Depth estimating Full Tensor Gravity data with the Adaptive Tilt Angle method

Abstract

Depth estimation procedures for potential field data are well recognised techniques. Both Euler and Werner methodologies are typically used as a series of automated steps and applied to both gridded and profile data. The Tilt Derivative Depth method works on gridded data and has been used extensively on magnetic data. Its advantage is its ability to produce a focused set of solutions and is now being commonly adopted for potential field data. This paper describes an Adaptive Tilt Angle method for depth estimating Full Tensor Gravity data. The method is an adaptation of the Tilt Derivative depth estimation procedure adopted for magnetic data. The procedure works on 4 of the independently measured Tensor components and produces sets of solutions that are more easily interpreted. The tilt angle method is defined as a ratio of the Tensor components in each of the X, Y and Z directions and assumes a vertical contact geological setting. The implementation of a scaling factor allows the technique to work on horizontal contacts. The scaling factor is essentially similar to the concept of a Structural Index as used with Euler depth estimation methods. The technique was tested successfully on an Air-FTG® survey data set over a shallow salt feature onshore USA and is now being routinely deployed. The benefits of the direct depth estimation technique are immense in that it not only provides constraint on other interpretative processing techniques, but quickly establishes a starting depth model for any detailed forward / inverse modelling exercises.