What is it about?
Joint inversion of different EM data but similar model parameter: resistivity or conductivity, with Gramian constraint (dot product of the model parameters).
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Why is it important?
Coincident data, especially those of similar model parameter can easily be incorporated into Gramian constrained Joint inversion to maximize the power of data and steer the inversion to a unique solution, which otherwise is absent in the individual standalone inversions.
Perspectives
This Gramian approach ought to become a regular constraint added to the traditional nonlinear least squares inversion to squeeze out maximum model parameter information from the data.
Jide Ogunbo
Read the Original
This page is a summary of: Mono‐Model Parameter Joint Inversion by Gramian Constraints: EM Methods Examples, Earth and Space Science, May 2019, American Geophysical Union (AGU),
DOI: 10.1029/2019ea000605.
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