Summary An accurate characterization of subsurface targets relies on the interpretation of multiple geophysical properties and their relationships. There are mainly two links to jointly invert different geophysical parameters: structural and petrophysical relationships. Structural approaches aim at minimizing topological differences and are widely popular since they need only a few assumptions about models. Conversely, methods based on petrophysical links rely mostly on the property values themselves and can provide a strong coupling between models, but they need to be treated carefully because specific direct relationship must be known or assumed. While some petrophysical relationships are widely accepted, it remains the question whether we may be able to detect them directly from the geophysical data. Currently, there is no reported development that takes full advantage of the flexibility of jointly estimating in-situ empirical relationships and geophysical models for a given geological scenario. We thus developed an algorithm for the two dimensional joint inversion of gravity and magnetotelluric data that seeks simultaneously for a density-resistivity relationship optimal for each studied site described trough a polynomial function. The iterative two-dimensional scheme is tested using synthetic and field data from Cerro Prieto, Mexico. The resulting models show an enhanced resolution with an increased structural and petrophysical correlation. We show that by fitting a functional relationship we increased significantly the coupled geological sense of the models at a little cost in terms of data misfit. joint inversion, correspondence maps, gravity, magnetotelluric © The Author(s) 2018. Published by Oxford University Press on behalf of The Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)
Geophysical Journal International – Oxford University Press
Published: May 18, 2018
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