A common early task when interpreting potential field observations is to separate data due to deep sources from that due to shallow ones. Depth separation is typically achieved by selective filtering of the observation set. A process that can only be approximate because although short wavelength features can only arise from shallow sources, long wavelength features can be both due to deep and due to shallow sources. We present an alternative approach to depth separation that makes use of the approximate inversion method Source Body Migration. Once a 3D density distribution is calculated it can be selectively forward modeled based on whether sources are predicted to be above or below the separation depth. In addition, a procedure will be given for determining the separation depth based on layer-by-layer forward models of the density distribution. The effectiveness of this method will be first demonstrated using simulated Full Tensor Gradiometry (FTG) observations then an example of its application to real FTG survey data given.

Presentation Date: Tuesday, October 13, 2020

Session Start Time: 8:30 AM

Presentation Time: 11:25 AM

Location: 362C

Presentation Type: Oral

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