Initial stress estimation in reservoirs by a stochastic inverse approach accounting for structures and heterogeneities.

@inproceedings{MazuyerGM2015,
 abstract = { The aim of this study is to estimate the initial stress in reservoirs before the production. Structures such as faults have an influence on the stress magnitude and orientation that can make a geomechanical study complicated. Anthropogenic structures such as wells could locally disturb the stress field. Moreover, the mechanical behavior of the rocks may change through time. Because of all this factors, stress is difficult to estimate. We investigate in this paper a way to make a geomechanical model dealing with the reservoir structures and heterogeneities. The method estimates stress with two distinct inversion loops. First, wellbore data (such as borehole breakouts, drilling induced failures and leak-off tests) are inverted to estimate the stress orientation and magnitude locally around wells. In the second inversion, we assume that the reservoir is in mechanical equilibrium, so the inner stress is in equilibrium with the external forces. Borehole data enable to roughly propose a global first stress state estimation in the whole reservoir which is not in equilibrium with the external forces. The system defined with this stress state and boundary conditions evolves until it reaches the mechanical equilibrium which is computed by a Finite Element Analysis. The obtained stress has to honor the local stress estimation near the wells and it is seen as the initial stress state before the exploitation of the reservoir. Because there are uncertainties on the boundary conditions and the first stress estimation, we propose a stochastic approach for running the Finite Element Analysis. },
 author = { Mazuyer, Antoine AND Giot, Richard AND Cupillard, Paul AND Conin, Marianne AND Thore, Pierre AND Caumon, Guillaume },
 booktitle = { 35th Gocad Meeting - 2015 RING Meeting },
 publisher = { ASGA },
 title = { Initial stress estimation in reservoirs by a stochastic inverse approach accounting for structures and heterogeneities. },
 year = { 2015 }
}