Towards stochastic interpretation of faulted structures using graph theory

@inproceedings{RUNKJRM44,
 abstract = { The interpretation of faults from geological and geophysical data is often challenging, due to
observation gaps and to the complexity of geophysical processes in fault zones. As a result, geological
interpretation of faulted structures may be ambiguous and under-constrained. Stochastic structural
modeling can sample structural uncertainties and may be used in multi-scenarios studies. However,
existing stochastic structural modeling methods either neglect some sources of uncertainty or only
consider very sparse or specific data types.
In this article, we propose a theoretical framework to stochastically interpret heterogeneous
data before the construction of a 3D subsurface model. The interpretations are represented by
two graphs: the first one gathers data belonging to the same geological structure (G correlation )
and is used to correlate fault observations. The second one (G branch ) details the contacts between
these structures. These graphs could be updated during stochastic simulations to generate several
interpretations while accounting for geometric and geologic rules. },
 author = { Godefroy, Gabriel AND Bonneau, Francois AND Caumon, Guillaume },
 booktitle = { 2016 RING Meeting },
 publisher = { ASGA },
 title = { Towards stochastic interpretation of faulted structures using graph theory },
 year = { 2016 }
}