A framework for 3-D joint inversion of MT, gravity and seismic refraction data
Version of Record online: 26 NOV 2010
© 2010 The Authors Geophysical Journal International © 2010 RAS
Geophysical Journal International
Volume 184, Issue 1, pages 477–493, January 2011
How to Cite
Moorkamp, M., Heincke, B., Jegen, M., Roberts, A. W. and Hobbs, R. W. (2011), A framework for 3-D joint inversion of MT, gravity and seismic refraction data. Geophysical Journal International, 184: 477–493. doi: 10.1111/j.1365-246X.2010.04856.x
- Issue online: 15 DEC 2010
- Version of Record online: 26 NOV 2010
- Accepted 2010 October 17. Received 2010 September 27; in original form 2010 August 8
- Inverse theory;
- Gravity anomalies and Earth structure;
- Seismic tomography
We present a 3-D joint inversion framework for seismic, magnetotelluric (MT) and scalar and tensorial gravity data. Using large-scale optimization methods, parallel forward solvers and a flexible implementation in terms of model parametrization allows us to investigate different coupling approaches for the various physical parameters involved in the joint inversion. Here we compare two different coupling approaches, direct parameter coupling where we calculate conductivities and densities from seismic slownesses and cross-gradient coupling, where each model cell has an independent value for each physical property and a structural similarity is enforced through a term in the objective function.
For both types of approaches we see an improvement of the inversion results over single inversions when the inverted data sets are generated from compatible models. As expected the direct coupling approach results in a stronger interaction between the data sets and in this case better results compared to the cross-gradient coupling. In contrast, when the inverted MT data is generated from a model that violates the parameter relationship in some regions but conforms with the cross-gradient assumptions, we obtain good results with the cross-gradient approach, while the direct coupling approach results in spurious features. This makes the cross-gradient approach the first choice for regions were a direct relationship between the physical parameters is unclear.