What is it about?
We introduce the use of the randomized singular value decomposition for focused inversion of three dimensional gravity data.
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Why is it important?
The randomized singular value decomposition (RSVD) provides an algorithm that is much faster than the standard Krylov based iterative algorithm for solving the relevant systems of equations. Also, this means that the memory usage can be controlled and overall computational costs made efficient. A new algorithm for the RSVD was introduced that is relevant for any case with limited data as compared to the model variables.
Perspectives
Demonstrating that the RSVD can be used for inversion of large data sets was interesting and has inspired us to continue our research along these lines. We hope that the provided approach is more generally useful.
Rosemary Anne Renaut
Arizona State University
Read the Original
This page is a summary of: A fast algorithm for regularized focused 3D inversion of gravity data using randomized singular-value decomposition, Geophysics, July 2018, Society of Exploration Geophysicists,
DOI: 10.1190/geo2017-0386.1.
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