3:48 PM - 3:51 PM
[STT13-P02] Pareto-optimal Joint Inversion Modelling and Data Set Compatibility Analysis
3-min talk in an oral session
Keywords:Multi-objective optimisation, Joint-inversion, Data set compatibility, Model uncertainty, Magnetotellurics
In order to generate unbiased joint inversion models, it is important to mitigate the influence of weighting and to analyse the compatibility of data sets. Therefore, we have developed a new approach to the joint inversion modelling of geophysical data. We present MOJO, a Pareto-optimal multi-objective joint inversion algorithm. It is based on an advanced genetic algorithm, hence it does not only calculate a single optimised model, but a distribution of possible models as final result. In contrast to common approaches, MOJO treats data sets as a separate objectives, which avoids spurious weighting. Additionally, we use the output of MOJO to calculate and evaluate curves of the trade-off between the different objectives. The shapes and evolutions of these curves yield a measure for the compatibility of the used data sets. Furthermore, the evaluation of the resulting model distribution provides valuable uncertainty estimates.