that method of using curvature attributes is more accurate in depth estimation.