Section: New Results
Scientific visualization, segmentation, surface approximation with faults and/or rapidly varying data in the Geosciences
Participants : Christian Gout, Dimitri Komatitsch, Anne-Gaëlle Saint-Guirons.
In many problems of geophysical interest, one has to deal with data that exhibit complex fault structures. This occurs for instance when describing the topography of seafloor surfaces, mountain ranges, volcanoes, islands, or the shape of geological entities, that can present large and rapid variations due for instance to the presence of faults in the structure. The usual approximation methods use to lead to instability phenomena or undesirable oscillations. The key point to get a good approximant consists in precisely define the locations of the large variations and the faults. To do that, we propose an automatic method that uses segmentation methods (developed by Gout and Le Guyader) to segment the Lagrange dataset in order to get several patchs delimited by large gradient (or faults) of the dataset Then, having the knowledge about the location of the discontinuities of the surface, we can generate a mesh (which takes into account the set of discontinuities) and a spline approximant is then computed.
The other part of this topic is the Fault modeling in 3D complex geophysical data. This kind of problems is of crucial interest in Geosciences as it consitutes an important exploration gap for reservoir characterization. Morevoer, it is well known that interpretation of faults in seismic data is today a time consuming manual task... and reducing time from exploration to production of an oil field has great economical benefits. A first work has been done in 2006 (Gout and Le Guyader [6]) but specific geophysical visualization problems limit the 3D applications of these results. A collaboration (linked to this topic) with M.P. Cani (INRIA Rhônes Alpes) has been rescheduled for 2007/2008.
The Ph. D. thesis (CIFRE at the University of Pau and TOTAL) of Guilhem Dupuy ''Creation et manipulation de maillages de grandes tailles: applications aux Geosciences'' under the direction of Dimitri Komatitsch and Bruno Jobard (Pau, Lab. d'Informatique) is also strongly linked to this theme.
