Defining a deep fault network for Australia, using 3D 'worming'

Abstract

Defining a deep fault network for Australia, using 3D 'worming'. The original work on multi-scale edge detection ('worming') done by Hornby et al. in 1999 has become increasingly popular as a starting point for rapid interpretation using potential field data. Both gravity and magnetic grids are used. Several improvements have been made in the following years such that it is routine to capture points, 'worms' and linear features in a form suitable for overlay in GIS packages. There are important extensions which have recently been completed: (a). support for gravity gradiometry using the measured gradients directly (b). creation of interface and foliation data implying 3D surfaces that are geolocated. (c). adaption of Euler deconvolution techniques to both full tensor gravity gradiometry (FTG) and a best located method for scalar measures. This paper reports on these new extensions applied to the Australian gravity grid and on issues arising from these efforts to improve/generalise the worming technology and get 3D contacts that can be interpreted. This large scale gravity dataset, with a high density of near surface features, contains far too many gradients interpreted as faults, so a thinning strategy is required to find the significant deep crustal faults. These deep crustal faults require proper attribution of depth, dip direction and dip, and also extent constraints. For the FTG case, the largest 3-survey merge attempted to date has occurred with data acquired in Kenya. The new and improved 3D worming has been applied in the context of rapidly defining the horst/graben layouts in an active rift zone. Some discussion and illustration of the present problems of how to build, merge and manage a 3D fault network, where the issues of faults terminating on other faults and which fault cuts which, will be shown and discussed.