Seismic inversion is a widely used technique, but it is difficult to quantitatively integrate its results in geological or reservoir models. This is in part due to the difference of scales, and to the difficulty in properly modelling the petro-elastic relationships. We propose to use stochastic seismic inversion, that computes a large number of fine scale models at a scale closer to the geomodel, to quantitatively estimate the uncertainty associated to the inversion process. We then expose how the results from stochastic inversion can be integrated into geomodels, to compute a seismic-driven facies model that accounts for uncertainties. It is also possible to compute porosity models guided by the wells and the seismic, illustrating the value that seismic can bring even when the well density is high.


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