Modelling and inversion of seismic waveform and electromagnetic data using integral equation methods
Main content
For seismic exploration and monitoring of reservoirs, full wave inversion (FWI) provides good information about the underlying subsurface structure. However, one of the many challenges that FWI faces, is that seismic data alone may not lead to the best possible discrimination between fluid pressure and saturation changes.
On the other hand, controlled source electromagnetic (CSEM) data is more sensitive to fluid saturation changes than seismic data, although its resolution is much lower. Therefore CSEM has been regarded as a supplement to seismic data, and have been mostly used in the exploration phase. However, recent results suggest that CSEM methods can also be useful for reservoir monitoring.
But the relation between FWI and CSEM is even more profound since the same kind of integral equations can be used to describe both seismic waveform and electromagnetic data. This constitutes the motivation and cornerstone of the present project, where we shall develop integral equation methods for the modelling and inversion of these data sets based on forward and inverse scattering series (FSS and ISS).
Compared to other integral equation methods, the main advantages of the scattering series methods are that in principle no a priori model of the subsurface is needed and that all reflection phenomena are included. In addition, the nonlinear inverse problem can be solved by a series of linear inverse problems. Nevertheless, the scattering series face also challenges related to convergence and efficiency, that shall be investigated.
Furthermore, to have similar methods for seismic waveform and electromagnetic data is a great advantage when it comes to perform a joint inversion of these different data types, as well as to further develop these methods by exploiting possible synergy effects.
Researchers working on this project:
PhD Student: Michael Ernesto López
Supervisor: Morten Jakobsen
Co-supervisor: Trond Mannseth