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Weighing geophysical data with trans-dimensional algorithms: An earthquake location case study
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  • Nicola Piana Agostinetti,
  • Alberto Malinverno,
  • Thomas Bodin,
  • Savka Dineva,
  • Christina Dahnér,
  • Edi H Kissling
Nicola Piana Agostinetti
University of Milano-Bicocca

Corresponding Author:[email protected]

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Alberto Malinverno
Lamont-Doherty Earth Observatory of Columbia University
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Thomas Bodin
CNRS, ENS Lyon, Université de  Lyon-1
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Savka Dineva
Luleå University of Technology
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Christina Dahnér
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Edi H Kissling
Swiss Federal Institute of Technology
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In geophysical inverse problems, the distribution of physical properties in an Earth model is inferred from a set of measured data. A necessary step is to select data that are best suited to the problem at hand. This step is performed ahead of solving the inverse problem, generally on the basis of expert knowledge. However, expert-opinion can introduce bias based on pre-conceptions. Here we apply a trans-dimensional algorithm to automatically weigh data on the basis of how consistent they are with the fundamental assumptions made to solve the inverse problem. We demonstrate this approach by inverting arrival times for the location of a seismic source in an elastic half space, under the assumptions of a point source and constant velocities. The key advantage is that the data do no longer need to be selected by an expert, but they are assigned varying weights during the inversion procedure.
19 Jan 2023Submitted to ESS Open Archive
20 Jan 2023Published in ESS Open Archive